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Xinmin Wang
Northeast Petroleum University

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Fault Diagnosis Based on Wavelet Genetic Neural Network for Motor Keyong Shao; Lijuan Han; Yang Liu; Xinmin Wang; Fengwu Zhang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In the motor fault diagnosis technology, vibration signals can fully reflect the motor operation conditions. In this paper, a linear motor fault diagnosis method based on wavelet packet and neural network was presented. The improved neural network system was designed with variable hidden layer neurons. The network chose different numerical values depending on different situations to reach the requirements that improving diagnostic accuracy and shortening the diagnosis time. The linear motor’s normal and two common faults vibration signals were analyzed and the vibration signals energy characteristics were extracted through wavelet packet, then identified fault through neural network. The experimental results show that this method can effectively improve the motor fault diagnosis accuracy. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4915
Co-Authors Fengwu Zhang Keyong Shao Lijuan Han Yang Liu