基于自适应采样的叶型曲面在机测量方法

On-Machine Measurement Method of Profile Surface Based on Adaptive Sampling

摘要: 采样策略是影响航空发动机叶片复杂曲面在机测量效率的关键因素，本文以航发涡轮叶片为研究对象，针对五轴在机测量平台在测量叶片的曲面形状特性问题提出了一种基于模拟退火算法的等r次距最优自适应采样，根据曲面的几何特征，自适应确定检测点的分布。仿真分析了曲率采样法和均匀采样法的采样结果，对比表明，本文自适应采样方法在相同采样点数的情况下，测量误差小，重构表面精度高，满足在机测量的精度和效率要求。通过对加工叶片进行在机测量实验，验证了本文方法对叶型曲面轮廓采样的有效性和可行性。

Abstract: Sampling strategy is a key factor affecting the efficiency of complex surface of aero-engine blade’s on-machine measuring. In this paper, taking aero-engine turbine blade as the research object, an optimal adaptive sampling with equal r intervals based on simulated annealing algorithm was pro-posed for the surface shape characteristics of the five-axis on-machine measurement platform. The distribution of detection points was determined adaptively according to the geometric characteris-tics of the surface. The results of curvature sampling method and uniform sampling method are simulated and analyzed. The comparison shows that the adaptive sampling method in this paper has small measurement error and high surface reconstruction accuracy under the condition of the same number of sampling points, which meets the requirements of accuracy and efficiency of on-machine measurement. The effectiveness and feasibility of the proposed method for sampling the profile of the blade surface were verified by measuring the blade in machine.