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Riccardo RUBINI

Professore Ordinario
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 - 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


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 - 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.


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 - 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

Piezoelectric accelerometers are commonly employed for diagnosing machine faults, due to their accuracy. In the last few years, however, MEMS (Micro Electro-Mechanical Systems) accelerometers have attracted strong interest thanks to their low cost. In this work, a synchronous electric motor with an integrated MEMS sensor is studied and results are compared from both MEMS and piezoelectric sensors. A modal analysis is performed, using data from all available sensors. Comparing the frequency response functions and the natural frequencies shows the limitations of the MEMS sensor. One can then correct the MEMS measurements, by using global statistical parameters calculated on the data or by defining a “filter” function between the signals, thus improving the signal-to-noise ratio. It is found that MEMS sensors may replace piezoelectric ones for diagnostic applications. This way, an inexpensive measurement system (which needs to be calibrated only once, before installation, against higher-accuracy sensors) can be used for vibration monitoring of electric motors.


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 - Reliability of a resistance spot welding process based on characteristics parameters [Relazione in Atti di Convegno]
Strozzi, Matteo; Grosso, Pasquale; Mottola, Giovanni; Rubini, Riccardo
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.


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 - 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 - 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.


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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: a Critical Comparison [Articolo su rivista]
Immovilli, Fabio; Bellini, Alberto; Rubini, Riccardo; C., Tassoni
abstract

Mechanical imbalances and bearing faults account for a large majority of faults in a machine, especially for smallmedium size machines. Therefore their diagnosis is an intensively investigated field of research. Recently many research activities were focused on the diagnosis of bearing faults by current signal. This paper compares the bearing fault detection capability obtained with vibration and current signals. The paper contribution is the use of a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults, modeled as a torque disturbance, and current components. The focus of the paper is on the theoretical development between torsional torque and current component amplitudes and a review of fault models used in literature. Another contribution is the realization of realistic incipient faults and their experimental validation. Radial effects are visible only in case of large failures that result in air-gap variations. Experiments are reported that confirm the proposed approach.


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 [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 - 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 - 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 bearing faults of induction machines by vibration or current signals: a critical comparison [Relazione in Atti di Convegno]
Bellini, Alberto; Immovilli, Fabio; Rubini, Riccardo; C., Tassoni
abstract

Early diagnosis of faults in induction machines is an extensively investigated field, for cost and maintenance savings.Mechanical imbalances and bearing faults account for a large majority of faults in a machine,especially for small-medium size machines. Therefore their diagnosis is an intensively investigatedfield or research.Recently many research activities were focused on the diagnosis of bearing faults by currentsignal. Stator current components are generated at predictablefrequencies related to the electrical supply and mechanical frequenciesof bearing faults. However their detection is not always reliable, since the amplitude of fault signaturesin the current signal is very low.This paper compares the bearing fault detection capabilityobtained with vibration and current signals.To this aim a testbed is realized that allows to testvibration and current signal on a machine with healthyor faulty bearings. Signal processing techniquesfor both cases are reviewed and compared in order toshow which procedure is best suited to the differenttype of bearing faults. The paper contribution is the use of a simple and effectivesignal processing technique for both current and vibrationsignals, and a theoretical analysis of the physical link betweenfaults and current components including torque ripple effects. As expected becauseof the different nature of vibration and current, bearingfault diagnosis is effective only for those fault whose mechanicalfrequency rate is quite low.Experiments are reported that confirm the proposed approach.


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


2007 - Dynamic modelling of composite acoustic boxes for automotive applications [Articolo su rivista]
Castagnetti, Davide; Dragoni, Eugenio; Rubini, Riccardo
abstract

Abstract: Automotive components must withstand shock loads and random vibrations during service which heavily affect their structural integrity. In this paper, an automotive acoustic box supporting two speakers for a car radio system is analysed. The box is made of talc-reinforced polypropylene, an injection-mouldable polymer. Shock load analysis and random response analysis are performed.


2007 - Effetto della posizione di montaggio del volano [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

Brescia, Italy


2006 - Simulazione dinamica e sintesi strutturale per il contenimento delle vibrazioni di un cogeneratore termoelettrico [Relazione in Atti di Convegno]
Benetti, Matteo; Castagnetti, Davide; Dragoni, Eugenio; Rubini, Riccardo; E., Zanichelli
abstract

This paper deals with the design and the vibration analysis of a small-size (30 kVA) cogeneration unit, which can produce electric and thermal energy both for domestic and industrial appliances. To optimize the machine unsatisfactory dynamic behaviour (vibrations and noise), a discrete system approach was at first considered, also employing the design of experiments (DOE) technique to easily attain the best solution, then FEM analysis and measures with accelerometers on a prototype were performed. The solutions obtained allowed a significant improvement of the cogenerator behaviour, without adding any costs, being the final structure of the machine almost equal to the original version.


2006 - Towards Object-Oriented Modeling of Complex Mechatronic Systems for the Manufacturing Industry [Relazione in Atti di Convegno]
Zanichelli, D; Secchi, Cristian; Rubini, Riccardo; Fantuzzi, Cesare; Bonfe', M; Borghi, D; Borsari, R; Sacchetti, E.
abstract

The advantages of object-oriented modeling, as modularity and reusability of components, are very important also for modeling manufacturing systems and not only for software development. In [1] a unified object-oriented approach for modeling both the logical and the physical part of a manufacturing machine has been proposed. In this paper we report an industrial application of this modeling strategy and the case study consists of the package forming unit of a filling machine for liquid food packaging, developed by Tetra Pak Carton Ambient S.p.a.


2003 - An experimental investigation on the sound emissionof an electrical pump [Articolo su rivista]
Dumas, Antonio; Rubini, Riccardo; G., Semprini
abstract

The noise emitted by an electrical pump is mainly generated by different sources, (mechanic impats of rotor, fluid dynamic turbolences) but it is also affected by th structural response of each component of the pump. In this paper experimental results of the acoustic characterisation of an electrical pump is presented in order to point out the influence of different noise sources to the emitted noise power. Different techniques of investigations have been performed: measurements of the acoustic field are carried out and compared with vibration response of the pump. A parallel investigation of the thermograph radiation during the start up was also performed in order to a better understanding of the localisation on noise sources


2003 - Problematiche di aspirazione e di rumorosità per le elettropompe a palette [Altro]
Dumas, Antonio; Semprini, G; Rubini, Riccardo; Seghedoni, L.
abstract

.


2002 - Localizzazione del difetto in un albero dalla misura degli spostamenti delle frequenze di vibrazione torsionale [Altro]
Rubini, Riccardo
abstract

In questo manoscritto è stata calcolata la Sensibilità Modale Locale alla Cricca per un albero in differenti condizioni al contorno soggetto a vibrazioni torsionali. Misurando la variazione del comportamento dinamico del corpo dovuta alle sue modifiche strutturali, questa funzione ha permesso di individuare e localizzare con buona precisione fratture anche di lieve profondità realizzate sull’albero


2002 - On the Source of Vibrations in Damaged Rolling Bearings [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

Rolling element bearings are the most widely used machine elements, so a great effort has been devoted to the development of effective procedures for their monitoring and diagnostics. Today, several signal processing techniques provide useful methodologies to extract diagnostic information from the vibrations of the machines, on the basis of estimated relations between cause and effect. One can state that vibration occurs due to the interaction between a damaged surface and a rolling element during machine running. However, the actual source of the vibration measured on the case is not completely clear. Usually, it is described as an impact, but the way of this hypothetic impact is difficult to explain. As a matter of fact, a rolling element in a bearing is highly loaded; when it strikes a surface defect, a brusque stiffness decrease takes place, caused by the lack of material corresponding to the damage. This sudden variation of load distribution between rolling elements seems a realistic hypothesis as a source of vibration. In this paper, a multi-degree of freedom non-linear model is implemented to determine the characteristics of the ball-race interaction in the loaded zone of a ball bearing. It simulates the dynamic behaviour of each rolling element in the presence of surface pitting. The variation of load distribution when the bearing runs is investigated both for integer and damaged bearing. A bearing without any surface damage but machined to introduce a stiffness variation is then studied and similarity between its behaviour and that of a damaged bearing is demonstrated. Experimental results confirm this outcome


2001 - A MDOF Model to Predict Ball-Race Interaction in a Damaged Roller Bearing [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

In the last few decades, machine diagnostics has undergone considerable developments in the direction of Predictive Maintenance. The state of the art in the field of machine monitoring suggests vibration analysis as the best approach to reach appreciable and reliable results. This technique is based on the identification and surveillance of the vibration source - constituted by elements such as shafts, belts, gears and rolling bearings - picking out machine case vibration, usually on a support. Rolling bearings are the most widely used machine elements, so a great deal of work has been dedicated to the development of effective procedures for their monitoring and diagnostics. However, little work has been focused on determining the actual dynamical behaviour of rolling elements during their impact on default: better knowledge of this behaviour should improve diagnostic technique application. The present work is the outcome of an extensive study carried out by the Authors [3,4], in order to relate the characteristics of a defect – shape, dimension and depth – to the signal picked up by a transducer mounted on the case


2001 - Application of the Envelope and Wavelet Transform Analyses for the Diagnosis of Incipient Faults in Ball Bearings [Articolo su rivista]
Rubini, Riccardo; Meneghetti, U.
abstract

Fatigue faults on the surface of rolling bearing elements are some of the most frequent causes of malfunctions and breakages of rotating machines. In normal operating conditions this kind of damage can be revealed by classical vibration analyses, such as Spectral or Envelope ones. Furthermore, this last technique - by working in time domain - makes it possible to monitor the longitudinal dimension of the defect. In this paper the limits of the mentioned methodologies are presented by showing their application to bearings affected by different pitting failures on the outer or inner race or a rolling element and subjected to a very low radial load. Results are compared with that obtained by an advanced signal processing method based on the evaluation of the Wavelet Transform. Effects of fault evolution are investigated.


2001 - Simulazione del comportamento dinamico di un elemento volvente in un cuscinetto integro e danneggiato: modello a più gradi di libertà [Altro]
Rubini, Riccardo
abstract

Il comportamento dinamico di un cuscinetto volvente danneggiato è un fenomeno complesso frutto della sovrapposizione di molteplici effetti: l’intensità delle forze di contatto – variabile in funzione della posizione dei corpi volventi rispetto alla direzione di applicazione del carico esterno – le dimensioni geometriche ed il numero di corpi volventi, la velocità di rotazione relativa tra gli anelli esterno ed interno, la posizione, la forma e la dimensione del difetto superficiale.In questo articolo, viene proposto un modello a parametri concentrati con un numero di gradi di libertà pari a quello dei corpi volventi che formano il cuscinetto in esame, al fine di perfezionare quello ad un grado di libertà creato in un lavoro precedente (Rubini e Meneghetti, 2001)


2001 - Simulazione del comportamento dinamico di un elemento volvente in un cuscinetto integro e danneggiato: modello ad un solo grado di libertà [Altro]
Rubini, Riccardo; U., Meneghetti
abstract

Nell’ambito della Manutenzione Predittiva dei cuscinetti volventi viene ricostruita – mediante un modello matematico a parametri concentrati ad un grado di libertà – la dinamica di un elemento volvente in presenza di un difetto di fatica sugli anelli. Obiettivo della simulazione è la valutazione della forza di impatto tra gli elementi volventi e la superficie del danno, causa delle vibrazioni del cuscinetto danneggiato e fonte, pertanto, di informazioni per la diagnostica


2000 - Effectiveness and Sensitivity of Vibration Processing Techniques for Local Fault Detection in Gears [Articolo su rivista]
Dalpiaz, G.; Rivola, A.; Rubini, Riccardo
abstract

This paper deals with gear condition monitoring based on vibration analysis techniques.The detection and diagnostic capability of some of the most effective techniques arediscussed and compared on the basis of experimental results, concerning a gear pair affectedby a fatigue crack. In particular, the results of new approaches based on time-frequency andcyclostationarity analysis are compared against those obtained by means of the well-acceptedcepstrum analysis and time-synchronous average analysis. Moreover, the sensitivityto fault severity is assessed by considering two different depths of the crack. The effect oftransducer location and processing options are also shown. In the case of the experimentalresults considered in this paper, the power cepstrum is practically insensitive to the crackevolution. Conversely, the spectral correlation density function is able to monitor the faultdevelopment and does not seem to be significantly influenced by the transducer position.Analysis techniques of the time-synchronous average, such as the ‘residual’ signal and thedemodulation technique, are able to localise the damaged tooth; however, the sensitivity ofthe demodulation technique is strongly dependent on the proper choice of the filtering bandand affected by the transducer location. The wavelet transform seems to be a good tool forcrack detection; it is particularly effective if the residual part of the time-synchronousaveraged signal is processed.


1999 - Impact Force between Rolling Ball and Surface Fault in Damaged Ball Bearings [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

A great deal of research work has been dedicated in the last few decades to the development of refined and effective procedures for rolling bearing monitoring and diagnostics through vibration analysis. The basic observation is that sudden impact and consequent casing vibration take place every time a rolling ball overpasses a surface defect. As far as the authors know, little work has been focused on characterizing the impact force itself, i. e. determining its actual pattern and value. In this paper, the problem of identifying impact force between rolling balls and races is tackled experimentally. The force is recovered by inverse filtering of the casing acceleration. Results indicate the potential effectiveness of the method.


1999 - Relazione fra la forza generata nell’urto e le condizioni del difetto superficiale in un cuscinetto a sfere danneggiato [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

Gli urti che si verificano in un cuscinetto a rotolamento fra corpi volventi ed anelli in presenza di un danno superficiale, eccitano delle vibrazioni, la cui analisi viene largamente impiegata nella diagnostica industriale per l’individuazione dei danneggiamenti in atto. È pertanto di notevole interesse conoscere l’entità e l’andamento delle forze trasmesse in questi urti e metterle in relazione con l’entità e la situazione del danno. In un precedente lavoro, gli Autori hanno proposto una metodologia per il rilievo sperimentale delle forze suddette. Nel presente lavoro, tale metodologia viene impiegata per determinare l’evoluzione delle forze d’urto in un cuscinetto portante con anello esterno danneggiato, in conseguenza dell’arrotondamento dei bordi e dell’estensione dei crateri di pitting, che si verificano successivamente alla prima comparsa del danneggiamento. Viene considerato anche il caso di difetti molto estesi, con conseguenti urti multipli, e viene infine studiato l’effetto di un indebolimento locale dell’anello


1998 - Ball Bearing Diagnostics Using Neural Networks [Relazione in Atti di Convegno]
Giuliani, G; Rubini, Riccardo; Maggiore, A.
abstract

Ball bearings can be affected by several damage typologies. Surface flaws on inner and outer races or on rolling elements are the main causes of failure. The passing of a rolling element upon a localised defect generates a wide band impulse: during machine running, this particular phenomenon repeats itself at the fault characteristic frequencies, which depend on the bearing geometry. The present work shows the results obtained by the application of the main MATLAB Neural Networks to experimental parameters extracted from the casing of the ball bearing of a test machine in operating condition. The analysed bearings were affected by the above mentioned damages, artificially created by electric erosion. A comparison between the results obtained by the application of different network architectures is reported


1998 - Diagnostic of Gear Systems Using the Spectral Correlation Density of the Vibration Signal [Relazione in Atti di Convegno]
Rubini, Riccardo; Sidahmed, M.
abstract

This paper is devoted to gear diagnostics using a new technique based on cyclostationary theory. Formulation of the method and calculation of the Spectral Correlation Density (SCD) are presented. The Spectral Correlation Function may be seen as a parameter measuring the ‘link’ between harmonic components. This technique is demonstrated on simulated example, and used to analyse real vibration signals measured on an industrial like gear system. SCD is compared to classical (but powerful) phase modulation technique for the diagnostics of spalling in gear teeth. The results show that SCD may detect this fault in an early stage


1998 - Gear Fault Monitoring: Comparison of Vibration Analysis Techniques [Relazione in Atti di Convegno]
Dalpiaz, G; Rivola, A; Rubini, Riccardo
abstract

This paper deals with gear condition monitoring based on vibration analysis techniques. The detection and diagnostic capability of some of the most effective techniques are discussed and compared on the basis of experimental results, concerning a gear pair affected by a fatigue crack. In particular, the results of new approaches based on time-frequency and cyclostationarity analysis are compared against those obtained by means of the well accepted cepstrum analysis and amplitude and phase demodulation of meshing harmonics. Moreover, the sensitivity to fault severity is assessed by considering two different depths of the crack. The effect of choosing different transducer locations and different processing options are also shown.In the case of the experimental results considered in this paper, the power cepstrum is practically insensitive to the crack evolution. Conversely, the Spectral Correlation Density function is able to monitor the fault development and does not seem to be significantly influenced by the transducer position. The demodulation techniques are able to localise the damaged tooth; however, their sensitivity is strongly dependent on the proper choice of the filtering band and is affected by the transducer location. The Wavelet transform seems to be a good tool for crack detection; it is particularly effective if the residual part of the time synchronous averaged signal is processed


1998 - Ricostruzione della forza d'urto in un cuscinetto a rotolamento in presenza di un danno superficiale [Relazione in Atti di Convegno]
Rubini, Riccardo; Meneghetti, U.
abstract

In questi ultimi decenni sono state svolte numerose ricerche intese a sviluppare metodi sempre più raffinati per l’individuazione dei danneggiamenti dei cuscinetti a rotolamento mediante l’analisi delle vibrazioni. Malgrado ciò, lo studio delle caratteristiche degli urti che si verificano fra corpi rotolanti ed anelli in presenza di un danno superficiale, e che sono la causa delle vibrazioni suddette, sembra avere ricevuto scarsa attenzione. Nel presen¬te lavoro tale problema viene affrontato per via sperimentale, con il metodo della cosid¬detta funzione filtro. Con questo procedimento la forza d’urto viene ricostruita rilevando la vibrazione del supporto, dopo avere preventivamente misurato la funzione di trasferimento. I risultati ottenuti sembrano confermare la validità del procedimento proposto, almeno per il caso di danno sull’anello esterno


1998 - Tecnica di sincronizzazione di segnali periodici per il calcolo della media temporale sincrona in presenza di fluttuazioni della frequenza fondamentale - Parte Prima: Presentazione del metodo [Altro]
Rubini, Riccardo
abstract

In questo lavoro viene proposta una originale tecnica di sincronizzazione di segnali periodici basata sulla forma del segnale stesso. Questo tipo di approccio permette di affrontare casi nei quali il segnale sincrono di riferimento è assente o inadeguato per la presenza di fluttuazioni della frequenza fondamentale


1998 - Tecnica di sincronizzazione di segnali periodici per il calcolo della media temporale sincrona in presenza di fluttuazioni della frequenza fondamentale - Parte Seconda: Applicazione agli ingranaggi [Altro]
Rubini, Riccardo
abstract

Allo scopo di effettuare una corretta valutazione della Media Temporale Sincrona del segnale di velocità rilevato da una macchina di prova ingranaggi è stata applicata la tecnica di sincronizzazione proposta nella parte prima (Rubini, 1998), basata su riferimenti legati alla forma del segnale stesso. I risultati - determinati sia in condizioni integre sia in presenza di una cricca di fatica al piede di un dente di una ruota dentata - vengono confrontati con quelli ottenuti prendendo come riferimento un segnale tachimetrico sincrono con quello originale (tecnica classica)


1998 - Use of the Wavelet Transform for the Diagnosis of Incipient Faults in Ball Bearings [Relazione in Atti di Convegno]
Rubini, Riccardo; U., Meneghetti
abstract

Rolling bearing monitoring is commonly accomplished through well established and efficient techniques, based on vibration analysis. Only in a few cases do these techniques not work properly, e.g. when the load is very low. However, due to the importance of rolling bearings as the most widely used machine elements, it seems interesting to analyse the efficiency of new or non classical techniques which could be applicable for monitoring special unusual cases


1997 - A Kineto-Elastodynamic Model of a Gear Testing Machine [Relazione in Atti di Convegno]
Dalpiaz, G; Rivola, A; Rubini, Riccardo
abstract

Tianjin, China


1997 - Diagnostic of gear systems using the spectral correlation density of the vibration signal [Altro]
Rubini, Riccardo; Sidahmed, M.
abstract

This paper is devoted to gear diagnostic using a new technique based on cyclostationary theory. It presents the theory and application to spalling fault detection in gear


1996 - Dynamic Modelling of Gear System for Condition Monitoring and Diagnostics [Relazione in Atti di Convegno]
Dalpiaz, G; Rivola, A; Rubini, Riccardo
abstract

A non-linear lumped parameter model of a gear system is proposed in order to study the modifications in torsional vibration due to faults. The model takes into account the mass distribution, torsional shaft stiffness and variable tooth-meshing stiffness and is validated by comparison with experimental results. Faults localized in one or a few teeth produce dynamic effects that are typically transient and timelocalized. Then, the wavelet transform - that produces a time-frequency representations suited for resolving very short-lived high frequency phenomena in the time domain - is applied to both numerical and experimental results for the detection of damaged teeth. The effectiveness of model both in the case of sound and damaged gears is discussed