Comparison of particle swarm and simulated annealing algorithms for induction motor fault identification

S. A. Ethni, B. Zahawi, D. Giaouris, P. P. Acarnley

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

31 Scopus citations

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.

Original languageBritish English
Title of host publication2009 7th IEEE International Conference on Industrial Informatics, INDIN 2009
Pages470-474
Number of pages5
DOIs
StatePublished - 2009
Event2009 7th IEEE International Conference on Industrial Informatics, INDIN 2009 - Cardiff, United Kingdom
Duration: 23 Jun 200926 Jun 2009

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
ISSN (Print)1935-4576

Conference

Conference2009 7th IEEE International Conference on Industrial Informatics, INDIN 2009
Country/TerritoryUnited Kingdom
CityCardiff
Period23/06/0926/06/09

Fingerprint

Dive into the research topics of 'Comparison of particle swarm and simulated annealing algorithms for induction motor fault identification'. Together they form a unique fingerprint.

Cite this