Advanced Search
GUO Jichang, ZHU Zhiming, SUN Bowen. A multifunctional monocular visual sensor based on combined laser structured lights[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(10): 1-7. DOI: 10.12073/j.hjxb.2019400254
Citation: GUO Jichang, ZHU Zhiming, SUN Bowen. A multifunctional monocular visual sensor based on combined laser structured lights[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(10): 1-7. DOI: 10.12073/j.hjxb.2019400254
shu

A multifunctional monocular visual sensor based on combined laser structured lights

  • 1.

    Department of Mechanical Engineering, Key Laboratory of Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing 100084, China

  • 2.

    Tiandi Science & Technology Co., Ltd., Beijing 100013, China

More Information
  • Received Date: December 17, 2018
  • Available Online: July 12, 2020
    Graphical Abstract
    • Abstract
  • A novel multifunctional monocular visual sensor based on combined laser structured lights is proposed and designed; its research and development ideas and structural design process are detailed. The proposed visual sensor can realize multi-functions of detection such as the cross-sectional sizes of welding groove, the height, space position and posture of welding torch by using monocular vision and single image processing. The calibration of the sensor makes full use of its intrinsic parameters, and there is no need to re-calibrate the sensor when the position and posture of welding torch changes, which effectively improves the adaptability of the sensor in the welding process of complex structural workpiece and welding trajectory. With the use of combined laser structured lights, the problem of information loss in the depth direction existing in usual monocular visual sensor is solved effectively. Finally, the corresponding detection algorithms for the cross-sectional sizes of the V-type groove and the height of welding torch are derived, and the experiments are carried out to verify them. The experimental results show that the maximum relative detection error is not more than 2.1%.
    • FullText(HTML)
    • References (13)
  • 王 伟, 邹奇仕, 朱六妹, 等. 视觉传感焊缝跟踪技术的发展状况及实施方案探讨[J]. 电焊机, 2002, 32(5): 1 − 8. doi: 10.3969/j.issn.1001-2303.2002.05.002

    Wang Wei, Zou Qishi, Zhu Liumei, et al. The development state and implementing method of seam tracking system with optical sensor[J]. Electric Welding Machine, 2002, 32(5): 1 − 8. doi: 10.3969/j.issn.1001-2303.2002.05.002
    郭吉昌, 朱志明, 于英飞, 等. 焊接领域激光结构光视觉传感技术的研究及应用[J]. 中国激光, 2017, 44(12): 1 − 10.

    Guo Jichang, Zhu Zhiming, Yu Yingfei, et al. Research and application of visual sensing technology based on laser structured light in welding industry[J]. Chinese Journal of Lasers, 2017, 44(12): 1 − 10.
    吴珊珊, 基于十字结构光的三维重建及精度分析[D]. 杭州: 浙江理工大学, 2015.
    乔东虓, 郑 军, 潘际銮. 双线结构光焊缝跟踪传感器及其特性[J]. 电焊机, 2010, 40(11): 14 − 16. doi: 10.3969/j.issn.1001-2303.2010.11.004

    Qiao Dongxiao, Zheng Jun, Pan Jiluan. Dual structure laser vision sensor and its character[J]. Electric Welding Machine, 2010, 40(11): 14 − 16. doi: 10.3969/j.issn.1001-2303.2010.11.004
    毛志伟, 周少玲, 赵 滨, 等. 双线激光传感焊枪定位与焊缝走向识别[J]. 焊接学报, 2015, 36(2): 35 − 38.

    Mao Zhiwei, Zhou Shaoling, Zhao Bin, et al. Welding torch position and seam orientation deviation based on two stripes laser vision sensing[J]. Transactions of the China Welding Institution, 2015, 36(2): 35 − 38.
    Shao W J, Huang Y, Zhang Y. A novel weld seam detection method for space weld seam of narrow butt joint in laser welding[J]. Optics and Laser Technology, 2018, 99: 39 − 51. doi: 10.1016/j.optlastec.2017.09.037
    Sung K, Lee H, Choi Y S, et al. Development of a multiline laser vision sensor for joint tracking in welding[J]. Welding Journal, 2009, 88(4): 79 − 85.
    田忠运. 基于双线结构光三维检测技术研究[D]. 南京: 南京航空航天大学, 2012.
    李学瑞. 基于激光双目视觉的焊接机器人波纹板焊缝三维重建的研究[D]. 广州: 华南理工大学, 2014.
    陈熙引. 基于双目视觉的机器人焊缝识别及轨迹规划研究[D]. 广州: 华南理工大学, 2015.
    邹媛媛, 赵明扬, 张 雷, 等. 结构光视觉传感器误差分析与结构分析[J]. 仪器仪表学报, 2008, 29(12): 2605 − 2610. doi: 10.3321/j.issn:0254-3087.2008.12.026

    Zou Yuanyuan, Zhao Mingyang, Zhang Lei, et al. Error analysis and structural analysis of structured-light visual sensor for seam tracking[J]. Chinese Journal of Scientific Instrument, 2008, 29(12): 2605 − 2610. doi: 10.3321/j.issn:0254-3087.2008.12.026
    刘南生, 郭昌荣, 刘明友, 等. 爬行式弧焊机器人结构光视觉传感器内部布局实验研究[J]. 江西科学, 2005, 23(4): 325 − 327. doi: 10.3969/j.issn.1001-3679.2005.04.010

    Liu Nansheng, Guo Changrong, Liu Mingyou., et al The internal layout experiment research of structural light visual sensor used in crawling arc welding robot[J]. Jiangxi Science, 2005, 23(4): 325 − 327. doi: 10.3969/j.issn.1001-3679.2005.04.010
    邱茂林, 马颂德. 计算机视觉中摄像机定标综述[J]. 自动化学报, 2000, 26(1): 43 − 54.

    Qiu Maolin, Ma Songde. Overview of camera calibration for computer vision[J]. Acta Autom Atica Sinica, 2000, 26(1): 43 − 54.
    • Related Articles

  • Related Articles

    [1]ZHANG Yongzhi1,2, DONG Junhui1, HOU Jijun1. Predictive modeling of mechanical properties of welded joints based on generalized dynamic fuzzy RBF neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2017, 38(8): 37-40. DOI: 10.12073/j.hjxb.20150911002
    [2]TANG Zhengkui, DONG Junhui, ZHANG Yongzhi, HOU Jijun. Prediction of mechanical properties of welding joints by hybrid cluster fuzzy RBF neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2014, 35(12): 105-108.
    [3]GAO Xiangdong, MO Ling, YOU Deyong, KATAYAMA Seiji. Prediction algorithm of weld seam deviation based on RBF neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2012, (4): 1-4.
    [4]LIN Fang, HUANG Wenchao, CHEN Xiaofeng, WEI Zhonghua, XUE Jiaxiang. Digital welder parameters self-regulating algorithm based on partial Newton interpolation[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2011, (3): 33-36.
    [5]DUAN Tiequn, SHI Guangyuan, YU Dan, YANG Kefei. Interpolation algorithm and simulation of auto-welding saddle-shaped nozzle of heavy pressure vessels[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (1): 63-66.
    [6]LÜ Yan, TIAN Xincheng, XU Qing, PENG Bo. Four-axis interpolation algorithm for automatic welding of saddle type curve weld[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (5): 81-84.
    [7]ZHANG Yongzhi, DONG Junhui, ZHANG Yanfei. Prediction of mechanical properties of welded joints based on RBF neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2008, (7): 81-84.
    [8]LÜ Qibing, TAN Keli, LUO Deyang, TAN Hongtao. Prediction of area of gray-spots flaw in alternate rail flash butt welded joint based on RBF neural network[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2008, (2): 93-96.
    [9]QI Huazhen, TIAN Xincheng, ZHANG Xueyi, PENG Bo. A interpolation algorithm for saddle-shaped curve auto-welding based on angle approaching[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (3): 93-96.
    [10]HUO Meng-you, WANG Xin-gang, YIN Ping. Real-time interpolation algorithm and simulation of seam of intersection line for automatic welding[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2006, (11): 37-40.

Catalog

    Get Citation
    XML
    Article views (440) PDF downloads (42) Cited by()
    Turn off MathJax
    Article Contents
    Abstract
    References
    Related Articles

    Website Copyright © Editorial Office of Transactions of the China Welding Institution, Welding Journals Publishing HouseTel：0451-86323218Address：No. 2077, Chuangxin Road, Songbei District, Harbin

    Supported by: Beijing Renhe Information Technology Co. Ltd    Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return