Image-based ice shape and accretion process prediction on wind turbine blades via deep learning with curvature consistency constraint

Key Points

• Accretion process prediction reveals enhanced accuracy with deep learning techniques, addressing wind turbine blade performance.
• Key evidence shows a notable improvement in prediction accuracy by up to 30% when utilizing curvature consistency constraints.
• Method involves advanced image-based analysis using deep learning, focusing on identifying ice formation on wind turbine blades.
• Results indicate significant potential for optimizing wind turbine efficiency and safety, requiring further external validation.