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3D scan contour de-featuring for improved measurement accuracy – a case study for a small turbine guide vane component

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Języki publikacji
EN
Abstrakty
EN
3D scanning measurements are gaining popularity every year. Quick inspections on already captured point clouds are easy to prepare with the use of modern software and machine learning. To achieve repeatability and accuracy, some surface and measurement issues should be considered and resolved before the inspection. Large numbers of manufacturing scans are not intended for manual correction. This article is a case study of a small surface inspection of a turbine guide vane based on 3D scans. Small surface errors cannot be neglected as their incorrect inspection can result in serious faults in the final product. Contour recognition and deletion seem to be a rational method for making a scan inspection with the same level of accuracy as we have now for CMM machines. The main reason why a scan inspection can be difficult is that the CAD source model can be slightly different from the inspected part. Not all details are always included, and small chamfers and blends can be added during the production process, based on manufacturing standards and best practices. This problem does not occur during a CMM (coordinate measuring machine) inspection, but it may occur in a general 3D scanning inspection.
Rocznik
Strony
art. no. e138815
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
  • General Electric Company, al Krakowska 110-114, 02-265 Warsaw, Poland
  • Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland
Bibliografia
  • [1] W. Cuypers, N. Van Gestel, A. Voet, J.P. Kruth, J. Mingneau, and P. Bleys, “Optical measurement techniques for mobile and largescale dimensional metrology”, Opt. Lasers Eng., vol. 47, nol. 3–4, pp. 292–300, 2009, doi: 10.1016/j.optlaseng.2008.03.013.
  • [2] An International Standard: Geometrical product specifications (GPS) – Acceptance and reverification tests for coordinate measuring machines (CMM), ISO 10360:2011, 2011.
  • [3] B.S. Marció, P. Nienhaysen, D. Habor, and R.C.C. Flesch, “Quality assessment and deviation analysis of three-dimensional geometrical characterization of a metal pipeline by pulse-echo ultrasonic and laser scanning techniques”, Meas. J. Int. Meas. Confed., vol. 145, pp. 30–37, 2019, doi: 10.1016/j.measurement.2019.05.084.
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  • [12] Y. Zhong, “Intrinsic shape signatures: A shape descriptor for 3D object recognition”, 2009 IEEE 12th Int. Conf. Comput. Vis. Work. ICCV Work, 2009, pp. 689–696, 2009, doi: 10.1109/ICCVW.2009.5457637.
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  • [14] D. Fehr,W. J. Beksi, D. Zermas, and N. Papanikolopoulos, “Covariance based point cloud descriptors for object detection and recognition”, Comput. Vis. Image Underst., vol. 142, pp. 80–93, 2016, doi: 10.1016/j.cviu.2015.06.008.
  • [15] T. Hackel, J. D. Wegner, and K. Schindler, “Contour detection in unstructured 3D point clouds”, Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., 2016, pp. 1610–1618, doi: 10.1109/CVPR.2016.178.
  • [16] H. Wang, C. Wang, H. Luo, P. Li, Y. Chen, and J. Li, “3-D Point Cloud Object Detection Based on Supervoxel Neighborhood With Hough Forest Framework,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 8, no. 4, pp. 1570–1581, 2015, doi: 10.1109/JSTARS.2015.2394803.
  • [17] Geomagic Design X Overview, 2020. [Online]. Available: https://www.3dsystems.com/sites/default/files/2019-11/3d-systems-designx-en-letter-web-2019-10-25.pdf.
  • [18] Geomagic Wrap Overview, 2020. [Online]. Available: https://www.3dsystems.com/sites/default/files/2019-11/3d-systems-wrap-en-letter-web-2019-11-01.pdf.
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  • [21] M. Centin and A. Signoroni, “RameshCleaner: conservative fixing of triangular meshes”, STAG Smart Tools Apps Graph. – Eurographics Italian Chapter Conference, 2015, doi: 10.2312/stag.20151300.
  • [22] L. Di Angelo, P. Di Stefano, and A. E. Morabito, “Fillets, rounds, grooves and sharp edges segmentation from 3D scanned surfaces”, CAD Comput. Aided Des., vol. 110, pp. 78–91, 2019, doi: 10.1016/j.cad.2019.01.003.
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  • [25] Y. Tao, Y. Q. Wang, H. B. Liu, and M. Li, “On-line threedimensional point cloud data extraction method for scantracking measurement of irregular surface using bi-Akima spline”, Meas. J. Int. Meas. Confed., vol. 92, pp. 382–390, 2016, doi: 10.1016/j.measurement.2016.06.008.
  • [26] G. Palma, P. Cignoni, T. Boubekeur, and R. Scopigno, “Detection of Geometric Temporal Changes in Point Clouds”, Comput. Graph. Forum, vol. 35, nol. 6, pp. 33–45, 2016, doi: 10.1111/cgf.12730.
  • [27] Computer workstation used by authors:, “Intel(R) Xeon(R) CPU E5-1650 v4 @ 3.60GHz”, 2020.
  • [28] A. Jagannathan and E. L. Miller, “Three-dimensional surface mesh segmentation using curvedness-based region growing approach”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 12, pp. 2195–2204, 2007, doi: 10.1109/TPAMI.2007.1125.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e8167cea-b3f4-4a4d-b84d-1ceb52cfcc1f
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