Abstract：Multi-point calibration linear measurement system exhibits a wider range and higher accuracy and reliability of measurements compared to the single-point or two-point calibration, and it has been widely used in many fields such as chemical analysis and physical testing. A mathematical model and simulation method to evaluate the measurement uncertainty of multi-point calibration linear measurement system by Monte Carlo method (MCM) was proposed. The specific evaluation process and application of MCM in uncertainty evaluation was introduced using the determination of manganese content in low alloy steel by inductively coupled plasma atomic emission spectrmetry(ICP-AES) as the example. Firstly, MCM method was used to evaluate the measurement uncertainty through simulation sampling analysis according to the probability distribution type of input quantity. Then the GUM method was used for evaluation. The experimental results showed that the average measurement value of manganese content in the specimen was (0.919±0.012)%, k=1.96, which was consistent with the expanded uncertainty calculated by the GUM method. The method given in the paper could be applied to the uncertainty evaluation of multi-point calibration linear measurement systems. And it solved the issues of the import of uncertainty measures introduced by reference values of standard samples and volatility of linear calibration, to a certain extent, which would promote the innovation and development of uncertainty assessment and application.
刘枫, 林莎莎, 石正岩, 齐丽璟, 刘颖. 蒙特卡洛法在多点校准线性测量系统不确定度评定中的应用[J]. 冶金分析, 2022, 42(4): 19-27.
LIU Feng, LIN Shasha, SHI Zhengyan, QI Lijing, LIU Ying. Uncertainty evaluation of the multi-point calibration linear measurement system based on Monte Carlo method. , 2022, 42(4): 19-27.
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