Acknowledgment
This study is partly supported by the QualiDrone Project (Intelligent, autonomous drone inspection of large structures within the energy industry, 64020-2099), the RELIABLADE project (Improving Blade Reliability through Application of Digital Twins over Entire Life Cycle, 64018-0068), and the AQUADA-GO project (Automated blade damage detection and near real-time evaluation for operational offshore wind turbines, 64022-1025, through the Energy Technology Development and Demonstration Program (EUDP) of Denmark.