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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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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

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  4/2016 - 10

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
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,842 KB) | Citation | Downloads: 423 | Views: 2,240

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  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 3,878 TCR
SCOPUS® Citations for all references: 5,302 TCR

Web of Science® Average Citations per reference: 134 ACR
SCOPUS® Average Citations per reference: 183 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-08-18 14:44 in 183 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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