Experimental Evidence of the Speed Variation Effect on SVM Accuracy for Diagnostics of Ball Bearings

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

A new method for motion synchronization among multivendor’s programmable controllers

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

Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field

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

A bearing fault model for Independent Cart Conveyor System and its validation

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

Experimental Evidence of the Speed Variation Effect on SVM Accuracy for Diagnostics of Ball Bearings

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

Sviluppo di una struttura di manutenzione basata sul monitoraggio delle condizioni per Sistemi a Carrelli Indipendenti

L\u2019obiettivo di questo lavoro \ue8 la diagnostica di Sistemi a Carrelli Indipendenti con particolare attenzione ai cuscinetti. Il Sistema a Carrelli Indipendenti \ue8 una tecnologia innovativa e promettente nell\u2019ambito delle macchine automatiche, che in alcuni casi pu\uf2 sostiture i tipici sistemi di trasporto basati su catene e cinghie guidate da motori rotativi. Il Sistema a Carrelli Indipendenti combina i vantaggi dei servomotori rotativi con quelli dei motori lineari. Esso consiste in una serie di motori lineari modulari di forma curva o rettilinea, che, combinati insieme, realizzano un circuito chiuso. I motori controllano una flotta di carrelli che sono tra loro indipendenti e questa caratteristica rende il sistema flessibile ad ogni tipo di prodotto e compito. Ognuno di questi carrelli \ue8 posizionato lungo i motori ed \ue8 collegato ad un binario fisso attraverso una serie di cuscinetti. Questo sistema pu\uf2 presentare un problema nel caso in cui vengano utilizzati numerosi carrelli, poich\ue9 in questo caso anche il numero dei cuscinetti aumenterebbe. L\u2019elevato numero di cuscinetti riduce il Mean Time Before Failure (MTBF) dell\u2019intera macchina, ma allo stesso tempo, grazie al fatto che ogni carrello \ue8 svincolato l\u2019uno dall\u2019altro, \ue8 possibile monitorare lo stato di salute di ogni carrello in maniera indipendente. La realizzazione di un sistema di condition monitoring per questi macchinari risulta stimolante anche se impegnativo, in quanto le condizioni di lavoro dei carrelli sono altamente non stazionarie per la variabilit\ue0 dei profili di carico e velocit\ue0. Questo studio tratta il problema dello sviluppo di un sistema di condition monitoring per questa tecnologia, che viene affrontato da diversi punti di vista. Per quanto riguarda l\u2019hardware, \ue8 stata realizzata una nuova tecnica per la sincronizzazione dei motion task fra i PLC di differenti costruttori, che vengono usati per il controllo dei Sistemi a Carrelli Indipendenti. Inoltre, sono stati eseguiti esperimenti ed usati metodi di calcolo avanzati per la valutazione della rigidezza dei cuscinetti. Per avere una panoramica completa dei possibili metodi di monitoraggio, sono state utilizzate sia tecniche data-driven che model-based per il rilevamento di guasti nel sistema. Per quanto riguarda i metodi data-driven, sono stati utilizzati algoritmi di machine learning per la identificazione di danni, cos\uec come sono state studiate nuove feature per la prognostica. Per quanto si riferisce al model-based, \ue8 stato sviluppato un modello che simula i segnali vibratori prodotti dai Sistemi a Carrelli Indipendenti con profilo di moto arbitrario. Per considerare l\u2019intera dinamica del sistema, \ue8 stato realizzato un modello multibody del carrello, dei cuscinetti e del binario. Entrambi i modelli realizzati prendono in considerazione profili di moto variabili, varie forme del circuito su cui i carrelli possono muoversi, la meccanica dei carrelli, la variazione dei carichi agenti e differenti tipi di danno nei cuscinetti. Per poter considerare diverse configurazioni del sistema, entrambi i modelli sono scalabili e modulari. Essi sono stati validati attraverso la comparazione tra i dati simulati e i dati reali rilevati attraverso una campagna sperimentale.The objective of this work is the condition monitoring of Independent Carts System with particular attention to bearings. The Independent Cart Conveyor System is a promising technology that could replace rotary driven chains and belts in the field of automatic machines. This system combines the benefits of servomotors 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 bearings, to a rail set on the motors themselves. A possible problem can rise with the use of this technology: with the demand of a high production rate, the number of movers necessary in the machine increases and consequently even the number of bearings increases. In this way the high number of rolling bearings reduces the Mean Time Before Failure (MTBF) of the whole machine, but at the same time, thanks to the independent control and the independent monitoring of each cart, it is possible to implement condition monitoring strategies for each cart. The condition monitoring of these elements is challenging for the non-stationary working conditions of variable load and speed profiles. The thesis deals with the problem of the development of a condition monitoring framework for this system from different points of view. About hardware, a new technique for the synchronization between PLCs of different vendors used for the control of this system has been developed. Moreover, bearing stiffness has been evaluated through experimental campaigns and advance computational methods. In order to get a 360-degree view of the possible solutions of this problem, data-driven and model-based condition monitoring techniques have been applied. As regards data-driven, machine learning techniques for fault detection have been used on the basis of an experimental campaign on a specific machine application, as well as a new feature for the prediction of bearing faults has been studied. As regards model-based, a model of the vibration signals produced by the carts with an arbitrary motion profile has been carried out. Moreover, the whole dynamics of the system has been taken into account by means of a multibody modelling of the cart, the bearings and the rail. Both models consider the variable motion profile, the shape of the conveyor path, the mechanical design of the cart, the load variation and the type of fault on the groove ball bearings. The models are scalable and modular in order to test different configurations of the system with different work parameters and both models have been validated by means of the comparison between the simulation results and the system variables recorded during experimental campaigns

Signal model of a cycloidal drive for diagnostic purposes

The study of gearboxes for diagnostic and prognostic purposes plays a major role in industrial applications, especially in the robotics and automation fields, where such devices are used extensively. The present work has been focused on the cycloidal drives, which are widely adopted thanks to their compactness and sturdiness, nevertheless they present a complex architecture. An analytical model of the vibrational behaviour of such a device has been developed aiming to obtain an efficient simulation tool, able to consider different faults occurring due to the natural wear of components. The model has been obtained thanks to a positional angular-based method giving the contacts patterns construction as a time-independent function, thus any input speed profile can be taken into account. Internal loads distribution has been a crucial aspect of the modelling, also needed in order to provide an estimate of the machine efficiency. This simulation tool may be finally generalized in order to extend the analysis capability to the epicyclic gear train family

Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field

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

Dynamic model of an independent carts system

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