【摘要】 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。更多还原

【Abstract】 The self-calibration uncertainty of ultra-precision stages caused by random measurement noise was evaluated using Monte Carlo simulations.The maximum uncertainty amplification factor of the self-calibration algorithm was used as the quantitative evaluation index.The evaluation used random sampling based on the joint probability density function of the self-calibration algorithm input parameters with statistical analysis of the output population.The simulation results show that the method is more versatile and reliable,and can effectively evaluate the self-calibration algorithm in the design phase so that it has more effect on the design of the self-calibration method for ultra-precision stages.更多还原