Abstract

A hybrid technique for diagnosing broken rotor bar fault of induction motor using Multi-Wavelet Transform (MWT) and radial basis neural network is presented. The stator currents of induction motor are preprocessed using multi-wavelet transform and the decomposed components are obtained. Then, these features are given as input to the neural network to identify fault. This paper compares the proposed hybrid technique with MWT-Feed Forward Neural Network (FFNN) and Discrete Wavelet Transform-FFNN techniques. These techniques are compared using the concept of classifier performance. From the simulation results, it is evident that the proposed method is superior to other methods with regard to objective proposed.

Keywords:

Broken rotor bar, classifier performance, multiwavelet transform , radial basis neural network,

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Competing interests

The authors have no competing interests.

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