Utilization of single point uncertainties for geometry element regression analysis in dimensional X-ray computed tomography

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(Konferenzbeitrag)


Details zur Publikation

Autorinnen und Autoren: Müller A, Hausotte T
Verlag: e-Journal of Nondestructive Testing
Jahr der Veröffentlichung: 2019
ISSN: 1435-4934
Sprache: Englisch


Abstract

The work outlined in this paper is examining ways to incorporate previously determined single point uncertainties of computed tomography (CT) measurements into a suitable regression analysis in order to evaluate standard geometry elements. The goal is to determine and reduce the measurement uncertainty for the specific parameters of a geometry element by using selective point rejections based on their single point uncertainty. Examinations show that the systematic error as well as the associated uncertainties can be reduced in certain scenarios compared to the statistical interpretations of repeated (simulated) measurements without considering the single point uncertainty. Nonetheless, these results still need to be verified for different data series and measurement setups.


FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Hausotte, Tino Prof. Dr.-Ing.
Lehrstuhl für Fertigungsmesstechnik
Müller, Andreas
Lehrstuhl für Fertigungsmesstechnik


Zitierweisen

APA:
Müller, A., & Hausotte, T. (2019). Utilization of single point uncertainties for geometry element regression analysis in dimensional X-ray computed tomography. In Proceedings of the 9th Conference on Industrial Computed Tomography. ​Centro Culturale Altinate San Gaetano, Padova, IT: e-Journal of Nondestructive Testing.

MLA:
Müller, Andreas, and Tino Hausotte. "Utilization of single point uncertainties for geometry element regression analysis in dimensional X-ray computed tomography." Proceedings of the 9th Conference on Industrial Computed Tomography, ​Centro Culturale Altinate San Gaetano, Padova e-Journal of Nondestructive Testing, 2019.

BibTeX: 

Zuletzt aktualisiert 2019-16-04 um 04:23