Abstract
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.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant 6140-3372, and by National Science and Technology Support Program of China under Grant 2015BAF01B01.
The authors would like to thank the anonymous referees for their valuable suggestions and comments.
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Yang, L., Li, E., Long, T. et al. A welding quality detection method for arc welding robot based on 3D reconstruction with SFS algorithm. Int J Adv Manuf Technol 94, 1209–1220 (2018). https://doi.org/10.1007/s00170-017-0991-9
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DOI: https://doi.org/10.1007/s00170-017-0991-9