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基于视觉的压力容器密封端焊孔轨迹提取

Vision-Based trajectory extraction of welding holes on the sealing end of pressure vessels

  • 摘要: 目前基于计算机视觉的焊缝提取研究大部分聚焦于平面对接焊缝和角接焊缝,关于复杂表面焊缝的研究工作较少,文中针对压力容器封头焊孔接管焊接,提出一种以圆或椭圆轨迹开孔的焊孔焊接轨迹提取方法.首先对点云进行预处理,以提高点云数据的质量和可靠性,然后通过在点云质心建立复数坐标系提取点云内轮廓,作为原始边界.在点云配准阶段,采用迭代最近点配准方法,以三个坐标轴转角及模板点云圆孔半径(椭圆为长半轴与短半轴)为设计变量,以配准误差为目标函数,构建非线性优化问题进行求解. 结果表明,该算法能够适用复杂表面的焊接,实现对焊接机器人的自动引导,并满足焊接误差及效率,验证了算法的可行性.

     

    Abstract: Most current research on weld seam extraction based on computer vision primarily focuses on planar butt welds and fillet welds, while there is limited research on weld seams on complex surfaces. This paper proposes a method for extracting welding trajectories for nozzle welds on pressure vessel heads, specifically for holes with circular or elliptical paths. Firstly, preprocess the point clouds to enhance the quality and reliability of the point clouds data. Subsequently, extract the inner contour of the point cloudss by establishing a complex coordinate system at the centroid of the point clouds, which will serve as the original boundary. In the point cloud registration stage, the Iterative Closest Point (ICP) algorithm is employed. A nonlinear optimization problem is formulated, where the design variables include the three rotation angles (Euler angles) and the geometric parameters of features in the template point cloud (the radius for a circular hole, or the major and minor axes for an elliptical one). The objective function is defined as the registration error, which is minimized to achieve optimal alignment. Experimental results demonstrate that this algorithm can be applied to the welding of complex surfaces, realize the automatic guidance for welding robots, meet the requirements for welding accuracy and efficiency, and thus verify the feasibility of the algorithm.

     

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