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基于焊枪轮廓特征提取的焊接偏差测定方法 被引量:4

Welding deviation measurement method based on welding torch contour feature extraction
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摘要 在熔化极气体保护焊(gas metal welding,GMAW)焊接过程中,由于弧光干扰严重,视觉系统难以同时准确提取焊缝和焊丝尖端,从而影响焊缝跟踪的精度.针对这个问题,提出一种定位焊枪中心来替代定位焊丝尖端的焊接偏差测定方法,并对该方法进行了可行性论证.首先,在增强熔池图像中的焊缝、焊枪边缘轮廓信息后,设置矩形窗获得边缘采样点.然后,使用聚类算法筛选出正确的边缘采样点,根据采样点利用最小二乘法拟合出焊缝直线和焊枪椭圆方程.最后,计算当前图像焊枪中心与焊缝直线的距离,与基准图像中的对应距离进行比较,测定出焊枪位置偏差量和焊枪摆幅偏差量.实际验证结果表明,焊枪中心与焊丝尖端的替代误差在0.2 mm以内,满足跟踪精度要求,具有较强的工程实际意义. In the welding process of gas metal welding(GMAW),due to the serious arc interference,it is difficult for the vision system to accurately extract the weld and the wire tip at the same time,thus affecting the accuracy of the weld tracking.An approach was proposed to locate the welding torch center instead of the welding wire tip.The feasibility of the method was demonstrated.First,after enhancing the weld seam and weld gun edge contour information in the molten pool image,a rectangular window was set to obtain the edge sampling point.Then,the clustering algorithm was used to screen out the correct edge sampling points.The weld line and the ellipse equation of the torch were fitted by the least squares method according to the sampling points.Moreover,the distance between the center of the current image welding torch and the straight line of the weld was calculated.Compared with the corresponding distance in the reference image,the amount of deviation of the welding torch position and the deviation of the welding gun swing were detected.The actual verification results show that the replacement error between the center of the welding torch and the tip of the welding wire is within 0.2 mm,which meets the requirements of tracking accuracy and has strong engineering practical significance.
作者 王中任 王小刚 刘德政 刘海生 WANG Zhongren;WANG Xiaogang;LIU Dezheng;LIU Haisheng(Hubei University of Arts&Science,Xiangyang,441053,China;Wuhan University of Science and Technology,Hubei,430081,China)
出处 《焊接学报》 EI CAS CSCD 北大核心 2020年第7期59-64,I0004,共7页 Transactions of The China Welding Institution
基金 湖北省科技创新专项(2017AFB153) “机电汽车”湖北省优势特色学科群开放基金(XKQ2020007).
关键词 焊缝视觉跟踪 熔池图像 焊接偏差 聚类算法 熔化极气体保护焊 weld seam tracking welding molten pool image welding deviation clustering algorithm gas metal arc welding
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