Abstract
A robotic system for combined thermal nondestructive testing of large-size parts, including data fusion, is described. The efficiency of combining results of infrared (IR) and ultrasonic IR thermographic inspection has been demonstrated on a complex-shape reference sample containing 18 surrogates of manufacture and in-service defects. The data fusion algorithms including IR image stitching in space and automated defect detection and characterization by using a neural network have demonstrated efficiency of the proposed approach in practical testing.
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