三坐标测量机一般表面上的自适应采样规划

Adaptive Sampling Planning of General Surfaces for Coordinate Measuring Machines

针对CAD模型已知的三坐标测量机一般表面(连续或非连续的基本特征表面)上的常用采样策略中存在的问题,提出一种自适应采样方法,并对测量边和面的情况分别给出了具体的采样算法.通过对选取的表面进行分析,采取步长自适应再分迭代自动规划出相应数目的采样点分布;并使采样点达到均匀分布且避开非连续区域.实验结果表明,该方法对于各种复杂情况的一般表面都有比较好的适应性,弥补了随机采样难以均匀化和基于数字序列采样对表面要求完整连续的不足.

Aiming at the limitations of conventional CAD model-based sampling strategies of general surfaces （continuous or discontinuous surfaces of basic features） for coordinate measuring machines （CMM）, an adaptive sampling method is proposed, and the detailed sampling algorithms for measuring edges and faces are presented. After analyzing the selected surface characteristics, step＇s adaptive subdivision and iteration are adopted to plan the sampling points＇ locations for the specified point number. The points are distributed evenly according to the surface shape, and located apart from the discontinuous areas. The experimental results show that the method has strong adaptability for general surfaces with different complexity, and tackles the shortages of random sampling strategy and number sequence-based sampling strategy.