Inter-turn short circuit stator fault identification for induction machines using computational intelligence algorithms

Under the umbrella of the Computational Intelligence (CI) the performance of a two algorithms: Particle swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO), when used for inter-turn short circuit stator winding fault of induction machine, is investigated in this paper. The proposed condition monitoring technique uses time domain terminal data in conjunction with the optimization algorithm and an induction machine model to indicate the presence of a fault and provide information about its nature and location.

The proposed technique is evaluated using experimental data obtained from a 1.5 kW wound rotor three-phase induction machine. PSO and BFO are shown to be effective in identifying the type and location of the fault without the need for prior knowledge of various fault signatures.

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