RWE + Quali Drone Complete First Autonomous Offshore Wind Blade Inspection on Spinning Turbines

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RWE + Quali Drone Complete First Autonomous Offshore Wind Blade Inspection on Spinning Turbines

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Danish startup Quali Drone, in collaboration with offshore wind developer and operator RWE and several other partners, successfully inspected offshore wind turbine blade damages using autonomous drone technology while the blades rotate at the Rødsand 2 Offshore Wind Farm in Denmark — the first operational deployment of this technology. "We have proven that it is possible to autonomously inspect offshore wind turbines with a drone of a certain size equipped with a visual camera, while the turbine is in operation. This is a major accomplishment for us. We have worked on everything from developing drone software and hardware to mission planning and online data infrastructure. Now, we have a commercially ready solution that can be tailored to wind farm operators' needs," said Jesper Smit, CEO of Quali Drone. "For the first time, we have successfully carried out a drone inspection of offshore wind turbines in operation. By using drones for autonomous inspections, we expect that downtimes and costs can be significantly reduced in the long run," said Marcus Mejborn, General Manager of Rødsand 2 Offshore Wind Farm, RWE. The context was that inspections of blade damages are usually carried out when the turbine has been stopped. The new AQUADA-GO project enables contact-free, real-time blade damage detection while the turbine is spinning, helping save turbine downtime. Drone-based blade inspection delivers significant savings through increased efficiency, while also reducing CO2 emissions and improving inspection safety. Technically, the project is based on the AQUADA technology developed at DTU Wind Energy's laboratory, combining drone technology with thermography and computer vision to detect surface damage and potential subsurface fractures on operational offshore wind turbine blades. DTU has developed an AI model that helps the drone automatically identify wind turbine blade abnormalities to indicate critical damage using AI algorithms and infrared imaging. The AI model is trained and improved with new inspection data each time the drone is deployed at wind farms. At scale, the new technology has been successfully demonstrated several times onshore by project partners including Quali Drone, RWE, Statkraft, TotalEnergies, DTU and Energy Cluster Denmark. The AQUADA-GO innovation project runs from 2022 to March 2026 with a total budget of DKK 17,796,010 and is supported by EUDP — the Energy Technology Development and Demonstration Program.