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Marco COCCONCELLI

Professore Associato
Dipartimento di Scienze e Metodi dell'Ingegneria

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Pubblicazioni

- Predictive Rolling Bearing Maintenance [Brevetto]
Cocconcelli, Marco; L., Bassi; D., Borghi; Rubini, Riccardo; Secchi, Cristian
abstract

A method of predicting a fault in a rolling bearing, the rolling bearing including inner and outer rings and rolling bodies evenly angularly distributed therebetween, the method comprising:. processing (in the DSP system 8) a position signal (x(t)) indicative of a relative angular position of the inner ring with respect to the outer rings, and a vibration signal (y(t)) (by the accelerometer 7) indicative of speed-related vibrations in the rolling bearing, such that they correspond to either an angular displacement of the rolling bodies equal to an integer number of angular gaps between adjacent rolling bodies or an integer number of complete rotations of the inner ring with respect to the outer ring; . space sampling (in the A/D acquisition board 9) the processed vibration signal (y(t)) based on the processed position signal (x(t)); and. predicting a fault in the rolling bearing based on the space-sampled vibration signal (y(t)).

2024 - Editorial Activity of the IFToMM-PC for the History of Mechanism and Machine Science in the Period 2018–2023 [Capitolo/Saggio]
Cocconcelli, M.; Ceccarelli, Marco; Gasparetto, A.
abstract

The mandate of the current steering committee of the IFToMM Permanent Commission for the History of Mechanism and Machine Science (PC-HMMS) ends in 2023, after two consecutive terms. This paper is aimed at summarizes the activities and results of the PC-HMMS by all its members in these six years (2018–2023). It is intended to be a brief final report - the first to date - to constantly monitor the state of health of the commission. In particular, the focus is on the editorial activity of the PC that has been developed on two main tracks: the publication of monographs and related books on HMMS, and the publication of the proceedings of conferences and workshops related to the HMMS topics. The paper, without claims of completeness, is intended to be a moment of reflection on what has been done and a starting point for the activity of the next board of the IFToMM PC-HMMS.

2024 - Experimental Setup for Non-stationary Condition Monitoring of Independent Cart Systems [Relazione in Atti di Convegno]
Jabbar, A.; D'Elia, G.; Cocconcelli, M.
abstract

The paper discusses the independent cart technology, which utilizes linear motors to move carts along a predetermined track autonomously. This technology offers control of individual speed profiles for each section along the track, frictionless propulsion mechanism, and the ability to start and stop loads quickly. Nevertheless, the initial cost of these systems is substantial, and regular condition monitoring is required to ensure optimal performance and long-term economic benefits. The paper provides an overview of various condition monitoring and signal processing techniques for analysis, including data-driven modeling with machine learning algorithms. The article presents an experimental setup based on the independent cart system and outlines a strategy for data acquisition that emphasizes specific conditions during each run of the system. The collected data is critical in monitoring the independent cart system’s condition and developing expertise in identifying different types of faults and their precise locations, utilizing hybrid modeling approaches.

2024 - Italian Teaching with Models from Mechanism Catalogues in 19th Century [Capitolo/Saggio]
Cocconcelli, M.; Ceccarelli, Marco
abstract

2024 - Nonlocal-Strain-Gradient-Based Anisotropic Elastic Shell Model for Vibrational Analysis of Single-Walled Carbon Nanotubes [Articolo su rivista]
Strozzi, Matteo; Elishakoff, Isaac E.; Bochicchio, Michele; Cocconcelli, Marco; Rubini, Riccardo; Radi, Enrico
abstract

2024 - Three Technical Reports in the Trial of Enzo Ferrari for the 1957 Mille-Miglia Car Crash [Capitolo/Saggio]
Cocconcelli, M.
abstract

In 1957, a car crash at the Mille Miglia – an Italian competition on a street circuit – caused the death of 11 people. As a matter of course, the car manufacturer, Enzo Ferrari, was investigated for negligent homicide. In order to clarify the car dynamics and the root causes, a first committee of technicians and academics had been assigned to produce an expert report. This report pointed directly towards the specific design of the tires used (made by the Belgian manufacturer Englebert) and, as a consequence, towards the Ferrari team and his owner. Other two reports followed, one provided by the defense and a third one to finally settle the issue. This paper won’t focus on the media aspect that the personalities involved aroused, but on the technical aspects of the reports produced by the three committees. Accidentally, these memories differ in the approach followed and allow a comparison on what the optimal approach should be to solve a technical problem, as well as a memory of a significant event in Italy which saw technical-scientific reasoning as the key to arriving at the truth and clearing Enzo Ferrari of all charges.

2023 - A Comparison of Shell Theories for Vibration Analysis of Single-Walled Carbon Nanotubes Based on an Anisotropic Elastic Shell Model [Articolo su rivista]
Strozzi, Matteo; Elishakoff, Isaac E.; Bochicchio, Michele; Cocconcelli, Marco; Rubini, Riccardo; Radi, Enrico
abstract

In the present paper, a comparison is conducted between three classical shell theories as applied to the linear vibrations of single-walled carbon nanotubes (SWCNTs); specifically, the evaluation of the natural frequencies is conducted via Donnell, Sanders, and Flügge shell theories. The actual discrete SWCNT is modelled by means of a continuous homogeneous cylindrical shell considering equivalent thickness and surface density. In order to take into account the intrinsic chirality of carbon nanotubes (CNTs), a molecular based anisotropic elastic shell model is considered. Simply supported boundary conditions are imposed and a complex method is applied to solve the equations of motion and to obtain the natural frequencies. Comparisons with the results of molecular dynamics simulations available in literature are performed to check the accuracy of the three different shell theories, where the Flügge shell theory is found to be the most accurate. Then, a parametric analysis evaluating the effect of diameter, aspect ratio, and number of waves along the longitudinal and circumferential directions on the natural frequencies of SWCNTs is performed in the framework of the three different shell theories. Assuming the results of the Flügge shell theory as reference, it is obtained that the Donnell shell theory is not accurate for relatively low longitudinal and circumferential wavenumbers, for relatively low diameters, and for relatively high aspect ratios. On the other hand, it is found that the Sanders shell theory is very accurate for all the considered geometries and wavenumbers, and therefore, it can be correctly adopted instead of the more complex Flügge shell theory for the vibration modelling of SWCNTs.

2023 - A European Researchers’ Night project on mechanical vibrations for high school students [Relazione in Atti di Convegno]
Cocconcelli, Marco; Fonte, Cosimo; Grosso, Pasquale; Mottola, Giovanni; Strozzi, Matteo; Rubini, Riccardo
abstract

The present works were conceived to be exhibited during the 2022 European Researchers’ Night (ERN 2022), at the University of Modena and Reggio Emilia. The idea is to illustrate the key concepts of mechanical vibration through the use of 3D models and virtual simulation analysis. The paper is directed to high school students planning to enroll in a mechanical engineering bachelor’s degree, in order to approach or consolidate some fundamental concepts of mechanical vibration. Topics not easy to explain, such as the natural frequencies of a body, could be presented more effectively using physical models. Mathematical formalism will be kept to a minimum, as it is beyond the scope of this paper.

2023 - Cross-Load Generalization of Bearing Fault Recognition with Decision Trees [Relazione in Atti di Convegno]
Briglia, Giovanni; Immovilli, Fabio; Cocconcelli, Marco; Lippi, Marco
abstract

The literature on condition monitoring is nowadays characterized by a wide variety of machine learning approaches. We argue that, in most of the works, the experimental evaluation is conducted in an oversimplified scenario, where training and test data contain samples obtained under the same radial and torsional load conditions. In this paper, we propose to apply an interpretable machine learning model, namely decision trees, to perform fault detection and recognition across different load configurations, a challenging benchmark that requires general-ization capabilities. The rules extracted from the trees provide explanations of the classification process.

2023 - Impact of noise model on the performance of algorithms for fault diagnosis in rolling bearings [Articolo su rivista]
Pancaldi, F; Dibiase, L; Cocconcelli, M
abstract

Condition monitoring of rolling bearings is attracting much interest since most of the production slowdowns depends on the damaging of these components. Several algorithms for fault detection have appeared in the technical literature in the last decade. In most cases, performance is assessed over both synthetic and experimental data. Unfortunately, the computer simulations adopt signal models that are trivial and are not able to predict the actual performance on the field. In this work we propose a framework suitable to fairly, quantitatively and objectively compare different algorithms for fault detection in rolling bearings. The vibration signal is obtained through computer simulations. The signal entailed by the damage is generated through the model at "impact-delay-line" already available in the technical literature. The machine noise is generated as a wideband component with the possible superposition of narrowband components. The wideband component has been modeled as additive white Gaussian noise, additive white noise drawn from an alpha-stable distribution and additive noise stemming from an autoregressive process. Narrowband components are modeled through trains of Gaussian pulses. The performance of three well known algorithms for fault detection are compared in terms of capability in identifying the theoretical cyclic frequencies related to a damage. In these scenarios the behavior of fault detectors are definitely far from that predicted by classical wideband noise models like, for instance, additive white Gaussian noise.

2023 - Nomograms in the History and Education of Machine Mechanics [Articolo su rivista]
Mottola, Giovanni; Cocconcelli, Marco
abstract

Computing formulae and solving equations are essential elements of scientific analysis. While today digital tools are almost always applied, analog computing is a rich part of the larger history of science and technology. Graphical methods are an integral element of computing history and still find some use today. This paper presents the history of nomograms, a historically-relevant tool for solving mathematical problems in various branches of science and engineering; in particular, we consider their role in mechanical engineering, especially for education, and discuss their mathematical properties. Each nomogram is a graphical description of a specific mathematical equation, designed such that the solution can be found through a simple geometric construction that can be performed with a straightedge. By design, using nomograms requires little skills and can be done even in adverse environments; a solution of sufficient accuracy for most purposes can then be found in a very short time. Another important advantage of nomograms is that they offer clear insight on the relationships between the variables, an insight which can be lost by looking at a complex equation. First introduced in the late 19th century, nomograms were used by engineers and scientists due to their speed with respect to manual calculations, before being superseded by computers. While now mostly obsolete in practice, nomograms can still prove useful in workshops and teaching classes: we thus also discuss their educational applications and present a few original examples.

2023 - On the performance comparison of diagnostic techniques in machine monitoring [Articolo su rivista]
Pancaldi, F.; Rubini, R.; Cocconcelli, M.
abstract

Predictive maintenance can save a lot of efforts in modern industry and condition monitoring is attracting a lot of attention accordingly. New algorithms for fault detection appear frequently in the technical literature, however an objective, quantitative and widely accepted approach to performance comparison is still lacking. In this paper, we propose a new method leading to a fair and reproducible performance assessment. The proposed solution is based on vibrational analysis and consists of searching and detecting the theoretical cyclic frequencies that appear as a specific "signature" of a fault. Each algorithm for condition monitoring relies on a metric, then the main idea is to quantitatively characterize the peaks of the metric emerging from the machine noise. We think that the wide adoption of the proposed approach could significantly foster the research in the fields of condition monitoring and predictive maintenance.

2023 - Plans for a Course on the History of Mechanisms and Machine Science [Relazione in Atti di Convegno]
Ceccarelli, M.; Cocconcelli, M.
abstract

Many universities offer optional courses within the curricula of studies that students can choose based on their interests. Usually, they are short courses of 3 ECTS (credits) but in some cases they can be proposed up to 6 ECTS. Moreover, they are often common to several degree courses, so the topics covered should be more general and transversal with respect to the specific engineering curriculum. In this paper, the background significance of the History of Mechanisms and Machine Science (MMS) is discussed by re-proposing a short course in technical formation curricula for engineers, preferably at Bachelor levels. After reviewing some previous preliminary experiences, the course proposal is outlined as based on the expectations in learning outcomes and with a general structure referring to basic literature. The target is to provide historical education backgrounds within the formation curriculum of a modern engineer.

2023 - Railway Axle Early Fatigue Crack Detection through Condition Monitoring Techniques [Articolo su rivista]
Gomez, María Jesús; Castejon, Cristina; Corral, Eduardo; Cocconcelli, Marco
abstract

: The detection of cracks in rotating machinery is an unresolved issue today. In this work, a methodology for condition monitoring of railway axles is presented, based on crack detection by means of the automatic selection of patterns from the vibration signal measurement. The time waveforms were processed using the Wavelet Packet Transform, and appropriate alarm values for diagnosis were calculated automatically using non-supervised learning techniques based on Change Point Analysis algorithms. The validation was performed using vibration signals obtained during fatigue tests of two identical railway axle specimens, one of which cracked during the test while the other did not. During the test in which the axle cracked, the results show trend changes in the energy of the vibration signal associated with theoretical defect frequencies, which were particularly evident in the direction of vibration that was parallel to the track. These results are contrasted with those obtained during the test in which the fatigue limit was not exceeded, and the test therefore ended with the axle intact, verifying that the effects that were related to the crack did not appear in this case. With the results obtained, an adjusted alarm value for a condition monitoring process was established.

2022 - Blind deconvolution criterion based on Fourier–Bessel series expansion for rolling element bearing diagnostics [Articolo su rivista]
Soave, E.; D'Elia, G.; Cocconcelli, M.; Battarra, M.
abstract

In the last years, Blind Deconvolution methods demonstrated their effectiveness for the diagnostics of rotating machines through the extraction of impulsive signatures directly from noisy observations. Recently, in this scenario the explicit combination between Blind Deconvolution and cyclostationary theory strongly improved the fault detection ability of this diagnostic tool. This work presents a novel criterion based on the Fourier–Bessel series expansion instead of the common Fourier transform. This idea comes from the comparison between the mathematical nature of the Fourier–Bessel and the Fourier series, based on modulated and constant amplitude sinusoidal functions, respectively. The two criteria are compared through the analysis of both simulated and real vibration signals of faulty bearings. The results highlight the ability of the proposed criterion to detect the fault-related source with a lower number of characteristic cyclic frequency harmonics, strongly reducing the computational time required by the algorithm.

2022 - Dynamic Analysis of a Semi-automatic Telegraph Key [Relazione in Atti di Convegno]
Fonte, C.; Cocconcelli, M.
abstract

The first telegraph key model was invented in 1846 by Alfred Vai, a close collaborator of Samuel F.B. Morse. Since then the telegraph key has changed several designs from the mechanical semi-automatic or bug to automatic systems, representing for years the main means of communication as well as the first means of electrical communication invented. Today telegraphy replaced by the telephone and the Internet, however, these devices are still used by about 3 million Amateur radio operators. In this paper, a dynamic analysis of a precise telegraph key model has done. The model is the Vibroplex Original Deluxe which is a semi-automatic model made by Vibroplex Company Inc., a historical company manufacturer of these devices, founded by Horace Greeley Martin (1873–1937). The feature of this device is to automatically generate points (in Morse code sense) by means of an oscillating mass. The validated model will be useful to test different setting parameters and how to manage them to get comfort for the operator.

2022 - Gravity Balancing of Parallel Robots by Constant-Force Generators [Capitolo/Saggio]
Mottola, G.; Cocconcelli, M.; Rubini, R.; Carricato, M.
abstract

This Chapter reviews the literature on gravity balancing for parallel robots by using so-called constant-force generators. Parallel robots are formed by several kinematic chains connecting, in parallel, a fixed base to a moving end-effector. A constant-force generator is a mechanism that is able to exert, at a given point, a force having constant magnitude and direction. Gravity balancing of serial robots is a well established technique; conversely, application in parallel robotics is controversial. Indeed, the addition of gravity-balancing mechanisms to a parallel robot may worsen its dynamic behavior, as shown in some referenced works. In this Chapter, we introduce a taxonomy of constant-force generators proposed so far in the literature, including mass and spring balancing methods, toghether with more niche concepts. We also summarize design considerations of practical concern.

2022 - Italian Historical Developments of Teaching and Museum Valorization of Mechanism Models [Articolo su rivista]
Ceccarelli, M.; Cocconcelli, M.
abstract

This paper presents an historical analysis of developments for the creation and usage of models of mechanisms in academic teaching fields, with the aim of re-evaluating the interest and usefulness of models in teaching and research, and of promoting their merits as a cultural heritage worthy of being preserved. The historical analysis is focused on developments in Italy, with specific attention given to physical models created and used for training young engineers in Italian engineering schools, using commercial products, but also original Italian creations. Examples are reported from the main Italian academic sites, where examples of such models of mechanisms have been preserved or have survived, also, as first attempts at museum valorization in terms of historical memorabilia of educational developments on mechanism design issues.

2022 - Modal analysis and condition monitoring for an electric motor through MEMS accelerometers [Relazione in Atti di Convegno]
Mottola, Giovanni; Grosso, Pasquale; Fonte, Cosimo; Strozzi, Matteo; Rubini, Riccardo; Cocconcelli, Marco
abstract

2022 - Nomograms: An Old Tool with New Applications [Relazione in Atti di Convegno]
Mottola, G.; Cocconcelli, M.
abstract

In this paper, we consider the history of nomograms as a computational tool in mechanical engineering, together with their potential applications for teaching purposes, and summarize the mathematical methods used to derive them. Nomograms are graphical descriptions of a mathematical problem, such that the desired solution may be derived through a simple geometric construction, which usually requires nothing more than a straightedge. This way, a reasonably accurate solution to a complex problem can be quickly obtained even in adverse environmental conditions by low-skilled users; moreover, a nomogram can provide immediate insight on the relationship between the variables. Nomograms date back to the 1800s and have been used by engineers for decades, due to their convenience over manual computation, before computers became widespread. While nomograms have now been largely superseded as engineering tools, our analysis shows that they can still have some applications in workshops and for teaching purposes.

2022 - Nomograms: history, properties and applications [Abstract in Atti di Convegno]
Mottola, Giovanni; Strozzi, Matteo; Rubini, Riccardo; Cocconcelli, Marco
abstract

2022 - Open Issues in Continuum Modeling of Carbon Nanotubes [Abstract in Atti di Convegno]
Strozzi, Matteo; Fonte, Cosimo; Rubini, Riccardo; Cocconcelli, Marco
abstract

2022 - Simulation of the vibration signal of cycloidal drives: preliminary results [Abstract in Atti di Convegno]
Grosso, Pasquale; Strozzi, Matteo; Rubini, Riccardo; Cocconcelli, Marco
abstract

2022 - Synthesis and optimization of an eight-bar linkage mechanism for seat suspensions [Articolo su rivista]
Spaggiari, A.; Cocconcelli, M.; Castagnetti, D.; Dragoni, E.; Rubini, R.
abstract

2021 - A Structured Approach to Machine Learning Condition Monitoring [Capitolo/Saggio]
Capelli, L.; Massaccesi, G.; Cavalaglio Camargo Molano, J.; Campo, F.; Borghi, D.; Rubini, R.; Cocconcelli, M.
abstract

The aim of the chapter is to explain the basic concepts of Machine Learning applied to condition monitoring in Industry 4.0. Machine learning is a common term used today in different fields, mainly related to an automated and self-learning routine in a decisional process. This chapter details how a Machine Learning approach may be structured, starting from a distinction between Supervised and Unsupervised approaches. These two classes have different advantages and disadvantages that constrain their application to specific boundary conditions. Machine Learning techniques are the core part of a structured methodology for the condition monitoring, but other phases, such as the pre-processing of data, the feature extraction and the evaluation of performances, are equally important for the success of a condition monitoring system. Together with standard parameters used to assess the performances of the machine learning method, a particular emphasis will be given to the interpretability of the results that can be determinant in the choice and development of a specific tool for condition monitoring in an industrial environment.

2021 - A Structured Approach to Machine Learning for Condition Monitoring: A Case Study [Capitolo/Saggio]
Cavalaglio Camargo Molano, J.; Campo, F.; Capelli, L.; Massaccesi, G.; Borghi, D.; Rubini, R.; Cocconcelli, M.
abstract

This chapter details the application of a machine learning condition monitoring tool to an industrial case study. The process follows the content of the corresponding tutorial chapter and is a step-by-step example of the setup of a monitoring kit in a packaging machine. The case study is particularly interesting since it is focused on Independent Carts System. This consists of a closed path made up of modular linear motors having a straight or curved shape and controls a fleet of carts independently. The application, not so common nowadays, proves the feasibility of the proposed condition monitoring approach in a non-trivial case, with scanty literature on it. The target is the diagnostics of ball bearings present in the wheels of the carts in order to reduce downtime due to the breakage of these components and to maximize their life cycle cutting down spare part costs. This chapter details the phase of feature extraction, the Machine Learning methods used, the results and the metrics for measuring them. Considerations will be made in particular on the acceptability/interpretability of the results and the industrial significance of the metrics.

2021 - Detectivity: A combination of Hjorth's parameters for condition monitoring of ball bearings [Articolo su rivista]
Cocconcelli, M.; Strozzi, M.; Cavalaglio Camargo Molano, J.; Rubini, R.
abstract

Hjorth's parameters are statistical time-domain parameters used in signal processing and introduced by Bo Hjorth in 1970. These parameters are Activity, Mobility and Complexity. They are related to the variance of the signal and of its subsequent derivatives. They are commonly used in the analysis of electroencephalography (EEG) signals for feature extraction, but also in the tactile signal analysis in robotic area. In this paper, Hjorth's parameters are applied to vibration signals for fault detection in ball bearings. In particular, two open-access datasets are used: the NASA bearing dataset of the University of Cincinnati and the Polytechnic of Turin rolling bearing dataset. In the first part of the paper the three parameters are used for monitoring the health of the bearings along their lifetime, proving their effectiveness in condition monitoring. In the second part, a new parameter is introduced, named Detectivity, that merges the information carried by Hjorth's parameters in a single value and is suitable for continuous monitoring of machines.

2021 - Future Challenges in Condition Monitoring from an Industrial Perspective: The Case of the Independent Carts Systems [Articolo su rivista]
Borghi, Davide; Cocconcelli, Marco
abstract

In this paper, the authors discuss about the future challenges of condition monitoring in an industrial context. One of the authors is Line Manager at Data Processing & Analytics for Equipment, Industry 4.0 & MES Products division of Tetra Pak Packaging Solutions S.p.A., a multinational company that approached condition monitoring and diagnostics fifteen years ago. So far, they have gained experience and have a clear idea of what the Industrial field expects in the coming years. In this paper, the analysis of a specific case study is an opportunity to suggest more general research themes on condition monitoring.

2020 - A bearing fault model for Independent Cart Conveyor System and its validation [Articolo su rivista]
Cavalaglio Camargo Molano, Jacopo; Capelli, Luca; Rubini, Riccardo; Borghi, Davide; Cocconcelli, Marco
abstract

Independent Cart Conveyor System is one of the most promising technology in automation industries. It combines the benefits of servo motors with the advantages of linear motors. It consists of a close path made up of modular linear motors having a curved or a straight shape that control a fleet of carts independently. Each cart is placed along the motors and it is connected, through rolling bearings, to a rail set on the motors themselves. The bearings are subject to wear and the condition monitoring of these elements is challenging for the non-stationary working conditions of variable load and variable speed profiles. This paper provides a bearing fault vibration model that takes into account the mechanical design of the cart, its motion profile, the shape of the conveyor path, the load variation and the type of fault on the rolling bearing.

2020 - A tool for validating and benchmarking signal processing techniques applied to machine diagnosis [Articolo su rivista]
Buzzoni, Marco; D’Elia, Gianluca; Cocconcelli, Marco
abstract

2020 - Condition Monitoring Techniques of Ball Bearings in Non-stationary Conditions [Relazione in Atti di Convegno]
Strozzi, M.; Rubini, R.; Cocconcelli, M.
abstract

Frequently, the Industry suggests non-trivial problems and new fields of research for the Academy. This is the case of the ball bearing diagnostics in direct-drive motors. Direct-drive motors are brushless motors fully controlled by the drive system. Thanks to an encoder or a resolver mounted on the shaft, they can perform complex motion profiles, such as polynomials or splines, including reverse rotation of the shaft. The main advantage of direct-drive motors is the removal of cams or gearboxes afterwards motor with a consequent strong reduction of economic and maintaining costs. Indeed, their main drawback is the difficulty to make diagnostics on the bearings. Regarding bearing diagnostics, most of the techniques present in literature are based on the search of fault-characteristic frequencies in the vibration spectrum of the motor. These fault frequencies are linearly dependent on the rotational frequency of the shaft if it is supposed constant. However, in direct-drive motors the rotational speed changes continuously and consequently the fault frequencies are meaningless. The paper reports a brief overview of some techniques for the condition monitoring of ball bearings in non-stationary conditions used by the Authors in the case of a packaging machine working under variable speed. The techniques adopted include an improved version of the computed order tracking, the cross-correlation function and three supervised learning approaches: artificial neural networks, artificial immune systems and support vector machines.

2020 - Condition monitoring and reliability of a resistance spot welding process [Relazione in Atti di Convegno]
Strozzi, Matteo; Cocconcelli, Marco; Rubini, Riccardo
abstract

The reliability of a resistance spot welding (RSW) process is studied monitoring the quality of the corresponding welding points. Each welding point is uniquely represented by a specific resistance characteristic curve over time. Five learning resistance characteristic curves, the good quality of the related welding points was experimentally verified by means of a non-destructive technique, are selected as a reference to check the quality of welding points related to different process resistance characteristic curves. A first estimate of the quality of the welding point is made comparing the corresponding process resistance characteristic curve with the learning maximum, minimum and average resistance characteristic curves. Both good quality and defective (glued or squeezed) welding points are observed. In order to more correctly identify the quality level of each welding point, two different parameters comparing the related process resistance characteristic curve with the learning average resistance characteristic curve are applied. First, the residual resistance, as the difference at each instant of time between the two resistance characteristic curves, is considered. Then, the Euclidean distance, as the geometric distance at each instant of time between the two resistance characteristic curves, is adopted. Finally, the trend of the quality of the welding points as their number increases for welding electrodes with a fixed number of dressings is investigated.

2020 - Metodologie non distruttive per l’individuazione di difetti su sanitari in ceramica: indagine sperimentale. [Altro]
Castagnetti, Davide; Cocconcelli, Marco; Spaggiari, Andrea; Strozzi, Matteo; Dragoni, Eugenio; Rubini, Riccardo
abstract

Metodologie non distruttive per l’individuazione di difetti su sanitari in ceramica: pianificazione sperimentale, prove sperimentali, analisi dei risultati, proposta di parametri identificativi dei difetti.

2020 - Motor Current Cyclic-Non-Stationary Analysis for Bearing Diagnostic [Relazione in Atti di Convegno]
D’Elia, G.; Cocconcelli, M.; Strozzi, M.; Mucchi, E.; Dalpiaz, G.; Rubini, R.
abstract

The Motor Current Signature Analysis (MCSA) is a research area focused on the diagnosis of components of electric motors based on post-processing of the current signal mainly. In particular, the bearing diagnostics is based on two different assumptions: the fault on the bearing causes a vibration of the shaft it supports, so there is an air gap variation between stator and rotor causing a modulation in the current signal; the fault on the bearing hinders the rotation of the shaft, so it can be modeled as an additional loading torque that the motor satisfies increasing the current signal. In this paper, a cyclic-non-stationarity analysis of the motor current is used to assess the status of ball-bearings in servomotors, running at variable speed. Both speed of the motor and motor current are provided by the control loop of the servomotor, that is no external sensors are used. The cyclic nature of the application allows an average of the cyclic-cyclic order maps to increase the signal-to-noise ratio. The proposed technique is successfully applied to both healthy and faulty bearings.

2020 - Motor current cyclic-non-stationarity analysis for bearing diagnostic [Relazione in Atti di Convegno]
D'Elia, G.; Cocconcelli, M.; Strozzi, M.; Mucchi, E.; Dalpiaz, G.; Rubini, R.
abstract

The Motor Current Signature Analysis (MCSA) is a research area focused on the diagnosis of components of electric motors based on post-processing of the current signal mainly. In particular, the bearing diagnostics is based on two different assumptions: the fault on the bearing causes a vibration of the shaft it supports, so there is an air gap variation between stator and rotor causing a modulation in the current signal; the fault on the bearing hinders the rotation of the shaft, so it can be modeled as an additional loading torque that the motor satisfies increasing the current signal. In this paper, a cyclic-non-stationarity analysis of the motor current is used to assess the status of ball-bearings in servomotors, running at variable speed. Both speed of the motor and motor current are provided by the control loop of the servomotor, that is no external sensors are used. The cyclic nature of the application allows an average of the cyclic-cyclic order maps to increase the signal-to-noise ratio. The proposed technique is successfully applied to both healthy and faulty bearings.

2020 - Preliminary orthotropic elastic model for the study of natural frequencies and mode shapes of a 3D printed Onyx thin circular cylindrical shell [Articolo su rivista]
Strozzi, M.; Giacomobono, R.; Rubini, R.; Cocconcelli, M.
abstract

The linear vibrations of a 3D printed Onyx thin circular cylindrical shell are considered. A model based on Sanders-Koiter shell theory and orthotropic elastic constitutive equations is adopted to obtain elastic strain and kinetic energy. The deformation of the middle surface of the shell is described in terms of longitudinal, circumferential and radial displacements, which are expanded by means of a double mixed series in terms of Chebyshev orthogonal polynomials along the longitudinal direction and harmonic functions along the circumferential direction of the shell. Free-free boundary conditions are considered. The Rayleigh-Ritz method is applied to calculate approximate natural frequencies and mode shapes. An isotropic elastic model is first adopted to obtain initial reference values for natural frequencies and mode shapes of the 3D printed shell. An experimental modal analysis is then performed to verify the accuracy of the initial isotropic elastic model and to find exact values for natural frequencies and mode shapes of the 3D printed shell. A more effective orthotropic elastic model is finally applied assuming different values of Young’s modulus along the longitudinal and circumferential directions of the shell. A parametric analysis is carried out by assuming a constant circumferential Young’s modulus and varying the longitudinal Young’s modulus. The goal is to minimise the difference between analytical and experimental results, in order to identify the actual orthotropy degree of the 3D printed shell.

2020 - The Italian Textbooks of Mechanics Applied to Machines in the Modern Age [Relazione in Atti di Convegno]
Cocconcelli, M.
abstract

The purpose of this paper, within the limits of the space available, is to trace the evolution of the textbooks of Mechanics Applied to Machines in Italy, considering a time period that goes from the second post-war period till today. The study presented does not pretend to be complete but wants to highlight the main changes in the textbooks of Applied Mechanics, correlating them to the historical period in which they were published. If we want to classify the textbooks according to common characteristics, it is proposed a classification in 3 main classes: the Masters, the Schools and the Courses. The first class brings together the textbooks published up to around 1970, by the professors who opened the first modern courses in Applied Mechanics in Italian universities. The second class brings together textbooks between 1970 and the 2000s, when the number of universities was growing, as the teaching and student population. The third class brings together textbooks from the 2000s to today. The publications no longer want to be a reference for all Applied Mechanics, but the topics are selected according to the specific study courses for which they are designed. It is stressed that the classification into the three proposed classes must be made based on the contents of the text and not purely on the date of publication.

2020 - The Teaching of Applied Mechanics through Textbooks in Italy [Articolo su rivista]
Cocconcelli, Marco
abstract

2020 - Time-varying metrics of cyclostationarity for bearing diagnostic [Articolo su rivista]
Pancaldi, F.; Rubini, R.; Cocconcelli, M.
abstract

Ball bearings represent the most adopted solution to support rotating elements. Separated by the cage, the rolling elements are induced by the kinematics of the system to roll and accidentally slip on the rings. In working conditions the continuous contact of the elements leads to a wearing of the bearing surfaces. As a consequence, the early detection of faults represents an issue for modern diagnostic systems. The mathematical model of faulted rolling bearings has been extensively investigated in the last decades and it is widely accepted that a faulted bearing is subject to an unwanted slippery leading to a cyclostationary vibration signal. This paper presents a novel approach to the diagnosis of rolling bearings based on the statistical definition of cyclostationarity. In particular, various metrics have been devised to track the “cyclostationary signature” of the vibration signal and the performance of the proposed algorithms has been assessed through both experimental measurements and synthetic data. Numerical results have shown that the new approach to fault detection is comparable to conventional techniques based on spectral kurtosis, demodulation and spectral correlation, and it can outperform them in some cases; furthermore the simplicity of the proposed algorithms leads to an intrinsic robustness against the mechanical noise typical of practical scenarios.

2020 - Virtual training of machine learning algorithm using a multibody model for bearing diagnostics on independent cart system [Relazione in Atti di Convegno]
Cavalaglio Camargo Molano, J.; Scurria, L.; Fonte, C.; Cocconcelli, M.; Tamarozzi, T.
abstract

Independent cart conveyor system is a new technology recently proposed in the field of automatic machines. This technology uses advance linear motors for moving several carts on a close-loop path. In this paper, a multibody model of the Independent cart conveyor system is used to train a machine learning algorithm for the diagnostics of ball bearings which support the carts. The multibody model provides several simulations both of healthy and faulted bearings, which are used to create the training dataset. The input features of the machine learning algorithm are statistical parameters that proved to be effective in the analysis of real vibration data. The final tests were carried out on experimental data recorded on a test rig and the fault detection algorithm was validated both in faulted and healthy cases in an industrial environment. The aim of this activity is to virtualize the training of a machine learning system for fault detection and to test its accuracy in a real environment.

2019 - Analysis of NASA Bearing Dataset of the University of Cincinnati by Means of Hjorth’s Parameters [Relazione in Atti di Convegno]
CAVALAGLIO CAMARGO MOLANO, Jacopo; Strozzi, Matteo; Rubini, Riccardo; Cocconcelli, Marco
abstract

2019 - Automated Bearing Fault Detection via Long Short-Term Memory Networks [Relazione in Atti di Convegno]
Immovilli, F.; Lippi, M.; Cocconcelli, M.
abstract

This paper presents a method for automated bearing fault detection via motor current analysis using Long Short-Term Memory networks. Minimal pre-processing is applied to current signals. The proposed approach is experimentally validated on a laboratory trial comprising different test sets for condition monitoring and fault diagnosis of a 6-poles induction motor. Preliminary results confirmed the effectiveness of the proposed method to detect various bearing faults under different operating conditions, such as: shaft radial load and output torque.

2019 - Bearing fault model for an independent cart conveyor [Relazione in Atti di Convegno]
Cocconcelli, M.; Cavalaglio Camargo Molano, J.; Rubini, R.; Capelli, L.; Borghi, D.
abstract

Independent cart conveyor system is an emerging technology in industries, trying to replace servo motors and kinematic chains in several applications. It consists of several carts on a closed-loop path, each of which can freely move with respect to the other carts. Basically, each cart is an servo linear motor, where the windings and the drives are on the frame and the magnets are on the moving carts together with a feedback device (e.g. a Hall sensor to track the position). The drive controls and actuates each cart independently according to the motion profile loaded. From a mechanical point of view, the carts are connected to the frame through a series of rollers placed on and under a mechanical guide. The rollers may be subject to a premature wear and the condition monitoring of these components is a no trivial challenge, due to non-stationary working conditions of variable speed profile and variable loads. This paper provides a bearing fault model taking into account the motion profile of the cart, the mechanical design of the cart, the geometry of the conveyor path, the expected loads and the type of fault on the roller bearings.

2019 - Comparison of metrics for peaks enhancement in variable speed conditions [Capitolo/Saggio]
Cocconcelli, Marco; Rubini, Riccardo; Pancaldi, Fabrizio; Capdessus, Cécile
abstract

The mathematical model of a faulted ball bearings has been extensively investigated in the last decades. So far, it is widely accepted that a faulted bearing is subject to an unwanted slip in working conditions and this leads to a cyclostationary vibration signal. In literature, various metrics have been devised to track the cyclic frequencies of the vibration signal, based on the statistical definition of cyclostationarity. In variable speed applications, the momentum of the mechanical system and dynamics loads play a fundamental role in the resulting amplitude of the vibration signal. A valuable metric for condition monitoring has to enhance the peaks of vibration signal related to a fault even if the dynamic load is not high. In this paper, five metrics are compared on a benchmark data from a variable speed application. The results indicate time-varying kurtosis (i.d. the moment of the fourth order of the data) as a possible winner.

2019 - Investigation on apparently related modes in experimental modal analysis [Abstract in Atti di Convegno]
Giacomobono, Roberto; Rubini, Riccardo; Cocconcelli, Marco; Strozzi, Matteo
abstract

2019 - Metodologie non distruttive per l’individuazione di difetti su sanitari in ceramica [Altro]
Castagnetti, Davide; Cocconcelli, Marco; Spaggiari, Andrea; Dragoni, Eugenio; Rubini, Riccardo
abstract

Studio di metodologie per l’individuazione, a fine linea di produzione, di difetti (sfili, cricche) su sanitari in ceramica

2018 - A new method for motion synchronization among multivendor’s programmable controllers [Articolo su rivista]
CAVALAGLIO CAMARGO MOLANO, Jacopo; Lahrache, Achraf; Rubini, Riccardo; Cocconcelli, Marco
abstract

This paper is aimed at increasing the number of possible architectures of distributed control systems by investigating and developing novel methods for the synchronization of axes between PLCs and iPCs of different vendors. In order to find a global solution to this problem, particular attention has been focused on programmable controllers that can manage axes by means of point-by-point control or motion instructions. Two synchronization algorithms have been developed and validated for real and virtual axes; they differ in computational load so that they can be used with programmable controllers having high or low computational performances.

2018 - An algorithm for the simulation of faulted bearings in non-stationary conditions [Articolo su rivista]
D'Elia, Gianluca; Cocconcelli, Marco; Mucchi, Emiliano
abstract

In the field of condition monitoring the availability of a real test-bench is not so common. Furthermore, the early validation of a new diagnostic technique on a proper simulated signal is crucial and a fundamental step in order to provide a feedback to the researcher and to increase the chances of getting a positive result in the real case. In this context, the aim of this paper is to detail a step-by-step analytical model of faulted bearing that the reader could freely and immediately use to simulate different faults and different operating conditions. The vision of the project is a set of tools accepted by the community of researchers on condition monitoring, for the preliminary validation of new diagnostics techniques. The tool proposed in this paper is focused on ball bearing, and it is based on the well-known model published by Antoni in 2007. The features available are the following: selection of the location of the fault, stage of the fault, cyclostationarity of the signal, random contributions, deterministic contributions, effects of resonances in the machine and working conditions (stationary and non-stationary). The script is provided for the open-source Octave environment. The output signal is finally analysed to prove the expected features.

2018 - Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field [Articolo su rivista]
Cocconcelli, Marco; Luca, Capelli; CAVALAGLIO CAMARGO MOLANO, Jacopo; Borghi, Davide
abstract

This paper describes a methodology, developed by the authors, for condition monitoring and diagnostics of several critical components in the large-scale applications with machines. For industry, the main target of condition monitoring is to prevent the machine stopping suddenly and thus avoid economic losses due to lack of production. Once the target is reached at a local level, usually through an R&D project, the extension to a large-scale market gives rise to new goals, such as low computational costs for analysis, easily interpretable results by local technicians, collection of data from worldwide machine installations, and the development of historical datasets to improve methodology, etc. This paper details an approach to condition monitoring, developed together with a multinational corporation, that covers all the critical points mentioned above.

2018 - Effect of Temperature on the Dynamic Response of Adhesively Mounted Accelerometers [Articolo su rivista]
Spaggiari, Andrea; Cocconcelli, Marco
abstract

This paper focuses on the effect of temperature on the frequency response function (FRF) of three different structural adhesives; namely a two component methylmethacrylate (HBM X60), a modified silane (Terostat 939) and a cyanoacrylate (Loctite 454). The structural adhesives are commonly used in vibration analysis to mount accelerometers on structures or machines. The stiffness of the adhesive can influence the response function on large frequency band, affecting the proportional excitation between the structure and the accelerometer. In the “system structure + adhesive + accelerometer”, the adhesive may acts like a filter between the source and the sink of vibrations. A variation of the dynamic response of the filter could lead to an erroneous analysis. The authors already investigated the relation between the frequency response function and operating conditions of the test. This paper expands the research by considering the temperature effect in order to depict a complete picture of the adhesive behavior on dynamic response of an accelerometer. A design of experiments (DOE) approach was used to test two bonded aluminum bases at different levels of temperature and frequency of the external sinusoidal excitation, supplied by an electromagnetic shaker. The results clearly demonstrate that the adhesive is not able to change the system response, therefore the signal transmission is good in the entire range of temperature regardless the adhesive chosen.

2018 - Experimental Evidence of the Speed Variation Effect on SVM Accuracy for Diagnostics of Ball Bearings [Articolo su rivista]
CAVALAGLIO CAMARGO MOLANO, Jacopo; Rubini, Riccardo; Cocconcelli, Marco
abstract

In recent years, we have witnessed a considerable increase in scientific papers concerning the condition monitoring of mechanical components by means of machine learning. These techniques are oriented towards the diagnostics of mechanical components. In the same years, the interest of the scientific community in machine diagnostics has moved to the condition monitoring of machinery in non-stationary conditions (i.e., machines working with variable speed profiles or variable loads). Non-stationarity implies more complex signal processing techniques, and a natural consequence is the use of machine learning techniques for data analysis in non-stationary applications. Several papers have studied the machine learning system, but they focus on specific machine learning systems and the selection of the best input array. No paper has considered the dynamics of the system, that is, the influence of how much the speed profile changes during the training and testing steps of a machine learning technique. The aim of this paper is to show the importance of considering the dynamic conditions, taking the condition monitoring of ball bearings in variable speed applications as an example. A commercial support vector machine tool is used, tuning it in constant speed applications and testing it in variable speed conditions. The results show critical issues of machine learning techniques in non-stationary conditions.

2018 - Experimental validation of a bearing fault model for an independent cart conveyor [Relazione in Atti di Convegno]
Cocconcelli, M.; Cavalaglio Camargo Molano, J.; Rubini, R.; Capelli, Luca
abstract

One of the most promising technology in industries is undoubtedly the independent cart conveyor system. It tries to replace induction motors and kinematic chains in several applications, especially in the field of automatic packaging machines. The independent cart conveyor system is made up of several induction linear motors. The carts are connected to the frame through a series of rollers, the bearings of which are subject to wear. In a previous paper the authors developed a theoretical model of the expected vibration signal from a faulted bearing, taking into account several design parameters. In this paper, the model is updated thanks to a new formulation of amplitude modulation effect and it is validated on the basis of an experimental campaign on a specific test-rig, where a bearing was artificially damaged on the external ring (the moving one). Finally, experiments have been used to validate the model in different configurations, proving the effectiveness of the proposed model and paving the way for future diagnostics of the independent cart conveyor.

2018 - Knife diagnostics with clustering techniques and support vector machines [Relazione in Atti di Convegno]
Lahrache, A.; Cocconcelli, M.; Rubini, R.
abstract

This paper is about analysis of experimental data, verifying the applicability of signal analysis techniques for condition monitoring of a packaging machine. In particular, the activity focuses on the cutting process that divides a continuous flow of packaging paper into single packages. The cutting process is made by a steel knife driven by a hydraulic system. Actually the knives are frequently substituted, causing frequent stops of the machine and consequent lost production costs. The aim of this paper is developing a diagnostic procedure to assess the wear condition of the blades, reducing the stops for maintenance. The packaging machine was sensorized with pressure sensor that monitors the hydraulic system driving the blade. Processing of the pressure data comprises three main steps: the selection of scalar quantities that could be indicative of the health state of the knife. A clustering analysis to setup a threshold between healthy and faulted knives. Finally, a Support Vector Machine (SVM) model to classify the health state of knife during its lifetime.

2017 - An unsupervised clustering method for assessing the degradation state of cutting tools used in the packaging industry [Relazione in Atti di Convegno]
Cannarile, Francesco; Baraldi, Piero; Compare, Michele; Borghi, Davide; Capelli, Luca; Cocconcelli, Marco; Lahrache, Achraf; Zio, Enrico
abstract

The objective of the present work is to develop a method for the identification of the degradation state of cutting tools (knives) used in the packaging industry. The main difficulties to be addressed are that i) only measurements of a physical quantity indirectly related to the knives degradation are available and ii) only the beginning and the end of operation of the knives are known, whereas no information is available on the component degradation state during its operation life. A method to identify the component degradation state is here proposed. First the general setting for extracting health indicators to measure the amount of knife degradation from a set of signals measured during operation is discussed. Then, an optimal subset of health indicators is selected based on monotonicity and trendability indexes. Finally, the optimal subset of health indicators is fed to a Fuzzy C-Means (FCM) clustering algorithm, which allows assessing the knife degradation state. The application of the proposed method to real condition monitoring knife data is shown to lead to satisfactory results.

2017 - Anomaly detection in a cutting tool by K-means clustering and Support Vector Machines [Articolo su rivista]
Lahrache, Achraf; Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper concerns the analysis of experimental data, verifying the applicability of signal analysis techniques for condition monitoring of a packaging machine. In particular, the activity focuses on the cutting process that divides a continuous flow of packaging paper into single packages. The cutting process is made by a steel knife driven by a hydraulic system. Actually, the knives are frequently substituted, causing frequent stops of the machine and consequent lost production costs. The aim of this paper is to develop a diagnostic procedure to assess the wearing condition of blades, reducing the stops for maintenance. The packaging machine was provided with pressure sensor that monitors the hydraulic system driving the blade. Processing the pressure data comprises three main steps: the selection of scalar quantities that could be indicative of the condition of the knife. A clustering analysis was used to set up a threshold between unfaulted and faulted knives. Finally, a Support Vector Machine (SVM) model was applied to classify the technical condition of knife during its lifetime.

2017 - Bayesian approach in the predictive maintenance policy [Relazione in Atti di Convegno]
Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria
abstract

In Industry, the maintenance policy is devoted to avoid sudden failures that can cause the stop of the system with a consequent loss of production, or - at least - to the minimization of the failure probability and/or the preservation of this probability under a fixed value. In such systems, the use of sensors for the monitoring of their degradation level is very useful. This gives the possibility to follow the time history of the component and to identify the most appropriate time for the maintenance activities, making possible the exploitation of the component for almost its whole useful life. The traditional preventive maintenance policy makes use of the a priori information on the population by assuming a probability distribution function and by estimating the involved statistical parameters [1]. By a monitoring system further information on the stochastic degradation process of the particular component belonging to the population can be available. Nevertheless, such sensors add new costs and exhibit inaccuracy in tracking the stochastic process. This inaccuracy implies an uncertainty in the supplied information. This occurs whether the degradation is defined as a geometric characteristic of the component or as the exhibition of a particular effect. For example, in a cutting tool, wear changes the geometrical characteristics causing an increase of superficial roughness on the machined parts. If a maximum value of roughness is accepted, the condition of failed cutting tool corresponds to the reaching of such value. In this case, the vibration signal is not a correct fault indicator because it is not suitable for tracking the degradation process. For these reasons, a predictive maintenance policy presupposes the identification of a signal well correlated to the degradation process and a high precision monitoring system. Components whose sudden failure can produce dramatic consequences on the system availability are considered. They must operate with a high required degree of reliability and the maintenance policy must assure a reliability level not lower than a pre-defined value. This paper is the second part of two [2], presenting an algorithm for the implementation of a sensor-driven predictive policy based on a Bayesian approach. Simulation results are supplied.

2017 - Combining blind separation and cyclostationary techniques for monitoring distributed wear in gearbox rolling bearings [Articolo su rivista]
D'Elia, G.; Cocconcelli, Marco; Mucchi, E.; Dalpiaz, G.
abstract

This work seeks to study the potential effectiveness of the Blind Signal Extraction (BSE) as a pre-processing tool for the detection of distributed faults in rolling bearings. In the literature, most of the authors focus their attention on the detection of incipient localized defects. In that case, classical techniques (i.e. envelope analysis) are robust in recognizing the presence of the fault and its characteristic frequency. However, when the fault grows, the classical approach fails, due to the change of the fault signature. De facto, in this case the signal does not contain impulses at the fault characteristic frequency, but more complex components with strong non-stationary contents. Moreover, signals acquired from complex machines often contain contributions from several different components as well as noise; thus the fault signature can be hidden in the complex system vibration. Therefore, pre-processing tools are needed in order to extract the bearing signature, from the raw system vibration. In this paper the authors focalize their attention on the application of the BSE in order to extract the bearing signature from the raw vibration of mechanical systems. The effectiveness and sensitivity of BSE is here exploited on the basis of both simulated and real signals. Among different procedures for the BSE computation, the Reduced-Rank Cyclic Regression algorithm (RRCR) is used. Firstly a simulated signal including the effect of gear meshing as well as a localized fault in bearings is introduced in order to tune the parameters of the RRCR. Next, two different real cases are considered, a bearing test-rig as an example of simple machine and a gearbox test-rig as an example of complex machine. In both examples, the bearings were degreased in order to accelerate the wear process. The BSE is compared with the usual pre-processing technique for the analysis of cyclostationary signals, i.e. the extraction of the residual signal. The fault detection is carried out by the computation of the Integrated Cyclic Modulation Spectrum on the extracted signals. The results indicate that the extracted signals via BSE clearly highlight the distributed fault signature, in particular both the appearance of the faults as well as their development are detected, whilst noise still hides fault grow in the residual signals.

2017 - Development and Validation of a Numerical Model for the Optimization of a Brace for Lower Limb [Relazione in Atti di Convegno]
Bellavita, G.; Cocconcelli, Marco; Castagnetti, Davide; Rubini, Riccardo
abstract

The orthopedic prosthesis, known as orthoses, are an external aid used for the correction of diseases which are the cause of a motor malfunction. Nowadays, the classification of different orthoses is performed by grouping them by type of apparatus that is subject to correction and on the basis of the length of the orthosis. In this study we analyze a specific orthosis of composite material, belonging to the AFO (Ankle-Foot-Orthosis) family. Passing through a process of “reverse engineering”, we define a non-linear computational model of the orthosis that describes the large displacement, the composite material, and the contact with the ground. The validation of the model against experimental tests, allows to use it to correlate the stiffness of the orthosis to its geometry, thus providing a useful tool to guide the structural improvements needed for adaptation to the patient.

2017 - Dynamic model of an independent carts system [Relazione in Atti di Convegno]
CAVALAGLIO CAMARGO MOLANO, Jacopo; Rossi, Stefano; Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper focuses on the dynamic modelling of a recent mechatronic device called independent carts system. Different companies gave different commercial names, but the mechanics behind is the same: different linear motors on a closed loop, controlled individually to increase the flexibility but keeping the speed of dedicated solutions, such as mechanical cams or chains. The proposed model covers both the mechanical and control parts of the systems. In this paper the preliminary results are shown, and the model is validated on a real independent carts system by Rockwell Automation. The mechanical model is assumed to be a planar model and the moving carts are supposed to be rigid bodies moving along a rail. Friction and gravity effect are taken into account. The electrical model comprises three PID control loops. The aim of this model is to simulate the behavior of the system in order to evaluate different scenarios and architectures of new machines, decreasing the cost of development and the time to market.

2017 - Experimental Investigation of Shaft Radial Load Effect on Bearing Fault Signatures Detection [Articolo su rivista]
Immovilli, Fabio; Cocconcelli, Marco
abstract

This paper investigates the influence of external radial load applied to the shaft on bearing fault detection based on vibration or current in induction motors operating under different conditions. This paper details the results of a laboratory trial comprising different test sets on the condition monitoring and fault diagnostic of a six-poles induction motor using a design of experiment (DOE) approach. The dedicated test setup comprises a custom-made fixture that allows us to dynamically vary the radial load applied to the output shaft. The aim is to investigate the effects of radial load on the fault diagnosis of shaft bearings and the interactions between other operating parameters, such as output torque. Specific scalar parameters have been proposed for the condition monitoring of the test motor from vibration and current data. The correct choice of the significant parameters is proven by the strong dependence on the damage returned by DOE results.

2017 - Extension of the predictive policy to a series of mechanical systems [Relazione in Atti di Convegno]
Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria
abstract

In the literature, a great interest is reserved to complex systems (i.e. serial or parallel or mixed systems), constituted by the interconnection of single elements. The evolution of system reliability depends on its structure as well as on the evolution of the reliability of its individual elements. Maintenance activities on systems strongly affect element aging and system’s operating life. Preventive maintenance, for example, is used to increase system availability reducing, as a consequence, the probability of failure. Generally, maintenance plans are performed with respect to some criteria depending on cost or on reliability/availability requirements. Therefore, the optimum maintenance scheduling of a system can be based on the minimization of the total cost or on the maximization of its availability. Many Authors emphasize the requirement on system reliability. In [1], for example, the concept of reliability equivalence from simple series and parallel systems to some complex systems is presented and reliability equivalence factors of complex systems are obtained. One of the most critical problems in preventive maintenance is the determination of the optimum frequency to perform maintenance actions on systems, in order to ensure a pre-defined level of availability. In this paper the predictive maintenance policy, for a single element, is extended to a system constituted by two series elements, named A and B. The transition from a single unit to a series system is not immediate and presents a great number of problems. Actually, when a maintenance action is scheduled for a system of this kind, the decision maker must decide if it is more convenient (with respect to some chosen criterion) to intervene on element A or B or on both. The proposed methodology deals with this practical problem in the context of the predictive maintenance policy. Research on this topic is in a running state and the methodology is only theoretically presented.

2017 - Mounting of accelerometers with structural adhesives: experimental characterization of the dynamic response [Articolo su rivista]
Cocconcelli, Marco; Spaggiari, Andrea
abstract

The use of accelerometers to monitor the vibrations of either complex machinery or simple components involves some considerations about the mounting of the sensor to the structure. Different types of mounting solutions are commonly used, but in all cases they can be classified in one of these categories: stud mounting, screw mounting, adhesive mounting, magnetic mounting, and probe sensing. Indeed, each of them has a specific field of application depending on e.g. the mounting surface conditions, the temperature, the accessibility to the specific mounting point, etc. The choice of the mounting solution has an important effect on the accuracy of the usable frequency response of the accelerometer, since the higher the stiffness of the fixing, the higher the low-pass frequency limit of the mounting. This article specifically focuses on adhesive mounting of accelerometers, which includes a great number of different products from the temporary adhesives like the beeswax to the permanent ones like cyanoacrylate polymers. Among the variety of commercial adhesives, three specific products have been experimentally compared to assess their transmissivity and the results are reported in this article. A two-component methylmethacrylate (HBM X60), a modified silane (Terostat 737), and a cyanoacrylate (Loctite 454) adhesive have been used to join two aluminum bases, one connected to an accelerometer and the other to the head of electromagnetic shaker. A design of experiment (DOE) approach was used to test the system at several levels of amplitude and frequency of the external sinusoidal excitation supplied by the shaker.

2017 - Numerical and Experimental Dynamic Analysis of IC Engine Test Beds Equipped with Highly Flexible Couplings [Articolo su rivista]
Cocconcelli, Marco; Troncossi, Marco; Mucchi, Emiliano; Agazzi, Alessandro; Rivola, Alessandro; Rubini, Riccardo; Dalpiaz, Giorgio
abstract

Driveline components connected to internal combustion engines can be critically loaded by dynamic forces due to motion irregularity. In particular, flexible couplings used in engine test rig are usually subjected to high levels of torsional oscillations and time-varying torque. This could lead to premature failure of the test rig. In this work an effective methodology for the estimation of the dynamic behavior of highly flexible couplings in real operational conditions is presented in order to prevent unwanted halts. The methodology addresses a combination of numerical models and experimental measurements. In particular, two mathematical models of the engine test rig were developed: a torsional lumped-parameter model for the estimation of the torsional dynamic behavior in operative conditions and a finite element model for the estimation of the natural frequencies of the coupling. The experimental campaign addressed torsional vibration measurements in order to characterize the driveline dynamic behavior as well as validate the models. The measurements were achieved by a coder-based technique using optical sensors and zebra tapes. Eventually, the validated models were used to evaluate the effect of design modifications of the coupling elements in terms of natural frequencies (torsional and bending), torsional vibration amplitude, and power loss in the couplings.

2017 - On the identification of the angular position of gears for the diagnostics of planetary gearboxes [Articolo su rivista]
D'Elia, G; Mucchi, E.; Cocconcelli, Marco
abstract

Generally, in planetary gearbox diagnostics, vibration transducers are placed on the gearbox case near the ring gear. The relative angular position of the planet gears with respect to the transducer is a useful information for the evaluation of vibration signals related to planet/sun gears. This angular position is usually unknown, or it is known with a large tolerance causing serious difficulties in both gears and bearing diagnostics. In fact, noise and spurious component from healthy planets could overhang the informative content about incipient faults. The present work seeks to propose two alternative methods for the identification of the angular position of the planet gears with respect to the transducer. The first one is based on the study of how the power flows inside the Time Synchronous Average of the ring gear, whilst the second method is based on a modified statistical parameter such as the Crest Factor. The effectiveness of these methods is assessed on the basis of actual vibration signals acquired from a faulty planetary gearbox. The knowledge of the exact angular position of the planet gears allows the diagnostics of both gears and bearings, as proven by extensive experimental activities reported in the paper.

2017 - Standard and natural motion protocols for the kinetic measurements of the squat [Relazione in Atti di Convegno]
Sancisi, Nicola; Cocconcelli, Marco; Rubini, Riccardo; Parenti Castelli, Vincenzo
abstract

Two motion protocols that describe the sequence of movements to be complied with by a subject to perform a controlled squat are presented. The protocols are intended to be used in gait analysis to obtain repeatable and reproducible results that can be compared among different studies. The first protocol (“standard”) is closer to other studies in the literature, in order to improve comparison with previous experimental results. The second protocol (“natural”) reproduces a squat movement more similar to natural conditions, also allowing a deeper knee flexion. The two motion protocols are tested by a volunteer on a gait lab. Results of experimental tests in terms of joint and foot-ground angles, ground reaction force and centre of pressure show the characteristics of the standard and natural squat, and the repeatability of the tests.

2017 - Statistical evidence of central moment as fault indicators in ball bearing diagnostics [Relazione in Atti di Convegno]
Cocconcelli, Marco; Curcurù, Giuseppe; Rubini, Riccardo
abstract

This paper deals with post processing of vibration data coming from a experimental tests. An AC motor running at constant speed is provided with a faulted ball bearing, tests are done changing the type of fault (outer race, inner race and balls) and the stage of the fault (three levels of severity: from early to late stage). A healthy bearing is also measured for the aim of comparison. The post processing simply consists in the computation of scalar quantities that are used in condition monitoring of mechanical systems: variance, skewness and kurtosis. These are the second, the third and the fourth central moment of a real-valued function respectively. The variance is the expectation of the squared deviation of a random variable from its mean, the skewness is the measure of the lopsidedness of the distribution, while the kurtosis is a measure of the heaviness of the tail of the distribution, compared to the normal distribution of the same variance. Most of the papers in the last decades use them with excellent results. This paper does not propose a new fault detection technique, but it focuses on the informative content of those three quantities in ball bearing diagnostics from a statistical point of view. In this paper, a discriminant function analysis is used, to determine which central moment has a high discrimination power in the diagnostics of ball bearing in stationary conditions.

2017 - Step-by-step algorithm for the simulation of a faulted gearbox [Relazione in Atti di Convegno]
D’Elia, Gianluca; Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper focuses on the simulation of expected vibration signal of a faulted gearbox. The main mechanical components simulated are ball bearings and ordinary gears. In a previous work [1] the authors presented a step-by-step algorithm for the simulation of faulted bearings. In this paper the model has been extended to include ordinary gears and their most common faults, such as pitting or crack on a tooth, the presence of backlash or bent shafts. Regarding the ball bearings model, the simulation takes into account the selection of the location of the fault's type, the stage of the fault, cyclostationarity of the signal, random contributions, deterministic contributions, eects of resonances in the machine and working conditions. Although several detailed models are available in literature, the scientic papers just outline the theoretical foundations of assumptions and features of the model - as supposed - leaving to the reader the task of converting all the procedure in lines of code. This is in contrast with the idea of "reproducible research", which posits the possibility of being able to reproduce the proposed procedure and verifying the conclusions of the paper. As soon as the model is veried by scientic community, it could be used as preliminary test-bench, for the validation of new diagnostics techniques that the reader could develop in the future. This project has been developed under a Creative Commons license (Attribution-ShareAlike 4.0 International). The reader could freely and immediately use to simulate dierent faults and dierent operating conditions on ordinary gearbox. The script is provided for the open- source Octave environment. The output signal is nally analyzed to prove the expected features. [1] G. D'Elia, M. Cocconcelli, E. Mucchi, R. Rubini and G. Dalpiaz, Step-by-step algorithm for the simulation of faulted bearings in non-stationary conditions, ISMA 2016, Leuven, Belgium, 19-21 September 2016.

2017 - Sviluppo concettuale e dimensionamento di massima di un sistema meccanico facente parte della sospensione pneumatica di un sedile di guida professionale per macchine off-road [Altro]
Spaggiari, Andrea; Castagnetti, Davide; Cocconcelli, Marco; Dragoni, Eugenio; Rubini, Riccardo; Panini, Alessandro
abstract

Sviluppo concettuale e dimensionamento di massima di un sistema meccanico facente parte della sospensione pneumatica di un sedile di guida professionale per macchine off-road

2017 - System monitoring and maintenance policies: a review [Relazione in Atti di Convegno]
Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria
abstract

In the industrial context, the main goal of the maintenance team is to avoid sudden failures that can cause the stoppage of the system with a consequent loss of production. This means that each maintenance action must be performed before the degradation level of a system exceeds a critical threshold beyond which the failure probability becomes high. The increasing importance given to maintenance is shown not only by the great deal of literature on the topic, but also by the interest in transforming this area from a managerial area to a branch of applied mathematics (Operational Research or Statistics). Maintenance is now considered as a subject and much research activity is concerned with its mathematical modeling rather than with the management processes relating to maintenance itself. In [1], Scarf evidences the great importance of the mathematical modeling of maintenance and the correlated strategic support given by the maintenance management information systems. Nevertheless, no model can be built without an exhaustive collection of data. By data, Author means not only specific figures regarding, for example, failure times, but all information related to the process under study. With the recent advent of condition monitoring and the development of appropriate decision models, critical components of a system can be tracked through appropriate variable(s) correlated to their degradation process, logistic support (for example, spares inventory) can be provided, maintenance history can be stored, predetermined maintenance activity can be alarmed and management reports can be produced. The use of condition monitoring techniques reduces the uncertainty operators feel about the current state of the plant. For example, knowledge about the vibration levels of a rotating bearing gives engineers confidence about its operation in the short term. Data acquired by monitoring systems, maintenance histories collected for specific components can be considered fundamental resources for the mathematical modeling of the maintenance activities. This paper is the first part of two [2], presenting the transition from preventive maintenance policy to the predictive one. In particular, the paper presents a brief review of the subject and some critical considerations about the two maintenance policies.

2016 - Artificial Immune System via Euclidean Distance Minimization for Anomaly Detection in Bearings [Articolo su rivista]
Montechiesi, Luca; Cocconcelli, Marco; Rubini, Riccardo
abstract

In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects

2016 - Knife diagnostics with empirical mode decomposition [Relazione in Atti di Convegno]
Cotogno, M.; Cocconcelli, M.; Rubini, R.
abstract

This paper deals with the condition monitoring of knives via the Empirical Mode Decomposition (EMD). The cutting process is basically transient, thus Fourier Analysis and similar signal processing tools aren’t optimal because they treat signals as they were periodic. EMD is a signal analysis technique which is particularly suited for non-stationary and/or non-linear data, since it adaptively decomposes the signal in a sum of Intrinsic Mode Functions (IMFs). The knives under analysis are used inside an automated packaging machine; they are hydraulically actuated and are mounted on a moving support, so it’s not possible to put sensors on them because of security reasons related to sensors wiring. Instead, the actuators control valve is hosted on a fixed machine part, so its pressure signal is the one analysed in this paper. The sum of two IMFs is used to estimate the knife state and to obtain a representation of the wearing process during a knife life.

2016 - Rilievo del movimento del dito indice: confronto fra stereofotogrammetria e accelerometri [Capitolo/Saggio]
Cocconcelli, Marco; Sancisi, Nicola; Mazzotti, Claudio; Rubini, Riccardo; Parenti Castelli, Vincenzo
abstract

Il movimento naturale del dito indice di un volontario è misurato e analizzato mediante due diversi sistemi di acquisizione. Il primo è un sistema stereofotogrammetrico e si basa sulla misura delle coordinate di marcatori collegati a ciascun segmento (falange o palmo della mano) tramite un gruppo di telecamere. Il secondo fa uso di sensori inerziali che integrano un accelerometro ed un giroscopio. Lo scopo dello studio è comprendere quanto i risultati dei due sistemi sono sovrapponibili e di conseguenza quanto le due tecniche di misura possono essere utilizzate in alternativa o combinate tra loro.

2016 - Step-by-step algorithm for the simulation of faulted bearings in non-stationary conditions [Relazione in Atti di Convegno]
D'Elia, Gianluca; Cocconcelli, Marco; Mucchi, E.; Rubini, Riccardo; Dalpiaz, Giorgio
abstract

The early validation of a new diagnostic technique on a proper simulated signal is crucial, in order to provide a feedback to the researcher and increasing the chances of getting a positive result in the real case-studies. While dozens of comprehensive models of ball bearing have proposed in literature so far, the complexity of these models accordingly increased. As supposed, the scientific papers just outline the theoretical foundations of assumptions and features of the model, leaving the reader the task of converting all in lines of code. The aim of this paper is to detail step-by-step an analytical model of faulted bearing that the reader could freely and immediately use to simulate different faults and different operating conditions. It is based on the model proposed by Antoni in 2007 and the features available are the following: selection of the location of the fault, stage of the fault, cyclostationarity of the signal, random contributions, deterministic contributions, effects of resonances in the machine and working conditions (stationary and non-stationary).

2016 - Sviluppo e validazione di un modello numerico per l'ottimizzazione di un'ortesi per arto inferiore [Capitolo/Saggio]
Bellavita, G.; Cocconcelli, Marco; Castagnetti, Davide; Rubini, Riccardo
abstract

Le protesi ortopediche, note come ortesi, sono un ausilio esterno utilizzato per la correzione di patologie che determinano un malfunzionamento motorio. La suddivisione delle diverse ortesi, ad oggi, viene eseguita mediante un raggruppamento per tipologia di apparato soggetto a correzione e attraverso la lunghezza dell’ortesi. In questo studio si analizza una specifica ortesi in materiale composito, appartenente alla famiglia AFO (Ankle-Foot-Orthosis). Attraverso un processo di “reverse engineering”, si definisce un modello computazionale dell’ortesi che tiene conto delle non linearità geometriche, del materiale e dovute al contatto con il suolo. Dopo aver convalidato il modello con specifiche prove sperimentali, lo si impiega per correlare la rigidezza dell’ortesi alla sua geometria, ottenendo un utile strumento per guidarne le modifiche strutturali necessarie per l’adattamento al paziente.

2015 - Evolution of gear condition indicators for diagnostics of planetary gearboxes [Relazione in Atti di Convegno]
D'Elia, Gianluca; Cocconcelli, Marco; Rubini, Riccardo; Dalpiaz, Giorgio
abstract

In the last decades diagnostics of planetary gearboxes became a necessity in different fields, such as Industry and Army, and a plethora of gear condition indicators (CI) were proposed. Among the others: FM4, NA4, ER and SI. All of these CIs have proved to be effective in specific conditions, but it is a matter of fact that several indicators may lead to different decisions, while the literature only reports case studies with positive responses for each CI. In this paper a critical comparison among different CIs is carried out during a complete life of a gearbox. In particular a test bench runs a three-stage gearbox for a non-stop target period of 700 hours. At the end of the test the presence of faults are evident from the analysis of the vibrations. Moreover two original CI, namely RV and CRV, have been introduced and tested. The evolution of CIs response is monitored during the test, showing different behavior in both parameter sensitivity and response dynamics. The data analysis allows a choice of the most promising indicators

2015 - Improvement of the dynamic behaviour of a test bed driveline by numerical and experimental investigations [Capitolo/Saggio]
Cocconcelli, Marco; Troncossi, Marco; Agazzi, Alessandro; Mucchi, Emiliano; Rubini, Riccardo; Rivola, Alessandro; Dalpiaz, Giorgio
abstract

This work regards the dynamic analysis of the coupling elements in IC engine test rigs from a numerical and experimental standpoint. Two mathematical models of an IC test rig have been developed: a torsional lumped-parameter (LP) model (developed in Matlab-Simulink) for the estimation of the torsional dynamic behavior and a 3D finite element (FE) model for the estimation of the natural frequencies of the coupling elements. The numerical models take into account the stiffness and damping of the flexible elements as well as the test rig inertia properties. A large experimental campaign has been carried out in order to validate the models. In particular, torsional vibration measurements have been achieved by a coder-based technique using high-quality optical sensors and equidistantly spaced markers (zebra tape) on the rotating components (high flexible couplings). Eventually, the validated models have been used in order to evaluate the effect of design modifications of the coupling elements in terms of natural frequencies (torsional and bending) and torsional vibration amplitude

2015 - Non-linear elasto-dynamic model of faulty rolling elements bearing [Relazione in Atti di Convegno]
Cotogno, Michele; Pedrazzi, Enrico; Cocconcelli, Marco; Rubini, Riccardo
abstract

In this paper an elasto-dynamic model of a defective sphere bearing is presented. This two-dimensional model can simulate local faults on the bearing races and rolling elements, and it is based on the non-linear Hertzian contact deformation of the rolling elements. In the model the outer race is supposed to be fixed, and the rolling elements are supposed to roll without slipping. These assumptions yield a total of z + 4 Degrees of Freedom (DOF), where z is the number of rolling ele-ments: three DOF come from the inner race (two displacements and one rotation), one DOF from the cage (rotation) and one DOF from each rolling element (i.e., z radial displacements). Each contact between the spheres and the races is modelled by a non-linear spring (Hertz contact theory) and a damper proportional to the spring stiffness (Palmgren). The model uses a kinematic approach to calculate the trajectory of the rolling elements when passing over the defect. This trajectory is introduced into the equations of motion for the calculation of the rolling elements deformations; subsequently, the internal bearing forces are calculated. The model inputs are the bearing and defect geometry, the materials characteristics and the radial load. The model outputs the overall force transmitted to the outer race, which accurately reproduces the typical behaviour exhibited by a faulty bearing both in time and frequency domain

2015 - On the Diagnostics of Planet Gear Bearings [Relazione in Atti di Convegno]
D'Elia, G.; Cocconcelli, M.; Mucchi, E.; Dalpiaz, G.
abstract

Bearings play a pivotal role in the rotating machine scenario, due to their ubiquity and importance. A crowd of signal processing procedures have been developed in order to extract information about incipient localised faults in bearings from the measured acceleration signals. In the case of bearings for planetary gear applications, additional complexities are introduced. First, transducers may only be placed on the exterior of the gearbox, usually rather far from bearings. Second, the rotational axes of the planet gears are not fixed, i.e. they move with respect to the gearbox housing and thus to the transducers. As a result, the vibration signature of the planet gear bearings can be altered by the variable transfer path. In this condition, the standard signal processing techniques fail, and the characteristic bearing fault frequencies cannot be determined. On the other hand, global indicators of the bearing health may be used, but they are not able to specify where the fault is located. In this paper, a pre-processing technique is applied to the vibration signals of a planetary gearbox in order to highlight the planet gear bearing signatures. This technique is based on the McFaddens time synchronous averaging method to extract the vibration data relative to each planet. Then, cyclostationary techniques such as the Cyclic Power has be applied to extract the bearing signature.

2015 - Ottimizzazione dei percorsi CNC per lavorazioni laser di superfici free form [Capitolo/Saggio]
Montanari, Federico; Cocconcelli, Marco; Orazi, Leonardo; Rubini, Riccardo
abstract

L’utilizzo della tecnologia Laser, in lavorazioni Laser Texturing ed Engraving, per la realizzazione di superfici free form è un’interessante alternativa alle lavorazioni EDM e di micro fresatura nella fabbricazione di stampi e matrici. Il tasso di rimozione del materiale di questo processo è tipicamente molto basso e la massima area di lavoro è limitata dal campo di spostamento massimo della testa di scansione galvanometrica ed anche dalla deformazione massima dello scanner o la curvatura della superficie. Di conseguenza, al fine di realizzare superfici free form o grandi, è necessario eseguire una serie di posizionamenti della testa laser rispetto al pezzo da lavorare, calcolati e controllati dal CNC. Il numero di questi posizionamenti può essere molto alto a causa della piccola quantità di materiale asportato in ciascuno di essi ed il tempo non operativo speso per spostare la testina di scansione può essere rilevante rispetto al tempo complessivo. In questo lavoro viene proposto un metodo basato sulla soluzione del problema del commesso viaggiatore, con lo scopo di ottimizzare il numero di spostamenti della testa di scansione e generalmente per ridurre il numero di movimenti degli assi a controllo numerico. Il metodo, che tenga conto sia l'architettura e le caratteristiche dinamiche del sistema CNC 5 assi, è stato implementato nel CALM software (Computer Aided Laser Manufacturing) utilizzato per programmare il percorso laser per parte texturing e applicata in casi industriali

2014 - Dynamic analysis of coupling elements in IC engine test rigs [Relazione in Atti di Convegno]
Cocconcelli, Marco; Agazzi, Alessandro; Mucchi, Emiliano; Dalpiaz, Giorgio; Rubini, Riccardo
abstract

This work regards the dynamic analysis of the coupling elements in IC engine test rigs from a numerical and experimental standpoint. Two mathematical models of an IC test rig have been developed: a torsional lumped-parameter (LP) model (developed in Matlab-Simulink) for the estimation of the torsional dynamic behavior and a 3D finite element (FE) model for the estimation of the natural frequencies of the coupling elements. The numerical models take into account the stiffness and damping of the flexible elements as well as the test rig inertia properties. A large experimental campaign has been carried out in order to validate the models. In particular, torsional vibration measurements have been achieved by a coder-based technique using high-quality optical sensors and equidistantly spaced markers (zebra tape) on the rotating components (high flexible couplings). Eventually, the validated models have been used in order to evaluate the effect of design modifications of the coupling elements in terms of natural frequencies (torsional and bending) and torsional vibration amplitude.

2014 - MULTIVARIATE ANALYSIS FOR BEARING CLASSIFICATION [Capitolo/Saggio]
Giuseppe, Curcurù; Cocconcelli, Marco; Rubini, Riccardo
abstract

Ball bearings are probably the most used components in mechanics. Since they usually connect mechanical parts with relative speed – like the rotor and stator in an electrical motor - they are at the core of the machine functionality. Damage in these components quickly lead to sudden and unexpected stop of machineries with a loss of production for industries. In a packaging machine, for example, an unexpected stop of a couple of hours may cause costs of loss-production which are several time the cost of the single broken component. The need to avoid unexpected stop becomes mandatory for Industry, which asked Academia ideas, algorithms and procedures to monitor the health of the bearings and predict any incipient fault. In the last decades a huge number of publications covered analysis of vibration data of monitored bearing. A massive number of signal processing techniques have been suggested both on a physical model of the component, or pure blind data analysis, such as the so-called artificial intelligent systems (Artificial Neural Networks, Support Vector Machines, etc…). Most of these intelligent systems require two steps: a training step that “teaches” the system about the correct classification of the incoming data (e.g. into “health bearing” class or “damaged bearing”), and a test step when the inner rules build in the training step are tested on unknown data. There’s a lot interest on intelligent system approaches, since they promise to automatically build the classification rules and they could be applied to different components, not only on the ball bearing. Unfortunately there is a hidden trouble: the intelligent systems work well if the incoming data vectors work well, i.e. they properly describe the signal changes related to an incipient damage. The aim of this paper is to prove that the RMS and Kurtosis values of the vibration data are good parameters that allow a proper classification of the bearing. Moreover the variability of these parameters is close related to the evolution of the damage, suggesting a simple procedure to make the bearings diagnostics

2014 - Spatial acceleration modulus for rolling elements bearing diagnostics [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo; Cotogno, Michele
abstract

Rolling Elements Bearing (REB) condition monitoring is mainly based on the analysis of acceleration (vibration) signal in the load direction. This is one of the three components of the acceleration vector in 3D space: the main idea of this paper is the recovery of additional fault information from all the three acceleration vector components by combining them to obtain the modulus of the spatial acceleration (SAM) vector. The REB diagnostic performances of the SAM are investigated and compared to the load direction vibration by means of two rough estimators of the ‘‘Signal-to-Noise’’ ratio (SNR) and the Spectral Kurtosis. The SAM provides a higher SNR than the single load direction. Finally, Spectral Kurtosis driven Envelope analysis is performed for further comparison of the two signals: its results highlight that demodulation of the SAM isn’t strictly necessary to extract the fault features.

2013 - A window based method to reduce the end-effect in Empirical Mode Decomposition [Articolo su rivista]
Cotogno, Michele; Cocconcelli, Marco; Rubini, Riccardo
abstract

Empirical Mode Decomposition technique (EMD) is a recent development in non-stationary and non-linear data analysis. It is an algorithm which adaptively decomposes the signal in the sum of Intrinsic Mode Functions (IMFs) from which the instantaneous frequency can be easily computed. EMD has proven its effectiveness but is still affected from various problems. One of these is the “end-effect”, a phenomenon occurring at the start and at the end of the data due to the splines fitting on which the EMD is based. Various techniques have been tried to overcome the end-effect, like different data extension or mirroring procedures at the data boundary. In this paper we made use of the IMFs orthogonality property to apply a symmetrical window to the data before EMD for end-effect reduction. Subsequently the IMFs are post-processed to compensate for data alteration due to windowing. The simulations show that IMFs obtained with this method are of better quality near the data boundaries while remaining almost identical to classical EMD ones

2013 - Advances in Condition Monitoring of Machinery in Non-Stationary Operations [Curatela]
Dalpiaz, G.; Rubini, Riccardo; D'Elia, G.; Cocconcelli, Marco; Chaari, F.; Zimroz, R.; Bartelmus, W.; Haddar, M.
abstract

The growing interest of the industrial world on the topics covered by the CMMNO involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition. The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. The condition monitoring of machines, particularly if operating in non-stationary conditions, requires the measurement of appropriate parameters related to the operating conditions and wear to be monitored and the subsequent processing of the acquired signals for diagnostic purposes

2013 - An experimental approach to automatically classify children with cerebral palsy [Relazione in Atti di Convegno]
Cocconcelli, Marco; Reggiani, G.; Ferrari, A.; Rubini, Riccardo
abstract

This experimental study is aimed at automatically classify the large indistinct group of children affected by diplegic Cerebral Palsy (CP), into four main clinical forms characterized by homogeneous walking patterns as clinically proposed by Ferrari et al. The classification is based on the use of data gathered on 104 patients at LAMBDA (Laboratorio per l’Analisi del Movimento del Bambino DisAbile, S.M.Nuova Hospital, Reggio Emilia, Italy) by means of an 8 cameras optoelectronic system (Vicon, UK) and the Total3Dgait biomechanical protocol. This paper deals with the use of expert systems, such as artificial neural networks (ANN), that are able to learn by examples. ANN has been widely used in mechanics for the resolution of pattern recognition and diagnostic problems. Our aims is to extend the use of these expert systems to classify the four diplegic forms through the analysis of the rotation angles of the lower limb joints along multiple gait cycles. On each walking trial of each patient a set of synthetic statistical parameters representative of joint angles, has been used as input to train a supervised ANN in order to divide patients into the four forms a priori clinically determined. The first attempt consists in a Feed- Forward network trained considering data coming from all the four forms. The effectiveness of the resulting ANN has been proved on a data set acquired by new patiens. In this case, the performace on the form recognition was encouraging but still far from an implementation in clinical routine. In order to improve the efficiency we simplified the recognition problem by creating a network which was asked first to distinguish between two macro- categories, consisting of two forms each. On the basis of the two splitted dataset returned by this first ANN layer, two further network were trained seperately. To these network was finally asked to provide the affinity with one of the original four forms. In this “system of networks” case, the overall performance increased significantly becoming clinically meaningful

2013 - Application of cyclostationary indicators for the diagnostics of distributed faults in ball bearings [Relazione in Atti di Convegno]
D'Elia, G.; Delvecchio, S.; Cocconcelli, M.; Dalpiaz, G.
abstract

This paper deals with the detection of distributed faults in ball bearings. In literature most of the authors focus their attention on the detection of incipient localized defects. In that case classical techniques (i.e. statistical parameters, envelope analysis) are robust in recognizing the presence of the fault and its characteristic frequency. In this paper the authors focalize their attention on bearings affected by distributed faults, due to the progressive growing of surface wear or to low-quality manufacturing process. These faults can not be detected by classical techniques; in fact, in this case the signal does not contain impulses at the fault characteristic frequency, but more complex components with strong non-stationary contents. Distributed faults are here detected by means of advanced tools directly derived from the theory of cyclostationarity. In particular three metrics - namely Integrated Cyclic Coherence (ICC), Integrated Cyclic Modulation Coherence (ICMC) and Indicator of Second-Order Cyclostationarity (ICS2x) - have been calculated in order to condense the information given by the cyclostationary analysis and to help the analyst in detecting the fault in a fast fault diagnosis procedure. These indicators are applied on actual signals captured on a test rig where a degreased bearing running under radial load developed accelerated wear. The results indicated that all the three cyclostationary indicators are able to detect both the appearance of a localized fault and its development in a distributed fault, whilst the usual approach fails as the fault grows. Copyright © 2013 by ASME.

2013 - Bearing fault model for induction motor with externally induced vibration [Articolo su rivista]
Immovilli, Fabio; Bianchini, C.; Cocconcelli, Marco; Bellini, Alberto; Rubini, Riccardo
abstract

This paper investigates the relationship between vibration and current in induction motors operated under external vibrations. Two approaches are usually available to define this relationship. The former is based on airgap variations, the latter on torque perturbation. This paper is focused on the airgap variations model. The ball bearing fault is modeled by contact mechanics. External vibrations often occur in many industrial applications where external induced vibrations of suitable amplitude cause cyclic radial loading on the machine shaft. The model is validated by experiments, thanks to a dedicated test setup, where an external vibration source (shaker) was employed, together with ball bearing alterations in order to decrease the stiffness of the support along radial direction. To maximize the effects of externally induced vibrations, the frequency chosen was near the flexural resonance of the rotor (determined by FEM analysis). The direction of the external vibration is radial with respect to the axis of the electric machine under test. During tests, both stator phase currents and vibration of the machine were sampled. The test setup allowed to vary machine speed and load, vibration amplitude and bearing stiffness (damage level). Radial effects are usually visible only in case of large failures that result in significant airgap variations, as confirmed by experiments

2013 - Developing of a monitoring system for air bubbles detection in an internal gear pump [Relazione in Atti di Convegno]
Cotogno, Michele; Cocconcelli, Marco; Rubini, Riccardo
abstract

The presence of air bubbles inside an internal gears pump usually leads to fast pump damage and breaking. When bubbles enter the high pressure chamber they may implode releasing pressure waves in the fluid that ultimately detach material from the gears and other crucial pump parts. This paper recalls and describes the activities performed in order to develop a condition monitoring system able to indicate the presence of air bubbles in an internal gear pump that feeds the hydraulic system of a packaging machine: this pump experienced a breakdown after only 3 minutes of air bubbles flowing in it. Since the machine is supposed to work continuously, an unexpected stop has heavy consequences in terms of loss of production time: therefore the machine producer decided to implement the condition monitoring (CM) of the pump. The producer’s goal is to use the warnings/alarms generated by the CM algorithm as a supplemental machine control signal: this may eventually command the stop of the machine to preserve it (and consequently the machine functionality) from fast damaging. The main phases of the development had been: data recording and analysis, diagnostic parameters identification, algorithm development and final algorithm validation in field tests. The data recording campaign included the simultaneous acquisition of 14 quantities of 5 different kinds (vibration, pressure, temperature, electrical torque and angular speed). The data analysis highlighted one of the vibration signals as the most significant to be monitored. Several signal features were analysed from the in order to evaluate their diagnostic capability point of view (i.e.: the ability to detect the presence of air bubbles in the pump); five features are used by the CM algorithm for the bubbles warning/alarm generation, these being the RMS, the bandpass filtered signal RMS, the Signal Entropy, the Spectral Mean Square Error and the Spectral Cumulative Difference. Currently, the algorithm is being tested and validated on recorded data and a field test campaign is being scheduled

2013 - Diagnostics by means of Artificial Immune Systems: a different approach for the fault detection of bearings in non-stationary conditions [Capitolo/Saggio]
L., Montechiesi; Cocconcelli, Marco; Rubini, Riccardo
abstract

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2013 - Effectiveness of the Spatial Acceleration Modulus for rolling elements bearing fault detection [Articolo su rivista]
Cotogno, Michele; Cocconcelli, Marco; Rubini, Riccardo
abstract

Rolling Elements Bearing (REB) condition monitoring is mainly based on the analysis of acceleration (vibration) signal in the load direction. This is one of the three components of the acceleration vector in 3D space: the main idea of this paper is the recovery of additional fault information from the other two acceleration vector components by combining them to obtain the modulus of the spatial acceleration (SAM) vector. The REB diagnostic performances of the SAM are investigated and compared to the load direction of vibration by means a rough estimator of the “Signal-to-Noise” Ratio and the Spectral Kurtosis. The SAM provides a higher SNR than the single load direction. Finally, Spectral Kurtosis driven Envelope analysis is performed for further comparison of the two signals: its results highlight that demodulation of the SAM isn’t strictly necessary to extract the fault features, which are already available in the raw signal spectrum

2012 - A window based method to reduce the end-effect in empirical mode decomposition [Relazione in Atti di Convegno]
Cotogno, Michele; Cocconcelli, Marco; Rubini, Riccardo
abstract

Empirical Mode Decomposition technique (EMD) is a recent development in non-stationary and non-linear data analysis. It is an algorithm that adaptively decomposes the signal in the sum of Intrinsic Mode Functions (IMFs) from which the instantaneous frequency can be easily computed. Differently from the Fourier Transform, the EMD does not decompose a signal into stationary harmonic components, but into a finite and small number of IMFs based on the local characteristic time scale of the data. EMD has been widely applied in different fields as seismic studies, structural health monitoring, whether forecast, image processing and financial applications. More recently different authors proposed the use of EMD for condition monitoring purpose, e.g. in bearing or gear diagnostics. EMD has proven its effectiveness, but is still affected from various computational problems. One of these is the “end-effect”, a phenomenon occurring at the beginning and at the end of the data due to the splines fitting on which the EMD is based. Different spline fitting introduces different instantaneous frequency components that may unnecessarily complicate the data analysis. Various techniques have been tried to overcome the end-effect, like different data extension or mirroring procedures at the data boundary. This paper proposes a windowing process to manage the end-effect phenomenon. Recently other researchers have covered the windowing approach, suggesting classic windows like Hanning or flat-top, but results are highly dependent of the processed data. In this paper it has made use of the IMFs orthogonality property to apply a symmetrical polynomial window to the data before EMD for end-effect reduction. Subsequently the IMFs are post-processed to compensate for data alteration due to windowing. The procedure is applied to simulated data to easily take into account different kind of sources like trend, chirp, etc. The simulations show that IMFs obtained with this method may prove a reduced end-effect, while they are almost identical to classical EMD ones in other cases, depending on the data complexity.

2012 - An algorithm to diagnose ball bearing faults in servomotors running arbitrary motion profiles [Articolo su rivista]
Cocconcelli, Marco; L., Bassi; Secchi, Cristian; Fantuzzi, Cesare; Rubini, Riccardo
abstract

This paper describes a procedure to extend the scope of classical methods to detectball bearing faults (based on envelope analysis and fault frequencies identification)beyond their usual area of application. The objective of this procedure is to allowcondition-based monitoring of such bearings in servomotor applications, where typicallythe motor in its normal mode of operation has to follow a non-constant angularvelocity profile that may contain motion inversions. After describing and analyzingthe algorithm from a theoretical point of view, experimental results obtained on areal industrial application are presented and commented

2012 - Application of the artificial immune systems for bearings diagnostic in servomotors [Relazione in Atti di Convegno]
L., Montechiesi; Cocconcelli, Marco; Rubini, Riccardo
abstract

Nowadays in industries we can assist to a technological evolutionary phase in design of machineries, from asynchronous motor-based (AMB) actuation to servomotor-based (SMB) actuation. This new type merges together the functions of a motor, a gearbox and a cam into a unique element which is the servomotor. The main advantages are the removal of complex mechanical components like gearboxes and cams which are subjected to wear, need maintenance, etc…, an improved easiness in the setup changing and an increased acceptable complexity of the motion profile. The main drawback regards the diagnostics activity, e.g. on bearings, where classical methods based on the research of the fault frequencies in the signal spectrum cannot be applied anymore, due to the consistent variability in the speed of the shaft. This paper tackles the bearing diagnostic in servomotors by means of an unsupervised learning approach: the artificial immune system, which has been developed and applied with success in the field of computer security, and – as the name suggests – its aim is to mimic the behavior of the human immune system which is able to recognize health hazards, like virus, even if never seen before

2012 - Artificial Immune System for Condition Monitoring Based on Euclidean Distance Minimization [Relazione in Atti di Convegno]
L., Montechiesi; Cocconcelli, Marco; Rubini, Riccardo
abstract

In recent years new alternative diagnostics methodologies have emerged, with particular interest to machineries operating in non-stationary conditions, which have shown to be a severe limit for standard consolidated approaches. In particular this paper focuses on the condition monitoring of ball-bearings in variable-speed applications. In this context the paper aims to present a simple method inspired and derived from the mechanisms of the immune system, and its application in a real case of bearing faults recognition. The proposed algorithm is a simplification of the original process, adapted to a particular case of a much bigger class of algorithms and methods grouped under the name of Artificial Immune Systems, which have proven to be useful and promising in many different application fields. The proposed algorithm is based on the Euclidean distance minimization in the evaluation of the binding between antigens. Experimental results are also provided with an explanation of the algorithm functioning

2012 - Diagnostic approach for an automated filling machine: setupand preliminary results [Relazione in Atti di Convegno]
M., Cotogno; G., Prata; Cocconcelli, Marco; Fantuzzi, Cesare; Rubini, Riccardo
abstract

High production rate machinery is more sensitive to stops and maintenance strategy due to higher loss of production. This paper presents the initial steps of a methodology which aim to realize a condition monitoring system to be embedded on a medicine capsule filler machine. The first required is the gathering and classifying of the machine criticalities, and in this paper a FMEA (Failure Mode and Effects Analysis) is performed, resulting in a cam follower as the main machine fault cause. Subsequently the initial phases of the diagnostic parameter identification process are presented. In this case the parameters chosen are the machine vibration data coming from a triaxial sensor mounted in 4 different locations on the machine. The selection of the best combination of accelerometer-location/accelerometer-axis involves the evaluation of the averaged vibration data and some of their statistical indicator such peak level, RMS and kurtosis. This approach has been applied in a framework of a applied research supported by Emilia Romagna Region, with the cooperation of LIAM (Industrial Laboratory for Packaging Machine Automation) and the company I.M.A. (Industria Macchine Automatiche)

2012 - Kurtosis over Energy Distribution Approach for STFT Enhancement in Ball Bearing Diagnostics [Relazione in Atti di Convegno]
Cocconcelli, Marco; R., Zimroz; Rubini, Riccardo; W., Bartelmus
abstract

This paper focuses on the diagnostics of ball bearings under time varying speed conditions. Compared to classical demodulation techniques, time-frequency approach allows to take into account transient occurrence or non-stationary phenomena along the timeline. Among the different time-frequency approaches available the simplest is the Short Time Fourier Transform (STFT). From a practical point of view, its implementation in an industrial environment has a main drawback: the industry usually needs a scalar value as output (like a semaphore: green, yellow and red light) to assess the bearing condition, while time-frequency approaches produce a bi-dimensional map that needs to be interpreted. The authors suggest to combine the information gathered by spectral kurtosis and energy distribution for the automatic selection of a filtering band that could extract from the STFT map the most informative component in time domain, reducing the complexity of the output to a mono-dimensional vector. A simple check if the output exceed a given threshold can then be used to obtain a scalar value

2012 - Mounting of accelerometers with structural adhesives: experimental characterization of the dynamic response [Capitolo/Saggio]
Cocconcelli, Marco; Spaggiari, Andrea; Rubini, Riccardo; Dragoni, Eugenio
abstract

The use of accelerometers to monitor the vibrations of either complex machinery or simple component involves some considerations about the mounting of the sensor to the structure. Different types of mounting solutions are commonly used but in all cases they can be classified in one of these categories: stud mounting, screw mounting, adhesive mounting, magnetic mounting and probe sensing. Indeed each of them has a specific field of application depending on e.g. the mounting surface conditions, the temperature, the accessibility to the specific mounting point, etc. The choice of the mounting solution has a important effect on the accuracy of the usable frequency response of the accelerometer, since the higher the stiffness of the fixing, the higher the low-pass frequency limit of the mounting. This paper specifically focuses on adhesive mounting of accelerometers, which includes a great number of different products from the temporary adhesives like the beeswax to the permanent ones like cyanoacrylate polymers. Among the variety of commercial adhesives, three specific glues have been experimentally compared to assess their transmissivity and the results are reported in this paper. A two component methylmethacrylate (HBM X60), a modified silane (Terostat 737) and a cyanoacrylate (Loctite 401) adhesives have been used to joint two aluminium bases, one connected to an accelerometer and the other to the head of electromagnetic shaker. A design of experiments (DOE) approach was used to test the system at several levels of amplitude and frequency of the external sinusoidal excitation supplied by the shaker.

2012 - STFT Based Approach for Ball Bearing Fault Detection in a Varying Speed Motor [Relazione in Atti di Convegno]
Cocconcelli, Marco; R., Zimroz; Rubini, Riccardo; W., Bartelmus
abstract

This paper focuses on the diagnostics of ball bearings in direct-drivemotors. These specific AC brushless motors are increasing their importance in automation machineries because they can work with a built-in flexibility. In particular the angular displacement of the shaft is continuously monitored by an embedded encoder while the control system allows to perform complex motion profiles such as polynomial ones, even with the inversion of the rotating direction. Direct-drive motors avoid the presence of a mechanical cams or gearboxes between the motor and the load with a subsequent money-saving. On the other side, unfortunately, the diagnostics of ball bearing in those motors is not trivial. In fact most of the solutions proposed in the literature require a constant frequency rotation of the shaft since the characteristic fault frequencies are directly proportional to speed of the motor. It follows that in a varying speed application the fault characteristic frequencies change instantaneously as the rotational frequency does. In this paper an industrial application is considered, where the direct drive motors are used in the kinematic chain of an automated packaging machine performing a cyclic polynomial profile. The basic idea is to focus on signal segmentation using the position profile of the shaft – directly measured by the encoder – as trigger. Next the single cycles of the machine is analysed in time domain, again using encoder signal machine contribution is deleted. Feature extraction for damage detection is done by applying the Short Time Fourier Transform (STFT), the STFT for each cycle is averaged in time-frequency domain in order to enhance fault signature. Finally, the sum of STFT coefficients is used as a simple indicators of damage.

2011 - About the classification of the children with cerebral palsy by means of artificial neural network [Articolo su rivista]
Reggiani, G.; Ferrari, A.; Cocconcelli, Marco; Rubini, Riccardo
abstract

This preliminary study deals with the classification of thediplegic children affected by cerebral palsy (CP) – based on theprotocol for gait analysis Total3Dgait used in LAMBDA motionanalysis laboratory at S.M. Nuova Hospital of Reggio Emilia– using kinematics data and by means of artificial neural network(ANN). The classification systems for cerebral palsy (CP)need to be continuously updated, according to specific aims andto significant changes observed over the years in the panoramaof CP. Ferrari et al., proposed a classification system where issuggested to divide the diplegic children into four main clinicalforms, according to the patterns of walking observable in thesesubjects

2011 - Accelerometri MEMS: caratterizzazione dinamica e confronto con i sensoripiezoelettrici [Capitolo/Saggio]
G., Scirè Mammano; Cocconcelli, Marco; Rubini, Riccardo; Dragoni, Eugenio
abstract

Gli accelerometri di tipo piezoelettrico sono probabilmente i più diffusi sensori diaccelerazione attualmente in commercio per l’ambito industriale. Hanno infatti un’ampiabanda dinamica di linearità,sono influenzati in modo trascurabile da rumore etemperatura, e possono misurare elevati valori di accelerazione. Negli ultimi anni sonostati proposti sul mercato dei nuovi tipi di accelerometri di tipo MEMS (Micro Electro-Mechanical Systems) che hanno la caratteristica di essere molto meno costosi deipiezoelettrici sia per i materiali impiegati sia per il processo di fabbricazione di massa. Sefino a poco tempo fa la qualità degli accelerometri MEMS non era paragonabile a quelladei piezoelettrici, la continua evoluzione tecnologica ha estremamente ridotto le differenzetra le due tipologie di sensori. Lo scopo di questo articolo è di confrontare le prestazionidinamiche di alcuni accelerometri di tipo piezoelettrico e di tipo MEMS, per valutarne ledifferenze, qualità e difetti, e fornire un’introduzione alle problematiche che nascono nelpassaggio da una tecnologia all’altra

2011 - Combining blind separation and cyclostationary techniques for monitoring distributed wear in gearbox rolling bearings [Relazione in Atti di Convegno]
G., D' Elia; S., Delvecchio; Cocconcelli, Marco; G., Dalpiaz
abstract

This work seeks to study the potential effectiveness of the Blind Signal Extraction as a pre-processing tool for the detection of distributed faults in rolling bearings. In literature, most of the authors focus their attention on the detection if incipient localized defects. In that case classical techniques (i.e. envelope analysis) are robust in recognizing the presence of the fault and its characteristic frequency. However, when the fault grows, the usual approach fails, due to the change of the fault signature. De facto, in this case the signal does not contain impulses at the fault characteristic frequency, but more complex components with strong non-stationary contents. Moreover, signals acquired from complex machines often contain contributions from several different components as well as noise; thus the fault signature can be hidden in the complex system vibration. Therefore, pre-processing tools are needed in order to extract the bearing signature, from the raw system vibration. In this paper authors focalize their attention on the application of Blind Signal Extraction (BSE) in order to extract the bearing signature from the raw vibration of a gearbox. The effectiveness and sensitivity of BSE is here exploited on the basis of both simulated and real signals. Firstly a simulated signal including the effect of gear meshing as well as a localized fault in bearings is introduced in order to tune the parameters of the BSE algorithm. Next, real vibration signals acquired from a gearbox where tow degreased bearing developed accelerated wear are analysed. In particular, the BSE is compared with the usual pre-processing technique for the analysis of cyclostationary signals, i.e. the extraction of the residual signal. The fault detection is carried out by the computation of the Integrated Cyclic Modulation Spectrum (ICMS) on the extracted signals. The results indicate that the extracted signals via BSE clearly highlight the distributed fault signature, in particular both the appearance of the faults as well as their development are detected, whilst noise still hides fault grow in the residual signals

2011 - Currents and Vibrations in Asynchronous Motor with Externally Induced Vibration [Relazione in Atti di Convegno]
Immovilli, Fabio; Bianchini, C.; Cocconcelli, Marco; Bellini, Alberto; Rubini, Riccardo
abstract

This paper presents an experimental investigation ofthe airgap variation model for vibration and current harmonicsrelationship in induction motors. To this aim, an external vibrationsource was employed, together with ball bearing alterationsin order to decrease stiffness. The direction of the externalvibration is radial with respect to the axis of the electricmachine under test. To maximize the effect of externally inducedvibrations, the frequency chosen was near the flexural resonanceof the rotor, determined by FEM analysis.During tests both currents and vibration of the machine wereacquired. The test rig allowed to vary speed, vibration level andbearing stiffness. An electromagnetic brake provided a variableoutput load for the electric machine. The focus of the paper isthe review of fault models used in literature. Radial effects areusually visible only in case of large failures that result in air-gapvariations, as the experiments confirmed

2011 - Diagnostics of Ball Bearings in Varying-Speed Motors by Means of Artificial Neural Networks [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo; R., Zimroz; W., Bartelmus
abstract

This paper deals with the diagnostics of ball bearings in direct-drive motors by means ofArtificial Neural Networks (ANN). Direct-drive motors are becoming commonly usedin automatic machines, e.g. in the field of packaging, since these motors are easilydriven by the control system to perform polynomial profiles of motion avoiding thepresence of gears train or cams between the motor and the load. An ordinary task of themotor involves continuous changes of the shaft speed and a cyclic inversion of itsrotating direction. The continuous change of rotational speed of the motor represent themain drawback in terms of diagnostics of the ball bearing, since the large part ofalgorithms proposed in the literature need a constant rotation frequency of the motor toidentify fault frequencies in the spectrum. In this paper the use of Artificial NeuralNetworks overcomes the constant-speed limits and they are proven to be a powerful toolto diagnose the health of ball bearing even in variable-speed applications

2011 - Fault Detection of Linear Bearings in Brushless AC Linear Motors by Vibration Analysis [Articolo su rivista]
Bianchini, C.; Immovilli, F.; Cocconcelli, M.; Rubini, R.; Bellini, A.
abstract

Electric linear motors are spreading in industrial automation because they allow for direct drive applications with very high dynamic performances, high reliability, and high flexibility in trajectory generation. The moving part of the motor is linked to the fixed part by means of linear bearings. As in many other electric machines, bearings represent one of the most vulnerable parts because they are prone to wear and contamination. In the case of linear roller bearings, this issue is even more critical as the rail cannot be easily fully enclosed and protected from environmental contamination, unlike the radial rotating bearing counterpart. This paper presents a diagnostic method based on vibration analysis to identify which signature is related to a specific fault

2011 - Overview on condition monitoring for bearings in variable speedconditions: the example of a packaging machine [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper proposes a review of some techniques for the diagnostics of ball bearingbased on the experience of the authors on an industrial application. Frequently engineering industrysuggests non-trivial problems and new fields of research for the academy. This is the case of bearingdiagnostics in direct-drive motors, for example. Direct-drive are brushless motors fully controlledby the drive system. Thanks to an encoder or a resolver mounted on the shaft they could performcomplex motion profiles such as polynomial or splines, including reverse rotation of the shaft. Themain advantage of direct-drive motors is the removal of cams or gearboxes afterwards the motorwith a consequent reduction of economic and maintaining costs. Indeed the main drawback is thedifficulty to make diagnostics on their bearings. Regarding the bearing diagnostics, most of theliterature techniques are based on the search of fault-characteristic frequencies in the vibration spectrumof the motor. These fault frequencies are linearly dependent on the rotational frequency of theshaft supposing it is constant. In direct-drive motors the rotational speed changes continuously andconsequently the fault frequencies are meaningless. Diagnostics of machineries in non-stationaryconditions is attractive and promising field and recently different papers have been proposed in literature[1] and thematic conference [2] organized, covering a wide range of applications, e.g. frommanufacturing [3] to mining industry [4]. Focusing on a specific industrial case the authors runthrough their experience on bearing diagnostics for a packaging machine working under variablespeed condition. The developed techniques include an improved version of the order tracking, theuse of correlation function, wavelet analysis and two supervised learning approaches: the artificialneural networks and the support vector machines. Moreover the closing part of the paper covers thebearing diagnostics by mean of the stator current signal analysis of the motor

2011 - STFT based Spectral Kurtosis and Energy Distribution approach for ball bearing fault detection in a varying speed motor [Relazione in Atti di Convegno]
Cocconcelli, Marco; R., Zimroz; Rubini, Riccardo; W., Bartelmus
abstract

This paper focuses on the diagnostics of ball bearings in direct-drive motors. These specific AC brushless motors are increasing their importance in automation machineries because they can work with a built-in flexibility. In particular the angular displacement of the shaft is continuously monitored by an embedded encoder while the control system allows to perform complex motion profiles such as polynomial ones, even with the inversion of the rotating direction. Direct-drive motors avoid the presence of a mechanical cams or gearboxes between the motor and the load with a subsequent money-saving. On the other side, unfortunately, the diagnostics of ball bearing in those motors is not trivial. In fact most of the solutions proposed in the literature require a constant frequency rotation of the shaft since the characteristic fault frequencies are directly proportional to speed of the motor. It follows that in a varying speed application the fault characteristic frequencies change instantaneously as the rotational frequency does. Moreover the direct link between the motor and load introduces dynamical effects on the vibration signal of the bearing by means of the load variations. In this paper an industrial application is considered, where the direct drive motors are used in the kinematic chain of an automated packaging machine performing a cyclic polynomial profile. The basic idea is to focus on signal segmentation using the position profile of the shaft – directly measured by the encoder – as trigger. Next the single cycles of the machine is analysed in time domain, again using encoder signal machine contribution is deleted. Feature extraction for damage detection is done by applying the Short Time Fourier Transform (STFT), the STFT for each cycle is averaged in time-frequency domain in order to enhance fault signature. For Averaged Cyclic STFT , the Spectral Kurtosis is used to select the optimal frequency band. To support this decision an Energy Distribution in frequency domain is used. Finally, the sum of STFT coefficients is used as a simple indicators of damage. Detection of the status of the bearing can be done automatically

2011 - Software per la diagnostica di difetti di usura distribuita in cuscinetti a sfere attraverso l’analisi vibrazionale [Relazione in Atti di Convegno]
Cocconcelli, Marco; S., Delvecchio; Rubini, Riccardo
abstract

Utilizzare la tecnica della Densità di Correlazione Spettrale applicataal segnale di vibrazione per ottenere un grafico che permetta divisualizzare la presenza e la posizione del difetto di usura distribuitain cuscinetti a sfere. Si sfruttano le potenzialità dell’ ambiente diprogrammazione LabVIEW e del relativo toolkit Sound and Vibrationper effettuare l’ implementazione di tale tecnica

2011 - Support Vector Machines for Condition Monitoring of Bearings in a Varying-Speed Machinery [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper deals with the diagnostics of ball bearings in direct-drive motors by means ofSupport Vector Machines (SVM). For the new generation of packaging machines,direct-drive motors have substituted parts of the mechanical transmission chains asgears train or cams between the motor and the load. In fact, a position feed-back is usedby the control system to perform polynomial profiles of motion involving continuouschanges of the shaft speed and a cyclic inversion of its rotating direction.The presenceof complex shaft dynamics provides a vibration signal extremely noisy, where theevents due to malfunctions or damages disappear and are not periodic, so the classicmethodologies for the monitoring of the support conditions based on the signal analysisin the frequency domain are ineffective. In this paper the use of Support VectorMachines overcomes the constant-speed limits and the SVM are proven to be apowerful and reliable tool to diagnose the health of ball bearing even in variable-speedapplications, based on experimental tests conducted on an industrial packaging machine

2011 - Use of Neural Networks in Children’s Cerebral Palsy Recognition by Gait Analysis Data [Capitolo/Saggio]
Reggiani, G.; Cocconcelli, Marco; Rubini, Riccardo; Borghi, C.; Ferrari, A.
abstract

The classification systems for cerebral palsy (CP) need to be continuouslyupdated, according to specific objectives and to significant changes observed over theyears in the panorama of CP. Ferrari et al. [1], recently proposed a classification systemthat aimed at subdividing the diplegic children into four main clinical sub-forms, on thebase of their walking pattern. This preliminary study deals with the classification of thediplegic children affected by CP and it is based on the walking pattern classification systemproposed by Ferrari and utilized in LAMBDA motion analysis laboratory at S. MariaNuova Hospital of Reggio Emilia. Using kinematics data recorded by means of anoptoelectronic system on children affected by CP, an Artificial Neural Network (ANN) wasimplemented to allow an automatic recognition of the form of the palsy. The ANN proposedcorrelates a set of suitable statistical parameters of the kinematics of walking with the typeof diplegic clinical form. The effectiveness of the resulting neural network has been provedon a control set of data

2010 - An Algorithm to Diagnose Ball Bearings Faults in Servomotors Running Arbitrary Motion Profiles [Relazione in Atti di Convegno]
L., Bassi; Cocconcelli, Marco; Secchi, Cristian; Rubini, Riccardo; Fantuzzi, Cesare
abstract

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2010 - Detection of Generalized Roughness on Ball Bearing by Cyclostationarity Technique [Relazione in Atti di Convegno]
G., D'Elia; Cocconcelli, Marco; Rubini, Riccardo
abstract

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2010 - Detection of the Centre of Pressure for the Double-Contact Problem between Feet and Platform in Gait Analysis [Capitolo/Saggio]
Cocconcelli, Marco; Rubini, Riccardo; Ferrari, A.; Costi, Stefania
abstract

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2010 - Diagnostics of distributed faults in ball bearings by means of vibration cyclostationary indicators [Relazione in Atti di Convegno]
D'Elia, Gianluca; Delvecchio, Simone; M., Cocconcelli; Dalpiaz, Giorgio
abstract

2010 - Sul riconoscimento delle forme di spasticità nella paralisi celebrale infantile mediante reti neurali [Relazione in Atti di Convegno]
Reggiani, G.; Ferrari, A.; Cocconcelli, Marco; Rubini, Riccardo
abstract

Il presente lavoro ha l’intento di presentare uno studio preliminare su un sistema di riconoscimento delle forme di spasticità della Paralisi Cerebrale Infantile (PCI), basato sul protocollo di analisi del movimento Total3Dgait in uso presso il LAMBDA (Laboratorio per l’Analisi del Movimento del Bambino DisAbile) dell’Arcispedale S.M. Nuova di Reggio Emilia [1], a partire dai dati rilevati ed elaborati da sistemi di analisi del cammino e classificati tramite l’utilizzo di reti neurali

2010 - Use of Neural Networks in Road Recognition by Vibration Data [Relazione in Atti di Convegno]
G., Reggiani; Cocconcelli, Marco; Rubini, Riccardo
abstract

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2010 - Wavelet Decomposition and Energy Distribution as Ball-Bearing Diagnostics Tools in Direct-Drive Motors [Relazione in Atti di Convegno]
G., Curcurù; Cocconcelli, Marco; Rubini, Riccardo
abstract

In the last decade different methodologies have been proposed for the detection of incipient bearing failures. Vibration measurements in both time and frequency domains have been used for the detection of localized defects. In this research, particular attention is given to dif-ferent wear evolution. In case of generalized roughness (due to contaminations, lack or loss of lubrication, corrosion, humidity, etc.), classical spectral analysis of the vibration signal does not exhibit characteristic frequencies but only unpredictable broadband changes. Furthermore, when direct-drive motors are employed – e.g. in the packaging machines – to provide complex laws of motion, interactions between different parts of the bearings are not periodic, so the detection of failures cannot be performed in the frequency domain. A wavelet based decomposition of the stator current is here proposed for the detection of generalized roughness of bearings in direct-drive motors. Stator current energy, computed in each node of the decomposition, is used as fault indicator and the frequency band, which is most sensitive to the degradation process, is identified. Experimental results are presented for different mo-tors with different working hours, operating in an industrial environment. In particular analy-sis of energy distribution among bandwidth in the wavelet decomposition is done and a com-parison between the energy level in healthy and faulty cases completes the paper. The results are normalized with respect to a healthy motor.

2009 - Comparison Between Time-Frequency Techniques to Predict Ball Bearing Fault in Drives Executing Arbitrary Motion Profiles [Relazione in Atti di Convegno]
Cocconcelli, Marco; Secchi, Cristian; Rubini, Riccardo; Fantuzzi, Cesare; Bassi, L.
abstract

In this paper Wavelet Transform (WT) and Hilbert-Huang Transform (HHT) are used as bearing diagnostics tools in drives executing arbitrary motion profiles. This field is increasingly drawing the attention of the industries because the modern electric motors work as electric cams inducing the shaft to move with a cyclic variable-velocity profile. The literature papers take into account only a constant velocity profile and they are not suitable for such applications. In fact literature methods analyse the signal only in the frequency domain, while in variable-velocity condition the bearing diagnostics should be performed in time domain. Both WT and HHT are time-frequency techniques which describe an input signal as a sum of specific functions. These functions are compared with a signal which simulates the expected vibrations of a bearing with a given fault, e.g. on the outer race. The comparison is done through a cross-correlation between the expected signal and the time-frequency techniques output. WT and HHT are used separately in an industrial case, which consists in bearing fault prediction in an automated packaging machine. In the end of the paper the WT and HHT results are discussed to analyse the different responses.

2009 - Correlation Between the Stator Current Signal and the Kinematic Model of the Rolling Bearing for the Diagnostics [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo
abstract

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2009 - Detection of Generalized Roughness Bearing Fault by Spectral Kurtosis Energy by Vibration or Current Signals [Articolo su rivista]
Immovilli, Fabio; Cocconcelli, Marco; Bellini, Alberto; Rubini, Riccardo
abstract

Generalized roughness is the most common damage occurring to rolling bearing. It produces a frequency spreading of the characteristics fault frequencies, thus being difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is here proposed in order to identify the spreading bandwidth related to specific conditions, relying on current or vibration measurements only. Then a diagnostic index based on the computation of the energy in the above defined bandwidth is used to diagnose bearing faults. The proposed method was validated experimentally with vibration signals, with robust and reliable results. The same procedure can be extended to current signals.

2009 - Fault Diagnosis of Linear Bearings in Brushless AC Linear Motors [Relazione in Atti di Convegno]
Bianchini, C.; Immovilli, Fabio; Cocconcelli, Marco; Rubini, Riccardo; Bellini, Alberto
abstract

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2009 - Introduction to a Simply and Fast Algorithm for Variable Speed Bearing Diagnostics [Capitolo/Saggio]
Cocconcelli, Marco; Rubini, Riccardo
abstract

In this paper a new algorithm for variable speed bearing diagnostics isproposed. The diagnostics of ball-bearing is used to be focused on constant speedapplications. In fact at constant speed bearing faults cause a vibration with particularcharacteristics that the analysis in the frequency domain reveals. The geometry of thebearing parts allows to find the correlation between faults frequencies and the rotationalfrequency of the shaft on which the bearing is mounted on. If the shaft moves with variablespeed or motion inversion, the instantaneous rotation frequency changes continuouslyand no fault characteristic frequency are available. Under the hypothesis that the shaftposition profile is known, this paper suggests to perform the diagnostics on variable speedapplications in two steps. In the first one both bearing geometry and the shaft positionprofile are used to make a simulated fault signal which is expected if a specific fault wouldbe present, while in the second step a comparison between the simulated signal and the realvibration signal is made in order to verify the presence of the fault in the bearing. Differenttest-studies are reported in order to validate the algorithm.

2009 - On the Detection of Distributed Roughness on Ball Bearings Via Stator Current Energy: Experimental Results [Relazione in Atti di Convegno]
G., Curcurù; Cocconcelli, Marco; Immovilli, Fabio; Rubini, Riccardo
abstract

This paper deals with the detection of distributed roughness on ball-bearings mounted on electric motors. Ball bearings allows the rotation of the motor’s shaft and moreover they are intensively used in industrial applications, so a failure of those components produces unexpected downtime of the line-production. Most of the literature techniques focus on the early detection of localized faults on bearing (e.g. on the outer ring) in order to determine the bearing life and to plan the bearing replacing. Localized faults can be detected because they have characteristic signatures which is revealed in the frequency spectrum of the vibration signal acquired by an external sensor, e.g. accelerometer. Unfortunately other faults exist which do not have a characteristic signatures and then they could not be foreseen accurately: e.g. the distributed roughness. In this paper the motor stator current energy is proposed as a fault indicator to identify the presence of the distributed roughness on the bearing. Moreover an orthogonal experiment is set to analyse, through a General Linear Model (GLM), the dependencies of the current energy to the roughness level, and two environmental conditions: the motor velocity and the loads applied externally. ANOVA investigates the statistical significance of the considered factors

2009 - On the Detection of Distributed Roughness on Ball Bearings Via Stator Current Energy: Experimental Results [Articolo su rivista]
G., Curcuru'; Cocconcelli, Marco; Immovilli, Fabio; Rubini, Riccardo
abstract

This paper deals with the detection of distributed roughness on ball-bearings mounted on electric motors. Ball bearings allows the rotation of the motor’s shaft and moreover they are intensively used in industrial applications, so a failure of those components produces unexpected downtime of the line-production. Most of the literature techniques focus on the early detection of localized faults on bearing (eg. on the outer ring) in order to determine the bearing life and to plan the bearing replacing. Localized faults can be detected because they have characteristic signatures which is revealed in the frequency spectrum of the vibration signal acquired by an external sensor, eg. accelerometer. Unfortunately other faults exist which do not have a characteristic signatures and then they could not be foreseen accurately: eg. the distributed roughness. In this paper the motor stator current energy is proposed as a fault indicator to identify the presence of the distributed roughness on the bearing. Moreover an orthogonal experiment is set to analyse, through a General Linear Model (GLM), the dependencies of the current energy to the roughness level, but also to other two environmental conditions: the motor velocity and the loads applied externally. ANOVA investigates the statistical significance of the considered factors.

2009 - Relationship Between Vibration Energy and Wear Condition of Ball Bearings Based on Reye’s Hypothesis [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo
abstract

This paper deals with the study of the correlation between the dynamic behavior of a failed ball bearing and wear defect development. Ball bearings are intensively used in industrial applications as supports for rotating machines, so a failure of those components produces unexpected downtime of the line-production. Most of the literature techniques focus on the early detection of localized faults on bearings (e.g. on the outer ring), but more recently some authors have also worked on distributed faults (e.g. generalized roughness).This paper focuses on distributed faults, in particular on the consequences of a lack of grease in ball bearings. This condition happens when the bearing is not maintained correctly or when it works in hostile conditions (e.g. chemical attack). In such cases there is not a pure rotation of the bearing spheres but friction between races and spheres. As a consequence, the presence of an external load generates friction forces which damage the bearing surfaces and increase the bearing vibration. This paper propose a new approach based on Reye’s hypothesis to assess the wear of the bearing surfaces. According to Reye’s hypothesis the mechanical work of the friction force is proportional to the material volume removed by reason of wear. By means of experimental tests it is possible to evaluate the proportional coefficient and to determine the relationship between the typology and intensity of the vibrations and the failure evolution. The aim of this work is to provide a monitoring methodology able to predict the residual life of the support

2008 - Analisi di Sensibilità di una Macchina Equilibratrice al variare di Parametri Cinematici e Dinamici [Capitolo/Saggio]
Cocconcelli, Marco; Rubini, Riccardo
abstract

Vengono riportati i risultati della simulazione dinamica di un equilibratore perruote da autotrazione allo scopo di individuare il legame tra differenti soluzioni costruttive esensibilità allo squilibrio dei trasduttori di misura. Basato su un recente brevetto [1], ildispositivo – del quale è stato realizzato un modello a parametri concentrati – unisce unaelevata sensibilità caratterizzata dalla flessibilità torsionale di particolari giunti complianti, aduna notevole precisione di lavoro ottenuta con una originale costruzione che introduce nelsistema due nuovi vincoli cinematici virtuali.

2008 - Diagnosis of mechanical faults by Spectral Kurtosis Energy [Relazione in Atti di Convegno]
Bellini, Alberto; Cocconcelli, Marco; Immovilli, Fabio; Rubini, Riccardo
abstract

Generalized roughness is the most common damage occouring to roller bearing. It produces a frequency spreading of the characteristics fault frequencies, thus being difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is here proposed in order to identify the spreading bandwidth related to a specific conditions, relying on current measurements only. Then a diagnostic index based on the computation of the energy in the above defined bandwidth is used to diagnose bearing faults. The proposed method was validated experimentally with vibration signals, with robust and reliable results. Subsequently it has been applied to stator currents monitoring.

2008 - Predictive maintenance of ball bearings for machines rotating with arbitrary velocity profiles [Relazione in Atti di Convegno]
Cocconcelli, Marco; Secchi, Cristian; Rubini, Riccardo; Fantuzzi, Cesare; Bassi, L.
abstract

Recent research and development on direct–drive motor technology and on their control system push forwardthe application of these devices as electric cams in a large numbers of industrial applications, such as examplemotion control system for packaging machineries. Performances of these devices are much higher than themechanical solutions for machine motion, in terms of precision and operational speed, and, of course, intime required to reconfigure the motion profile.However, classical approaches to the ball bearing diagnosis that use analysis of vibration signals are notlonger applicable, as they have been developed on the hypothesis of drive constant speed. In fact, in mostof the current industrial application, the control system drives the motor to follow a complex and cyclic (i.e.motor shaft reverses its motion direction at each operational cycle) non constant speed motion profile.In those application, even Computed Order Tracking [1] (COT), which is the main fault bearing diagnosistechnique used in non-constant velocity applications, fails to detect incipient faults, as highlighted by Fyfeand Munck in [2].This paper presents a new procedure that modifies the COT to be successfully applicable to the diagnosisproblem of ball bearings in variable speed motion applications.

2007 - A Kineto-Elastodynamic Model of a Compliant Mechanism [Relazione in Atti di Convegno]
Cocconcelli, Marco; Rubini, Riccardo
abstract

Ivalo, Finland