Algorithm Design and Software Development for Parameter Extraction of Welding Seam Feature
Konferenz: MEMAT 2022 - 2nd International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology
07.01.2022 - 09.01.2022 in Guilin, China
Tagungsband: MEMAT 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Dai, Xianling (School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China)
Shen, Yi; Yuan, Mingxin; Bian, Xiang (School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China & Zhangjiagang Industrial Technology Research Institute, Jiangsu University of Science and Technology, Zhangjiagang, Jiangsu, China)
Inhalt:
In order to accurately extract the characteristic parameters of the welding seams in the digital model of welding parts, improve the speed of the welding robot to accurately select the welding process, and then to improve welding quality and efficiency, a welding seam recognition software based on the parameter extraction algorithm of welding seam feature is developed. First, the spatial position relationship of the welded joint is determined by the STL model based on welded parts. Then the weld characteristics based on the joint form and the groove shape are identified according to the joint space position and the minimum contour line. Next Then, the commonality analysis was carried out for each groove in the joint, and the extraction model of the welding seam characteristic parameters related to the welding process was established. Finally, the development of recognition software for the welding seam feature is completed by combining the principle of the parameter extraction algorithm and the MFC single file application program. The test results show that the proposed welding seam feature parameter extraction algorithm can accurately identify 4 types of joint forms and 10 groove types, as well as accurately extract parameters such as weld gap, groove included angle and welded plate thickness, which is characterized by wide weld feature recognition and complete information extraction. The recognition software for the welding seam feature is simple to operate and fast to run, and has the functions of welding seam feature recognition, groove feature parameter extraction and information management of welding seams, which further verifies the effectiveness of the proposed algorithm.