Rolling bearing fault diagnosis based on fine-grained multi-scale Kolmogorov entropy and WOA-MSVM

Author:

wang Bing,li Huimin,Hu Xiong,Wang Cancan,Sun Dejian

Publisher

Elsevier BV

Reference32 articles.

1. Skidding dynamic performance of rolling bearing with cage flexibility under accelerating conditions;Liu;Mech. Syst. Signal Process.,2021

2. Average combination difference morphological filters for fault feature extraction of bearing;Lv;Mech. Syst. Signal Process.,2018

3. Sound based Degradation status recognition for railway point machines based on soft-threshold wavelet Denoising, WPD, and ReliefF;Sun;IEEE Trans. Instrum. Meas.,2024

4. Entropy feature fusion-based diagnosis for railway point machines using vibration signals based on kernel principal component analysis and support vector machine;Sun;IEEE Intelligent Transportation Systems,2022

5. A fault diagnosis method combined with LMD, sample entropy and energy ratio for roller bearings;Han;Measurement,2015

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