Knowledge Commons of Institute of Automation,CAS
A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm | |
Yang, Lei1,2; Li, En1; Long, Teng1,2; Fan, Junfeng1,2; Mao, Yijian1,2; Fang, Zaojun1; Liang, Zize1 | |
发表期刊 | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY |
2018 | |
卷号 | 94期号:1-4页码:1209-1220 |
文章类型 | Article |
摘要 | In the modern manufacturing industry, the welding quality is one of the key factors which affect the structural strength and the comprehensive quality of the products. It is an important part to establish the standard of welding quality detection and evaluation in the process of production management. At present, the detection technologies of welding quality are mainly performed based on the 2D image features. However, due to the influence of environmental factors and illumination conditions, the welding quality detection results based on grey images are not robust. In this paper, a novel welding detection system is established based on the 3D reconstruct technology for the arc welding robot. The shape from shading (SFS) algorithm is used to reconstruct the 3D shapes of the welding seam and the curvature information is extracted as the feature vector of the welds. Furthermore, the SVM classification method is adopted to perform the evaluation task of welding quality. The experimental results show that the system can quickly and efficiently fulfill the detection task of welding quality, especially with good robustness for environmental influence cases. Meanwhile, the method proposed in this paper can well solve the weakness issues of conventional welding quality detection technologies. |
关键词 | Welding Quality Sfs 3d Reconstruction Feature Extraction Svm |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1007/s00170-017-0991-9 |
关键词[WOS] | VISION ; SYSTEM ; TRACKING ; MACHINE ; MODELS ; LASER ; SHAPE |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(6140-3372) ; National Science and Technology Support Program of China(2015BAF01B01) |
WOS研究方向 | Automation & Control Systems ; Engineering |
WOS类目 | Automation & Control Systems ; Engineering, Manufacturing |
WOS记录号 | WOS:000419114100093 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/20704 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Li, En |
作者单位 | 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 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yang, Lei,Li, En,Long, Teng,et al. A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,2018,94(1-4):1209-1220. |
APA | Yang, Lei.,Li, En.,Long, Teng.,Fan, Junfeng.,Mao, Yijian.,...&Liang, Zize.(2018).A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm.INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,94(1-4),1209-1220. |
MLA | Yang, Lei,et al."A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm".INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 94.1-4(2018):1209-1220. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Yang et al. - 2018 -(2802KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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