Feature parameters extraction of ship welds based on spatial position and contour distance

YUAN Mingxin; DAI Xianling; LIU Chao; SUN Hongwei; WANG Lei

doi:10.12073/j.hjxb.20211208002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2023 > 44(1): 84-92. > DOI: 10.12073/j.hjxb.20211208002

YUAN Mingxin, DAI Xianling, LIU Chao, SUN Hongwei, WANG Lei. Feature parameters extraction of ship welds based on spatial position and contour distance[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(1): 84-92. DOI: 10.12073/j.hjxb.20211208002

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Feature parameters extraction of ship welds based on spatial position and contour distance

1.
School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China
2.
Jiangsu Automation Research Institute, Lianyungang 222006, China
3.
Suzhou Mingtu Intelligent Technology Co., Ltd., Zhangjiagang, 215600, China

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Received Date: December 04, 2021
Available Online: January 12, 2023

Graphical Abstract

Abstract

Abstract

In order to accurately extract the characteristic parameters of the welding seams in the digital model of ship welding parts, and then to realize the adaptive and rapid matching and selection of welding processes in the robot database system, a feature parameter extraction algorithm of ship welds based on spatial position and contour distance is proposed. First, the spatial position relationship of the welded joint is determined by the recognition of the surface to be determined based on the Helen formula, and the weld feature is recognized through the combination of the minimum contour distance; then the feature points and lines at the weld groove are identified based on the total number of contour lines and the two end points with the smallest outline distance; finally, the final weld feature parameters related to the welding process are extracted based on the mathematical model built through the three types of welded joints. The test results show that the proposed welding seam feature parameter extraction algorithm can accurately identify 4 types of joint forms and 10 groove types, as well as accurately extract parameters such as weld gap, groove included angle and welded plate thickness, which is characterized by wide weld feature recognition and complete information extraction. Compared with other related recognition algorithms, the recognition rate of the proposed algorithm reaches 100%, and the recognition efficiency is increased by 16.06%, which further verifies the effectiveness of the algorithm.
- ship weld,
- feature recognition,
- parameter extraction,
- joint spatial position,
- contour distance

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References (20)

References

何银水, 余卓骅, 李健, 等. 基于视觉特征的厚板机器人焊接焊缝轮廓的有效提取[J]. 机械工程学报, 2019, 55(17): 56 − 60. doi: 10.3901/JME.2019.17.056

He Yinshui, Yu Zhuohua, Li Jian, et al. Effective Weld Seam Profile Extraction via Visual Features for Robotic Welding with Thick Steel Plates[J]. Journal of Mechanical Engineering, 2019, 55(17): 56 − 60. doi: 10.3901/JME.2019.17.056

Fan Junfeng, Jing Fengshui, Yang Lei, et al. A precise seam tracking method for narrow butt seams based on structured light vision sensor[J]. Optics and Laser Technology, 2018, 109(27): 616 − 626.

Lu Yonghua, Zhang Jia, Li Xiaoyan, et al. A robust method for adaptive center extraction of linear structured light stripe[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2020, 37(4): 586 − 596.

Zhu Huayu, Lu Yonghua, Li Yanlong, et al. Method for detecting weld feature size based on line structured light[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2021, 38(3): 383 − 392.

岳建锋, 杜博宇, 王天琪, 等. 基于激光单目视觉系统的焊缝提取[J]. 天津工业大学学报, 2015, 34(6): 84 − 88. doi: 10.3969/j.issn.1671-024x.2015.06.018

Yue Jianfeng, Du Boyu, Wang Tianqi, et al. Extraction of welding seam based on monocular vision of laser[J]. Journal of Tianjin Polytechnic University, 2015, 34(6): 84 − 88. doi: 10.3969/j.issn.1671-024x.2015.06.018

Wen Junshao, Yu Huang, Yong Zhang. A novel weld seam detection method for space weld seam of narrow butt joint in laser welding[J]. Optics and Laser Technology, 2018, 99(10): 39 − 51.

Wang Peijie, Shao Wenjun, Gong Shuahang, et al. High-precision measurement of weld seam based on narrow depth of field lens in laser welding[J]. Science and Technology of Welding and Joining, 2016, 21(4): 267 − 274. doi: 10.1080/13621718.2015.1104094

张泽南, 仲梁维. 基于SolidWorks的自动焊缝标注的二次开发[J]. 软件工程, 2020, 23(5): 17 − 20. doi: 10.19644/j.cnki.issn2096-1472.2020.05.005

Zhang Zenan, Zhong Liangwei. The Second Development of Automatic Weld Labeling Based on SolidWorks[J]. Software Engineering, 2020, 23(5): 17 − 20. doi: 10.19644/j.cnki.issn2096-1472.2020.05.005

张帅, 杨龙兴, 丁力. 基于自适应双边滤波的V型焊缝特征提取研究[J]. 制造技术与机床, 2021, 25(7): 125 − 129. doi: 10.19287/j.cnki.1005-2402.2021.07.024

Zhang Shuai, Yang Longxing, Ding Li. Research on feature extraction of V-shaped welds based on adaptive bilateral filter[J]. Manufacturing Technology & Machine Tool, 2021, 25(7): 125 − 129. doi: 10.19287/j.cnki.1005-2402.2021.07.024

Lei Ting, Rong Youmin, Wang Hui, et al. A review of vision-aided robotic welding[J]. Computers in Industry, 2020, 12(3): 115 − 127.

Yang Lei, Liu Yanhong, Peng Jinzhu. An automatic detection and identification method of welded joints based on deep neural network[J]. Network Weekly News, 2019, 7(3): 164952 − 164961.

李湘文, 吴宏宝, 洪波, 等. 旋转电弧机器人V形坡口焊缝跟踪模型与仿真[J]. 焊接学报, 2020, 41(8): 85 − 89,102. doi: 10.12073/j.hjxb.20190814005

Li Xiangwen, Wu Hongbao, Hong Bo, et al. V-groove weld tracking model and simulation of rotatingarc robot[J]. Transactions of The China Welding Institution, 2020, 41(8): 85 − 89,102. doi: 10.12073/j.hjxb.20190814005

Zhan Yongshuai, Yang Guowei, Wang Qiqi, et al. Weld Feature Extraction Based on Fully Convolutional Networks[J]. Chinese Journal of Lasers, 2019, 46(3): 36 − 43.

孙博文, 朱志明, 郭吉昌, 等. 基于组合激光结构光的视觉传感器检测算法及图像处理流程优化[J]. 清华大学学报(自然科学版), 2019, 59(6): 445 − 452. doi: 10.16511/j.cnki.qhdxxb.2019.26.004

Sun Bowen, Zhu Zhiming, Guo Jichang, et al. Detection algorithms and optimization of image processing for visual sensors using combined laser structured light[J]. Journal of Tsinghua University(Science and Technology), 2019, 59(6): 445 − 452. doi: 10.16511/j.cnki.qhdxxb.2019.26.004

Jawad Muhammad, Halis Altun, Essam Abo-Serie. Welding seam profiling techniques based on active vision sensing for intelligent robotic welding[J]. The International Journal of Advanced Manufacturing Technology, 2017, 88(4): 127 − 145.

Jaime F. Aviles-Viñas, Reyes Rios-Cabrera, Ismael Lopez-Juarez. On-line learning of welding bead geometry in industrial robots[J]. The International Journal of Advanced Manufacturing Technology, 2016, 83(14): 217 − 231.

洪磊, 杨小兰, 钟冬平. 基于斜率分析法的焊缝条纹直线特征提取分析[J]. 焊接学报, 2017, 38(8): 91 − 94,133.

Hong Lei, Yang Xiaolan, Zhong Dongping. Feature extraction and analysis of weld seam stripe line on slope analysis method[J]. Transactions of The China Welding Institution, 2017, 38(8): 91 − 94,133.

Xiao Runquan, Xu Yanling, Hou Zhen, et al. An adaptive feature extraction algorithm for multiple typical seam tracking based on vision sensor in robotic arc welding[J]. Sensors and Actuators:A. Physical, 2019, 29(7): 77 − 85.

应灿. 焊接机器人工作站协同运动的轨迹优化研究[D]. 广州: 华南理工大学, 2013.

Ying Can. Research of trajectory optimization of welding robot workstation’ s cooperative motion[D]. Guangzhou: South China University of Technology, 2013.

张鹏贤, 刘志辉, 于桐. 基于激光光栅的焊口数字轮廓视觉测量[J]. 电焊机, 2018, 48(7): 8 − 12.

Zhang Pengxian, Liu Zhihui, Yu Tong. Vision measurement for digital contour of weld bore based on laser grating[J]. Electric Welding Machine, 2018, 48(7): 8 − 12.

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Feature parameters extraction of ship welds based on spatial position and contour distance