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In-line inspection of advanced components remains a challenging task in industry. The authors will describe an automated methodology that uses numerical simulations to automatically determine the best set of experimental parameters to inspect the structure on defects using active thermography. The inspection is performed using a robotic arm and advanced path-planning tools to determine the optimal positions of the measurement points and excitation points. During the path planning, the directional emissivity is considered for the complex surface, and a minimization of the amount of measurement points is performed. The numerical simulation optimization used a genetic algorithm and spline regression model to optimize the heat power, robot speed, camera frame rate, and excitation timing to fulfill the automatic inspection.

Optimized robotic setup for automated active thermography using advanced path planning and visibility study