Aportación al mantenimiento predictivo de motores de inducción mediante modernas técnicas de análisis de la señal

La presente tesis cuenta con dos objetivos. Por una parte introducir y validar un método de análisis de corrientes estatóricas para el diagnóstico de máquinas de inducción conectadas a la red que operan en estado transitorio, basado en el uso de filtros de rechazo de frecuencia en combinación con la distribución de Wigner-Ville, con especial interés en su aplicación para la detección incipiente de defectos. El segundo objetivo consiste en replicar de la manera más fidedigna posible el proceso de rotura de una barra en el rótor de un motor de inducción. Para ello se ha diseñado un ensayo encaminado a provocar dicha avería sometiendo un motor a fatiga. Con este objetivo se ha construido un banco de pruebas y emplazado los sensores necesarios, así como un sistema de recogida de datos de manera automatizada. Adicionalmente, se ha diseñado los programas de procesamiento de los mismos, también para ser llevado a cabo de la manera lo más desatendida posible.Climente Alarcón, V. (2012). Aportación al mantenimiento predictivo de motores de inducción mediante modernas técnicas de análisis de la señal [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/15915Palanci

Time-frequency vibration analysis for the detection of motor damages caused by bearing currents

[EN] Motor failure due to bearing currents is an issue that has drawn an increasing industrial interest over recent years. Bearing currents usually appear in motors operated by variable frequency drives (VFD); these drives may lead to common voltage modes which cause currents induced in the motor shaft that are discharged through the bearings. The presence of these currents may lead to the motor bearing failure only few months after system startup. Vibration monitoring is one of the most common ways for detecting bearing damages caused by circulating currents; the evaluation of the amplitudes of well-known characteristic components in the vibration Fourier spectrum that are associated with race, ball or cage defects enables to evaluate the bearing condition and, hence, to identify an eventual damage due to bearing currents. However, the inherent constraints of the Fourier transform may complicate the detection of the progressive bearing degradation; for instance, in some cases, other frequency components may mask or be confused with bearing defect-related while, in other cases, the analysis may not be suitable due to the eventual non-stationary nature of the captured vibration signals. Moreover, the fact that this analysis implies to lose the time-dimension limits the amount of information obtained from this technique. This work proposes the use of time-frequency (T-F) transforms to analyse vibration data in motors affected by bearing currents. The experimental results obtained in real machines show that the vibration analysis via T-F tools may provide significant advantages for the detection of bearing current damages; among other, these techniques enable to visualise the progressive degradation of the bearing while providing an effective discrimination versus other components that are not related with the fault. Moreover, their application is valid regardless of the operation regime of the machine. Both factors confirm the robustness and reliability of these tools that may be an interesting alternative for detecting this type of failure in induction motors.This work was supported in part by IPES (which is a joint research laboratory between the Laboratory Ampere and Safran) and in part by the Spanish 'Ministerio de Economia y Competitividad' (MINECO) and FEDER programme in the framework of the 'Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia' (ref: DPI2014-52842-P)."Prudhom, A.; Antonino-Daviu, J.; Razik, H.; Climente Alarcón, V. (2017). Time-frequency vibration analysis for the detection of motor damages caused by bearing currents. Mechanical Systems and Signal Processing. 84:747-762. https://doi.org/10.1016/j.ymssp.2015.12.008S7477628

Rotor-Bar Breakage Mechanism and Prognosis in an Induction Motor

[EN] This paper proposes a condition-based maintenance and prognostics and health management (CBM/ PHM) procedure for a rotor bar in an induction motor. The methodology is based on the results of a fatigue test intended to reproduce in the most natural way a bar breakage in order to carry out a comparison between transient and stationary diagnosis methods for incipient fault detection. Newly developed techniques in stator-current transient analysis have allowed tracking the developing fault during the last part of the test, identifying the failure mechanism, and establishing a physical model of the process. This nonlinear failure model is integrated in a particle filtering algorithm to diagnose the defect at an early stage and predict the remaining useful life of the bar. An initial generalization of the results to conditions differing from the ones under which the fatigue test was developed is studied.Climente Alarcon, V.; Antonino-Daviu, J.; Strangas, EG.; Riera-Guasp, M. (2015). Rotor-Bar Breakage Mechanism and Prognosis in an Induction Motor. IEEE Transactions on Industrial Electronics. 62(3):1814-1825. doi:10.1109/TIE.2014.2336604S1814182562

Reliable Detection of Rotor Winding Asymmetries in Wound Rotor Induction Motors via Integral Current Analysis

(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works[EN] Current analysis has been widely employed in academy and industry for the diagnosis of rotor damages in cage induction motors. The conventional approach based on the FFT analysis of steady-state current (MCSA) has been recently complemented with the development of alternative techniques that rely on the time-frequency analysis of transient quantities of the machine. These techniques may bring important advantages that are related to the avoidance of eventual false indications provided by the classical MCSA. Moreover, their application is also suitable for variable speed conditions. However, the application of current-based methodologies to wound rotor induction motors (WRIM) has been much less studied and, hence, their validation in field WRIM is scarce. The present work proposes the application of an integral methodology based on the analysis of both stationary and transient currents for the diagnosis of winding asymmetries in WRIM. The method, based on up to five different fault evidences, is validated in laboratory motors and it is subsequently applied to a large field motor (1,500 kW) that was showing signs of abnormal rotor functioning. The results prove that the method is of interest for the field since it helps to ratify without ambiguity the existence of eventual asymmetries in the rotor windings, with no interference with the machine operation. However, due to the complex constructive nature of the rotor winding as well as the presence of auxiliary systems (slip rings, brushes, contactors, etc ), once the fault presence is detected, it may be interesting the utilization of complementary tools to accurately locate the root cause of the asymmetry.This work was supported in part by the Spanish Ministerio de Economia y Competitividad and in part by the Fondo Europeo de Desarrollo Regional Program in the framework of the Proyectos i+d del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant dpi2014-52842-P.Antonino-Daviu, J.; Quijano Lopez, A.; Climente Alarcón, V.; Garín-Abellán, C. (2017). Reliable Detection of Rotor Winding Asymmetries in Wound Rotor Induction Motors via Integral Current Analysis. IEEE Transactions on Industry Applications. 53(3):2040-2048. https://doi.org/10.1109/TIA.2017.2672524S2040204853

Transient-Based Rotor Cage Assessment in Induction Motors Operating With Soft Starters

[EN] The reliable assessment of the rotor condition in induction motors is a matter of increasing concern in the industry. Although rotor damages are more likely in line-started motors operating under high inertias, some cases of broken rotor bars in motors supplied via soft starters have been also reported in the industry. Motor current signature analysis (MCSA) is the most widely spread approach to diagnose such failures. However, its serious drawbacks in many real industrial applications have encouraged investigation on alternative methods enhancing the reliability of the diagnosis. This paper extends a recently introduced diagnosis methodology relying on the startup current analysis to the case of soft-starter-operated motors. The approach has proven to provide very satisfactory results, even in cases where the classical MCSA does not lead to correct diagnosis conclusions. However, its extension to operation under soft starters was still a pending issue. The experimental results shown in this paper ratify the validity of the proposed diagnosis approach in soft-starteroperated induction motors.This work was supported by the Spanish “Ministerio de Economía y Competitividad” (MINECO) in the framework of the “Proyectos I+D del Subprograma de Generación de Conocimiento, Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia” under Grant DPI2014-52842-PCorral Hernández, JÁ.; Antonino-Daviu, J.; Pons Llinares, J.; Climente Alarcón, V.; Francés-Galiana, V. (2015). Transient-Based Rotor Cage Assessment in Induction Motors Operating With Soft Starters. IEEE Transactions on Industry Applications. 51(5):3734-3742. https://doi.org/10.1109/TIA.2015.2427271S3734374251

Recent Educational Experiences in Electric Machine Maintenance Teaching

[EN] Maintenance of electric machines and installations is a particularly important area; eventual faults in these devices may lead to significant losses in terms of time and money. The investment and concern in developing proper maintenance protocols have been gradually increasing over recent decades. As a consequence, there is a need to instruct future engineers in the electric machines and installations maintenance area. The subject ¿Maintenance of Electric Machines and Installations¿ has been designed under this idea. It is taught within an official master degree in Maintenance Engineering. This work describes the educational experiences reached during the initial years of the teaching of the subject. Aspects such as student profiles, subject approaches, design of the syllabus, methodology and structure of the laboratory sessions are remarked in the work. In addition, the paper discusses other educational strategies which are being introduced to increase the interest in the subject, such as integration of Information and Communication Technologies (ICT), promotion of the collaborative work, inclusion of the possibility of remote learning or development of new assessment systems.This work was supported by the Conselleria d’Educació, Formació i Ocupació of the Generalitat Valenciana, in the framework of the ‘‘Ayudas para la Realización de Proyectos de I+D para Grupos de Investigación Emergentes’’, project reference GV/2012/020.Antonino Daviu, JA.; Pons Llinares, J.; Climente Alarcón, V. (2013). Recent Educational Experiences in Electric Machine Maintenance Teaching. International Journal of Engineering Pedagogy. 3(3):21-26. https://doi.org/10.3991/ijep.v3iS3.2742S21263

Enhanced Simulink Induction Motor Model for Education and Maintenance Training

[EN] The training of technicians in maintenance requires the use of signals produced by faulty machines in different operating conditions, which are difficult to obtain either from the industry or through destructive testing. Some tasks in electricity and control courses can also be complemented by an interactive induction machine model having a wider internal parameter configuration. This paper presents a new analytical model of induction machine under fault, which is able to simulate induction machines with rotor asymmetries and eccentricity in different load conditions, both stationary and transient states and yielding magnitudes such as currents, speed and torque. This model is faster computationally than the traditional method of simulating induction machine faults based on the Finite Element Method and also than other analytical models due to the rapid calculation of the inductances. The model is presented in Simulink by Matlab for the comprehension and interactivity with the students or lecturers and also to allow the easy combination of the effect of the fault with external influences, studying their consequences on a determined load or control system. An associated diagnosis tool is also presented.This work was supported by the Spanish Ministerio de Ciencia e Innovación under the framework of the Programa Nacional de Proyectos de Investigación Fundamental, Project Reference DPI2011-23740Pineda-Sanchez, M.; Climente Alarcón, V.; Riera-Guasp, M.; Puche-Panadero, R.; Pons Llinares, J. (2012). Enhanced Simulink Induction Motor Model for Education and Maintenance Training. Journal of Systemics, Cybernetics and Informatics. 10(2):92-97. http://hdl.handle.net/10251/105282S929710

Combination of Noninvasive Approaches for General Assessment of Induction Motors

[EN] There exists no single quantity able to diagnose all possible failures taking place in induction motors. Currents and vibrations monitoring are rather common in the industry, but each of these quantities alone can only detect some specific failures. Moreover, even for the specific faults that a quantity is supposed to detect, many problems may rise. As a consequence, a reliable and general diagnosis system cannot rely on a single quantity. On the other hand, it would be desirable to rely on quantities that can be measured in a noninvasive way, which is a crucial requirement in many industrial applications. This paper proposes a twofold method to detect electromechanical failures in induction motors. The method relies on analysis of currents (steady state + transient) combined with analysis of infrared data captured by using appropriate cameras. Each of these noninvasive techniques may provide complementary information that may be very useful to diagnose an enough wide range of failures. In the present paper, the detection of three illustrative faults is analyzed: broken rotor bars, cooling system problems and bearing failures. The results show the potential of the methodology that may be particularly suitable for large, expensive motors, where the prevention of eventual failures justifies the costs of such system, due to the catastrophic implications that these unexpected faults may have.Picazo-Rodenas, MJ.; Antonino-Daviu, J.; Climente Alarcon, V.; Royo, R.; Mota-Villar, A. (2015). Combination of Noninvasive Approaches for General Assessment of Induction Motors. IEEE Transactions on Industry Applications. 51(3):2172-2180. doi:10.1109/TIA.2014.2382880S2172218051

The use of a Multi-label Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults based on the Start-up Transient

[EN] In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity, while three "problem transformation" methods are tested and compared. For the feature extraction stage, the startup current is exploited using two well-known time-frequency (scale) transformations. This is the first time that a multi-label framework is used for the diagnosis of co-occurring fault conditions using information coming from the start-up current of induction motors. The efficiency of the proposed approach is validated using simulation data with promising results irrespective of the selected time-frequency transformation.This work was supported in part by the Spanish MINECO and FEDER program in the framework of the "Proyectos I + D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia" under Grant DPI2014-52842-P and in part by the Horizon 2020 Framework program DISIRE under the Grant Agreement 636834.Georgoulas, G.; Climente Alarcón, V.; Antonino-Daviu, J.; Tsoumas, IP.; Stylios, CD.; Arkkio, A.; Nikolakopoulos, G. (2016). The use of a Multi-label Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults based on the Start-up Transient. IEEE Transactions on Industrial Informatics. 13(2):625-634. https://doi.org/10.1109/TII.2016.2637169S62563413

Transient tracking of low and high-order eccentricity-related components in induction motors via TFD tools

[EN] The present work is focused on the diagnosis of mixed eccentricity faults in induction motors via the study of currents demanded by the machine. Unlike traditional methods, based on the analysis of stationary currents (Motor Current Signature Analysis (MCSA)), this work provides new findings regarding the diagnosis approach proposed by the authors in recent years, which is mainly focused on the fault diagnosis based on the analysis of transient quantities, such as startup or plug stopping currents (Transient Motor Current Signature Analysis (TMCSA)), using suitable time-frequency decomposition (TFD) tools. The main novelty of this work is to prove the usefulness of tracking the transient evolution of high-order eccentricity-related harmonics in order to diagnose the condition of the machine, complementing the information obtained with the low-order components, whose transient evolution was well characterised in previous works. Tracking of high-order eccentricity-related harmonics during the transient, through their associated patterns in the time-frequency plane, may significantly increase the reliability of the diagnosis, since the set of fault-related patterns arising after application of the corresponding TFD tool is very unlikely to be caused by other faults or phenomena. Although there are different TFD tools which could be suitable for the transient extraction of these harmonics, this paper makes use of a WignerVille distribution (WVD)-based algorithm in order to carry out the time-frequency decomposition of the startup current signal, since this is a tool showing an excellent trade-off between frequency resolution at both high and low frequencies. Several simulation results obtained with a finite element-based model and experimental results show the validity of this fault diagnosis approach under several faulty and operating conditions. Also, additional signals corresponding to the coexistence of the eccentricity and other non-fault related phenomena making difficult the diagnosis (fluctuating load torque) are included in the paper. Finally, a comparison with an alternative TFD tool the discrete wavelet transform (DWT) applied in previous papers, is also carried out in the contribution. The results are promising regarding the usefulness of the methodology for the reliable diagnosis of eccentricities and for their discrimination against other phenomena. © 2010 Elsevier Ltd.All rights reserved.This work was supported by the Spanish 'Ministerio de Educacion y Ciencia', in the framework of the 'Programa Nacional de proyectos de Investigacion Fundamental', project reference DP12008-06583/DPI.Climente Alarcón, V.; Antonino-Daviu, J.; Riera-Guasp, M.; Pons Llinares, J.; Roger-Folch, J.; Jover-Rodriguez, P.; Arkkio, A. (2011). Transient tracking of low and high-order eccentricity-related components in induction motors via TFD tools. Mechanical Systems and Signal Processing. 25(2):667-679. https://doi.org/10.1016/j.ymssp.2010.08.008S66767925