中文

Journal of Shanghai University（Natural Science Edition） ›› 2026, Vol. 32 ›› Issue (2): 240-250.doi: 10.12066/j.issn.1007-2861.2535

• Communication and Information Engineering • Previous Articles    

A deep learning-based non-destructive testing method by combining ultrasonic phased array sector scanning and total focusing method

CHU Qingyuan1,2,3, CHU Haijian1,2,3   

  1. 1. School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, China;
    2. Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China;
    3. Shanghai Key Laboratory of Energy Engineering Mechanics, Shanghai University, Shanghai 200444, China
  • Received:2023-06-13 Published:2026-05-11

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Abstract: To improve the efficiency and accuracy of ultrasonic phased array (PA) scanning, a nondestructive testing approach that combines sector scanning and the total focusing method (TFM) is proposed with the assistance of a deep learning model, namely, YOLOv5s. Using this method, the self-trained YOLOv5s model was applied for preliminary defect recognition on sector scanning images to enable the rapid identification of possible defect regions. Software was developed for the total focusing method imaging system to image possible defects in possible defect regions based on the Qt platform. The results obtained from the test of the assessment block indicate that this new proposed approach can take advantage of not only the high imaging efficiency of ultrasonic phased array sector scanning but also the high accuracy of the total focusing method to achieve improvements in both test efficiency and accuracy.

Key words: ultrasonic phased array (PA), total focusing method (TFM), deep learning, combined test approach

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