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作 者:贾瑞燕[1,2] 李海超[1] 魏方锴[2] 徐勇[3] 周宇飞 JIA Ruiyan;LI Haichao;WEI Fangkai;XU Yong;ZHOU Yufei(State Key Laboratory of Precision Welding and Joining of Materials and Structures,Harbin Institute of Technology,Harbin,150001,China;Harbin Electric Machinery Company Limited,Harbin,150040,China;Harbin Intelligence Robot Technology Company,Harbin,150036,China)
机构地区:[1]哈尔滨工业大学,材料结构精密焊接与连接全国重点实验室,哈尔滨150001 [2]哈尔滨电机厂有限责任公司,哈尔滨150040 [3]哈尔滨阿尔特机器人技术有限公司,哈尔滨150036
出 处:《焊接学报》2024年第11期50-54,共5页Transactions of The China Welding Institution
基 金:黑龙江省重点研发计划项目(GA21A401)。
摘 要:针对大型水电站发电机磁极变长度、变间隙的复杂焊缝存在的示教编程效率低、精度差的问题,开发了一种基于光栅视觉传感的焊缝识别及机器人轨迹免示教生成技术.采用安装于机器人末端的光栅传感器获取不同部位的磁极焊缝点云,提出了一种结合机器人工具位姿变换矩阵和迭代最近点算法(ICP)的点云配准算法,得到大尺寸磁极焊缝完整点云数据.基于随机采样一致性(RANSAC)开发了焊缝识别算法,实现了机器人焊接轨迹的自动生成.结果表明,该算法可识别出多种复杂工况的磁极焊缝,识别率高,抗干扰能力强,平均识别误差在±0.4 mm范围内,满足焊接要求.Aiming at the problems of low efficiency and poor accuracy of teaching programming in complex welds with variable magnetic pole length and gap of large hydropower generators,a technology of welding seam identification and robot track generation without teaching was developed based on grating visual sensing.A grating sensor installed at the end of the robot was used to obtain the point cloud of the magnetic pole weld at different positions.A point cloud registration algorithm combining the robot tool pose transformation matrix and iterative closest point algorithm(ICP)was proposed to obtain the complete point cloud data of the large size magnetic pole weld.Based on random sampling consistency(RANSAC),a weld recognition algorithm was developed to realize the automatic generation of robot welding trajectories.The results show that the algorithm can identify a variety of complex magnetic pole welds with high recognition rate and strong anti-interference ability,and the average recognition error is with in±0.4 mm,which meets the welding requirements.
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