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The properties of terrestrial laser system intensity in measurements of technical conditions of architectural structures

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Terrestrial laser scanning (TLS) is one of the instruments for remote detection of damage of structures (cavities, cracks) which is successfully used to assess technical conditions of building objects. Most of the point clouds analysis from TLS relies only on spatial information (3D–XYZ). This study presents an approach based on using the intensity value as an additional element of information in diagnosing technical conditions of architectural structures. The research has been carried out in laboratory and field conditions. Its results show that the coefficient of laser beam reflectance in TLS can be used as a supplementary source of information to improve detection of defects in constructional objects.
Słowa kluczowe
Rocznik
Strony
779--792
Opis fizyczny
Bibliogr. 29 poz., rys., wykr.
Twórcy
autor
  • Koszalin University of Technology, Faculty of Civil Engineering Environmental and Geodetic Sciences, Śniadeckich 2, 75-453 Koszalin, Poland
autor
  • Koszalin University of Technology, Faculty of Civil Engineering Environmental and Geodetic Sciences, Śniadeckich 2, 75-453 Koszalin, Poland
  • Vilnius Gediminas Technical University, Department of Geodesy and Cadastre, Saulėtekio 11, LT-10223, Vilnius, Lithuania
autor
  • Vilnius Gediminas Technical University, Department of Geodesy and Cadastre, Saulėtekio 11, LT-10223, Vilnius, Lithuania
  • Vilnius Gediminas Technical University, Department of Geodesy and Cadastre, Saulėtekio 11, LT-10223, Vilnius, Lithuania
Bibliografia
  • [1] Sohn, H.G., Lim, Y.M., Yun, K.H., Kim, G.H. (2005). Monitoring Crack Changes in Concrete Structures. Comput. Civ. Infrastruct. Eng., 20, 52-61.
  • [2] Wagner, W., Ullrich, A., Ducic, V., Melzer, T., et al. (2006). Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS J. Photogramm. Remote Sens., 60, 100-112.
  • [3] Blaszczak-Bak, W., Sobieraj, A. (2016). Application of Regression Line to Obtain Specified Number of Points in Reduced Large Datasets. 2016 Baltic Geodetic Congress (BGC Geomatics), 40-44.
  • [4] Błaszczak-Bąk, W., Sobieraj-Żłobińska, A., Kowalik, M. (2017). The OptD-multi method in LiDAR processing. Meas. Sci. Technol., 28, 7500-9.
  • [5] Gordon, S.J., Lichti, D.D. (2007). Modeling Terrestrial Laser Scanner Data for Precise Structural Deformation Measurement. J. Surv. Eng., 133, 72-80.
  • [6] Suchocki, C., Damięcka, M., Jagoda, M. (2008). Determination of the building wall deviations from the vertical plane. 7th International Conference on Environmental Engineering, ICEE 2008 - Conference Proceedings, 1488-1492.
  • [7] Szulwic, J., Ziolkowski, P., Janowski, A. (2017). Combined Method of Surface Flow Measurement Using Terrestrial Laser Scanning and Synchronous Photogrammetry. Proceedings - 2017 Baltic Geodetic Congress (Geomatics), BGC Geomatics 2017, 1-6.
  • [8] Liu, W., Chen, S., Hauser, E. (2011). LiDAR-based bridge structure defect detection. Exp. Tech., 35, 27-34.
  • [9] Janowski, A., Bobkowska, K., Szulwic, J. (2018). 3D modelling of cylindrical-shaped objects from lidar data - an assessment based on theoretical modelling and experimental data. Metrol. Meas. Syst., 25(1), 47-56.
  • [10] Laefer, D.F., Truong-Hong, L., Carr, H., Singh, M. (2014). Crack detection limits in unit based masonry with terrestrial laser scanning. NDT E Int., 62, 66-76.
  • [11] Teza, G., Galgaro, A., Moro, F. (2009). Contactless recognition of concrete surface damage from laser scanning and curvature computation. NDT E Int., 42, 240-249.
  • [12] Kuçak, R.A., Kiliç, F., Kisa, A. (2016). Analysis of terrestrial laser scanning and photogrammetry data for documentation of historical artifacts. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., XLII-2/W1, 155-158.
  • [13] Olsen, M.J., Kuester, F., Chang, B.J. (2010). Hutchinson, T.C., Terrestrial Laser Scanning-Based Structural Damage Assessment. J. Comput. Civ. Eng., 24, 264-272.
  • [14] Armesto-González, J., Riveiro-Rodríguez, B., González-Aguilera, D., Rivas-Brea, M.T. (2010). Terrestrial laser scanning intensity data applied to damage detection for historical buildings. J. Archaeol. Sci., 37, 3037-3047.
  • [15] Dai, K., Li, A., Hexiao, Z., Chen, S., et al. (2018). Surface damage quantification of postearthquake building based on terrestrial laser scan data. Int. Assoc. Struct. Control Monit., 1-18.
  • [16] Guldur, B., Hajjar, J. (2014). Laser-based structural sensing and surface damage detection. Report No. NEU-CEE-2014-03.
  • [17] Chen, S.E. (2012). Laser Scanning Technology for Bridge Monitoring. Intech, 71-93.
  • [18] Jelalian, A.V. (1992). Laser Radar Systems. Artech House.
  • [19] Kaasalainen, S., Jaakkola, A., Kaasalainen, M., Krooks, A., et al. (2011). Analysis of incidence angle and distance effects on terrestrial laser scanner intensity: Search for correction methods. Remote Sens., 3, 2207-2221.
  • [20] Sasidharan, S.A. (2016). Normalization scheme for Terrestrial LiDAR Intensity Data by Range and Incidence Angle. Int. J. Emerg. Technol. Adv. Eng., 6, 1-7.
  • [21] Tan, K., Cheng, X. (2016). Correction of incidence angle and distance effects on TLS intensity data based on reference targets. Remote Sens., 8, 1-20.
  • [22] Bucksch, A., Lindenbergh, R.C., Van Ree, J. (2007). Error budget of Terrestrial Laserscanning: Influence of the intensity remission on the scan quality. III Int. Sci. Congr. Geo-Siberia, 113-122.
  • [23] Pesci, A., Teza, G. (2008). Effects of surface irregularities on intensity data from laser scanning: An experimental approach. Ann. Geophys., 51, 839-848.
  • [24] Voegtle, T., Schwab, I., Landes, T. (2008). Influences of different materials on the measurements of a terrestrial laser scanner (TLS). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 1061-1066.
  • [25] Suchocki, C., Katzer, J., Panuś, A. (2017). Remote Sensing to Estimate Saturation Differences of Chosen Building Materials Using Terrestrial Laser Scanner. Reports Geod. Geoinformatics, 103, 94-105.
  • [26] Suchocki, C., Katzer, J., Rapiński, J. (2018). Terrestrial Laser Scanner as a Tool for Assessment of Saturation and Moisture Movement in Building Materials. Period. Polytech. Civ. Eng., 1-6.
  • [27] Roncat, A., Bergauer, G., Pfeifer, N. (2010). Retrieval of the backscatter cross-section in full-waveform LIDAR data using B-splines. Proc. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., XXXVIII, 137-142.
  • [28] Pfeifer, N., Höfle, B., Briese, C., Rutzinger, M., et al. (2018). Analysis Of The Backscattered Energy In Terrestrial Laser Scanning Data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, 1045-1052.
  • [29] Boehler, W., Marbs, A. (2003). Investigating Laser Scanner Accuracy. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 34, 696-701.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cf7d8ac5-7997-4cf7-876a-98036bb96b1d
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