Fault Diagnosis of Rolling Bearing Based on FV-FBE

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Fault Diagnosis of Rolling Bearing Based on FV-FBE

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[1]LEI Wenping,SONG Shenglin,HAO Wangshen,et al.Fault Diagnosis of Rolling Bearing Based on FV-FBE[J].Journal of Zhengzhou University (Engineering Science),2020,41(05):82-86.[doi:10.13705/j.issn.1671-6833.2020.03.020]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 41卷 Number of periods: 2020 05 Page number: 82-86 Column: Public date: 2020-10-01

Title:: Fault Diagnosis of Rolling Bearing Based on FV-FBE

Author(s):: LEI Wenping1; SONG Shenglin1; HAO Wangshen1; CHEN Hong1; HU Xin2; 1.College of Mechanical and Power Engineering, Zhengzhou University,Zhengzhou 450001， China; 2.Zhengzhou Expert Technology Co.,Ltd.,Zhengzhou 450001， China

Keywords:: full vector spectrum; frequency band entropy; fault diagnosis; rolling bearing

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2020.03.020

Abstract:: It was not comprehensive to extract the vibration signal of rotating machinery from single channel signal. In order to extract the weak fault features of rolling bearing accurately from the strong background noise, a fault diagnosis algorithm of rolling bearing based on full vector frequency band entropy(FV-FBE) was proposed in this paper. The short time Fourier transform was used to calculate the frequency band entropy(FBE). And according to the FBE minimum principle, the bandwidth and center frequency of the dual channel signal band-pass filter were designed adaptively. The filtered dual channel signal was demodulated by the full vector Hilbert envelope, and the full vector envelope spectrum was obtained for fault diagnosis of rolling bearing. The experimental results showed that the FV-FBE algorithm could extract the fault features of rolling bearing comprehensively and accurately, which was better than the full vector envelope spectrum obtained by spectral kurtosis algorithm and had strong anti-interference ability.

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Last Update: 2020-10-23