Bearing Fault Diagnosis Method Based on RCMFDE-SPLR and Ocean Predator Algorithm Optimizing Support Vector Machine

Bearing Fault Diagnosis Method Based on RCMFDE-SPLR and Ocean Predator Algorithm Optimizing Support Vector Machine

For the problem that rolling bearing fault characteristics are difficult to extract accurately and the fault diagnosis accuracy is not high, an unsupervised characteristic selection method of refined composite multiscale fluctuation-based dispersion entropy (RCMFDE) combined with self-paced learning...

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Bibliographic Details
Main Authors: Mingxiu Yi, Chengjiang Zhou, Limiao Yang, Jintao Yang, Tong Tang, Yunhua Jia, Xuyi Yuan
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Entropy
Subjects:
characteristic extraction
refine composite multiscale fluctuation dispersion entropy
self-paced learning and low-redundant regularization
Online Access:https://www.mdpi.com/1099-4300/24/11/1696

Internet

https://www.mdpi.com/1099-4300/24/11/1696

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