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Fractional Envelope Analysis for Rolling Element Bearing Weak Fault Feature Extraction 被引量：6
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作者 Jianhong Wang Liyan Qiao +1 位作者 Yongqiang Ye YangQuan Chen 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2017年第2期353-360,共8页
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 extractio... 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. © 2017 Chinese Association of Automation. 展开更多
关键词 Bearings (machine parts) Condition monitoring EXTRACTION Fault detection Feature extraction Frequency domain analysis Hilbert spaces Mathematical transformations Spectrum analysis
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