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Bayesian analysis of a flow meter calibration problem.

Kok, G J P*; van der Veen, A M H*; Harris, P M; Smith, I M; Elster, C* (2015) Bayesian analysis of a flow meter calibration problem. Metrologia, 52 (2). pp. 392-399.

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A turbine flow meter indicates the volume of fluid flowing through the device per unit of time. Such a flow meter is commonly calibrated at a few known flow rates over its measurement range, and in daily practice a calibration curve is fitted to calibration data using an ordinary least squares approach. This approach does not consider prior knowledge that may exist about the flow meter. A Bayesian analysis enables prior knowledge in the form of a prior distribution to be taken into account. A Bayesian inference results in a posterior distribution for the unknown parameters of the calibration curve that may be seen as the most comprehensive uncertainty analysis about these unknowns. This paper investigates for a flow meter calibration problem the influence of prior knowledge on values of the calibration curve and their associated uncertainties. It presents the results of a Bayesian analysis and compares them to those obtained by an ordinary least squares approach.

Item Type: Article
Subjects: Mathematics and Scientific Computing
Mathematics and Scientific Computing > Measurement Uncertainties
Identification number/DOI: 10.1088/0026-1394/52/2/392
Last Modified: 02 Feb 2018 13:13
URI: http://eprintspublications.npl.co.uk/id/eprint/6634

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