计量学报2025，Vol.46Issue(6)：839-846,8.DOI:10.3969/j.issn.1000-1158.2025.06.08
基于精配准和改进灰狼算法的叶片截面线轮廓度误差评定
Evaluation of Blade Section Profile Error Based on Fine Registration and Improved Grey Wolf Optimizer
摘要
Abstract
Taking the blade as an example,based on the iterative closest point(ICP)fine registration and following generation product specification(GPS),a method for evaluating the line profile error by introducing the Improved Grey Wolf optimizer(IGWO)is proposed.Firstly,a line profile evaluation model is established according to the minimum zone theory.Secondly,the theoretical profile line is interpolated and fitted by using Non-Uniform Rational B-Spline(NURBS),and the shortest distance from the measurement points to the NURBS is calculated by the subdivision approximating method.Logistic chaotic mapping was used to initialize the wolves,and merge Levy flight strategy to update Wolves position.With ICP parameters as variables,the profile error is computed iteratively based on IGWO combined with subdivision approximating;and the calculation accuracy of GA,PSO and WOA algorithms is compared.The experimental results show that this method can be used to evaluate the line profile error of blade.Based on ICP registration,the calculation accuracy of the profile is increased by 26.79%,and compared with GWO,the convergence speed and calculation accuracy of GWO are improved,and it is better than other algorithms.关键词
几何量计量/线轮廓度/改进灰狼算法/最小区域/非均匀有理B样条/分割逼近Key words
geometric measurement/line profile/IGWO/minimum zone/NURBS/subdivision approach分类
通用工业技术引用本文复制引用
郝博麒,徐旭松,王树刚,徐晨..基于精配准和改进灰狼算法的叶片截面线轮廓度误差评定[J].计量学报,2025,46(6):839-846,8.基金项目
2021年江苏高校"青蓝工程"(苏教师函[2021]11号) （苏教师函[2021]11号）
