Automatic defect detection in ultrasonic TOFD D-scan data using image processing methods

In ultrasonic time of flight diffraction（TOFD） D-scan image,only a small fraction represents defects,whereas the majority is redundant.Because of the low contrast between defect and background image,it is difficult to manually interpret TOFD image.In addition,due to the nature of the weak amplitude of ultrasonic diffracted signals,the human factor introduces inconsistency into the interpretation.In order to automatically distinguish weld defects from the D-scan image,a defect detection method based on image processing technique is proposed.First,image pre-processing including clutter and noise suppression is conducted.Second,information entropy based image segmentation technique is employed to extract defects in the pre-processed image.At last,mathematical morphology based post-processing is carried out.The experimental results show that with the proposed method,TOFD can be used for automatic weld defect detection with satisfactory level of reliability.