Recognition of the Type of Welding Joint Based on Line Structured-light Vision

被引:0
|
作者
Wang Xiuping [1 ,2 ]
Fan Xi [1 ]
Fan Ying [2 ]
Bai Ruilin [2 ]
机构
[1] Wuxi Profess Coll Sci & Technol, Wuxi 214028, Peoples R China
[2] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China
关键词
Wavelet transform; Probabilistic neural network; Welding joint; Line structured-light;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To recognize the type of welding joint is an essential precondition for extracting features of weld seam and guiding robot tracking seam automatically. A method based on a line laser structured-light vision for recognizing the type of welding joint is studied in this paper. Images of welding joint captured by camera are preprocessed firstly for noise reduction and enhancement with wavelet transform, and the reconstructed images are convened to binary ones using appropriate thresholds. Then some features of binary images are further extracted and formed feature vectors which are input into a PNN classifier for classification. Combined with the position relationship of laser and camera, four types of welding joint are eventually recognized. Experimental results show that, this method has a high recognition rate.
引用
收藏
页码:4383 / 4386
页数:4
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