Bearing Fault Recognition Based on Improved Wavelet Denoising and EMD Method

被引：0
|
作者：
Zhang, Tongsheng [1 ]
Xu, Min [1 ]
机构：
[1] Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450052, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON CONTROL SYSTEM AND AUTOMATION (CSA 2013) | 2013年
关键词：
wavelet threshold denoising; EMD; energy-correlation coefficient method; fault diagnosis; EMPIRICAL MODE DECOMPOSITION;
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：
A method combining improved wavelet threshold denoising and EMD is applied to bearing fault diagnosis. The original signal will be denoised by the improved wavelet threshold method, then the denoised signal will be decomposed into several IMFs (intrinsic mode functions) by EMD adaptivly. The IMFs reflecting the fault characteristics are selected through energy-correlation coefficient method and fault frequency will be got from envelope spectrum analysis. The experiment results prove that the method can extract fault characteristic frequency effectively.
引用
收藏
页码：427 / 432
页数：6
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