Determination of wind turbine blade damages and calculationof damage area using image processing based methods

Wind turbines are exposed to harsh environmental conditions and dynamic loads due to the environments in which they are located, and as a result, they experience various structural damages over time. Damage occurring particularly on turbine blades can reduce aerodynamic performance, negatively affect energy efficiency, and lead to more significant structural problems in the long term. Therefore, effective and rapid detection of damage on turbine blades is of great importance. Currently, turbine damages are generally detected through physical inspection by authorized personnel or with the help of high-resolution camera-equipped devices such as drones. However, the fact that wind turbines are often located in hard-to-reach areas, especially in offshore environments, makes these processes both time-consuming and more costly. In this thesis study, a drone-based imaging method is proposed to enable faster, safer, and more cost-effective detection and repair of damage on wind turbine blades. Within this scope, damaged blade images obtained from Rass Wind Energy were utilized, and the damaged areas were identified using image processing techniques, followed by the measurement of the damage dimensions. Based on the type of the detected damage, a classification was made, appropriate repair materials were selected, and the steps to be followed during the repair process were outlined. With this thesis study, the proposed method aims to minimize physical intervention during the damage analysis process, thereby facilitating and accelerating the repair of damaged wind turbine blades.