首页|中厚板多层多道焊视觉测量与工艺规划

中厚板多层多道焊视觉测量与工艺规划

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针对中厚板多层多道焊的焊道测量问题,提出利用焊缝检测和焊道尺寸视觉测量的信息融合自适应微调焊枪位置的方法。首先基于结构光视觉传感器系统采集焊缝图像,在典型图像处理算法的基础上,结合FROSAC提取算法提取焊缝特征信息;将提取到的特征点进行坐标转换,采用视觉测量获得焊道轮廓和尺寸信息,来修正机器人的运动路径;根据焊缝特征信息分析工艺参数对焊道成型的影响,确定焊道层数、各焊道的工艺参数以及焊枪的偏移量,完成多层多道焊接工艺规划;最后基于搭建的机器人焊接视觉系统在12 mm母材上进行V形坡口多层多道焊接试验。结果表明:该方法下坡口填充良好,焊道尺寸平均测量误差小于0。2 mm,满足多层多道焊接工业应用需求。
Visual measurement and process planning of multi-layer and multi-pass welding of medium and heavy plate
Aiming at the weld channel measurement of multi-layer and multi-pass welding of medium-thick plate,the method of adaptive fine-tuning of the weld gun position using the fusion of information from weld seam detection and visual measurement of weld channel dimensions is proposed.Firstly,based on the structured optical vision sensor system,the weld seam images are acquired,and the weld seam feature information is extracted based on typical image processing algorithms combined with FROSAC extraction algorithm.The number of layers,the process parameters of each weld channel and the offset of the welding torch are determined based on the information of the weld seam characteristics,and the multi-layer and multi-pass welding process planning is completed.Finally,based on the robot welding vision system built on the 12 mm-base material for V-bevel multi-layer and multi-pass welding test,the results show that the method under the bevel fill well,the average measurement error of the weld channel size is less than 0.2 mm,meeting the needs of multi-layer and multi-pass welding industrial applications.

multi-layer and multi-pass planningstructured light vision sensorthree dimensional inspectionFROSAC algorithmwelding process parameters

王天琪、张树浩、龙斌、王克宽

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天津工业大学天津市现代机电装备技术重点试验室,天津 300387

中国石油集团工程技术研究有限公司,天津 300451

多层多道规划 结构光视觉传感器 三维检测 FROSAC算法 焊接工艺参数

天津市科技特派员项目天津市"项目+团队"重点培养专项资助项目天津市教委科研计划资助项目

20YDTPJC00780XC2020532019KJ011

2024

天津工业大学学报
天津工业大学

天津工业大学学报

CSTPCD北大核心
影响因子:0.404
ISSN:1671-024X
年,卷(期):2024.43(3)
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