Wind energy system fault classification using deep CNN and improved PSO‐tuned extreme gradient boosting

Abstract Intelligent fault diagnosis for wind energy systems requires identifying unique characteristics to differentiate various fault types effectively, even when data discrepancy occurs due to the unpredictable and dynamic nature of its environment. This article addresses some of the challenges o...

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Bibliographic Details
Main Authors: Chun‐Yao Lee, Edu Daryl C. Maceren
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:IET Renewable Power Generation
Subjects:
Online Access:https://doi.org/10.1049/rpg2.13091
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