Fault diagnosis method of rolling bearing based on AFD algorithm

被引：4
作者：
机构：
[1] School of Traffic and Transportation, Beijing Jiaotong University
[2] Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University
[3] Infrastructure Inspection Center, China Academy of Railway Sciences
来源：
Liang, Y. | 1600年 / Chinese Academy of Railway Sciences卷 / 34期
关键词：
Adaptive Fourier decomposition; Fault diagnosis; Kurtosis; Mono-component signal; Resonant demodulation; Rolling bearing;
D O I：
10.3969/j.issn.1001-4632.2013.01.14
中图分类号：
学科分类号：
摘要：
Adaptive Fourier decomposition (AFD) algorithm decomposes the vibration signal of rolling bearing into a series of mono-components, and the kurtosis of each mono-component is calculated. The kurtosis is arranged in descending order. The inflection point of kurtosis becoming stable is adaptively sought out and the corresponding mono-component signals before inflection point are summed up, then the envelope is taken as the resonance demodulation. According to the frequency spectrum obtained from demodulation, whether rolling bearing has fault is judged and the fault location is determined. Taking N205EM-type rolling bearing for example, the experiment results indicate that the proposed method is accurate and effective in extracting the fault information of rolling bearing without presetting filter frequency band and the absence of negative frequency" with no physical meaning. The spectrum characteristics better than traditional resonance demodulation are obtained. The proposed method is effective in diagnosing the fault of rolling bearing."
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收藏
页码：95 / 100
页数：5
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