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November 19, 2025Future InternetOpen Access

AI-Driven Damage Detection in Wind Turbines: Drone Imagery and Lightweight Deep Learning Approaches

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Authors

AHAhmed HamdiHNHassan N. Noura

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Overview

Analysis demonstrates high accuracy in detecting issues in wind turbines, suggesting deep learning can enhance maintenance efficiency.

Key Points

  • Real-time monitoring can improve maintenance strategies for wind turbines, enhancing performance.
  • Deep learning achieved 98.9% accuracy with a compact MobileNetV3 model for turbine evaluations.
  • The analysis focuses on drone-acquired imagery using advanced lightweight architectures like MobileNetV3 and ResNet.
  • Results indicate potential for autonomous inspection solutions in renewable wind energy management.

Cite This Study

Hamdi et al. (2025) studied this question.

synapsesocial.com/papers/6924fed1c0ce034ddc350ed4https://doi.org/10.3390/fi17110528
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  5. 5Hybrid CNN-GRU framework for wind turbine blade defect classification and data-driven severity assessment for predictive maintenance2026