基于微粒群算法的复杂曲面轮廓度误差计算

Profile Error Computation of Complicated Surface Based on Particle Swarm Optimization

针对复杂曲面轮廓度误差计算的数学模型比较复杂,并且难以用传统数值优化方法求解这一问题,提出了一种基于微粒群算法(PSO)并结合等参数线区域来计算复杂曲面轮廓度误差的方法.根据NURBS曲面的u和v参数构造等参数线区域,通过微粒群算法在等参数线区域内搜索与测量点距离最近的点,实现了复杂曲面轮廓度误差的计算.实验结果表明,该方法搜索速度快,计算精度高,用于求解曲面轮廓度误差是行之有效的.

For the mathematical model of profile error of surface is very complicated, and it is difficult for solving by traditional numerical method, an equal parameter lines area combined particle swarm optimization（PSO） is proposed for computing the profile error of complicated surface. The equal parameter lines area is constructed by u and v parameter of NURBS surface theory model. The profile error computation of complicated surface is implemented by searching closest distance point using particle swarm optimization in equal parameter lines area. The experiment results show the proposed method can improve searching efficiency and has higher precision.