Autonomous Optical Inspection of Large Scale Freeform Surfaces

It is estimated that 80% of wind turbine blade failures can be back-tracked to defects which were introduced during production. Blades that are nonconforming to the intended design of their outer geometry are likely to underperform concerning aerodynamic lift, and can, therefore, cause their turbines to have a lower than nominal power output.

Furthermore, small, usually discrete, surface aberrations can lead to turbulence in the boundary ow around the blade. This turbulence reduces the lift even more and can lead to surface erosion, which potentially can cause blade failure within a few years after installment. Consequently, geometric quality inspection in the production is vital to the performance and expected lifetime of a blade, and thus also to the business cases of the blade manufactures, owners, and operators.

This thesis studies how the geometric inspection of blades can be automated, through the development and construction of a novel autonomous robotic scanner system. The studied scanner modality is optically based and relies on a structured light camera-projector system, which samples point clouds from the blade's surface.

Experiments demonstrate the system's capabilities in measuring the outermost 20 meters of 55 meter long blades. The Modular Freeform Gauge approach is used to study the scanner system's metrological performance. Additionally, the thesis considers the interaction between light and materials, with the purpose of selecting the optimal parameters, such as the coding strategy, for the structured light scanner.