Sulzer Schmid, the Swiss company examining UAV technology for rotor blade inspections, and AI specialist Nnaisense have partnered to develop an artificial intelligence engine to automatically detect rotor blade damage on wind turbines. This is expected to bring the dual benefits of improving productivity and consistency.
The partners are aiming to build the industry’s most powerful Artificial Intelligence engine able to recognise damage based on the inspection of images. The initial version will be able to flag all areas of concern on any given damaged blade. Ensuing upgrades will add other capabilities such as the ability to establish damage categories and severity levels.
“Maintaining the structural integrity of rotor blades is critical to maximising energy output and ensuring the safe operation of wind turbines. We are convinced that we will be able to transfer our extensive expertise in surface defect recognition from other industries to the wind industry and are looking forward to our cooperation with Sulzer Schmid, an innovator in its own space”, commented Faustino Gomez, CEO of Nnaisense.
The autonomously flying drones of the 3DX Inspection Platform of Sulzer Schmid offer high-definition quality and consistent image acquisition time as well as 100 per cent blade coverage while minimising human errors and operational risks.
The image tools ensure detailed and efficient damage assessment. With the support of an AI-enabled inspection software, the review work of blades will be improved. Instead of having to review the entire surface of the blades, they will simply need to focus on the pre-selected areas of concern. This technology progress will not only significantly boost the productivity of the reviewing teams but will also improve the quality of damage annotation processes.
Read about Volvo’s AI research in improving quarry safety here.