Fault Recognition of Rolling Bearings Based on Parameter Optimized Multi-Scale Permutation Entropy and Gath-Geva

Fault Recognition of Rolling Bearings Based on Parameter Optimized Multi-Scale Permutation Entropy and Gath-Geva

To extract fault features of rolling bearing vibration signals precisely, a fault diagnosis method based on parameter optimized multi-scale permutation entropy (MPE) and Gath-Geva (GG) clustering is proposed. The method can select the important parameters of MPE method adaptively, overcome the disad...

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Bibliographic Details
Main Authors: Haiming Wang, Qiang Li, Shaopu Yang, Yongqiang Liu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Entropy
Subjects:
rolling bearing
fault recognition
parameter optimized multi-scale permutation entropy
skewness
GG fuzzy clustering
Online Access:https://www.mdpi.com/1099-4300/23/8/1040

Internet

https://www.mdpi.com/1099-4300/23/8/1040

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