基于线激光3D相机视觉引导客车踏板自动化焊接系统研究

孙超; 费大奎; 李荣; 王子然; 尤勇; 刘厚涛; 谷森

doi:10.7512/j.issn.1001-2303.2026.02.05

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基于线激光3D相机视觉引导客车踏板自动化焊接系统研究
Research on Automated Welding System for Bus Pedal Based on Line Laser 3D Camera Vision Guidance
2026年56卷第2期页码：48-55
收稿：2025-06-30，

修回：2025-10-16，

纸质出版：2026-02-20
DOI： 10.7512/j.issn.1001-2303.2026.02.05
稿件说明：

移动端阅览

孙超，费大奎，李荣，等.基于线激光3D相机视觉引导客车踏板自动化焊接系统研究［J］.电焊机，2026，56（2）：48-55. DOI： 10.7512/j.issn.1001-2303.2026.02.05.

SUN Chao, FEI Dakui, LI Rong, et al.Research on Automated Welding System for Bus Pedal Based on Line Laser 3D Camera Vision Guidance[J].Electric Welding Machine, 2026, 56(2): 48-55. DOI： 10.7512/j.issn.1001-2303.2026.02.05.

摘要

目前国内客车踏板焊接以人工为主，自动化程度低，研发面向客车踏板自动化焊接系统，实现客车踏板的智能制造具有实际意义。基于直射式激光三角测量法原理设计线激光3D相机，提出一种优化Steger光条中心算法提取激光中心线，完成3D相机的内参、畸变参数及激光平面参数标定，并采用标准陶瓷球规仪验证其扫描精度。搭建由自研线激光3D相机、ABB机械手、焊接电源及焊枪组成的自动化焊接系统，完成手眼标定，设计包含包含点云处理、轮廓角点提取、焊缝坐标匹配及焊接姿态规划的客车踏板焊缝路径规划方法。最终对客车踏板实物进行自动化焊接试验，并通过电磁无损探伤评价焊缝质量。优化Steger算法的激光中心线提取时间为0.6 s，优于传统算法的1.3 s；自研3D相机扫描精度达0.2 mm，球面度与空间距离测量最大误差分别为0.319 5 mm、0.325 7 mm；所搭建系统的客车踏板焊接成功率达87.5%，焊缝成形良好。研究表明，该自动化焊接系统可实现客车踏板的自动化焊接，满足企业生产要求，为同类构件的自动化焊接提供了技术参考。

Abstract

Currently

the welding of bus pedals in China is predominantly manual

with low automation levels. Developing an automated welding system for bus pedals holds practical significance for achieving intelligent manufacturing. This study designs a line laser 3D camera based on the principle of direct laser triangulation. An optimized Steger algorithm for light strip center extraction is proposed. Calibration of the 3D camera's internal parameters

distortion parameters

and laser plane parameters was completed

and its scanning accuracy was verified using a standard ceramic ball gauge. An automated welding system

consisting of a self-developed line laser 3D camera

an ABB robot

a welding power supply

and a welding torch

was constructed. Hand-eye calibration was performed. A weld seam path planning method for bus pedals

encompassing point cloud processing

contour corner point extraction

weld seam coordinate matching

and welding posture planning

was designed. Finally

automated welding tests were conducted on actual bus pedals

and weld quality was evaluated via electromagnetic non-destructive testing. The optimized Steger algorithm achieved a laser centerline extraction time of 0.6 s

outperforming the traditional algorithm's 1.3 s. The self-developed 3D camera demonstrated a scanning accuracy of 0.2 mm

with maximum errors in sphericity and spatial distance measurement being 0.3195 mm and 0.3257 mm

respectively. The success rate of bus pedal welding using the developed system reached 87.5%

with well-formed welds. The research indicates that this automated welding system can achieve automated welding of bus pedals

meeting production requirements and providing a technical reference for the automated welding of similar components.

关键词

Keywords

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