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Comparison of Particle Swarm and Simulated Annealing Algorithms for Induction Motor Fault Identification

Lookup NU author(s): Dr Salaheddine Ethni, Dr Bashar Zahawi, Dr Damian Giaouris, Professor Paul Acarnley

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Abstract

The performance of two stochastic search methods, particle swarm optimisation (PSO) and simulated annealing (SA), when used for fault identification of induction machine stator and rotor winding faults, is evaluated in this paper. The proposed condition monitoring technique uses time domain terminal data in conjunction with the optimization algorithm to indicate the presence of a fault and provide information about its nature and location. The technique is demonstrated using experimental data from a laboratory machine.


Publication metadata

Author(s): Ethni SA, Zahawi B, Giaouris D, Acarnley PP

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 7th IEEE International Conference on Industrial Informatics

Year of Conference: 2009

Pages: 470-474

Date deposited: 21/05/2010

ISSN: 1935-4576

Publisher: IEEE

URL: http://dx.doi.org/10.1109/INDIN.2009.5195849

DOI: 10.1109/INDIN.2009.5195849

Library holdings: Search Newcastle University Library for this item

ISBN: 9781424437597


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