Reprint

Measurement Uncertainty

Edited by
May 2023
202 pages
  • ISBN978-3-0365-6608-5 (Hardback)
  • ISBN978-3-0365-6609-2 (PDF)

This book is a reprint of the Special Issue Measurement Uncertainty that was published in

Engineering
Physical Sciences
Summary

This reprint focuses on a very important topic in metrology, which is represent by measurement uncertainty. Any good metrologist or scientist in engineering knows that no measurement makes sense without an associated uncertainty value: without an uncertainty value, no decision can be taken; no comparisons can be made; no conformity can be assessed. Any decision, comparison or conformity assessment made without considering the measurement uncertainty affecting the measurement value is completely useless and meaningless. Stated that, it becomes very clear that uncertainty in measurement plays indeed a very important rule in our everyday life. This is the reason why there is a great need to have a fruitful academic and scientific discussion on this topic.

We have been speaking about measurement uncertainty for less than 30 years, since the concept of “measurement uncertainty” has been introduced in 1995 by the “Guide to the expression of uncertainty in measurement” (GUM). Thirty years seems to be many, but still the concept of measurement uncertainty has not been spread worldwide and the GUM is a document that is not known everywhere. On the other hand, this document should be considered not only in academic scenario, but also in any technical and industrial scenario, where it is pivotal to know the meaning of measurement uncertainty, identify the uncertainty contributions and know how these contributions affect the final measurement result.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
random-fuzzy variables; Kalman filter; systematic uncertainty contributions; styling; measurement uncertainty; random contribution; systematic contribution; probability density functions; possibility distributions; random-fuzzy variables; t-norms; measuring bridge; calibration; non-conventional instrument transformer; sampled values; digital output; synchronization; digitalization; measurement uncertainty; metrological traceability; key comparison; digital calibration certificate; uncertain number; metrology; nuclear data; data evaluation; systematic distortion factor; unrecognized source of uncertainties; digital calibration certificate; DCC; machine-readable; data communication; uncertainty; Monte Carlo method; MCM; measurement uncertainty; guide to the expression of uncertainty in measurement; measurement modelling; uncertainty propagation; metrological traceability; uncertain number; information fusion; possibility theory; information fusion system design; digital signal processing; spectral resolution; frequency domain analysis; frequency–domain interpolation; frequency uncertainty; uncertainty assessment; three-dimensional point clouds; ISO 15530; data-driven metrology; model-based definition; virtual twin; bayesian modeling; Hamiltonian Monte Carlo; diagnostic uncertainty; expert opinion data; verbal probability; n/a; Tsallis q-Gaussian distribution; characteristic function; numerical inversion; linear measurement model; measurement uncertainty