AQUADA-GO: Automated blade damage detection and near real-time evalu-ation for operational offshore wind turbines

The AQUADA-GO project aims to develop a methodology for automated, non-contact, near real-time blade damage detection and risk evaluation in a single step using thermography and computer vision without stop-ping the normal operation of the wind turbines. The project will demonstrate both software implementation and hardware integration in an all-in-one drone platform.

The project will shift the current labor-intensive multi-step blade inspection paradigm to an automated and single-step solution that does not require stopping the normal power production of wind turbines. The project will be demonstrated in an offshore wind farm and eventually create a turnkey solution ready for market entry. The success criteria of the project are:

• the proposed new inspection solution is developed and successfully demonstrated offshore at RWE-owned wind farms;

• the new solution reduces the blade inspection time by up to 80% and the inspection cost by up to 50% compared to the existing solutions currently available on the market;
the new solution reduces the LCOE* of offshore wind energy by 2-3% over 25-30 years’ project lifetime.

* Levelized Cost of Energy: Calculates present value of total cost of building and operating a power plant over an assumed lifetime.