- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | CHENG Yao, CHEN Bingyan, ZHANG Weihua, LI Fuzhong. Fault Diagnosis of Axle-Box Bearing Based on Weighted Combined Improved Envelope Spectrum[J]. Journal of Southwest Jiaotong University, 2024, 59(1): 142-150. doi: 10.3969/j.issn.0258-2724.20220019
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Since the weak fault feature of train axle-box bearings is difficult to be extracted in a wide frequency band, this paper proposes a weighted combined improved envelope spectrum (WCIES) for fault diagnosis based on the second-order cyclostationary of bearing fault signals. First, the fine demodulation of the vibration signal in the full frequency band is achieved by decomposing the vibration signal into the dual-frequency domain composed of spectral and cyclic frequencies through the spectral coherence algorithm. The candidate fault frequency of the bearing is identified based on the local feature of spectral coherence. Then, the 1/3-binary tree filter is applied to divide the spectral frequency into a series of narrowbands with different center frequencies and bandwidths, and the mode of spectral coherence is integrated along the spectral frequency in the narrow band to obtain the narrowband IES. Then, the CIES of each decomposition layer is constructed by taking the ratio of the energy of the candidate fault frequency in the narrowband IES as the diagnostic index. Finally, the weighted average of the WCIES of different decomposition layers is performed, and the WCIES of the bearing vibration signal is obtained. The research results show that the advantage of the proposed method is that it can fully integrate the bearing fault information distributed in different narrowbands and does not depend on the nominal fault period information. Compared with the existing methods, it can more effectively reveal the characteristic frequency and harmonic characteristics of bearing faults and has advantages in extracting and identifying weak faults of axle-box bearings.
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