Review of state-of-the-art surface defect detection on wind turbine blades through aerial imagery: Challenges and recommendations☆

Maintenance is a critical aspect of wind power generation as it not only ensures the efficient operation of wind turbines, but also their continuous availability and functionality. For wind turbine blades, regular maintenance is essential to optimise power output and minimise operational downtime. While various maintenance strategies are well-documented, such as predictive approaches using Machine Learning and traditional visual inspections, there is limited research on leveraging aerial imagery for detecting defects on turbine blades. The objective of this review paper is to address this by focusing on the challenges and requirements for effective surface defect detection in wind turbine blades through aerial imagery. The task of inspecting surface defects on wind turbine blades is particularly difficult due to data scarcity, substantial computational requirements, and the geometric difficulties inaccurately localising defects. By addressing these issues, we aim to identify and propose promising future directions to overcome these challenges at hand, thereby ensuring a progression of research and development in this field.