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

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