An initial point alignment method of narrow weld using laser vision sensor

被引:9
作者
Fan, Junfeng [1 ,2 ]
Jing, Fengshui [1 ,2 ]
Yang, Lei [1 ,2 ]
Long, Teng [1 ,2 ]
Tan, Min [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
Initial point alignment; Image processing; Laser vision sensor; Narrow weld; Welding robot; SEAM TRACKING; POSITION; SYSTEM; PENETRATION;
D O I
10.1007/s00170-018-3184-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, an initial point alignment method of narrow weld using laser vision sensor is presented on the basis of the relationship between the feature point of laser stripe and initial point. The whole initial point alignment process contains two stages. At the first stage, the initial point image is captured, and the image coordinates of the feature point of laser stripe and initial point are obtained. At the second stage, according to the relationship between the feature point of laser stripe and initial point, the three-dimensional (3D) coordinates of initial point could be determined to achieve initial point alignment. The initial point alignment method mainly includes vision sensing and motion control two parts. Firstly, a new laser vision sensor with a uniform LED surface light source is developed to capture the high signal-to-noise ratio (SNR) image including narrow weld, and the feature point of laser stripe and initial point are detected using the image processing method. Secondly, initial point alignment control system including feature verification and controller is designed to achieve initial point alignment control. Finally, a series of initial point alignment experiments of straight and curve narrow weld are conducted to test the performance of the proposed method. Experimental results indicate the alignment error is less than previous methods, which could be used in automatic welding process.
引用
收藏
页码:201 / 212
页数:12
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