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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2016 - 10

 HIGH-IMPACT PAPER 

Broken Bar Fault Detection in IM Operating Under No-Load Condition

RELJIC, D. See more information about RELJIC, D. on SCOPUS See more information about RELJIC, D. on IEEExplore See more information about RELJIC, D. on Web of Science, JERKAN, D. See more information about  JERKAN, D. on SCOPUS See more information about  JERKAN, D. on SCOPUS See more information about JERKAN, D. on Web of Science, MARCETIC, D. See more information about  MARCETIC, D. on SCOPUS See more information about  MARCETIC, D. on SCOPUS See more information about MARCETIC, D. on Web of Science, OROS, D. See more information about OROS, D. on SCOPUS See more information about OROS, D. on SCOPUS See more information about OROS, D. on Web of Science
 
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Download PDF pdficon (1,842 KB) | Citation | Downloads: 1,337 | Views: 1,672

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
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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.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 12 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 11
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Cited-By CrossRef

[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


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