A Method of Gear Fault Diagnosis based on CWT and ANN

摘要：

Aimed at the engine rotor fault, a new diagnosis method based on Wavelet Transform and artificial neural network (ANN) is proposed. Firstly,according to the wavelet transform theories, the original signals are sampling repeatedly, and the continuous wavelet transform (CWT) is used for the signals sampled. Afterward, the obtained signals are decomposed to fixed layer so as to obtain the frequency band characteristics of the original signals. So the traditional spectrum features are extracted, and the feature vector is obtained. Second, we use ANN technique to diagnose the selected features intelligently. The results adequately prove that the methods of feature extraction and feature selection advanced in this paper are rational and effective.

关键词： gear fault diagnosis CWT ANN

作者: ZhiAn Song YuFeng Song

作者单位: Shangdong University of Science and Technology, Qingdao 266510, China

会议类型: 国际会议

会议名称: The Second International Conference on Business Intelligence and Financial Engineering(BIFE 2009)(第二届商务智能与金融工程国际会议)

会议地点: 北京

会议语种:英文

页码: 42-45

在线出版日期: 2009-07-24（万方平台首次上网日期，不代表论文的发表时间）