Examples of measurement uncertainty evaluations in accordance with the revised GUM

2016 Joint IMEKO TC1-TC7-TC13 Symposium: Metrology Across the Sciences: Wishful Thinking?

Runje, B.^1 ; Horvatic, A.^1,3 ; Alar, V.^1 ; Medic, S.^2 ; Bosnjakovic, A.^3

University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Ivana Lucica 1, Zagreb

10000, Croatia^1

Karlovac University of Applied Science, Trg J.J.Strossmayera 9, Karlovac

47000, Croatia^2

Institute of Metrology of Bosnia and Herzegovina, Augusta Brauna 2, Sarajevo

71000, Bosnia and Herzegovina^3

关键词: Asymmetric distribution;    Bayesian approaches;    Coverage intervals;    Guide to the expression of uncertainty in measurements;    Measurement uncertainty;    Propagation of distributions;    Propagation of uncertainties;    Standard uncertainty;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/772/1/012008/pdf
DOI  :  10.1088/1742-6596/772/1/012008

来源: IOP

【 摘 要 】

The paper presents examples of the evaluation of uncertainty components in accordance with the current and revised Guide to the expression of uncertainty in measurement (GUM). In accordance with the proposed revision of the GUM a Bayesian approach was conducted for both type A and type B evaluations.The law of propagation of uncertainty (LPU) and the law of propagation of distribution applied through the Monte Carlo method, (MCM) were used to evaluate associated standard uncertainties, expanded uncertainties and coverage intervals. Furthermore, the influence of the non-Gaussian dominant input quantity and asymmetric distribution of the output quantity y on the evaluation of measurement uncertainty was analyzed. In the case when the probabilistically coverage interval is not symmetric, the coverage interval for the probability P is estimated from the experimental probability density function using the Monte Carlo method. Key highlights of the proposed revision of the GUM were analyzed through a set of examples.