A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm
文献类型:期刊论文
作者 | Yang, Lei1,2![]() ![]() ![]() ![]() ![]() ![]() ![]() |
刊名 | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
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出版日期 | 2018 |
卷号 | 94期号:1-4页码:1209-1220 |
关键词 | Welding Quality Sfs 3d Reconstruction Feature Extraction Svm |
DOI | 10.1007/s00170-017-0991-9 |
文献子类 | Article |
英文摘要 | 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. |
WOS关键词 | VISION ; SYSTEM ; TRACKING ; MACHINE ; MODELS ; LASER ; SHAPE |
WOS研究方向 | Automation & Control Systems ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000419114100093 |
资助机构 | National Natural Science Foundation of China(6140-3372) ; National Science and Technology Support Program of China(2015BAF01B01) |
源URL | [http://ir.ia.ac.cn/handle/173211/20704] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
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 |
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. |
入库方式: OAI收割
来源:自动化研究所
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