Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms

Conference item

Duan, F and Zivanovic, R (2013). Induction Motor Stator Fault Detection by a Condition Monitoring Scheme Based on Parameter Estimation Algorithms. 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED). Valencia 27 - 30 Aug 2013 Taylor & Francis. https://doi.org/10.1080/15325008.2015.1089336
AuthorsDuan, F and Zivanovic, R
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.

KeywordsInduction Motor; Stator Fault Detection; Condition Monitoring; Parameter Estimation Algorithms; 0906 Electrical And Electronic Engineering; Energy
Year2013
JournalTaylor and Francis
PublisherTaylor & Francis
ISSN1532-5008
Digital Object Identifier (DOI)https://doi.org/10.1080/15325008.2015.1089336
Accepted author manuscript
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Publication dates
Print27 Aug 2013
Publication process dates
Deposited27 Jun 2018
Accepted21 Aug 2013
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https://openresearch.lsbu.ac.uk/item/878y5

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