Gear Fault Diagnosis System Based on Wavelet Neural Networks

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 selforganization 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.

作者: Qibing Zhu

作者单位: College of Electromechanical Engineering Hangzhou Dianzi University Hangzhou, Zhejiang 310038 P.R.China

会议类型: 国际会议

会议名称: 第三届国际脉冲动力系统及应用学术会议

会议地点: 青岛

会议语种:英文

在线出版日期: 2006-07-21（万方平台首次上网日期，不代表论文的发表时间）