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Calculation of Expanded Uncertainty in Measurements Using the Kurtosis Method when Implementing a Bayesian Approach

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Measurement Techniques Aims and scope

Expanded uncertainty is evaluated according to the revised Guide to the Expression of Uncertainty in Measurement. The methodology of estimation is based on procedures that are independent of the probability density function of the measurand. It is shown that in using this methodology, the relative error of estimation of expanded uncertainty can be greater than 100%. A new method is proposed for computing expanded uncertainty with this shortcoming removed. In this method, the kurtosis of the distribution of input variables is calculated when computing the expanded uncertainty. The proposed method is compared with modeling using the Monte Carlo method, and close results are obtained.

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References

  1. JCGM 100:2014, Evaluation of Measurement Data. Guide to the Expression of Uncertainty in Measurement. Committee Draft.

  2. JCGM 101:2008, Evaluation of Measurement Data – Supplement 1 to the Guide to the Expression of Uncertainty in Measurement – Propagation of Distributions using the Monte Carlo Method.

  3. I. P. Zakharov, “Derivation of a reliable estimate of the coverage factor in compiling an uncertainty budget for measurements,” Sist. Obrab. Inform., No. 3, 41–44 (2013).

  4. N. A. Burmistrova, A. V. Stepanov, and A. G. Chunovkina, “Bayesian estimates of systematic errors of measuring instruments,” Izmer. Tekhn., No. 9, 6–10 (2015).

  5. A. A. Danilov and S. A. Shumarova, “On the asymmetry of the probability density function of the error of the results of measurements obtained by means of the complex measurement channels of measurement systems,” Izmer. Tekhn., No. 11, 60–61 (2012).

  6. P. Täubert, Abschätzung der Genauigkeit von Meßergebnissen, VEB Verlag Technik, Berlin (1987).

    Google Scholar 

  7. F. Adunka (ed.), Messunsicherheiten: Theorie und Praxis, Vulkan-Verlag, Essen (2000), 2nd ed.

    Google Scholar 

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Authors and Affiliations

  1. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    I. P. Zakharov & O. A. Botsyura

Authors
  1. I. P. Zakharov
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  2. O. A. Botsyura
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Correspondence to I. P. Zakharov.

Additional information

Translated from Izmeritel’naya Tekhnika, No. 4, pp. 26–29, April, 2019.

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Zakharov, I.P., Botsyura, O.A. Calculation of Expanded Uncertainty in Measurements Using the Kurtosis Method when Implementing a Bayesian Approach. Meas Tech 62, 327–331 (2019). https://doi.org/10.1007/s11018-019-01625-x

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  • DOI: https://doi.org/10.1007/s11018-019-01625-x

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