论文部分内容阅读
为评价超精密工作台自标定过程中由随机测量误差引起的标定不确定度,提出了基于M on te C arlo模拟的自标定不确定度定量评价方法。该方法以自标定算法的最大不确定度放大倍数为评价指标,通过根据算法输入参数联合概率密度函数的大量随机抽样,以及对算法输出样本的统计来完成。仿真表明:该方法具有较好的通用性及可靠性,可在自标定方案设计阶段,有效地评价所使用算法的合理性,这对于超精密工作台自标定算法的设计及选择具有指导意义。
In order to evaluate the calibration uncertainty caused by random measurement error during the calibration of ultra-precision workbench, a quantitative evaluation method of self-calibration uncertainty based on MonteCarlo simulation is proposed. This method uses the maximum uncertainty of self-calibration algorithm as the evaluation index, through a large number of random sampling based on the input parameters of the algorithm combined with the probability density function, and the statistics of the output samples of the algorithm. The simulation results show that this method has good universality and reliability, and can effectively evaluate the rationality of the algorithm used in the self-calibration scheme design stage, which is instructive for the design and selection of self-calibration algorithm of ultra-precision workbench.