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Appl. Sci. 2016, 6(7), 190; doi:10.3390/app6070190

A Model to Determinate the Influence of Probability Density Functions (PDFs) of Input Quantities in Measurements

Dpto. de Ingeniería Mecánica, Química y Diseño Industrial, ETS de Ingeniería y Diseño Industrial, Universidad Politécnica de Madrid, 28012 Madrid, Spain
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Author to whom correspondence should be addressed.
Academic Editor: Kuang-Cha Fan
Received: 18 April 2016 / Revised: 9 June 2016 / Accepted: 21 June 2016 / Published: 28 June 2016
(This article belongs to the Special Issue Design and Applications of Coordinate Measuring Machines)
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Abstract

A method for analysing the effect of different hypotheses about the type of the input quantities distributions of a measurement model is presented here so that the developed algorithms can be simplified. As an example, a model of indirect measurements with optical coordinate measurement machine was employed to evaluate these different hypotheses. As a result of the different experiments, the assumption that the different variables of the model can be modelled as normal distributions is proved. View Full-Text
Keywords: coordinate metrology; Monte Carlo method; uncertainty; copulas theory; metrological traceability coordinate metrology; Monte Carlo method; uncertainty; copulas theory; metrological traceability
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MDPI and ACS Style

Caja, J.; Maresca, P.; Gómez, E. A Model to Determinate the Influence of Probability Density Functions (PDFs) of Input Quantities in Measurements. Appl. Sci. 2016, 6, 190.

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