Blade Profile Profile Error Evaluation Based on Improved ICP Algorithm
LU Heng1,XU Xu-song1,WANG Shu-gang2,WANG hao1
1. College of Mechanical Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
2. Wuxi Metrology and Testing Institute, Wuxi, Jiangsu 214100, China
Abstract To address the problem of poor registration precision of traditional iterative closest point (ICP) algorithm, an improved ICP algorithm was proposed.First, a new type line data registration method based on vector alignment was used, considering that the measured data of CMM show orderly array and one-to-one correspondence.Secondly, based on the traditional ICP algorithm, non-uniform rational B-spline (NURBS) curve fitting was carried out for the registration data, and then the adaptive particle swarm optimization (PSO) algorithm was used to further accurately register the measurement data.Finally, the evaluation method of blade profile error based on the minimum region was used to evaluate the accuracy.Experimental results show that, compared with the traditional ICP algorithm, the improved method can further converge on the original convergence value, and the contour error is reduced by 28.57%.This method can effectively improve the accuracy of the evaluation of blade profile error and provide a reliable basis for the evaluation of blade machining quality.
［1］李超. 基于测量数据的航发叶片型面快速重构方法研究 ［D］. 成都: 电子科技大学, 2018.
［2］魏小华, 徐文俊, 徐雪雅. 基于改进Sierra抖动算法的微离焦投影三维轮廓测量技术研究 ［J］. 计量学报, 2020, 41 (6): 669-675.
Wei X H, Xu W J, Xu X Y. Study on Improved Sierra Dithering Algorithm for Micro-defocusing Projector Three-dimensional Profile Measurement Technology ［J］. Acta Metrologica Sinica, 2020, 41 (6): 669-675.
［3］史建华, 刘盼. 大尺寸航空发动机叶片的高效型面检测方法 ［J］. 计量学报, 2018, 39 (5): 605-608.
Shi J H, Liu P. Efficient Profile Detection Method for Large-size Aero-engine Blade ［J］. Acta Metrologica Sinica, 2018, 39 (5): 605-608.
［4］何帅, 陈富民, 李建华, 等. 叶身型线轮廓度评定方法研究 ［J］. 西安交通大学学报, 2019, 53 (8): 175-182.
He S, Chen F M, Li J H, et al. Research on evaluation method of blade profile profile ［J］. Journal of Xi ′an Jiaotong University, 2019, 53 (8): 175-182.
［5］田社平, 韦红雨, 颜德田. 基于遗传算法的lp数据拟合及其应用 ［J］. 计量学报, 2005, 26 (3): 284-288.
Tian S P, Wei H Y, Yan D T. lp data fitting based on genetic algorithm and its application ［J］. Acta Metrologica Sinica, 2005, 26 (3): 284-288.
［6］吴锋, 钱宗才, 杭洽时, 等. 基于轮廓的力矩主轴法在医学图像配准中的应用 ［J］. 第四军医大学学报, 2001, 22 (6): 567-569.
Wu F, Qian Z C, Hang Q S, et al. Application of contour-based torque spindle method in medical image registration ［J］. Journal of Fourth Military Medical University, 2001, 22 (6): 567-569.
［7］刘晶. 叶片数字化检测中的模型配准技术及应用研究 ［D］. 西安:西北工业大学, 2006.
［8］Yang J L, Li H D, Campbell D, et al. Go-ICP: a globally optimal solution to 3D ICP point-set registration ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, 38 (11): 2241-2254.
［9］Xu G L, Du S Y, Xue J R. Precise 2Dpoint set registration using iterative closest algorithm and correntropy ［C］. // IEEE International Joint Conference on Neural Networks. New York, USA, 2016: 4627-4631.
［10］Lamine T M, Gokhool T, Checchin P, et al. CICP: cluster iterative closest point for sparse-dense point cloud registration ［J］. Robotics and Autonomous Systems, 2018, 108: 66-86.
［11］Chetverikov D, Stepanov D, Krsek P. Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm ［J］. Image and Vision Computing, 2005, 23 (3): 299-309.
［12］Wu Z Z, Chen H C, Du S Y, et al. Correntropy based scale ICP algorithm for robust point set registration ［J］. Pattern Recognition: The Journal of the Pattern Recognition Society, 2019, 93: 14-24.
［13］施法中. 计算机辅助几何设计与非均匀有理B样条(修订版) ［M］. 北京:高等教育出版社, 2013.
［14］蔺小军, 吴刚, 单秀峰, 等. 基于叶片截面线CMM测量数据的ICP配准改进算法 ［J］. 机械工程学报, 2020, 56 (2): 1-8.
Lin X J, Wu G, Shan X F, et al. Improved ICP Registration Algorithm Based on CMM Measured Data of Blade Sections ［J］. Journal of Mechanical Engineering, 2020, 56 (2): 1-8.
［15］张岩, 吴水根. MATLAB优化算法 ［M］. 北京:清华大学出版社, 2017.
［16］王跃灵, 旺玥, 王琪, 等. 基于自适应粒子群遗传算法的柔性关节机器人动力学参数辨识 ［J］. 计量学报, 2020, 41 (1): 60-66.
Wang Y L, Wang Y, Wang Qi, et al. Dynamic Parameter Identification of Flexible Joint Robot Based on Adaptive Particle Swarm Genetic Algorithm ［J］. Acta Metrologica Sinica, 2020, 41 (1): 60-66.
［17］全国产品尺寸和几何技术规范标准化技术委员会. 产品几何技术规范 (GPS)标准汇编 ［S］. 2014.
2022, Vol. 43 
