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Marco Wolf, Martin Müller, Matthias Rösslein

Modelling and Simulation of Complex Measurement Settings using the Monte-Carlo Method

Keywords: measurement uncertainty, Modelling, Simulation, Monte-Carlo method, ISO-GUM

Measurement uncertainty evaluation gains more importance, because one can compare results only with additional information about the quality of the measurement. The first supplement to the GUM introduces the Monte-Carlo method to calculate the measurement uncertainty. It is not subject to the restrictions of the uncertainty propagation, but uses the full information of arbitrary input distributions and does not need to assume that the model can be linearized. The software MUSE utilizes the Monte-Carlo method and provides support to the user modelling complex measurement setups. We introduce basic models which are used for modelling measurements. The process itself gets modularized for a better overview and structure.

tm – Technisches Messen, Oldenbourg Wissenschaftsverlag

Print ISSN: 0171-8096
Volume: 74, 10/2007
Pages: 485 - 493

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