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Wind Turbine Fault Diagnosis with Imbalanced SCADA Data Using Generative Adversarial Networks

Wind turbine fault diagnostics is essential for enhancing turbine performance and lowering maintenance expenses. Supervisory control and data acquisition (SCADA) systems have been extensively recognized as a feasible technology for the realization of wind turbine fault diagnosis tasks due to their c...

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Principais autores: Hong Wang, Taikun Li, Mingyang Xie, Wenfang Tian, Wei Han
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2025-02-01
Serier:Energies
Fag:
wind turbine
fault diagnosis
imbalanced SCADA data
generative adversarial networks
long short-term memory networks
convolutional neural networks
Online adgang:https://www.mdpi.com/1996-1073/18/5/1158
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