基于最大熵区间分析的测量不确定度评定

doi:10.3969/j.issn.1000-1158.2019.01.28

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Abstract In order to improve the accuracy of measurement uncertainty evaluation, the maximum entropy interval analysis method was proposed. Firstly, the model was established combining maximum entropy algorithm and Bayesian model.Secondly, asymmetry of lower and upper bounds for sample information of input quantity was analysised, and the Jaynes entropy and Lagrange were obtained the shortest interval.Lastly, the input information was divided the sample interval to determine the ratio of the measured uncertainty, considering the input uncertainty with probability distribution of the transfer process.The simulation results show that the algorithm has less range of measurement uncertainty and the result is more accurate.

Key words： metrology uncertainty evaluation maximum entropy interval analysis Bayesian model

Received: 18 September 2017 Published: 07 January 2019

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	YAO Cheng-qian

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YAO Cheng-qian. Measurement Uncertainty Evaluation Based on Maximum Entropy Interval Analysis[J]. Acta Metrologica Sinica, 2019, 40(1): 172-176.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2019.01.28 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2019/V40/I1/172

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