Induction motor stator faults diagnosis by using parameter estimation algorithms

Fang Duan, Rastko Zivanovic

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

7 Citations (Scopus)

Abstract

Parameter estimation is a cost-effective method for fault detection of induction motors. This method is based on detecting change of the characteristic parameters at presence of fault. However, the challenge of parameter estimation is nonlinearity of a machine model which results in multiple local minima involved during the computation process. This paper investigates the suitability of local and global search methods to be used in the estimation of characteristic parameters that are indicating stator short circuit faults. Results of practical case studies are presented where two search methods (local and global) are evaluated and compared. A further study in noisy environment proves the feasibility of diagnosing the fault based on stator currents with low signal to noise ratio.

Original languageEnglish
Title of host publicationProceedings - 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013
PublisherIEEE Computer Society
Pages274-280
Number of pages7
ISBN (Print)9781479900251
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013 - Valencia, Spain
Duration: 27 Aug 201330 Aug 2013

Publication series

NameProceedings - 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013

Conference

Conference2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, SDEMPED 2013
CountrySpain
CityValencia
Period27.08.201330.08.2013

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