Transient Analysis and Motor Fault Detection using the Wavelet Transform

Peer ReviewedPostprint (updated version

Bearings Fault Detection Using Inference Tools

The most used electric machine in the industry is the Induction Motor (IM), due to its simplicity and reduced cost. The analysis of the origin of IMs failures exhibits that the bearings are the major source of fault, and even a common cause of degradation in other kinds of motors as Permanent Magnet Synchronous Machines.Peer ReviewedPostprint (published version

EMA Fault Detection Using Fuzzy Inference Tools

Acoustic emission (AE) is one of the most important non-destructive testing (NDT) methods for materials, constructions and machines. Acoustic emission is defined as the transient elastic energy that is spontaneously released when materials undergo deformation, fracture, or both. This interdisciplinary book consists of 17 chapters, which widely discuss the most important applications of AE method as machinery and civil structures condition assessment, fatigue and fracture materials research, detection of material defects and deformations, diagnostics of cutting tools and machine cutting process, monitoring of stress and ageing in materials, research, chemical reactions and phase transitions research, and earthquake prediction.Peer ReviewedPostprint (published version

Nova shema za izravno upravljanje momentom asinkronih motora napajanih iz trofaznog izmjenjivača

This paper presents a novel controller based on Direct Torque Control (DTC) strategy. This controller is designed to be applied in the control of Induction Motors (IM) fed with a three-level Voltage Source Inverter (VSI). This type of inverter has several advantages over the standard two-level VSI, such as a greater number of levels in the output voltage waveforms, lower dV/dt, less harmonic distortion in voltage and current waveforms and lower switching frequencies. In the new controller, torque and stator flux errors are used together with the stator flux angular frequency to generate a reference voltage vector. Experimental results of the novel system are presented and compared with those obtained for Classical DTC system employing a two-level VSI. The new controller is shown to reduce the ripple in the torque and flux responses. Lower current distortion and switching frequency of the semiconductor devices are also obtained in the new system presented.U ovome se članku opisuje novi regulator zasnovan na strategiji izravnog upravljanja momentom i razvijen za primjenu u upravljanju asinkronim motorima napajanim iz trorazinskih izmjenjivača napona. Taj tip izmjenjivača ima nekoliko prednosti u odnosu na standardne dvorazinske izmjenjivače napona, kao što je veći broj razina u izlaznom valnom obliku napona, niži du/dt, manja distorzija harmonika u valnim oblicima napona i struje i niže frekvencije komutacije. U novom regulatoru moment i pogreške u statorskom toku koriste se zajedno s kutnom frekvencijom statora za tvorbu referentne vrijednosti vektora napona. Eksperimentalni su rezultati novog sustava prikazani i uspoređeni s rezultatima klasičnog sustava koji koristi dvorazinski pretvarač napona. Novi regulator pokazuje smanjeni šum u odzivima momenta i toka motora. U predloženom je sustavu također postignuta i manja distorzija struje i manja frekvencija komutacije poluvodičkih sklopova

Eines d’autor: avaluació de noves eines orientades al desenvolupament de competències genèriques per la millora del procés d’aprenentatge autònom dels estudiants

Els cursos on-line massius (Massive Open On-line Courses) estan emergent i suposarà un gran repte en l’educació universitària en els propers anys. Universitats com Standford i MIT han començat aquest any cursos en obert amb una matriculació de centenars de milers d’estudiants en les seves assignatures pilots. Aquests cursos es basen en deixar material docent en servidors, on els estudiants poden seguir en qualsevol moment, i des de qualsevol lloc el curs. Per generar aquest cursos, es necessari tenir bones eines que permetin generar bon material, i que el docent no necessiti concentrar-se en el programari, i si en els mètodes que desitgi aplicar. Dintre d’aquest objectiu, ja des de fa uns anys han aparegut unes eines anomenades “rapid eLearning Tools” que prometen generar materials didàctics de qualitat amb gran facilitat. Entenem per “eines ràpides”, aquelles que, amb uns coneixements a nivell d’usuari d’informàtica, les eines permeten obtenir productes multimèdia de bona qualitat, sense la necessitat de invertir un temps excessiu en la seva generació. Existeixen moltes eines ràpides d’autor a l’actualitat, amb una gran varietat de prestacions. Un dels objectius necessaris és conèixer les ofertes actuals en el mercat dels programaris i tenir una avaluació seguint uns criteris objectius. Aquests s’han definit amb criteris d’us del docent i impacte en el material obtingut.Peer Reviewe

Novelty detection based condition monitoring scheme applied to electromechanical systems

This study is focused on the current challenges dealing with electromechanical system monitoring applied in industrial frameworks, that is, the presence of unknown events and the limitation to the nominal healthy condition as starting knowledge. Thus, an industrial machinery condition monitoring methodology based on novelty detection and classification is proposed in this study. The methodology is divided in three main stages. First, a dedicated feature calculation and reduction over each available physical magnitude. Second, an ensemble structure of novelty detection models based on one-class support vector machines to identify not previously considered events. Third, a diagnosis model supported by a feature fusion scheme in order to reach high fault classification capabilities. The effectiveness of the fault detection and identification methodology has been compared with classical single model approach, and verified by experimental results obtained from an electromechanical machine. © 2018 IEEE.Postprint (author's final draft

Incremental learning framework-based condition monitoring for novelty fault identification applied to electromechanical systems

A great deal of investigations are being carried out towards the effective implementation of the 4.0 Industry new paradigm. Indeed, most of the machinery involved in industrial processes are intended to be digitalized aiming to obtain enhanced information to be used for an optimized operation of the whole manufacturing process. In this regard, condition monitoring strategies are being also reconsidered to include improved performances and functionalities. Thus, the contribution of this research work lies in the proposal of an incremental learning framework approach applied to the condition monitoring of electromechanical systems. The proposed strategy is divided in three main steps, first, different available physical magnitudes are characterized through the calculation of a set of statistical-time based features. Second, a modelling of the considered conditions is performed by means of self-organizing maps in order to preserve the topology of the data; and finally, a novelty detection is carried out by a comparison among the quantization error value achieved in the data modelling for each of the considered conditions. The effectiveness of the proposed novelty fault identification condition monitoring methodology is proved by means of the evaluation of a complete experimental database acquired during the continuous working conditions of an electromechanical system. © 2018 IEEE.Peer ReviewedPostprint (author's final draft