Rolling bearing fault diagnosis using refinement envelope analysis based on the EMD method

被引：0
|
作者：
Yu, Bo [1 ]
Liu, Jinzhao [2 ]
Wang, Chengguo [2 ]
机构：
[1] China Three Gorges Univ, Coll Sci, Inst Intelligent Vis & Image Informat, Yichang 443002, Peoples R China
[2] China Acad Railway Sci, Beijing 100081, Peoples R China
来源：
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES | 2007年 / 2卷
关键词：
rolling bearing fault; response modulation methods; EMD methods; DTFT refinement;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The empirical mode decomposition (EMD) is a new method for adaptive decomposition of nonlinear and non-stationary signals. This paper combines the EMD method and the conventional response modulation method to analyze the fault in the rolling bearing. B-spline EMD is also investigated to extract the high frequency components of the signal. Then we use discrete time Fourier transform (DTFT) to get the refinement spectrum analysis. The results show that the combination of these two methods performs excellently.
引用
收藏
页码：562 / +
页数：2
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