• ISSN 0258-2724
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CHEN Bingyan, GU Fengshou, ZHANG Weihua, SONG Dongli, CHENG Yao. Axle-Box Bearing Fault Diagnosis Based on Multiband Weighted Envelope Spectrum[J]. Journal of Southwest Jiaotong University, 2024, 59(1): 201-210. doi: 10.3969/j.issn.0258-2724.20220047
Citation: CHEN Bingyan, GU Fengshou, ZHANG Weihua, SONG Dongli, CHENG Yao. Axle-Box Bearing Fault Diagnosis Based on Multiband Weighted Envelope Spectrum[J]. Journal of Southwest Jiaotong University, 2024, 59(1): 201-210. doi: 10.3969/j.issn.0258-2724.20220047

Axle-Box Bearing Fault Diagnosis Based on Multiband Weighted Envelope Spectrum

doi: 10.3969/j.issn.0258-2724.20220047
  • Received Date: 15 Jan 2022
  • Rev Recd Date: 20 Jul 2022
  • Available Online: 12 Dec 2022
  • Publish Date: 29 Aug 2022
  • To enhance the robustness of axle-box bearing fault detection under complex interference noise, the envelope spectrum construction method for axle-box bearing fault diagnosis is investigated by cyclic spectral analysis and considering the distribution difference of bearing fault information and threshold denoising. Firstly, the frequency domain signal-to-noise ratio is proposed as a new measure for bearing fault information quantification to evaluate the fault-related information in different spectral frequency bands of the spectral coherence. Secondly, a fault characteristic information distribution function with spectral frequency as the variable is constructed and an information threshold is adaptively determined to identify the spectral frequency components that are rich in fault information and dominated by interference noise in the spectral coherence; further, a weight function based on the fault characteristic information distribution function and the information threshold is designed. Finally, a multiband weighted envelope spectrum is generated from the spectral coherence with the weight function and is used to detect different axle-box bearing faults by analyzing the bearing fault characteristic frequencies. The analysis results of the experimental data of railway axle-box bearings show that compared with typical spectral coherence-based envelope spectrum methods, the multiband weighted envelope spectrum can accurately detect the faults of the outer race, rolling element and inner race of the axle-box bearing under complex interference noise and can achieve higher performance quantification indicators (frequency domain signal-to-noise ratio and negentropy).

     

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