Articles | Volume 11, issue 1
https://doi.org/10.5194/jsss-11-75-2022
https://doi.org/10.5194/jsss-11-75-2022
Regular research article
 | 
09 Mar 2022
Regular research article |  | 09 Mar 2022

Structure of digital metrological twins as software for uncertainty estimation

Ivan Poroskun, Christian Rothleitner, and Daniel Heißelmann

Related authors

Six-degree-of-freedom pose estimation with µm/µrad accuracy based on laser multilateration
Jan Nitsche, Matthias Franke, Nils Haverkamp, and Daniel Heißelmann
J. Sens. Sens. Syst., 10, 19–24, https://doi.org/10.5194/jsss-10-19-2021,https://doi.org/10.5194/jsss-10-19-2021, 2021
Short summary

Related subject area

Measurement theory, uncertainty and modeling of measurements: Measurement uncertainty
Metrological assessment of a robotic total station for use in post-earthquake emergency conditions
Giulio D'Emilia and Emanuela Natale
J. Sens. Sens. Syst., 12, 187–195, https://doi.org/10.5194/jsss-12-187-2023,https://doi.org/10.5194/jsss-12-187-2023, 2023
Short summary
Approximate sequential Bayesian filtering to estimate 222Rn emanation from 226Ra sources using spectral time series
Florian Mertes, Stefan Röttger, and Annette Röttger
J. Sens. Sens. Syst., 12, 147–161, https://doi.org/10.5194/jsss-12-147-2023,https://doi.org/10.5194/jsss-12-147-2023, 2023
Short summary
Evaluation of precision, accuracy and threshold for the design of vibrotactile feedback in eye tracking applications
Anke Fischer, Thomas M. Wendt, Lukas Stiglmeier, Philipp Gawron, and Kristof Van Laerhoven
J. Sens. Sens. Syst., 12, 103–109, https://doi.org/10.5194/jsss-12-103-2023,https://doi.org/10.5194/jsss-12-103-2023, 2023
Short summary
Influence of measurement uncertainty on machine learning results demonstrated for a smart gas sensor
Tanja Dorst, Tizian Schneider, Sascha Eichstädt, and Andreas Schütze
J. Sens. Sens. Syst., 12, 45–60, https://doi.org/10.5194/jsss-12-45-2023,https://doi.org/10.5194/jsss-12-45-2023, 2023
Short summary
Towards efficient application-dependent dimensional measurements with computed tomography: optimized reduction of measurement duration using continuous scan mode: experimental investigations
Christian Orgeldinger, Florian Wohlgemuth, Andreas Michael Müller, and Tino Hausotte
J. Sens. Sens. Syst., 11, 219–223, https://doi.org/10.5194/jsss-11-219-2022,https://doi.org/10.5194/jsss-11-219-2022, 2022
Short summary

Cited articles

Alexandrescu, A.: Modern C++ Design: Generic Programming and Design Patterns Applied, Addison-Wesley Longman Publishing Co., Inc., USA, ISBN 0-201-70431-5, 2001. a
Allard, A. and Fischer, N.: Sensitivity analysis in practice: providing an uncertainty budget when applying supplement 1 to the GUM, Metrologia, 55, 414–426, https://doi.org/10.1088/1681-7575/aabd55, 2018. a
Beck, K.: Test Driven Development. By Example (Addison-Wesley Signature), Addison-Wesley Longman, Amsterdam, ISBN 0321146530, 2002. a
Eichstädt, S., Elster, C., Härtig, F., Heißelmann, D., Kniel, K., and Wübbeler, G.: VirtMet – applications and overview, in: VirtMet 2021: 1st International Workshop on Metrology for Virtual Measuring Instruments and Digital Twins, PTB Berlin, Berlin, 2021. a, b, c, d
Forbes, A. B., Smith, I. M., Härtig, F., and Wendt, K.: Overview of EMRP joint research project NEW06 “Traceability for computationally-intensive metrology”, in: Series on Advances in Mathematics for Applied Sciences, World Scientific, 164–170, https://doi.org/10.1142/9789814678629_0019, 2015. a
Download
Short summary
The paper proposes a structure for the creation of new simulation software for uncertainty estimation. The structure was derived from the well-established VCMM. To make it easy to apply the software structure to specific projects, a supporting software library (written in C++) was created. The library provides all the components necessary to create software for uncertainty estimation. The software structure and library proposed can be used in different domains of metrology.