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Development of a virtual metrological CT for numerical measurement uncertainty determination using aRTist 2

Monte-Carlo based numerical measurement uncertainty determination for CT measurements according to GUM supplement 1
  • Florian Wohlgemuth

    Since 2017, Florian Wohlgemuth has been a research associate at the Institute of Manufacturing Metrology in the X-ray computed tomography group. His main fields of research are metrological structural resolution and realistic simulations of CT measurements.

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    , Andreas Michael Müller

    Since 2016, Andreas Müller has been a research associate at the Institute of Manufacturing Metrology in the photogrammetry group. His main fields of research are computer vision algorithms and measurement uncertainty analysis.

    and Tino Hausotte

    Tino Hausotte has been professor and head of the Institute of Manufacturing Metrology at the Friedrich-Alexander-University Erlangen-Nuremberg since 2011. Under his management, the institute specialises on research about the topics X-ray computed tomography, surface and coordinate metrology, micro- and nanometrology, photogrammetry and measurement uncertainty evaluation.

Published/Copyright: July 4, 2018

Abstract

The development of a virtual metrological CT for numerical measurement uncertainty determination at the Institute of Manufacturing Metrology (Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Germany) using the software aRTist 2 by the BAM German Federal Institute for Materials Research and Testing is described. The virtual metrological CT uses a Monte-Carlo approach for numerical measurement uncertainty determination. Results demonstrating that numerical uncertainty determination according to GUM Supplement 1 and in accordance with uncertainty determination according to guideline VDI/VDE 2630 Part 2.1 is possible for selected measurement tasks are presented.

Zusammenfassung

Die Entwicklung eines virtuellen metrologischen CTs (VMCT) zur numerischen Messunsicherheitsbestimmung am Lehrstuhl für Fertigungsmesstechnik der Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) wird beschrieben. Das VMCT basiert auf der Software aRTist 2 der Bundesanstalt für Materialforschung und -prüfung. Das virtuelle metrologische CT benutzt einen Monte-Carlo-Ansatz zur numerischen Messunsicherheitsermittlung. Ergebnisse, die für ausgewählte Messaufgaben die Möglichkeit einer numerischen Messunsicherheitsbestimmung nach GUM Supplement 1 und in Übereinstimmung mit nach der Richtlinie VDI/VDE 2630 Blatt 2.1 bestimmten Messunsicherheiten demonstrieren, werden vorgestellt.

Award Identifier / Grant number: IND59 Microparts

Funding statement: The developments presented in this article were partly financed by the EURAMET EMRP project IND59 Microparts.

About the authors

Florian Wohlgemuth

Since 2017, Florian Wohlgemuth has been a research associate at the Institute of Manufacturing Metrology in the X-ray computed tomography group. His main fields of research are metrological structural resolution and realistic simulations of CT measurements.

Andreas Michael Müller

Since 2016, Andreas Müller has been a research associate at the Institute of Manufacturing Metrology in the photogrammetry group. His main fields of research are computer vision algorithms and measurement uncertainty analysis.

Tino Hausotte

Tino Hausotte has been professor and head of the Institute of Manufacturing Metrology at the Friedrich-Alexander-University Erlangen-Nuremberg since 2011. Under his management, the institute specialises on research about the topics X-ray computed tomography, surface and coordinate metrology, micro- and nanometrology, photogrammetry and measurement uncertainty evaluation.

Acknowledgment

The developments benefitted from thesis works by dedicated students who are listed as authors of the relevant publications of the institute quoted in the bibliography. The Division 8.3 (Radiological Methods) at the BAM German Federal Institute for Materials Research and Testing which developed aRTist 2 not only supported the developments by providing a modified version of aRTist 2, but was also very supportive in providing information and through helpful discussions.

References

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Received: 2018-04-19
Accepted: 2018-06-18
Published Online: 2018-07-04
Published in Print: 2018-12-19

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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