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机构地区:[1]湘潭大学焊接机器人及其应用湖南省重点实验室,湘潭411105
出 处:《焊接学报》2018年第5期25-28,共4页Transactions of The China Welding Institution
基 金:国家自然科学基金资助项目(51575468);湖南省自然科学联合基金资助(2015JJ6107)
摘 要:多层堆焊时,第二层焊缝受第一层焊缝的形状和焊接质量影响较大,一般需经人工观察实时调整堆焊参数和焊枪姿态,急需一种精准高效的堆焊三维曲面识别技术,以满足自动化堆焊的要求.针对这一问题,提出一种基于采样点三维数据的分区间Kriging插值增长的Delaunay三角剖分模型,该方法根据磁控旋转电弧堆焊传感器采集的焊缝采样点数据,利用Kriging插值算法加权处理,得到相应的内点,将这些数据点进行分区间增长的Delaunay三角剖分,投影到三维空间中形成三角网格面片,完成堆焊曲面重建.结果表明,该方法的曲面重建效果较好,实时性较高.In the process of the multi-layer welding,the second layer is affected greatly by the shape and welding quality of the first layer,which subjects to the artificial observation and real-time adjustment of welding parameters. In order to meet the requirements of automatic surfacing,a precise and efficient 3D surface recognition technology is needed urgently. To solve this problem,a Delaunay triangulation model based on Kriging interpolation between three-dimensional data of sampling points is proposed. According to the data collected by magnetron rotary arc surfacing sensor, the data of the sampling points are smoothed and weighted by Kriging interpolation algorithm to obtain the corresponding interior points. Then the Delaunay triangulation of these data points with increasing division is performed to triangle mesh patches in the projected three-dimensional space to complete surfacing surface reconstruction. The results show that the method has a better surface reconstruction effect and higher real-time performance.
关 键 词:磁控旋转电弧 多层堆焊 曲面重建 KRIGING插值 DELAUNAY三角剖分
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