Wavelet neural network based on particle swarm optimization algorithm and its application in fault diagnosis of gear-box

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作者：
College of Mechanical Engineering and Automatization, North University of China, Taiyuan 030051, China [1 ]
机构：
来源：
J Vib Shock | 2007年 / 5卷 / 133-136期
关键词：
Algorithms - Failure analysis - Neural networks - Optimization - Wavelet transforms;
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学科分类号：
摘要：
A particle swarm optimization (PSO) algorithm is proposed instead of the traditional stochastic-gradient algorithm to optimize parameters of a wavelet neuralnetwork. Then, the PSO trained wavelet neuralnetwork is applied to a gear-box fault diagnosis experiment. The experimental result indicates that the wavelet neural network training method based on the PSO algorithm is an effective training algorithm, and meanwhile it is also an available approach to solve fault diagnosis problems.
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