Laser Additive Manufacturing Machine Vision System Development

Han CHEN; Jieliang REN; Shuai YAN; Xiaopeng SHI; Zhiyong LI

doi:10.7512/j.issn.1001-2303.2022.02.05

Important Issuse | Views : 0 下载量: 20 CSCD: 0

PDF
Export
Share
Collection
Album

Laser Additive Manufacturing Machine Vision System Development
Vol. 52, Issue 2, Pages: 36-41(2022)
DOI： 10.7512/j.issn.1001-2303.2022.02.05

扫描看全文

陈　汉，任杰亮，闫　帅，等.面向机器人激光增材制造的机器视觉系统标定算法［J］.电焊机，2022，52（2）：36-41.

CHEN Han, REN Jieliang, YAN Shuai, et al.Laser Additive Manufacturing Machine Vision System Development[J].Electric Welding Machine, 2022, 52(2): 36-41.
陈　汉，任杰亮，闫　帅，等.面向机器人激光增材制造的机器视觉系统标定算法［J］.电焊机，2022，52（2）：36-41. DOI： 10.7512/j.issn.1001-2303.2022.02.05.

CHEN Han, REN Jieliang, YAN Shuai, et al.Laser Additive Manufacturing Machine Vision System Development[J].Electric Welding Machine, 2022, 52(2): 36-41. DOI： 10.7512/j.issn.1001-2303.2022.02.05.

摘要

随着现代智能制造的快速发展，金属增材制造、绿色再制造、焊接等领域大量使用机器人等自动化装备，视觉传感是机器人智能制造的关键环节。针对上述需求设计了一套基于线结构光的视觉传感器，并对其进行标定，自主开发了用于机器人激光增材制造的机器视觉系统。该系统通过Matlab相机标定工具包实现相机的内外参数标定，利用Labview编程提取出像素坐标，根据最小二乘法拟合出相机坐标系下的光平面方程，实现像素坐标到光平面坐标的转换，最后针对视觉传感器与机器人的“Eye-in-Hand”系统实现手眼标定，完成像素坐标到机器人三维基坐标的转换。实验结果表明，开发的视觉传感器具有较高的定位精度，各方向平均误差仅为1 mm。

Abstract

With the rapid development of modern intelligent manufacturing, Robots and other automation equipment are widely used in metal additive manufacturing, green remanufacturing, welding and other fields. Visual sensing is a key link in robot intelligent manufacturing. This article addresses the above requirements, Designed and calibrated a set of vision sensors based on laser structured light, and independently developed a machine vision system for the robotic laser additive manufacturing process. This method realizes the internal and external parameter calibration of the camera through the Matlab camera calibration toolkit, uses Labview programming to extract the pixel coordinates, fits the laser plane equation in the camera coordinate system according to the least square method, and realizes the conversion from pixel coordinates to laser plane coordinates. Finally, the "Eye-in-Hand" system of the vision sensor and the robot realizes hand-eye calibration, and obtains the conversion of pixel coordinates to the three-dimensional base coordinates of the robot. Experiments show that the developed vision sensor has high positioning accuracy.

关键词

增材制造机器视觉线结构光手眼标定

Keywords

additive manufacturingmachine visionline structured lightEye-in-Hand calibration

references

杨强，鲁中良，黄福享，等. 激光增材制造技术的研究现状及发展趋势［J］. 航空制造技术， 2016（12）：26-31.

YANG Qiang，LU Zhongliang，HUANG Fuxiang， et al. Research on Status and Development Trend of Laser Additive Manufacturing［J］. Aeronautical Manufacturing Technology， 2016（12）：26-31.

邓俊豪. 基于视觉传感的电弧增材成形形貌检测与预测建模研究［D］. 上海：上海交通大学， 2019.

DENG Junhao. Research on Forming Information Acquisition and Prediction Modeling in Wire and Arc Addictive Manufacturing Based on Vision Sensing［D］. Shanghai： Shanghai JiaoTong University， 2019.

李友浩. 基于线结构光的电弧增材制造熔积层形貌三维测量［D］. 湖北：华中科技大学， 2016.

Li youhao. Deposition layer’s 3D Measurement of Arc-based Addictive Manufacturing Baesd on Line-structured Light［D］. Hubei： Huazhong University of Science & Technology， 2016.

D. Buchbinderet al. High Power Selective Laser Melting （HP SLM） of Aluminum Parts［J］. Physics Procedia， 2011（12）： 271-278.

Baufeld B.， O.V.D. Biest， et al.， Additive manufacturing of Ti-6Al-4V components by shaped metal deposition［J］. Microstructure and mechanical properties Materials & Design， 2010（31）：106-111.

Murr L.E.， et al.， Fabrication of Metal and Alloy Components by Additive Manufacturing： Examples of 3D Materials Science［J］. Journal of Materials Research and Technology， 2012，1（1）： 42-54.

Zhuang Zhao. Additive seam tracking technology based on laser vision［J］. The International Journal of Advanced Manufacturing Technology， 2021（25）：1-15.

Tsai R Y. Versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses［J］. IEEE Journal of Robotics and Automation， 1987，RA-3（4）： 323-344.

Faugeras O D， Luong Q T， Maybank S J. Camera self-calibration： Theory and experiments［C］. European conference on computer vision. Springer， Berlin， Heidelberg， 1992： 321-334.

聂红梅，刘忠艳.基于OpenCV的摄像机标定研究［J］.微处理机，2017，38（06）：58-61.

Nie Hongmei， Liu Zhongyan. Research on Camera Calibration Based on OpenCV［J］. Microprocessors， 2017，38（06）：58-61.

高磊，莫冰.摄像机标定系统的设计［J］.电脑与电信，2017（12）：36-38.

GAO Lei MO Bing. Design of Camera Calibration System［J］.Computer & Telecommunication， 2017（12）：36-38.

ZHANG Z Y. A flexible new technique for camera calibration［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence， 2000，22（11）： 1330-1334.

陈涛. 强噪声下的激光视觉焊缝跟踪系统研究［D］. 广东：华南理工大学， 2020.

CHEN Tao. Research on Laser Vision Seam Tracking System under Strong Background Noise［D］. South China university of Technology， 2020.

龚国基. 基于主动光视觉传感的焊缝自动跟踪系统研究［D］. 广东：华南理工大学， 2016.

GONG Guoji. Research on automatic seam tracking system based on active vision sensor［D］.Guangdong：South China university of Technology， 2016.

王研博. 面向焊缝跟踪的线激光检测技术研究［D］. 广东：华南理工大学， 2017.

WANG Yanbo. Reasearch on the Line Laser Detection Technology for Weld Seam Tracking［D］. Guangdong：South China university of Technology， 2017.

编辑部网址：http：//www.71dhj.comhttp://www.71dhj.com

Alert me when the article has been cited

提交

Application Research and Prospect of Inspection Technology for Metal Additive Manufacturing

Research on Welding Path Planning of Medium-thick Plate Based on the Data Driven of Point Cloud

Overview of Development and Application of Built-up Welding Technology