Evaluation of expanded uncertainty at glass thermometer calibration

Igor Zaharov,Anastasiia Brikman,Oleksandr Zaharov,Olesia Botsiura

doi:10.24027/2306-7039.4.2019.195953

Abstract

A method for calibrating a glass thermometer is investigated and a procedure for measurement uncertainty evaluation based on the kurtosis method is developed. The correlation between the indication of the reference and calibrated thermometers at uncertainty evaluation is taken into account. The effectiveness of the reduction method applying in calculating the uncertainty of correlated measurements is demonstrated. Uncertainty budgets have been drawn up, which can be used as the basis for developing software tools to automate the uncertainty evaluation. A real example of the measurement uncertainty evaluation at glass thermometer calibration is considered. It is shown that taking into account the correlation between the measurement results of the calibrated and reference thermometers allows to reduce the values of the combined and expanded measurement uncertainty by almost 1.5 times. The coincidence of the results obtained by the proposed method and the Monte Carlo method is shown.

Highlights

Glass thermometers are widespread in laboratory and industrial practice due to the high accuracy, cheapness, ease of use [1]
Since the measurements by both thermometers are carried out simultaneously under the same conditions, the instability of the temperature of the thermostat causes a statistical interrelation between their indications, which must be taken into account when developing the procedure of measurement uncertainty evaluation
The article considers the procedure for measurement uncertainty evaluation based on the Bayesian approach [4], which implements the kurtosis method proposed by the authors [8]

Summary

Introduction

Glass thermometers are widespread in laboratory and industrial practice due to the high accuracy, cheapness, ease of use [1]. Like other measuring instruments, need periodic calibration. In this case, in accordance with the requirements of the standard ISO/ IEC 17025 [2], it is necessary to evaluate the measurement uncertainty. Since the measurements by both thermometers are carried out simultaneously under the same conditions, the instability of the temperature of the thermostat causes a statistical interrelation (correlation) between their indications, which must be taken into account when developing the procedure of measurement uncertainty evaluation. Since [6] is based on the Bayesian approach to the measurement uncertainty evaluation, this approach should be used in the revised Guide (NewGUM). The article considers the procedure for measurement uncertainty evaluation based on the Bayesian approach [4], which implements the kurtosis method proposed by the authors [8]. Where TT is the limit of temperature unevenness in the thermostat

Standard uncertainty evaluation of input quantities:

Calculating expanded uncertainty:

Conclusions