In-service X-ray radiography of offshore wind blades (RADBLAD)

"The first phase of the project will demonstrate the feasibility of using agile mobile wall-climbing robots, portable radiography equipment and artificial intelligence (AI) technologies to perform asset management of off-shore wind farms located in extreme and challenging environments. Gaining access to off-shore wind turbine blades is difficult and expensive e.g. with large cranes on ships or climbing with rope/platform systems. Because of the difficulty of deploying large systems off-shore, a modular approach is required to easily transport lightweight systems to test sites and assemble them quickly. A modular wall climbing robot, assembled on site, will carry the radiography deployment system up the wind tower. Two arms will extend on either side of a blade positioned in a 90 degree configuration so that the source and detector are on either side of the blade. An intelligent positioning system will keep the two aligned and normal to each other as the complex aerodynamic shape of the blade is inspected along the width of the blade. The climbing robot will then move a small distance up the tower and repeat coverage of the blade width. Allowing a full length of the blade, with inspection starting from the tip of the blade up to the blade root.

An intelligent control positioning system will be required since the blade shape and curvature will be different in each horizontal plane and the source/detector will need to adapt to the shape for optimum imaging. To cope with blade in-plane and out-of-plane vibrations, the X-ray source and detector will be kept stationary with respect to a blade by designing passive compliance into the deployment arm.

Embedded intelligence will carry out automated defect detection and classification and enable autonomous decision making for further inspection and intervention."