Research on trajectory recognition and control technology of structured light vision-assisted welding

WANG Hao; ZHAO Xiaohui; XU Longzhe; JIANG Hao; LIU Yu

doi:10.12073/j.hjxb.20220715002

TRANSACTIONS OF THE CHINA WELDING INSTITUTION > 2023 > 44(6): 50-57. > DOI: 10.12073/j.hjxb.20220715002

WANG Hao, ZHAO Xiaohui, XU Longzhe, JIANG Hao, LIU Yu. Research on trajectory recognition and control technology of structured light vision-assisted welding[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(6): 50-57. DOI: 10.12073/j.hjxb.20220715002

Citation:

PDF (5613 KB)

Research on trajectory recognition and control technology of structured light vision-assisted welding

Jilin University, Changchun, 130025, China

More Information

Received Date: July 14, 2022
Available Online: May 14, 2023

Graphical Abstract

Abstract

Abstract

Three trajectory recognition and control techniques for laser multi-point positioning, pre-welding trajectory fitting, and seam real-time tracking for structured light vision-assisted welding are investigated. A CNN model, adaptive feature extraction algorithm, a priori model, and coordinate matrix conversion are proposed as the core of the welding trajectory recognition process for these three. Welding trajectory control models are proposed for each of the above three, which including a taught trajectory correction model, a pre-welding trajectory fitting model, and a real-time deflection correction model for seam tracking. The experiments prove that laser multi-point positioning, pre-welding trajectory fitting model can efficiently identify the weld trajectory curve before welding, and the welding trajectory basically coincides with the centerline of the seam; when welding in the real-time seam tracking model, the real-time deviation is mainly controlled within ± 0.2 mm, with an average deviation of 0.1160 mm. The results show that the welding trajectory identification process and trajectory control model mentioned in this paper are sufficient to ensure stable operation of structured light vision-assisted welding.
- structured light vision,
- trajectory recognition and control,
- welding

FullText(HTML)

References (12)

References

Zou Y, Li J, Chen X. Seam tracking investigation via striped line laser sensor[J]. Industrial Robot:An International Journal, 2017, 44(5): 609 − 617. doi: 10.1108/IR-11-2016-0294

Zou Y, Chen X, Gong G, et al. A seam tracking system based on a laser vision sensor[J]. Measurement, 2018, 127: 489 − 500. doi: 10.1016/j.measurement.2018.06.020

Zou Y, Zhu M, Chen X. A Robust Detector for Automated Welding Seam Tracking System[J]. Journal of Dynamic Systems, Measurement, and Control, 2021, 143(7): 071001. doi: 10.1115/1.4049547

Zou Y, Wang Y, Zhou W, et al. Real-time seam tracking control system based on line laser visions[J]. Optics & Laser Technology, 2018, 103: 182 − 192.

Zou Y, Chen J, Wei X. Research on a real-time pose estimation method for a seam tracking system[J]. Optics and Lasers in Engineering, 2020, 127: 105947. doi: 10.1016/j.optlaseng.2019.105947

Zhao Z, Luo J, Wang Y, et al. Additive seam tracking technology based on laser vision[J]. The International Journal of Advanced Manufacturing Technology, 2021, 116(1): 197 − 211.

Xiao R, Xu Y, Hou Z, 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, 297: 111533. doi: 10.1016/j.sna.2019.111533

Zhang G, Yun T-J, Oh W-B, et al. A study on seam tracking in robotic GMA welding process[J]. Materials Today:Proceedings, 2020, 22: 1771 − 1777. doi: 10.1016/j.matpr.2020.03.010

Xue B, Chang B, Peng G, et al. A Vision Based Detection Method for Narrow Butt Joints and a Robotic Seam Tracking System[J]. Sensors, 2019, 19(5): 1144. doi: 10.3390/s19051144

Wu Q Q, Lee J P, Park M H, et al. A study on the modified Hough algorithm for image processing in weld seam tracking[J]. Journal of Mechanical Science and Technology, 2015, 29(11): 4859 − 4865. doi: 10.1007/s12206-015-1033-x

Muhammad J, Altun H, Abo-Serie E. A robust butt welding seam finding technique for intelligent robotic welding system using active laser vision[J]. The International Journal of Advanced Manufacturing Technology, 2018, 94(1): 13 − 29.

Fan J, Jing F, Yang L, et al. A precise seam tracking method for narrow butt seams based on structured light vision sensor[J]. Optics & Laser Technology, 2019, 109: 616 − 626.

[1]	WU Zhen, WANG Fazhan, AN Gaoling, LIU Taiping, LI Zhen, ZHENG Jianxiao, MA Shan. Research on efficient welding heat source model for large and complex structures[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2015, 36(10): 61-64.
[2]	SONG Gang, LIU Che, SONG Qiuping, LIU Liming. Study on phase matching control system for pulsed laser-arc hybrid welding based on Labview[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2014, 35(10): 13-16.
[3]	DENG Yongjun, CHEN Huabin, LIN Tao, CHEN Shanben. Auto-calibration method of vision system for mobile welding robot based on OpenCV[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2012, (7): 45-48.
[4]	LI Jun, YANG Jianguo, TAN Xing, FANG Hongyuan. Experimental investigation on controlling welding hot crack with welding with trailing rotating extrusion[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (12): 45-48.
[5]	ZHENG Jun, PAN Jiluan. Multi-information detection system of welding process based on passive vision[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2010, (11): 49-52.
[6]	GONG Yefei, DAI Xianzhong, LI Xinde. Robust joint recognition with structured-light vision sensing[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (9): 85-88.
[7]	YAN Dongyang, SHI Qingyu, WU Aiping, Silvanus JUERGEN. A high-efficiency welding simulation method based on welding temperature[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (8): 77-80.
[8]	GU Jinmao, HUANG Pengfei, LU Zhenyang, YIN Shuyan. The current cycle control of AC short circuit transition welding method and system[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (4): 73-76.
[9]	YAO Xiongliang, LIU Qingjie, SUN Qian, ZHOU Qixin. Numerical simulation on welding deformation of spherical cap structure based on ABAQUS[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (6): 89-92.
[10]	YAO Shangwei. Application of nanotechnology in welding technology[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2007, (3): 109-112.

Cited By

Cited by

Periodical cited type(1)

伏承炜，侯国清，马蓉，李渊博. TIG电弧电流密度分布研究现状和进展. 焊管. 2025(05): 9-17 .

Other cited types(0)

Get Citation

PDF

XML

Article views (374) PDF downloads (106) Cited by(1)

Turn off MathJax

Article Contents

Abstract

References

Research on trajectory recognition and control technology of structured light vision-assisted welding