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Modelling of Measurements, System Theory and Uncertainty Evaluation

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Data Modeling for Metrology and Testing in Measurement Science

Summary

Modelling of measuring systems or processes is an indispensable prerequisite of modern uncertainty evaluation. Per se, any modelling remains imperfect; it is always reduced to relevant influences, system parameters, and behaviour. Therefore, in uncertainty evaluation, it is important to consider the effects of imperfect modelling. Derived from the classical theory of signals and systems, this contribution explains the basic approaches to systematic modelling of continuous measuring systems. The approach used is based on the cause–effect analysis and a subsequent design of the model of the measurement by means of standardised components. Emphasis is put on modelling of nonlinear and also time-variant systems and, consequently, on the effects of disregarding nonlinearities and time-variant (dynamic) behaviour. The chapter demonstrates that, based on carefully analysing and understanding the measurement, it is possible to reach proper modelling of measurements and one may sufficiently describe the relevant effects of imperfect modelling.

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Authors and Affiliations

  1. Physikalisch-Technische Bundesanstalt, Bundesallee 100, Braunschweig, Germany D-38116

    Klaus-D. Sommer

Authors
  1. Klaus-D. Sommer
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Correspondence to Klaus-D. Sommer .

Editor information

Editors and Affiliations

  1. Metrologica (INRIM), Divisione Termodinamica, Istituto Nazionale di Ricerca, Strada delle Cacce 73, Torino, 10135, Italy

    Franco Pavese

  2. MSC , Module 13 , National Physics Laboratory , Hampton Road, Teddington, Middlesex, TW11 0LW, United Kingdom

    Alistair B. Forbes

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© 2009 Birkhäuser Boston

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Sommer, KD. (2009). Modelling of Measurements, System Theory and Uncertainty Evaluation. In: Pavese, F., Forbes, A. (eds) Data Modeling for Metrology and Testing in Measurement Science. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4804-6_9

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