AQUADA-GO Demonstrates First Autonomous Inspection of Operational Offshore Wind Turbines

The Danish startup Quali Drone has in collaboration with the 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. The solution significantly increases safety and reduces the cost and CO₂ emissions associated with blade inspections.

Challenge

Traditionally, wind turbine blades were inspected using rope access, suspended platforms, ground-based cameras, or drones relying on optical imaging. These methods could only identify visible surface damage such as erosion, dirt, and cracks, while critical damage beneath the blade surface often remained undetected. Furthermore, inspections required the wind turbine to be shut down, resulting in additional costs due to downtime and lost revenue.

Solution

The AQUADA-GO innovation project developed a drone technology that combines thermography, artificial intelligence, and computer vision to enable automated, contactless, real-time blade damage detection while the wind turbine remains in operation. The technology can automatically detect both surface damage and potential subsurface fractures in operational wind turbine blades.

The project builds on the AQUADA technology developed at the DTU Wind Energy laboratory. Quali Drone developed the software implementation and hardware integration, resulting in an all-in-one drone platform for wind turbine inspections that is ready for market deployment and commercial use. The solution was developed in close collaboration with RWE, Statkraft, and TotalEnergies.

Result

The new drone technology and platform have been successfully demonstrated several times onshore by the project partners at wind farms owned by Statkraft and RWE. Most recently, the concept was demonstrated offshore, for the first time, using drone imagery to identify surface blade damage at the Rødsand 2 offshore wind farm.

The solution is expected to deliver significant cost savings for wind farm operators through increased inspection efficiency and reduced turbine downtime. In addition, it is expected to reduce CO₂ emissions and improve safety during wind turbine inspections.