uncertainty estimation ; metrological digital twins ; VCMM ; VPB ; vmlib ; Monte Carlo
Zusammenfassung
Ongoing digitalization in metrology and the ever-growing complexity of measurement systems have increased the effort required to create complex software for uncertainty estimation. To address this issue, a general structure for uncertainty estimation software will be presented in this work. The structure was derived from the Virtual Coordinate Measuring Machine (VCMM), which is a well-established tool for uncertainty estimation in the field of coordinate metrology. To make it easy to apply the software structure to specific projects, a supporting software library was created. The library is written in a portable and extensible way using the C++ programming language. The software structure and library proposed can be used in different domains of metrology. The library provides all the components necessary for uncertainty estimation (i.e., random number generators and GUM S1-compliant routines). Only the project-specific parts of the software must be developed by potential users. To verify the usability of the software structure and the library, a Virtual Planck-Balance, which is the digital metrological twin of a Kibble balance, is currently being developed.
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Open Access Gold
Rechteinformation
CC BY 4.0 ; Creative Commons Attribution 4.0 License
Themenbereich der Metrologie
Länge, dimensionelle Metrologie
Forschungsprojekt
VirtMet
Förderinformationen (1)
Titel der Förderung: VirtMet
Zitierung
Poroskun, I., Rothleitner, C., & Heißelmann, D. (2022). Structure of digital metrological twins as software for uncertainty estimation. Journal of Sensors and Sensor Systems, 11(1), 75–82. https://doi.org/10.5194/jsss-11-75-2022
