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.