一种基于激光视觉的机器人焊接相交曲线路径提取与跟踪方法

IF 5.6 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Wenze Ren , Keyi Huang , Jiahui Feng , Yuxing Feng , Jinsong Lin , Jun Zheng
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引用次数: 0

摘要

随着制造业的不断进步,自动化和智能化焊接技术在工业领域的应用越来越广泛。相贯焊缝作为复杂空间曲线的一种典型形式,广泛应用于管道、桁架等结构构件的连接。提出了一种基于直线激光视觉传感器的相交焊缝提取与实时跟踪方法。首先,采用大景深线激光视觉传感器对工件进行扫描。将RANSAC算法与自适应遗传粒子群优化算法(GA-APSO)相结合,实现了焊缝曲线的高精度提取。然后使用NURBS曲线重构提取的焊缝,并进行参数插值以保证机器人焊接运动均匀。在焊接过程中,传感器对焊缝进行连续扫描,提出的双向滑动窗口点提取方法能够在电弧光和飞溅干扰下快速可靠地识别焊缝点。结合局部曲线校正算法,实时调整焊接轨迹,显著提高了焊接精度。实验结果表明,焊接轨迹与真焊缝的最大偏差为0.83 mm,具有较强的实际工程应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel laser vision-based robotic welding path extraction and tracking method for intersecting curves
With the continuous advancement of manufacturing, automated and intelligent welding technologies have seen increasingly widespread application across industrial fields. As a typical form of complex spatial curves, intersecting weld seams are widely used in the joining of pipelines, trusses, and other structural components. This paper proposes an extraction and real-time tracking method for intersecting weld seams based on a line laser vision sensor. First, a large–depth-of-field line laser vision sensor is employed to scan the workpiece. By combining the RANSAC algorithm with an adaptive genetic particle swarm optimization algorithm (GA-APSO), the weld seam curve is extracted with high accuracy. The extracted seam is then reconstructed using a NURBS curve, with parameter interpolation applied to ensure uniform robot welding motion. During the welding process, the sensor continuously scans the seam, and a proposed bidirectional sliding-window point extraction method enables fast and reliable identification of weld points under arc light and spatter interference. Together with a local curve correction algorithm, the welding trajectory is adjusted in real time, significantly improving weld precision. Experimental results show that the maximum deviation between the welding trajectory and the true seam is 0.83 mm, demonstrating strong potential for practical engineering applications.
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来源期刊
Measurement
Measurement 工程技术-工程:综合
CiteScore
10.20
自引率
12.50%
发文量
1589
审稿时长
12.1 months
期刊介绍: Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.
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