Artificial Neural Networks for Automatic Classification of Induction Machine Faults
In this paper, new classification method of induction motor faults is proposed that permit to give a best solution to the classification problem. This method based on Time–frequency representation for classification of the current waveforms. It is composed of two steps: feature extraction and rule decision. Artificial neural networks (ANN) are used for decision criterion. The diagnosis allows the detection of bearing fault, stator fault and the rotor fault. The flexibility of this method allows an accurate classification independent from the level of load. This method is validated on a 5.5-kW induction motor test bench.
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