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熔滴—焊缝同步视觉焊接偏差测定方法 被引量:2

Measurement method for simultaneous visual welding deviation of droplet-weld seam
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摘要 由于无轨爬行式焊接机器人运动方式自由灵活,导致存在超前监测误差的主动视觉传感方法焊缝跟踪精度不高。被动视觉传感方法无超前监测误差,但需采用昂贵的熔池相机,从而导致设备成本增加。针对以上问题,设计了一种由双摄像机组成的视觉采集系统,并提出一种熔滴—焊缝同步采集焊接偏差测定方法。首先,通过标定分别校正熔滴和焊缝图像,然后将熔滴、焊缝图像信息融合到同一图像坐标系中。进一步,采用凹点区域检测方法定位熔滴图像中的焊丝尖端,并采用最小二乘法拟合焊缝边缘直线。最后,利用焊丝尖端与焊缝边缘直线的位置关系,在已建立的焊接偏差量测定模型中计算出当前时刻焊接偏差量。实验结果表明,在实验室环境下,采用熔滴—焊缝同步视觉方法,焊接误差可以控制在0.2 mm以内,具有较高焊缝跟踪精度和重要应用前景。 The trackless crawling welding robot moves freely and flexibly,which leads to the low seam tracking accuracy of the active visual sensing method with advanced monitoring errors.The passive vision sensing method has no advanced monitoring error,but requires the use of an expensive molten pool camera,resulting in increased equipment costs.Aiming at these problems,a visual acquisition system composed of dual cameras was designed,and a method for measuring the welding deviation of the simultaneous collection of droplets and welds was proposed.The image of the droplet and weld were calibrated separately,and then the image information of the droplet and weld were merged into the same image coordinate system.Then,the method of pit area detection was used to locate the tip of the welding wire in the droplet image.In addition,the straight line of the weld edge was fitted using the least square method.The positional relationship between the tip of the welding wire and straight line of the weld edge was employed to calculate the current welding deviation in the established welding deviation measurement model.The experimental results showed that welding error could be controlled within 0.2mmapplying the droplet-weld synchronous vision method,which had a higher weld tracking accuracy and important application prospects.
作者 王小刚 王中任 刘海生 WANG Xiaogang;WANG Zhongren;LIU Haisheng(College of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081,China;School of Mechanical Engineering, Hubei University of Arts and Science, Xiangyang 441053,China;Key Laboratory of Intelligent Manufacturing and Machine Vision of Xiangyang City, Xiangyang 441053,China)
出处 《计算机集成制造系统》 EI CSCD 北大核心 2022年第5期1352-1360,共9页 Computer Integrated Manufacturing Systems
基金 湖北省高校产学研合作资助项目(2019AFB727) “机电汽车”湖北省优势特色学科群资助项目(XKQ2020007)。
关键词 无轨爬行式焊接机器人 同步视觉 熔滴 焊缝跟踪 凹点检测 trackless crawling welding robot synchronous vision molten drop weld tracking pit detection
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