基于遗传算法的散乱数据点的NURBS曲面拟合与优化  

The Nurbs Surface Fitting and Optimization of Scattered Points’Data Based on Genetic Algorithm

作　　者：张志强[1] 李建军[1] 赵坚[1] 

机构地区：[1]天津城市建设学院能源与机械工程系,天津300384

出　　处：《天津城市建设学院学报》2010年第1期41-43,共3页Journal of Tianjin Institute of Urban Construction

基　　金：建设部科研开发项目(04-228)

摘　　要：将遗传算法与散乱数据点的NURBS曲面拟合优化问题有机结合,根据反求得到的控制顶点生成NURBS曲面并利用遗传算法对曲面进行优化,使曲面在满足给定容差和光顺度的条件下,能用较少的控制顶点来表达.给出此类问题的遗传因子和评价函数,计算出曲面的控制顶点及与其对应的权因子.通过数值仿真验证了此方法对于简化拟合曲面表述的有效性.The Nurbs surface can be obtained and optimized by genetic algorithm on the controlling points,which can be solved by the B-spline surface expression on the given scattered points’ data.So on the controlling that the surface meets the given tolerance and smoothing degree,the surface can be expressed by fewer controlling points.The genetic gene and evaluating function are given and the controlling points and their corresponding weight genes are computed.By numerical simulation this method is verified for the validity of the simplified representation of the fitting surface.

关 键 词：遗传算法 曲面拟合 NURBS曲面 评价函数 

分 类 号：TH122[机械工程—机械设计及理论] TP391.73[自动化与计算机技术—计算机应用技术]