Detection of fillet weld joints using an adaptive line growing algorithm for robotic arc welding

被引:51
作者
Dinham, Mitchell [1 ]
Fang, Gu [1 ]
机构
[1] Univ Western Sydney, Sch Comp Engn & Math, Penrith, NSW 1797, Australia
基金
澳大利亚研究理事会;
关键词
Robotic arc welding; Fillet weld; Welding seam detection; SEAM; POSITION; ENVIRONMENT; RECOGNITION; VISION;
D O I
10.1016/j.rcim.2013.10.008
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
One of the main challenges for robotic welding in low to medium volume manufacturing or repair work is the time taken to programme the robot path for a new job. It is often cheaper and more efficient to weld the parts manually. There are many papers published on the detection of butt welds, however there is no mature method for the identification of fillet welds which are more common. This paper presents a novel method that can autonomously identify fillet weld joints regardless of the base material, surface finish and surface imperfections such as scratches, mill scale and rust The new method introduces an adaptive line growing algorithm for robust identification of weld joints regardless of the shape of the seam. The proposed method is validated through experiments using an industrial welding robot in a workshop environment The results show that this method can detect realistic fillet weld joints for industrial arc welding applications. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:229 / 243
页数:15
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