Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction

被引:32
|
作者
Wang, Jianhong [1 ]
Qiao, Liyan [2 ]
Ye, Yongqiang [3 ]
Chen, YangQuan [2 ]
机构
[1] Nantong Univ, Sch Sci, Nantong 226019, Peoples R China
[2] Univ Calif, Sch Engn, Merced 95343, CA USA
[3] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Peoples R China
基金
中国国家自然科学基金;
关键词
Fractional analytic signal; fractional envelope analysis; fractional Hilbert transform; rolling element bearing; weak fault feature extraction; HILBERT TRANSFORM; SPECTRAL KURTOSIS; DIAGNOSIS; MACHINES;
D O I
10.1109/JAS.2016.7510166
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 bearing weak fault feature extraction is crucial to mechanical fault diagnosis and machine condition monitoring. Envelope analysis based on Hilbert transform has been widely used in bearing fault feature extraction. A generalization of the Hilbert transform, the fractional Hilbert transform is defined in the frequency domain, it is based upon the modification of spatial filter with a fractional parameter, and it can be used to construct a new kind of fractional analytic signal. By performing spectrum analysis on the fractional envelope signal, the fractional envelope spectrum can be obtained. When weak faults occur in a bearing, some of the characteristic frequencies will clearly appear in the fractional envelope spectrum. These characteristic frequencies can be used for bearing weak fault feature extraction. The effectiveness of the proposed method is verified through simulation signal and experiment data.
引用
收藏
页码:353 / 360
页数:8
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