The purpose of this paper is to introduce structured light image processing technology into pipeline welding automation projects, and develop a vision‐based pipeline girth‐welding robot. The welding torch can accurately track the weld and complete the omni‐orientation welding automatically.
Weld image processing adopts the base theory including Laplacian of Gaussian filter, neighbourhood mean filter, largest variance threshold segmentation and morphologic, etc. obtains good effect of weld recognition.
The paper uses a vision sensor to achieve the weld character's recognition and extraction, directly control the robot tracking weld to complete automation welding. Compared with the existing pipeline welding devices, it does not need the lay orbit or plot tracking mark, which can shorten the assistant time to improve the productivity.
The research findings can satisfy the need of whole‐directional automation welding for large diameter transportation pipe's circular abutting weld. It fits for the automation welding for the long‐distance transportation pipe of petroleum, natural gas, and water.
Aiming at the character recognition and extract of V‐type weld, the method combining the neighbourhood mean filter algorithm with the largest variance threshold segmentation is proposed to obtain the quick weld image processing speed.
Yue, H., Li, K., Zhao, H. and Zhang, Y. (2009), "Vision‐based pipeline girth‐welding robot and image processing of weld seam", Industrial Robot, Vol. 36 No. 3, pp. 284-289. https://doi.org/10.1108/01439910910950568Download as .RIS
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