Wavelet Neural Network Based on Modified PSO and Its Application in Fault Diagnosis of Gearbox

被引：0

作者：

Liu Ying ^{[1
]}

Liu Jie ^{[1
]}

Huang Fu Feng Ying ^{[1
]}

Pan Hongxia ^{[1
]}

机构：

[1] Tianjin Univ Technol & Educ, Key Lab High Speed Cutting & Precis Machining, Tianjin 300222, Peoples R China

来源：

ISTM/2009: 8TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-6 | 2009年

关键词：

PSO; wavelet neural network; gearbox;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A modified particle swarm optimization-compound model PSO with stochastic inertia weigh is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to the fault diagnosis experiment of gearbox. The experimental result indicates that the wavelet neural-network training method based on the modified PSO is effective. This is an available approach to solve the problems on condition monitoring and fault diagnosis.

引用

页码：1647 / 1650

页数：4

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