Wind Turbine Blade

Wind turbine blade research centers on improving inspection and maintenance to enhance efficiency and reduce downtime in wind energy production. Current efforts focus on automated defect detection using deep learning models like U-Net and Vision Transformers, often incorporating techniques like sparse filtering and physics-constrained recurrent neural networks to improve accuracy and generalization, particularly in challenging real-world scenarios such as drone-based inspections. These advancements are crucial for optimizing wind farm operations, reducing maintenance costs, and maximizing the lifespan and energy output of wind turbines.