A model-based approach for in-situ automatic defect detection in welds using ultrasonic phased array

被引:6
|
作者
Bouzenad, Abd Ennour [1 ,2 ]
Yaacoubi, Slah [1 ]
Montresor, Silvio [2 ]
Bentahar, Mourad [2 ]
机构
[1] Inst Soudure, Equipe Monitoring & Intelligence Artificielle, 4 Blvd Henri Becquerel, F-57970 Yutz, France
[2] Le Mans Univ, Grad Sch IA GS, Inst Acoust, CNRS,Lab Acoust Univ Mans LAUM,UMR 6613, Av Olivier Messiaen, F-72000 Le Mans, France
关键词
Decision-making; Intelligent system; Weld diagnosis; Quality control; Defect detection; Image processing; Ultrasonic testing; RECOGNITION; COMPONENTS; MATRIX;
D O I
10.1016/j.eswa.2022.117747
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The accuracy of diagnosis performed by human operators is closely related to different factors such as fatigue and subjectivity. The solution can be in developing intelligent systems that aid humans in decision-making. In that sense, the present paper proposes a model-based methodology for automatic analysis of ultrasonic data to detect, locate, and size defects in welds. For this purpose, a novel reference image construction technique is developed basing on Shannon entropy. Using this reference image, an original image metric is proposed. This metric also enables to determine the length of the detected defects. Three case studies are used to validate the proposed model where defects are first simulated numerically, and then artificial and natural. To assess the relevance of the proposed model, results are compared with those obtained by experts. The comparison is satisfactory, which offers the possibility of transposing the proposed approach of diagnosis to other techniques in which a sequence of images can be obtained.
引用
收藏
页数:18
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