More efficient techniques are requested by the industry for quality control of complex industrial components that frequently include non-accessible features and multi-material parts. X-ray computed tomography is capable of carrying out a wide variety of analyses, simultaneously and without the need to destroy the work-piece; this makes it the only measurement technology available for some complex measurement tasks. However, multiple factors influence the measurement accuracy, being the surface extraction process among the main ones, especially in multi-material parts. In this work, surface extraction procedures based on gradient detection are applied to a multi-material gap reference standard and the results are analysed in comparison to those previously obtained applying procedures based on threshold. A discussion of the used algorithms and the obtained results is presented.

Surface extraction procedures based on gradient algorithm for X-ray computed tomography measurement of multi-material parts

Zanini F.;Carmignato S.
2019

Abstract

More efficient techniques are requested by the industry for quality control of complex industrial components that frequently include non-accessible features and multi-material parts. X-ray computed tomography is capable of carrying out a wide variety of analyses, simultaneously and without the need to destroy the work-piece; this makes it the only measurement technology available for some complex measurement tasks. However, multiple factors influence the measurement accuracy, being the surface extraction process among the main ones, especially in multi-material parts. In this work, surface extraction procedures based on gradient detection are applied to a multi-material gap reference standard and the results are analysed in comparison to those previously obtained applying procedures based on threshold. A discussion of the used algorithms and the obtained results is presented.
2019
European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3317083
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