Rolling bearing fault feature extraction based on maximum correlated kurtosis deconvolution and improved autocorrelation spectral kurtograph

Chencheng He; Wenbo Wang

doi:10.1117/12.2689626

10 August 2023 Rolling bearing fault feature extraction based on maximum correlated kurtosis deconvolution and improved autocorrelation spectral kurtograph

Chencheng He, Wenbo Wang

Author Affiliations +

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 127483E (2023) https://doi.org/10.1117/12.2689626
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

In order to further improve the separation and detection accuracy of bearing fault characteristics, A new method for early fault diagnosis of rolling bearings based on Maximum Correlated Kurtosis Deconvolution and autocorrelation kurtograph was proposed. Firstly, the vibration signal of bearing fault is denoised by Maximum Correlated Kurtosis Deconvolution; Then, the improved autocorrelation spectral kurtograph is used to select the optimal frequency center and bandwidth of fault features. According to the optimal frequency center and bandwidth, the band pass filtering is carried out to remove noise and random pulse irrelevant components in the band signal. Finally, the sub-signal after bandpass filtering is analyzed by envelope spectrum, identify fault frequency and realize early fault diagnosis of rolling bearing. In the experiment, different types of bearing fault data verify the effectiveness of the proposed method.

Citation Download Citation

Chencheng He and Wenbo Wang "Rolling bearing fault feature extraction based on maximum correlated kurtosis deconvolution and improved autocorrelation spectral kurtograph", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 127483E (10 August 2023); https://doi.org/10.1117/12.2689626

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KEYWORDS

Autocorrelation

Tunable filters

Electronic filtering

Optical filters

Signal processing

Feature extraction

Vibration

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