Fault feature extraction based on wavelet analysis

被引：0

作者：

Zang Xian-feng ^{[1
]}

Zhang Zheng-dao ^{[1
]}

Bai Rui-lin ^{[1
]}

Peng Zhu-miao ^{[1
]}

机构：

[1] So Yangtze Univ, Sch Commun & Control Engn, Wuxi 214122, Peoples R China

来源：

Proceedings of the 2007 Chinese Control and Decision Conference | 2007年

关键词：

wavelet analysis; feature extraction; fault diagnosis;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The vibration signals of a system always carry the dynamic information of the system. These signals are very useful for the feature extraction and fault diagnosis. However, in many cases, because these signals have very low signal-to-ratio (SNR), it is difficult to extract feature components and the application of information. Therefore, A de-noising method based on wavelet analysis is applied to feature extraction for electrical signals, and the feature sound is extracted successfully.

引用

页码：619 / +

页数：4