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Deformation Analysis of a Composite Bridge during Proof Loading Using Point Cloud Processing

Abstract

Remote sensing in structural diagnostics has recently been gaining attention. These techniques allow the creation of three-dimensional projections of the measured objects, and are relatively easy to use. One of the most popular branches of remote sensing is terrestrial laser scanning. Laser scanners are fast and efficient, gathering up to one million points per second. However, the weakness of terrestrial laser scanning is the troublesome processing of point clouds. Currently, many studies deal with the subject of point cloud processing in various areas, but it seems that there are not many clear procedures that we can use in practice, which indicates that point cloud processing is one of the biggest challenges of this issue. To tackle that challenge we propose a general framework for studying the structural deformations of bridges. We performed an advanced object shape analysis of a composite foot-bridge, which is subject to spatial deformations during the proof loading process. The added value of this work is the comprehensive procedure for bridge evaluation, and adaptation of the spheres translation method procedure for use in bridge engineering. The aforementioned method is accurate for the study of structural element deformation under monotonic load. The study also includes a comparative analysis between results from the spheres translation method, a total station, and a deflectometer. The results are characterized by a high degree of convergence and reveal the highly complex state of deformation more clearly than can be concluded from other measurement methods, proving that laser scanning is a good method for examining bridge structures with several competitive advantages over mainstream measurement methods.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
SENSORS no. 18, edition 12, pages 4332 - 4350,
ISSN: 1424-8220
Language:
English
Publication year:
2018
Bibliographic description:
Ziółkowski P., Szulwic J., Miśkiewicz M.: Deformation Analysis of a Composite Bridge during Proof Loading Using Point Cloud Processing// SENSORS. -Vol. 18, iss. 12 (2018), s.4332-4350
DOI:
Digital Object Identifier (open in new tab) 10.3390/s18124332
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  1. Riveiro, B.; Morer, P.; Arias, P.; De Arteaga, I. Terrestrial laser scanning and limit analysis of masonry arch bridges. Constr. Build. Mater. 2011, 25, 1726-1735, doi:10.1016/j.conbuildmat.2010.11.094. open in new tab
  2. Riveiro, B.; González-Jorge, H.; Varela, M.; Jauregui, D. V Validation of terrestrial laser scanning and photogrammetry techniques for the measurement of vertical underclearance and beam geometry in structural inspection of bridges. Measurement 2013, 46, 784-794, doi:10.1016/j.measurement.2012.09.018. open in new tab
  3. Xu, X.; Yang, H.; Neumann, I. Monotonic loads experiment for investigation of composite structure based on terrestrial laser scanner measurement. Compos. Struct. 2018, 183, 563-567, doi:10.1016/j.compstruct.2017.07.001. open in new tab
  4. Yang, H.; Xu, X.; Neumann, I. Deformation behavior analysis of composite structures under monotonic loads based on terrestrial laser scanning technology. Compos. Struct. 2018, 183, 594-599, doi:10.1016/j.compstruct.2017.07.011. open in new tab
  5. Xu, X.; Yang, H.; Neumann, I. Deformation monitoring of typical composite structures based on terrestrial laser scanning technology. Compos. Struct. 2018, 202, 77-81, doi:10.1016/j.compstruct.2017.11.049. open in new tab
  6. Kitratporn, N.; Takeuchi, W.; Matsumoto, K.; Nagai, K. Structure deformation measurement with terrestrial laser scanner at pathein bridge in Myanmar. J. Disaster Res. 2018, 13, 40-49, doi:10.20965/jdr.2018.p0040. open in new tab
  7. Schnabel, R.; Wahl, R.; Klein, R. Efficient RANSAC for Point-Cloud Shape Detection. Comput. Graph. Forum 2007, 26, 214-226, doi:10.1111/j.1467-8659.2007.01016.x. open in new tab
  8. Chróścielewski, J.; Miśkiewicz, M.; Pyrzowski, Ł.; Sobczyk, B.; Wilde, K. A novel sandwich footbridge-Practical application of laminated composites in bridge design and in situ measurements of static response. Compos. Part B Eng. 2017, 126, 153-161, doi:10.1016/j.compositesb.2017.06.009. open in new tab
  9. Chróścielewski, J.; Miśkiewicz, M.; Pyrzowski, Ł.; Rucka, M.; Sobczyk, B.; Wilde, K. Modal properties identification of a novel sandwich footbridge-Comparison of measured dynamic response and FEA. Compos. Part B Eng. 2018, 151, 245-255, doi:10.1016/j.compositesb.2018.06.016. open in new tab
  10. Schreiber, T. Clustering for data reduction and approximation. Comput. Graph. Geom. 1999, 1, 1-24.
  11. Floater, M.S.; Iske, A. Thinning algorithms for scattered data interpolation. BIT Numer. Math. 1998, 38, 705-720, doi:10.1007/BF02510410. open in new tab
  12. Hou, J.; Chau, L.P.; He, Y.; Chou, P.A. Sparse Representation for Colors of 3D Point cloud Via Virtual Adaptive Sampling. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, LA, USA, 5-9 March 2017; pp. 2926-2930, doi:10.1109/ICASSP.2017.7952692. open in new tab
  13. Fua, P.; Sander, P. Reconstructing Surfaces from Unstructured 3D Points. In Proceedings of the Image Understanding Workshop, San Diego, CA, USA, 26-29 January 1992; pp. 615-625.
  14. Rusu, R.B.; Marton, Z.C.; Blodow, N.; Dolha, M.; Beetz, M. Towards 3D Point cloud based object maps for household environments. Rob. Auton. Syst. 2008, 56, 927-941, doi:10.1016/j.robot.2008.08.005. open in new tab
  15. Davis, J.; Marschner, S.R.; Garr, M.; Levoy, M. Filling Holes in Complex Surfaces Using Volumetric Diffusion. In Proceedings of the 1st International Symposium on 3D Data Processing Visualization and Transmission (3DPVT 2002), Padova, Italy, 19-21 June 2002; pp. 428-441. open in new tab
  16. Boissonnat, J.-D. Geometric Structures for Three-Dimensional Shape Representation. ACM Trans. Graph. 1984, 3, 266-286, doi:10.1145/357346.357349. open in new tab
  17. Faugeras, O.D.; Hebert, M.; Mussi, P.; Boissonnat, J.D. Polyhedral approximation of 3-D objects without holes. Comput. Vis. Graph. Image Process. 1984, 25, 169-183, doi:10.1016/0734-189X(84)90101-4. open in new tab
  18. Hoppe, H.; DeRose, T.; Duchamp, T.; McDonald, J.; Stuetzle, W. Surface Reconstruction from Unorganized Points; ACM: New York, NY, USA, 1992; Volume 26, ISBN 0897914791. open in new tab
  19. Curless, B.; Levoy, M. A Volumetric Method for Building Complex Models from Range Images. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, New Orleans, LA, USA, 4-9 August 1996; pp. 303-312. open in new tab
  20. Mercat, C. Discrete Riemann surfaces and the Ising model. Commun. Math. Phys. 2001, 218, 177-216, doi:10.1007/s002200000348. open in new tab
  21. Carr, J.C.; Beatson, R.K.; Cherrie, J.B.; Mitchell, T.J.; Fright, W.R.; McCallum, B.C.; Evans, T.R. Reconstruction and Representation of 3D Objects with Radial Basis Functions. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, Los Angeles, CA, USA, 12-17 August 2001; pp. 67-76, doi:10.1145/383259.383266. open in new tab
  22. Kazhdan, M.; Hoppe, H. Screened poisson surface reconstruction. ACM Trans. Graph. 2013, 32, 29. open in new tab
  23. Liu, Y.J.; Xu, C.X.; Fan, D.; He, Y. Efficient Construction and Simplification of Delaunay Meshes. ACM Trans. Graph. 2015, 34, 13, doi:10.1145/2816795.2818076. open in new tab
  24. Boissonnat, J.-D.; Shi, K.-L.; Tournois, J.; Yvinec, M. Anisotropic Delaunay Meshes of Surfaces. ACM Trans. Graph. 2015, 34, 1-11, doi:10.1145/2721895. open in new tab
  25. Shewchuk, J.R. Delaunay Mesh Generation; Chapman and Hall/CRC: Boca Raton, FL, USA, 2012; ISBN 9781584887300. open in new tab
  26. Dey, T.K.; Zho, W. Approximate medial axis as a Voronoi subcomplex. In CAD Computer Aided Design; ACM: New York, NY, USA, 2004; Volume 36, pp. 195-202, doi:10.1016/S0010-4485(03)00061-7. open in new tab
  27. Edelsbrunner, H. Shape Reconstruction with Delaunay Complex. In Latin American Symposium on Theoretical Informatics; Springer: Berlin, Germany, 1998; pp. 119-132. open in new tab
  28. Kolluri, R.; Shewchuk, J.R.; O'Brien, J.F. Spectral Surface Reconstruction from Noisy Point Clouds. In Proceedings of the 2004 Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, Nice, France, 8-10 July 2004; p. 11, doi:10.1145/1057432.1057434. open in new tab
  29. Dey, T.K.; Goswami, S. Tight Cocone: A Water-tight Surface Reconstructor. J. Comput. Inf. Sci. Eng. 2003, 3, 302, doi:10.1115/1.1633278. open in new tab
  30. Boissonnat, J.D.; Gazais, F. Smooth surface reconstruction via natural neighbour interpolation of distance functions. Comput. Geom. Theory Appl. 2002, 22, 185-203, doi:10.1016/S0925-7721(01)00048-7. open in new tab
  31. Amenta, N.; Bern, M.; Kamvysselis, M. A New Voronoi-Based Surface Reconstruction Algorithm. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, Orlando, FL, USA, 19-24 July 1998; pp. 415-421. open in new tab
  32. Si, H. TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator. ACM Trans. Math. Softw. 2015, 41, 1-36, doi:10.1145/2629697. open in new tab
  33. Su, T.; Wang, W.; Lv, Z.; Wu, W.; Li, X. Rapid Delaunay triangulation for randomly distributed point cloud data using adaptive Hilbert curve. Comput. Graph. 2016, 54, 65-74, doi:10.1016/j.cag.2015.07.019. open in new tab
  34. Gonzaga de Oliveira, S.L.; Nogueira, J.R. An evaluation of point-insertion sequences for incremental Delaunay tessellations. In Computational and Applied Mathematics; Springer: Berlin, Germany, 2018; Volume 37, pp. 641-674, doi:10.1007/s40314-016-0358-0. open in new tab
  35. Girardeau-Montaut, D.; Roux, M. Change detection on points cloud data acquired with a ground laser scanner. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2005, 36, W19.
  36. Lindenbergh, R.; Pfeifer, N. A statistical deformation analysis of two epochs of terrestrial laser data of a lock. In Proceedings of the 7th Conference on Optical 3-D Measurement Techniques, Vienna, Austria, 3-5 October 2005; Vienna University of Technology: Vienna, Austria, 2005; pp. 61-70.
  37. Zeibak, R.; Filin, S. Change Detection via Terrestrial Laser Scanning. In Proceedings of the ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007, Espoo, Finland, 12-14 September 2007; pp. 430-435. open in new tab
  38. Kang, Z.; Zhang, L.; Yue, H.; Lindenbergh, R. Range Image Techniques for Fast Detection and Quantification of Changes in Repeatedly Scanned Buildings. Photogramm. Eng. Remote Sens. 2013, 79, 695-707, doi:10.14358/PERS.79.8.695. open in new tab
  39. Zhang, X.; Glennie, C.; Kusari, A. LiDAR Using a Weighted Anisotropic Iterative Closest Point Algorithm. Ieee J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 3338-3346, doi:10.1109/JSTARS.2015.2398317. open in new tab
  40. Janowski, A.; Nagrodzka-Godycka, K.; Szulwic, J.; Ziolkowski, P. Remote sensing and photogrammetry techniques in diagnostics of concrete structures. Comput. Concr. 2016, 18, 405-420, doi:10.12989/cac.2016.18.3.405. open in new tab
  41. Szulwic, J.; Ziolkowski, P.; Janowski, A. Combined Method of Surface Flow Measurement Using Terrestrial Laser Scanning and Synchronous Photogrammetry. In Proceedings of the 2017 Baltic Geodetic Congress (BGC Geomatics) BGC Geomatics, Gdansk, Poland, 22-25 June 2017, pp. 110-115, doi:10.1109/BGC.Geomatics.2017.54. open in new tab
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Gdańsk University of Technology

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