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Automatic Identification of Crack in Ultrasonic Infrared Imaging

Ultrasonic Infrared Imaging is a novel NDE technique, which performs well on material internal defect detection, such as metal fatigue crack, composite material impact damage and adhesion and so on. Traditional defect identification often depends on eyes and professional experience, which can’t give a clear conclusion of defect information. The identification algorithm based on time sequence images is low-level. Therefore, taking the crack detection in Ultrasonic IR Imaging as an example, after contrastive analysis of shape characters and gray distribution between crack region and normal region, characteristic parameters for different regions was creatively extracted in this paper. An automatic recognition algorithm based on Weighted Support Vector Machines is put forward for crack recognition. Subsequently, the correctness of the algorithm was validated by experiments.