面向在机测量的动态测量不确定度评定与实验研究

Research on Evaluation and Experiment of Dynamic Measurement Uncertainty for On-machine Measurement

针对在机测量系统不确定度量化评定难题,研究了面向在机测量的动态测量不确定度评定方法及策略,设计了评定框架;引入量值特性分析并融合黑箱理论进行了不确定度分量分析,规划了网格点阵式和正交连续式等两种样本集;按照极大似然估计原则对采样数据拟合,得到不确定度分量的分布规律及概率密度函数;建立了面向在机测量的动态测量不确定度评定数学模型,并基于自适应蒙特卡洛法进行不确定度的传递合成。利用所构建的在机测量系统,开展了动态测量不确定度评定实验,验证了方法的可行性。

Aiming at the problem of the uncertainty evaluation oriented to on-machine measurement system,the method and strategy of uncertainty evaluation oriented to on-machine measurement are studied,and the evaluation framework is designed.The quantitative characteristic analysis method is introduced and the black box theory is integrated to analyze the uncertainty.Two kinds of sample set programming methods,cubic lattice sample set and orthogonal continuous sample set,are proposed.According to the maximum likelihood estimation approach,the distributions and PDFs of uncertainty components are obtained by distribution fitting.The mathematical model of uncertainty evaluation oriented to on-machine measurement is established.and then the uncertainty transfer and synthesis are carried out based on the adaptive MCM.Using the on-machine measurement system,the uncertainty evaluation experiment of dynamic measurement is carried out to verify the feasibility of the method.