Details
Title
3D scan contour de-featuring for improved measurement accuracy – a case study for a small turbine guide vane componentJournal title
Bulletin of the Polish Academy of Sciences Technical SciencesYearbook
2021Volume
69Issue
5Authors
Affiliation
Jamontt, Marcin : General Electric Company, al Krakowska 110-114, 02-265 Warsaw, Poland ; Pyrzanowski, Paweł : Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, PolandKeywords
3d scan ; flatness ; turbine guide vane ; small surfaces ; point clouds ; contour recognition ; contour de-featuringDivisions of PAS
Nauki TechniczneCoverage
e138815Bibliography
- W. Cuypers, N. Van Gestel, A. Voet, J. P. Kruth, J. Mingneau, and P. Bleys, “Optical measurement techniques for mobile and large-scale dimensional metrology,” Opt. Lasers Eng., vol. 47, no. 3–4, pp. 292–300, 2009, doi: 10.1016/j.optlaseng.2008.03.013.
- An International Standard: Geometrical product specifications (GPS) – Acceptance and reverification tests for coordinate measuring machines (CMM), ISO 10360:2011, 2011.
- 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.
- GOM Inspect Brochure, 2019. [Online]. Available: https://www.3dteam.pl/wp-content/uploads/2020/11/GOM-Software.pdf.
- Geomagic Control X Overview, 2020. [Online]. Available: https://www.3dsystems.com/sites/default/files/2020-10/3d-systems-controlx- en-letter-web-2020-10-07.pdf.
- An International Standard: Dimensioning and Tolerancing, ASME Y14.5, 2019.
- An International Standard: Geometrical tolerancing, ISO 1101, 2017.
- J. Fan, L. Ma, A. Sun, and Z. Zou, “An approach for extracting curve profiles based on scanned point cloud,” Meas. J. Int. Meas. Confed., vol. 149, p. 107023, 2020, doi: 10.1016/j.measurement.2019.107023.
- L. Li, M. Sung, A. Dubrovina, L. Yi, and L. J. Guibas, “Supervised fitting of geometric primitives to 3D point clouds,” Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., 2019, pp. 2647–2655, doi: 10.1109/CVPR.2019.00276.
- Y. Liu and Y. Xiong, “Automatic segmentation of unorganized noisy point clouds based on the Gaussian map,” CAD Comput. Aided Des., vol. 40, no. 5, pp. 576–594, 2008, doi: 10.1016/j.cad.2008.02.004.
- Y. Yang, H. Fang, Y. Fang, and S. Shi, “Three-dimensional point cloud data subtle feature extraction algorithm for laser scanning measurement of large-scale irregular surface in reverse engineering,” Meas. J. Int. Meas. Confed., vol. 151, p. 107220, 2020, doi: 10.1016/j. measurement.2019.107220.
- 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.
- M. Pauly, R. Keiser, and M. Gross, “Multi-scale Feature Extraction on Point-Sampled Surfaces,” vol. 22, no. 3, pp. 281–289, 2003.
- 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.
- 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.
- 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.
- 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.
- 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.
- The StL Format, 2021. [Online]. Available: http://www.fabbers.com/tech/STL_Format.
- G. Lavoué, F. Dupont, and A. Baskurt, “A new CAD mesh segmentation method, based on curvature tensor analysis,” CAD Comput. Aided Des., vol. 37, no. 10, pp. 975–987, 2005, doi: 10.1016/j.cad.2004.09.001.
- 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.
- 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.
- L. Di Angelo and P. Di Stefano, “Geometric segmentation of 3D scanned surfaces,” CAD Comput. Aided Des., vol. 62, pp. 44–56, 2015, doi: 10.1016/j.cad.2014.09.006.
- Q. Li, X. Huang, S. Li, and Z. Deng, “Feature extraction from point clouds for rigid aircraft part inspection using an improved Harris algorithm,” Meas. Sci. Technol., vol. 29, no. 11, 2018, doi: 10.1088/1361-6501/aadff6.
- Y. Tao, Y. Q. Wang, H. B. Liu, and M. Li, “On-line three-dimensional point cloud data extraction method for scan-tracking 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.
- G. Palma, P. Cignoni, T. Boubekeur, and R. Scopigno, “Detection of Geometric Temporal Changes in Point Clouds,” Comput. Graph. Forum, vol. 35, no. 6, pp. 33–45, 2016, doi: 10.1111/cgf.12730.
- Computer workstation used by authors: “Intel(R) Xeon(R) CPU E5‒1650 v4 @ 3.60GHz.” 2020.
- 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.