Development of a reconstruction quality metric for optical three-dimensional measurement systems in use for hot-state measurement object

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Quentin, L.; Beermann, r.; Kästner, M.; Reithmeier, E.: Development of a reconstruction quality metric for optical three-dimensional measurement systems in use for hot-state measurement object. In: Optical Engineering 59 (2020), Nr. 6, 064103. DOI: https://doi.org/10.1117/1.OE.59.6.064103

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10316

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Abstract: 
Optical three-dimensional (3-D) geometry measurements are state of the art when it comes to contactless quality control and maintenance of the shape of technical components that exclude tactile measurements due to filigree or internal structures. Optical inspection methods are also characterized by a fast and high-resolution 3-D inspection of complex geometries. And due to their noncontact principle, they can carry out measurements in places that would otherwise not be accessible due to harsh environmental conditions or specimens such as hot forged parts. However, there are currently no methods to estimate the reconstruction quality for the optical 3-D geometry measurements of hot objects. The mainly used geometric measurement standards cannot be used for the characterization of hot measurements since the calibrated geometrical values are not transferable to high temperatures. For the development of such a metric, we present the fundamentals of the concepts and algorithms for an estimation of the reconstruction quality are presented and evaluated using a two-dimensional simulation model. The generated findings were applied to the 3-D geometry measurement of a hot object in a laboratory environment. The results are compared with general state-of-the-art reconstruction quality metrics.
License of this version: CC BY 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
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1 image of flag of Germany Germany 16 50.00%
2 image of flag of United States United States 7 21.88%
3 image of flag of China China 3 9.38%
4 image of flag of Austria Austria 3 9.38%
5 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 3.12%
6 image of flag of Israel Israel 1 3.12%
7 image of flag of United Kingdom United Kingdom 1 3.12%

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