Leveraging generative adversarial networks for data augmentation to improve fault detection in wind turbines with imbalanced data

Leveraging generative adversarial networks for data augmentation to improve fault detection in wind turbines with imbalanced data

In the realm of modern power systems, wind turbines (WTs) have gained significant environmental advantages, making them pivotal in the expanding landscape of wind power generation. The paramount task of ensuring the effective monitoring and fault classification of WTs is indispensable for the stabil...

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Bibliographic Details
Main Authors: Subhajit Chatterjee, Yung-Cheol Byun
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
Subjects:
Machine learning
Deep learning
Generative adversarial networks
Fault classification
Imbalanced data
Wind turbines
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025000799
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