Fault diagnosis of induction motors using discrete wavelet transform and artificial neural network

Abstract

This paper proposes a fault diagnosis method for induction motors based on DWT (Discrete Wavelet Transform) and artificial NN. The proposed algorithm is based on ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters. Proposed fault diagnosis method consists of data preprocessing part by frequency analysis of vibration signal, and fault classifier for fault isolation by ART2 NN. Especially, the data preprocessing part which converts the sampled signals into the frequency domain by DWT is very important to improve the performance of the fault diagnosis. In this paper both rotor and bearing faults of the induction motors are considered for diagnosis. The experiment results demonstrate the effectiveness of the proposed fault diagnosis method of induction motors. © 2011 Springer-Verlag.