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Broken Bar Fault Detection in IM Operating Under No-Load ConditionRELJIC, D.   , JERKAN, D. , MARCETIC, D. , OROS, D. |
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Author keywords
fault detection, current measurement, fast Fourier transform, induction motor, spectral analysis
References keywords
induction(17), rotor(14), motors(12), analysis(10), diagnosis(9), industry(7), detection(7), machines(6), fault(6), energy(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 63 - 70
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04010
Web of Science Accession Number: 000390675900010
SCOPUS ID: 85007559647
Abstract
This paper presents a novel method for broken rotor bar detection in a squirrel-cage induction motor (IM). The proposed method applies a single-phase AC voltage as a test signal on motor terminals, resulting in a stator backward-rotating magnetic field. The field ultimately causes additional current components in the stator windings whose magnitudes depend on the broken bar fault severity, even if the motor is unloaded. This allows robust broken bar fault detection based only on standard motor current signature analysis (MCSA) technique. The proposed fault detection method is at first verified via simulations, using an IM model based on finite element analysis (FEA) and multiple coupled circuit approach (MCCA). The subsequent experimental investigations have shown good agreement with both theoretical predictions and simulation results. |
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[1] Electrical Signature Analysis for Condition Monitoring of Permanent Magnet Synchronous Machine, SALOMON, C. P., FERREIRA, C., LAMBERT-TORRES, G., TEIXEIRA, C. E., BORGES DA SILVA, L. E., SANTANA, W. C., BONALDI, E. L., DE OLIVEIRA, L. E. L., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 18, 2018.
Digital Object Identifier: 10.4316/AECE.2018.04011 [CrossRef] [Full text]
[2] WITHDRAWN: Performance assessment and transient behavioral analysis of electrical machines under fault conditions, Katta, Pradeep, Karunanithi, K., Materials Today: Proceedings, ISSN 2214-7853, 2020.
Digital Object Identifier: 10.1016/j.matpr.2020.11.082 [CrossRef]
[3] A Study of Fault Diagnosis Based on Electrical Signature Analysis for Synchronous Generators Predictive Maintenance in Bulk Electric Systems, Salomon, Camila Paes, Ferreira, Claudio, Sant’Ana, Wilson Cesar, Lambert-Torres, Germano, Borges da Silva, Luiz Eduardo, Bonaldi, Erik Leandro, de Oliveira, Levy Ely de Lacerda, Torres, Bruno Silva, Energies, ISSN 1996-1073, Issue 8, Volume 12, 2019.
Digital Object Identifier: 10.3390/en12081506 [CrossRef]
[4] Investigation on Electromagnetic Performance of Induction Motor with Rotor Bar Faults considering Motor Current Signals, PARK, Y.-S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 20, 2020.
Digital Object Identifier: 10.4316/AECE.2020.04005 [CrossRef] [Full text]
[5] Health monitoring of induction motors through embedded systems-simulation of broker rotor bar fault and abnormal gear teeth fault, Gandhi, Priyanka, Turk, Dr Neelam, Dahiya, Dr Ratna, Microprocessors and Microsystems, ISSN 0141-9331, Issue , 2020.
Digital Object Identifier: 10.1016/j.micpro.2020.103077 [CrossRef]
[6] Automatic Early Broken-Rotor-Bar Detection and Classification Using Otsu Segmentation, Lopez-Ramirez, Misael, Ledesma-Carrillo, Luis M., Garcia-Guevara, Francisco M., Munoz-Minjares, Jorge, Cabal-Yepez, Eduardo, Villalobos-Pina, Francisco J., IEEE Access, ISSN 2169-3536, Issue , 2020.
Digital Object Identifier: 10.1109/ACCESS.2020.3002545 [CrossRef]
[7] Vibration Based Broken Bar Detection in Induction Machine for Low Load Conditions, MATIC, D., KANOVIC, Z., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.01007 [CrossRef] [Full text]
[8] Current Park’s Vector Pattern Technique for Diagnosis of Broken Rotor Bars Fault in Saturated Induction Motor, Abdellah, Chaouch, Mama, Chouitek, Meflah Abderrahmane, Mohamed Reda, Mohammed, Belaid, Journal of Electrical Engineering & Technology, ISSN 1975-0102, Issue 4, Volume 18, 2023.
Digital Object Identifier: 10.1007/s42835-022-01342-6 [CrossRef]
[9] Broken Rotor Bar Fault Detection Using Advanced IM Model and Artificial Intelligence Approach, Reljic, Dejan, Jerkan, Dejan, Kanovic, Zeljko, IEEE EUROCON 2019 -18th International Conference on Smart Technologies, ISBN 978-1-5386-9301-8, 2019.
Digital Object Identifier: 10.1109/EUROCON.2019.8861767 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
