A state-of-the-art survey of welding radiographic image analysis: Challenges, technologies and applications

被引:22
作者
Liu, Tianyuan [1 ]
Zheng, Pai [1 ]
Bao, Jinsong [2 ]
Chen, Huabin [3 ]
机构
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong 999077, Peoples R China
[2] Donghua Univ, Coll Mech Engn, Shanghai 201620, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Mat Sci & Engn, Shanghai 200240, Peoples R China
关键词
Welding; Non-destructive testing; Radiographic image; Image analysis; Deep learning; X-RAY IMAGES; DEFECT DETECTION; WELDED-JOINTS; AUTOMATIC CLASSIFICATION; NEURAL-NETWORKS; DISCONTINUITIES DETECTION; CONTRAST ENHANCEMENT; ACTIVE CONTOURS; NDT SYSTEM; PART II;
D O I
10.1016/j.measurement.2023.112821
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Welding radiographic image analysis (WRIA) is a key technology for welding automated non-destructive testing. Although there already exist some valuable surveys on WRIA, they do not provide a systematic overview of the challenges faced by WRIA and lack a careful distinction and comparison of the core feature techniques in WRIA. With the rapid development of the WRIA area, it is both urgent and challenging to comprehensively review the relevant studies. Therefore, this paper provides an extensive review of 164 papers published in the recent quarter century (1997-2021) ever since its first coined. Three key aspects, namely the challenges faced by WRIA, the evolutionary paths involved in the technology, and the specific application tasks are further discussed in detail. At last, potential future perspectives for WRIA are explored in terms of problem setup, technical improvement, and humanistic care, so as to provide useful insights to both academic researchers and industrial practitioners.
引用
收藏
页数:19
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