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

Ethni, SA; Zahawi, B; Giaouris, D; Acarnley, PP

doi:10.1109/INDIN.2009.5195849

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

Lookup NU author(s): Dr Salaheddine Ethni, Dr Bashar Zahawi, Professor 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.