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袁明新, 戴现令, 刘超, 孙宏伟, 王磊. 基于空间位置和轮廓线距离的船舶焊缝特征参数提取[J]. 焊接学报, 2023, 44(1): 84-92. DOI: 10.12073/j.hjxb.20211208002
引用本文: 袁明新, 戴现令, 刘超, 孙宏伟, 王磊. 基于空间位置和轮廓线距离的船舶焊缝特征参数提取[J]. 焊接学报, 2023, 44(1): 84-92. DOI: 10.12073/j.hjxb.20211208002
YUAN Mingxin, DAI Xianling, LIU Chao, SUN Hongwei, WANG Lei. Feature parameters extraction of ship welds based on spatial position and contour distance[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(1): 84-92. DOI: 10.12073/j.hjxb.20211208002
Citation: YUAN Mingxin, DAI Xianling, LIU Chao, SUN Hongwei, WANG Lei. Feature parameters extraction of ship welds based on spatial position and contour distance[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(1): 84-92. DOI: 10.12073/j.hjxb.20211208002

基于空间位置和轮廓线距离的船舶焊缝特征参数提取

Feature parameters extraction of ship welds based on spatial position and contour distance

  • 摘要: 为了实现船舶焊接件数字模型中焊缝特征参数的精确提取,进而完成机器人数据库系统中焊接工艺的自适应快速匹配和快速选择,提出了基于空间位置和轮廓线距离的船舶焊缝特征参数提取算法. 首先基于海伦公式识别待判定面来确定接头空间位置关系,并结合最小轮廓线距离完成焊缝特征识别;然后基于轮廓线总条数和最小轮廓线距离的两端点,识别出焊缝坡口处特征点及线;最后基于三类焊接接头所建的数学模型提取出与焊接工艺相关的焊缝特征参数. 测试结果表明,文中焊缝特征参数提取算法能准确识别4类接头形式和10种坡口类型,以及准确提取焊缝间隙、坡口夹角和焊接件板厚等参数,具有焊缝特征识别广且信息提取齐全的优点. 与其他相关识别算法相比,文中算法的识别率达到100%,而识别效率提升了16.06%,从而进一步验证了算法的有效性.

     

    Abstract: In order to accurately extract the characteristic parameters of the welding seams in the digital model of ship welding parts, and then to realize the adaptive and rapid matching and selection of welding processes in the robot database system, a feature parameter extraction algorithm of ship welds based on spatial position and contour distance is proposed. First, the spatial position relationship of the welded joint is determined by the recognition of the surface to be determined based on the Helen formula, and the weld feature is recognized through the combination of the minimum contour distance; then the feature points and lines at the weld groove are identified based on the total number of contour lines and the two end points with the smallest outline distance; finally, the final weld feature parameters related to the welding process are extracted based on the mathematical model built through the three types of welded joints. 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. Compared with other related recognition algorithms, the recognition rate of the proposed algorithm reaches 100%, and the recognition efficiency is increased by 16.06%, which further verifies the effectiveness of the algorithm.

     

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