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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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fault detection, current measurement, fast Fourier transform, induction motor, spectral analysis
induction(17), rotor(14), motors(12), analysis(10), diagnosis(9), industry(7), detection(7), machines(6), fault(6), energy(6)
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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
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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 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]
 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]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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