基于轨迹在线识别的3D折线焊缝机器人摆动GMAW实时跟踪方法

doi:10.3901/JME.2022.14.116

机械工程学报 ›› 2022, Vol. 58 ›› Issue (14): 116-125.doi: 10.3901/JME.2022.14.116

• 特邀专栏：大型构件视觉测量与机器人加工 • 上一篇下一篇

扫码分享

基于轨迹在线识别的3D折线焊缝机器人摆动GMAW实时跟踪方法

贾爱亭, 洪波, 李湘文, 高佳篷, 吴格飞, 屈原缘

湘潭大学机械工程学院湘潭 411105

收稿日期:2021-07-01 修回日期:2021-12-10 出版日期:2022-07-20 发布日期:2022-09-07
通讯作者: 洪波(通信作者)，男，1960年出生，博士，教授，博士研究生导师。主要研究方向为焊接机器人及自动化。E-mail：hongbo@xtu.edu.cn
作者简介:贾爱亭，男，1991年出生，博士。主要研究方向为焊接机器人及自动化。E-mail：jat0929@163.com
基金资助:
国家自然科学基金(51575468)、长株潭标志性工程计划重大标志性创新示范工程(2019XK2303)、潭市科技计划(ZD-ZD20191007)、湖南省自然科学基金(2020JJ4089)、2019年湖南省研究生科研创新(XDCX2019B099)和2020年湖南省研究生科研创新(XDCX2020B128)资助项目。

Real Time Tracking Method of 3D Zigzag Welding Robot Swing GMAW Based on Online Trajectory Detection

JIA Aiting, HONG Bo, LI Xiangwen, GAO Jiapeng, WU Gefei, QU Yuanyuan

College of Mechanical Engineering, Xiangtan University, Xiangtan 411105

Received:2021-07-01 Revised:2021-12-10 Online:2022-07-20 Published:2022-09-07

摘要/Abstract

摘要： 3D折线焊缝大量存在于海工装备、大型起重装备、物流运输装备等制造领域中，属于典型的复杂轨迹焊缝，主要通过示教再现的方式进行自动焊接。大量的重复示教工作严重限制了焊接效率和质量，实现焊缝实时跟踪是提高焊接质量和效率的有效途径。针对3D折线焊缝实时跟踪问题，建立一种基于轨迹在线识别的机器人摆动熔化极气体保护焊(Gas metal arcwelding，GMAW)实时跟踪系统。首先，提出一种基于点云数据处理的3D折线焊缝起焊点焊枪位姿检测方法，获取焊缝起焊点焊枪位姿；利用3D折线焊缝位姿信息在线快速提取方法获取焊接过程中焊缝位姿信息，实现焊缝轨迹在线识别。然后，利用摆动电弧偏差识别方法获取焊缝偏差。最后，提出一种基于轨迹在线识别的3D折线焊缝机器人摆动GMAW实时跟踪方法，利用模糊PID控制方法实现焊缝实时跟踪。针对折角范围为130°～230°的典型3D折线焊缝的焊接试验表明，起焊点寻位位置检测误差小于0.4 mm，姿态估计误差小于1.8°，焊缝跟踪误差不超过0.4 mm，满足3D折线焊缝实时跟踪的要求。

关键词: 3D折线焊缝, GMAW, 轨迹在线识别, 焊缝跟踪

Abstract: 3D zigzag-line welding seams are extensively found in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. They are typical complex trajectory welds, and they are mainly automatically welded through teaching.A large number of repeated teaching work severely limits welding efficiency and quality. Realizing real-time tracking of welds is an effective way to improve welding quality and efficiency. Aiming at the problem of real-time tracking of 3D zigzag-line welding seams, a robot swinging GMAW real-time tracking system based on trajectory detection is established.Firstly, a method based on point cloud data processing is proposed to detect the starting pose of 3Dzigzag-line welding seam, and the pose information is obtained by the online fast extraction method to realize the online detection of 3Dzigzag-line welding seam trajectory. Secondly, the weld deviation is obtained by using the swing arc deviation identification method. Finally, a real-time tracking method of 3D zigzag-line welding seam robot swing GMAW based on on-line trajectory detection is proposed, and the fuzzy PID control method is used to realize the real-time tracking of 3D zigzag-line welding seam. Welding experiments for typical 3D zigzag-line welding seams with a folding angle range of 130° -230° show that the detection error of the starting position is less than 0.4 mm, the attitude estimation error is less than 1.8°, and the welding seam tracking error does not exceed 0.4 mm, satisfying the Requirements for real-time tracking of 3D zigzag-line welding seams.

Key words: 3D zigzag-line welding seam, gas metal arc welding, online trajectory detection, seam tracking

中图分类号:

TG409

贾爱亭, 洪波, 李湘文, 高佳篷, 吴格飞, 屈原缘. 基于轨迹在线识别的3D折线焊缝机器人摆动GMAW实时跟踪方法[J]. 机械工程学报, 2022, 58(14): 116-125.

JIA Aiting, HONG Bo, LI Xiangwen, GAO Jiapeng, WU Gefei, QU Yuanyuan. Real Time Tracking Method of 3D Zigzag Welding Robot Swing GMAW Based on Online Trajectory Detection[J]. Journal of Mechanical Engineering, 2022, 58(14): 116-125.

参考文献

[1] PEDRO N, NUNO M. Direct off-line robot programming via a common CAD package[J]. Robotics and Autonomous Systems, 2013, 61(8):896-910.
[2] KHELIFA B, SASA C, JAMSHED I, et al. IRoSim:Industrial robotics simulation design planning and optimization platform based on CAD and knowledgeware technologies[J]. Robotics and Computer Integrated Manufacturing, 2016, 42:121-134.
[3] XU Yanling, LV Na, FANG Gu, et al. Welding seam tracking in robotic gas metal arc welding[J]. Journal of Materials Processing Technology, 2017, 248:18-30.
[4] 邹焱飚,周卫林,王研博.基于概率连续模型的激光视觉焊缝自动跟踪[J].机械工程学报, 2017, 53(10):70-78. ZOU Yanbiao, ZHOU Weilin, WANG Yanbo. Laser vision seam automatic tracking based on probability continuous model[J]. Journal of Mechanical Engineering, 2017, 53(10):70-78.
[5] WANG Nianfeng, ZHONG Kaifan, SHI Xiaodong, et al. A robust weld seam recognition method under heavy noise based on structured-light vision[J]. Robotics and Computer-Integrated Manufacturing, 2020, 61:101821.
[6] 郭亮,张华.狭小空间不连续折线焊缝识别移动机器人跟踪系统[J].机械工程学报, 2019, 55(17):8-13. GUO Liang, ZHANG Hua. Discontinuous fold line welding seam recognition and mobile robot tracking system in narrow space[J]. Journal of Mechanical Engineering, 2019, 55(17):8-13.
[7] LI Jinquan, CHEN Zhe, RAO Gang, et al. Structured light-based visual servoing for robotic pipe welding pose optimization[J]. IEEE Access, 2019, 7:138327-138340.
[8] LI Gaoyang, HONG Yuxiang, GAO Jiapeng, et al. Welding seam trajectory recognition for automated skip welding guidance of a spatially intermittent welding seam based on laser vision sensor[J]. Sensors, 2020, 20(13):3657.
[9] ZOU Yanbiao, CHEN Jiaxin, WEI Xianzhong. Research on a real-time pose estimation method for a seam tracking system[J]. Optics and Lasers in Engineering, 2020, 27:105947.
[10] DINHAM M, FANG G. Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding[J]. Robotics and Computer-Integrated Manufacturing, 2013, 29(5):288-301.
[11] PENG R, NAVARRO-ALARCON D, WU V, et al. A point cloud-based method for automatic groove detection and trajectory generation of robotic arc welding tasks[C]//202017th International Conference on Ubiquitous Robots (UR). Kyoto:IEEE, 2020:380-386.
[12] ZENG Jinle, CHANG Baohua, DU Dong, et al. A vision-aided 3D path teaching method before narrow butt joint welding[J]. Sensors, 2017, 17(5):1099.
[13] YAN Minzhi, ZHANG Ke, LIU Di, et al. Autonomous programming and adaptive filling of lap joint based on three-dimensional welding-seam model by laser scanning[J]. Journal of Manufacturing Processes, 2020, 53:396-405.
[14] VRUSHALI P, INDRANEEL P, KALAICHELVI V, et al. Extraction of weld seam in 3d point clouds for real time welding using 5 dof robotic arm[C]//20195th International Conference on Control, Automation and Robotics (ICCAR). Beijing:IEEE, 2019:727-733.
[15] YANG Lei, LIU Yanhong, PENG Jinzhu, et al. A novel system for off-line 3D seam extraction and path planning based on point cloud segmentation for arc welding robot[J]. Robotics and Computer-Integrated Manufacturing, 2020, 64:101929.
[16] 石永华,王国荣, YOO W,等.高速旋转电弧传感器的数学模型[J].机械工程学报, 2007(11):217-223. SHI Yonghua, WANG Guorong, YOO W, et al.Mathematic model of high speed rotational arc sensor[J]. Journal of Mechanical Engineering, 2007(11):217-223.
[17] 乐健,张华,张奇奇,等.基于机器人旋转电弧传感器跟踪仰焊焊缝[J].焊接学报, 2016, 37(9):56-60, 131. LE Jian, ZHANG Hua, ZHANG Qiqi, et al. Overhead weld tracking by robots based on rotating arc sensor[J]. Transactions of the China Welding Institution, 2016, 37(9):56-60, 131.
[18] 洪波,易世洪,庞争林,等.间隙CO₂气体保护焊的磁控焊缝跟踪方法[J].焊接学报, 2017, 38(11):1-6, 129. HONG Bo, YI Shihong, PANG Zhenglin, et al. A seam tracking method which is controlled by magnetic field for CO₂ gas shielded welding with narrow gap[J]. Transactions of the China Welding Institution, 2017, 38(11):1-6, 129.
[19] MARTIN A, ROBERT C. Random sample consensus:a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM, 1981, 24(6):381-395.
[20] HONG Bo, JIA Aiting, HONG Yuxiang, et al. Online extraction of pose information of 3D zigzag-line welding seams for welding seam tracking[J]. Sensors, 2021, 21(2):375.
[21] SRIVASTAVA S, AISWARYA P G, GUPTA M, et al. A comparative study of PID and neuro-fuzzy based control schemes for a 6-DoF robotic arm[J]. Journal of Intelligent&Fuzzy Systems, 2018, 35(5):5317-5327.
[22] MEZA J L, SANTIBANEZ V, SOTO R, et al. Fuzzy self-tuning PID semiglobal regulator for robot manipulators[J]. IEEE Transactions on Industrial Electronics, 2011, 59(6):2709-2717.
[23] LE Jian, ZHANG Hua, CHEN Xiaoqi. Realization of rectangular fillet weld tracking based on rotating arc sensors and analysis of experimental results in gas metal arc welding[J]. Robotics and Computer-Integrated Manufacturing, 2018, 49:263-276.

基于轨迹在线识别的3D折线焊缝机器人摆动GMAW实时跟踪方法

Real Time Tracking Method of 3D Zigzag Welding Robot Swing GMAW Based on Online Trajectory Detection

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	樊丁, 李德全, 侯英杰, 黄健康, 冯毅. GMAW潜弧焊电弧-熔池耦合行为数值分析[J]. 机械工程学报, 2024, 60(2): 159-167.
[2]	辛杨桂, 高世一, 赵运强, 李苏, 徐望辉, 余陈. 机器人搅拌摩擦焊接力-位混合控制的应用研究[J]. 机械工程学报, 2023, 59(8): 91-98.
[3]	郭震, 张理, 周伟, 毕贵军, 韩冰. 立向高速GMAW驼峰焊缝的试验研究[J]. 机械工程学报, 2020, 56(14): 73-80.
[4]	王万东, 王志江, 胡绳荪, 薛坤喜, 赵冠成. 基于Hammerstein模型的GMAW-P焊接熔深自适应预测控制[J]. 机械工程学报, 2019, 55(19): 138-145.
[5]	黄军芬, 薛龙, 黄继强, 邹勇, 马可, 焦向东. 基于视觉传感的GMAW熔透状态预测[J]. 机械工程学报, 2019, 55(17): 41-47.
[6]	王志江, 薛坤喜, 吴定勇, 杨辉, 申俊琦, 刘杰, 胡绳荪. 基于视觉传感的机器人焊缝纠偏控制系统[J]. 机械工程学报, 2019, 55(17): 48-55.
[7]	邹焱飚, 周卫林, 王研博. 基于概率连续模型的激光视觉焊缝自动跟踪[J]. 机械工程学报, 2017, 53(10): 70-78.
[8]	王林, 武传松, 杨丰兆, 高进强. 外加磁场对高速GMAW电弧和熔池行为的主动调控效应[J]. 机械工程学报, 2016, 52(2): 1-6.
[9]	丁雪萍, 李桓. 焊接电流影响GMAW双丝焊电弧等离子体的数值模拟研究^*[J]. 机械工程学报, 2016, 52(16): 71-76.
[10]	高向东, 吴嘉杰. 微间隙焊缝磁光成像检测及跟踪方法[J]. 机械工程学报, 2015, 51(4): 71-77.
[11]	高延峰;张华;毛志伟. 以旋转电弧为传感器的移动机器人角焊缝跟踪[J]. , 2009, 45(9): 64-71.
[12]	张轲;吴毅雄;吕学勤;金鑫. 差速驱动式移动焊接机器人动力学建模[J]. , 2008, 44(11): 116-120.
[13]	梁明;王国荣;钟继光. 采用微型排水罩的药芯焊丝水下焊接焊缝自动跟踪系统[J]. , 2007, 43(3): 148-153.
[14]	石永华;王国荣;YOO Won-Sang;NA Suck-Joo. 高速旋转电弧传感器的数学模型[J]. , 2007, 43(11): 217-223.
[15]	张华;潘际銮;徐健宁;刘国平;刘伟力;刘正文;阎炳义;高力生. 无轨导全位置爬行式弧焊机器人系统[J]. , 2006, 42(7): 85-91.