摘要
以毛细管电泳仪检出限的不确定度评定为例,探讨了Python软件在MCM不确定度评定中的具体应用。首先采用GUM法对不确定度进行评定,再采用Python软件以MCM法进行对比分析。结果表明,两种评定方法结果相同。与GUM相比,MCM直接通过计算获得不确定度结果,评定过程更加方便易行。通过对实际采样数据的分析,发现数据的采样对不确定度评定结果有很大影响。由于GUM分析时采用的理论模型与实际数据不一定相符,造成不确定度计算结果存在偏差,而以实际采样数据为基础的MCM能够获得更真实、更可靠的不确定度计算结果。
For the evaluation of uncertainty on detection limit of capillary electrophoresis,a specific application of Monte Carlo method(MCM)with Python software was discussed.GUM(Guide to the Representation of Measurement Uncertainty)and MCM were applied on the evaluation of uncertainty to achieve a comparative analysis.The results showed that the two evaluation methods had the same conclusion.Different with GUM,MCM obtained the uncertainty result directly through calculation,and the whole process was more convenient and easy.Furthermore,through the analysis of the actual data,it was found that samples had a great influence on the result.As the theoretical model used in GUM analysis did not match the actual data perfectly,there was a deviation in the calculation result of uncertainty,and the MCM based on the actual sampling data could obtain more realistic and reliable calculation results of uncertainty.
作者
王舵
Wang Duo(Liaoning Institute of Measurement,Shenyang 110004,China)
出处
《化学分析计量》
CAS
2021年第6期80-84,共5页
Chemical Analysis And Meterage
