Local oscillatory-characteristic decomposition and its application in roller bearing fault diagnosis

被引：0
|
作者：
Zhang K. [1 ]
Shi Y.-C. [1 ]
Tang M.-Z. [1 ]
Wu J.-T. [1 ]
机构：
[1] School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2016年 / 35卷 / 01期
关键词：
Fault diagnosis; Local oscillatory-characteristic decomposition; Mono-oscillatory component; Nonstationary signal; Roller bearing;
D O I：
10.13465/j.cnki.jvs.2016.01.016
中图分类号：
学科分类号：
摘要：
A new self-adaptive time-frequency analysis method named local oscillatory-characteristic decomposition (LOD) was proposed. This method was based on local oscillatory characteristics of a signal itself, the operations including differential, coordinates domain transform and piecewise linear transform were used to decompose the signal into a series of mono-oscillatory components (MOC), their instantaneous frequency had physical meanings, and thus they were suitable for processing multi-component signals. After illustrating the decomposition principle of LOD in detail, the LOD was compared with the empirical mode decomposition (EMD) method and the local mean decomposition (LMD) method by analyzing simulated signals. The results showed that the LOD method is superior to the other two. Meanwhile, aiming at the multi-component modulated feature of roller bearing fault vibration signals, the LOD was applied in roller bearing fault diagnosis. The results demonstrated that the LOD can extract fault characteristics in roller bearing fault vibration signals effectively. © 2016, Chinese Vibration Engineering Society. All right reserved.
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页码：89 / 95
页数：6
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