Spot size and detector unsharpness determination for numerical measurement uncertainty determination

Orgeldinger C, Wohlgemuth F, Müller A, Hausotte T (2019)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2019

Publisher: e-Journal of Nondestructive Testing

Event location: Padova

URI: http://www.ndt.net/iCT2019

Open Access Link: https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_12.pdf

Abstract

As the experimental measurement uncertainty evaluation for comp uted tomography is currently an expensive and time-consuming task, numerical uncertainty evaluation (according to GUM Supplement 1) using a virtual CT is a promising alternative. For this digital twin to simulate accurate measure ment results, the virtual CT system needs to be modelled as reallistically as possible using adequate input parameters for the simulation. This paper describes a method for the separateddetermination of two significant input parameters: focal spot size and detector unsharpness. The method is tested using a widerange of measurement parameters on a Zeiss Metrotom 1500 with different test specimen. It could be shown that the method yields reasonable results for most parameters. In addition, the re is a dependence of the focal spot size on the ratio of tube voltage and tube current at constant power. This contradicts the wide-spread rule of thumb that the spot size depends on the tube power only. Indications of a changing focal spot shape at high powers could be detected.

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How to cite

APA:

Orgeldinger, C., Wohlgemuth, F., Müller, A., & Hausotte, T. (2019). Spot size and detector unsharpness determination for numerical measurement uncertainty determination. In Proceedings of the 9th Conference on Industrial Computed Tomography. Padova, IT: e-Journal of Nondestructive Testing.

MLA:

Orgeldinger, Christian, et al. "Spot size and detector unsharpness determination for numerical measurement uncertainty determination." Proceedings of the 9th Conference on Industrial Computed Tomography, Padova e-Journal of Nondestructive Testing, 2019.

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