摘要
测量不确定度有多种评定模型,采用不同的评定模型可能得到不同的结果。为了保证求得的不确定度数值有足够的精度,必须对不同模型计算出的测量不确定度进行有效的验证。文中首次研究了测量不确定度评定模型的验证,该方法首先通过埃奇沃思级数展开来表示出测量数据的分布函数,然后由蒙特卡罗模拟法产生大量符合此分布函数的测量数据的模拟值,计算出该模拟值的标准差作为不确定度评定的验证值,从而实现对各种不确定度评定模型的验证。最后通过多个实例分析说明了该方法的有效性。
There are many models used in measurement uncertainty evaluation. The verification of uncertainty evaluation is necessary in order to ensure the accuracy of the measuring results. A novel verification method of the measurement uncertainty evaluation is described. The distribution function of the measuring data is expressed by Edgeworth expansion firstly. A large number of simulative measuring data according with this kind of distribution is then generated by Monte Carlo simulation. The standard deviation of these simulative values is calculated, and which is considered as the valid value of the uncertainty evaluation. Therefore the verification of the uncertainty evaluation model is realized. Finally, the rationality and validity of the applied methods is compared and confirmed by various measurement examples.
出处
《计量学报》
EI
CSCD
北大核心
2007年第3期193-197,共5页
Acta Metrologica Sinica
基金
国家自然科学基金(50375011
50675011)
关键词
计量学
测量不确定度
验证
蒙特卡罗模拟
Metrology
Measurement uncertainty
Verification
Monte Carlo simulation
