Measurement uncertainty assessment for virtual assembly-Reference-Cited by-同舟云学术

Measurement uncertainty assessment for virtual assembly

Published:2021-04-22 Issue:1 Volume:10 Page:101-108
ISSN:2194-878X
Container-title:Journal of Sensors and Sensor Systems
language:en
Short-container-title:J. Sens. Sens. Syst.

Author:

Kaufmann Manuel,Effenberger Ira,Huber Marco F.

Abstract

Abstract. Virtual assembly (VA) is a method for datum definition and quality prediction of assemblies considering local form deviations of relevant geometries. Point clouds of measured objects are registered in order to recreate the objects' hypothetical physical assembly state. By VA, the geometrical verification becomes more accurate and, thus, increasingly function oriented. The VA algorithm is a nonlinear, constrained derivate of the Gaussian best fit algorithm, where outlier points strongly influence the registration result. In order to assess the robustness of the developed algorithm, the propagation of measurement uncertainties through the nonlinear transformation due to VA is studied. The work compares selected propagation methods distinguished from their levels of abstraction. The results reveal larger propagated uncertainties by VA compared to the unconstrained Gaussian best fit.

Publisher

Copernicus GmbH

Subject

Electrical and Electronic Engineering,Instrumentation

Link

https://jsss.copernicus.org/articles/10/101/2021/jsss-10-101-2021.pdf

Reference15 articles.

1. Chong, C.-Y. and Mori, S.: Convex Combination and Covariance Intersection Algorithms in Distributed Fusion, in: 4th Inter. Conf. on information fusion, 7–10 August 2001, Montreal, Canada, WeA2-11-18, 2001.

2. Deutsches Institut für Normung e.V.: Geometrische Produktspezifikation (GPS) – Geometrische Tolerierung: Bezüge und Bezugssysteme (ISO 5459:2011); Deutsche Fassung EN ISO 5459:2011, 17.040.30, Beuth, Berlin, 99 pp., 2011.

3. Deutsches Institut für Normung e.V.: Geometrische Produktspezifikation (GPS) – Geometrische Tolerierung: Bezüge und Bezugssysteme, 01.100.20; 17.040.10, Beuth, Berlin, 236 pp., 2017.

4. Fleßner, M., Müller, A., Götz, D., Helmecke, E., and Hausotte, T.: Assessment of the single point uncertainty of dimensional CT measurements, in: 6th Conference on Industrial Computed Tomography, edited by: Diederichs, R., 6th Conference on Industrial Computed Tomography (iCT) 2016, Wels, Austria, 9–12 February 2016, available at: https://www.ndt.net/article/ctc2016/papers/ICT2016_paper_id48.pdf (last access: 18 April 2021), 2016.

5. Galovska, M., Petz, M., and Tutsch, R.: Unsicherheit bei der Datenfusion dimensioneller Messungen, Tech. Mess., 79, 238–245, https://doi.org/10.1524/teme.2012.0227, 2012.

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