散乱数据点集的三角划分算法研究

Research on triangulation algorithm for scattered data points

在对当前的三角网格划分方法进行比较分析后,提出了一种散乱数据点集的3D三角网格划分算法,该算法不需如同二维划分方法一样要对散乱点集对应的自由曲面分片投影,并可自然处理含有凹边界及孔域的曲面数据点集,利用网格扩展、边界环分裂和边界环封闭,根据曲面的变化逐层推进生成三角网格,使算法能方便地处理非封闭曲面、空间剪裁曲面、封闭曲面、空间多连通曲面等各种曲面的散乱数据。

After the analysis of different algorithms which deal with triangulation of scattered data points, an effective triangulation algorithm for scattered data points is put forward. This algorithm solves the problem that data points must be partitioned for multi-projection realized by traditional 2D triangulation methods. The three basic processing operations of 3D triangulation algorithm composed by boundary loop extending, splitting, closing are summarized. The mesh can be created with the change of curved face. The algorithm can deal with scattered data of diversified surface.