Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM

Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM

To solve the problem of fault signals of wind turbine bearings being weak, not easy to extract, and difficult to identify, this paper proposes a fault diagnosis method for fan bearings based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Grey Wolf Algorithm Optim...

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Bibliographic Details
Main Authors: Liping Liu, Ying Wei, Xiuyun Song, Lei Zhang
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Energies
Subjects:
CEEMDAN
fuzzy entropy
wind turbine
fault diagnosis
bearings
GWO-KELM
Online Access:https://www.mdpi.com/1996-1073/16/1/48

Internet

https://www.mdpi.com/1996-1073/16/1/48

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