WindDefNet: A Multi-Scale Attention-Enhanced ViT-Inception-ResNet Model for Real-Time Wind Turbine Blade Defect Detection

WindDefNet: A Multi-Scale Attention-Enhanced ViT-Inception-ResNet Model for Real-Time Wind Turbine Blade Defect Detection

Real-time non-intrusive monitoring of wind turbines, blades, and defect surfaces poses a set of complex challenges related to accuracy, safety, cost, and computational efficiency. This work introduces an enhanced deep learning-based framework for real-time detection of wind turbine blade defects. Th...

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Bibliographic Details
Main Authors: Majad Mansoor, Xiyue Tan, Adeel Feroz Mirza, Tao Gong, Zhendong Song, Muhammad Irfan
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Machines
Subjects:
wind turbine blade defect
inception-ResNet
ViT
fault detection
wind energy
Online Access:https://www.mdpi.com/2075-1702/13/6/453
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