ANN based fault diagnosis of permanent magnet synchronous motor under stator winding shorted turn

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TitreANN based fault diagnosis of permanent magnet synchronous motor under stator winding shorted turn
Type de publicationJournal Article
Year of Publication2015
AuteursMoosavi S.S, Djerdir A., Ait-Amirat Y., Khaburi D.A
JournalELECTRIC POWER SYSTEMS RESEARCH
Volume125
Pagination67-82
Date PublishedAUG
Type of ArticleArticle
ISSN0378-7796
Mots-clésANN, Diagnosis method justification, Fault diagnosis, Fault feature extraction, Inter-turn short circuit, PMSM
Résumé

The fault detection and diagnosis in electrical motors is a topic of increasing interest in the field of highly reliable and fault-tolerant measurement and control systems. This paper focuses on inter-turn short circuit fault diagnosis in stator windings of a Permanent magnet synchronous motor (PMSM). A multilayer artificial neural network (MANN) has been used for diagnosis and classification of different levels of short circuit. The analytical and finite element method (FEM) based results have been validated by experimental results. Experimental data have been employed to train ANN. (C) 2015 Elsevier B.V. All rights reserved.
DOI10.1016/j.epsr.2015.03.024