A Novel Intelligent Method for Bearing Fault Diagnosis Based on EEMD Permutation Entropy and GG Clustering

A Novel Intelligent Method for Bearing Fault Diagnosis Based on EEMD Permutation Entropy and GG Clustering

For a rolling bearing fault that has nonlinearity and nonstationary characteristics, it is difficult to identify the fault category. A rolling bearing clustering fault diagnosis method based on ensemble empirical mode decomposition (EEMD), permutation entropy (PE), linear discriminant analysis (LDA)...

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Bibliographic Details
Main Authors: Jingbao Hou, Yunxin Wu, Hai Gong, A. S. Ahmad, Lei Liu
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Applied Sciences
Subjects:
intelligent fault diagnosis
rolling element bearing
ensemble empirical mode decomposition
permutation entropy
linear discriminant analysis
clustering
Online Access:https://www.mdpi.com/2076-3417/10/1/386

Internet

https://www.mdpi.com/2076-3417/10/1/386

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