In this paper a method for enhancing the capabilities of Neural Networks novelty filters using genetic algorithms is described, and a method for detecting shorted turns in rotating machines using such computational intelligence techniques (neural network and genetic algorithm) is presented. The methods of signal processing and detection of faults in operating machines is discussed. The use of novelty filters for the detection of shorted turns and mechanical failures in operating machines is described. Genetic algorithm has been used to train the neural network to enhance its Capabilities as a novelty detector. The proposed technique has been applied on an induction machine and the simulation results have been presented to show the effectiveness of the proposed technique.
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