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Vision-based pipeline girth-welding robot and image processing of weld seam

机译:基于视觉的管道围焊机器人及焊缝图像处理

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Purpose - 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. Design/methodology/approach - 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. Findings - 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. Practical implications - 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. Originality/value - 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.
机译:目的-本文的目的是将结构化光图像处理技术引入管道焊接自动化项目中,并开发一种基于视觉的管道环焊机器人。焊炬可以准确跟踪焊缝,并自动完成全方位焊接。设计/方法/方法-焊接图像处理采用高斯滤波器的拉普拉斯算子,邻域均值滤波器,最大方差阈值分割和形态学等基础理论,在焊接识别中取得了良好的效果。发现-本文使用视觉传感器实现焊缝特征的识别和提取,直接控制机器人跟踪焊缝以完成自动化焊接。与现有的管道焊接装置相比,不需要铺设轨道或轨迹跟踪标记,可以缩短辅助时间,提高生产率。实际意义-研究结果可以满足大直径运输管圆形对接焊缝全方向自动焊接的需要。适用于石油,天然气和水的长途运输管道的自动化焊接。独创性/价值-针对V型焊缝的特征识别和提取,提出了一种将邻域均值滤波算法与最大方差阈值分割相结合的方法,以获得较快的焊缝图像处理速度。

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