Gear fault diagnosis system based on wavelet neural networks

被引：0
|
作者：
Zhu, Qibing [1 ]
机构：
[1] Hangzhou Dianzi Univ, Coll Electromech Engn, Hangzhou 310038, Zhejiang, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES A-MATHEMATICAL ANALYSIS | 2006年 / 13卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A new approach for gear fault diagnosis based on wavelet neural networks (WNN) is presented. WNN is a combination of time-frequency localization characteristic of wavelet transform and self-organization training function of artificial neural network. It is more suitable for extracting mechanical fault information. This network is used to distinguish the condition of gear, and then diagnose its fault. The experiment results show that WNN is practical in the field of faults diagnosis.
引用
收藏
页码：671 / 673
页数：3
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