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Analiza dokładności określania lokalizacji obiektów podziemnych za pomocą georadaru z wykorzystaniem danych lidarowych
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Abstrakty
Ground penetrating radar (GPR) is one of the most useful non-destructive techniques for locating underground objects. Advancements in this technology have facilitated the development of new sensors over the past decade. In this paper, an accuracy assessment of the location of underground objects using various GPR antennas is presented. To achieve the stated goals, measurements of 5 concrete slabs, reinforced with steel bars of various diameters and located at variable depths were taken. The experiment includes the usage of three GPR antennas to assess the format, characteristics, and differences of extracted data. This set of antennas from different manufacturers varied in terms of operating frequency. Additional lidar data from TLS (terrestrial laser scanning) was utilized in the methodology to provide precise surface measurements and therefore, external orientation of the surveyed data. The experiment allowed for the determination of vertical and horizontal accuracy for three tested antennas and the assessment of increasing errors value with greater depth of the measured items, which is important for surveying accuracy forecasting.
Georadar jest jedną z najbardziej użytecznych nieinwazyjnych technik lokalizowania obiektów podziemnych. Postęp w tej technologii w ostatniej dekadzie ułatwił rozwój nowych sensorów. W artykule przedstawiono ocenę dokładności lokalizacji prętów zbrojeniowych znajdujących się w obrębie badanego obiektu z wykorzystaniem różnych anten. Aby osiągnąć założone cele, wykonano pomiary 5 płyt betonowych, zbrojonych prętami stalowymi o różnych średnicach i znajdujących się na różnych głębokościach. Eksperyment obejmował wykorzystanie trzech anten o różnej częstotliwości do oceny rozmiaru, charakterystyki i różnic wyodrębnionych danych. W metodyce eksperymentu wykorzystano dodatkowo dane lidarowe z naziemnego skanowania laserowego (TLS), aby zapewnić precyzyjne pomiary powierzchni, a tym samym zewnętrzną orientację przestrzenną pozyskanych danych. Eksperyment pozwolił na wyznaczenie dokładności pionowej i poziomej dla trzech wykorzystanych anten oraz ocenę rosnącej wartości błędów wraz z większą głębokością mierzonych elementów, co jest istotne dla predykcji dokładności pomiarów.
Czasopismo
Rocznik
Tom
Strony
611--628
Opis fizyczny
Bibliogr. 34 poz., il., tab.
Twórcy
autor
- Warsaw University of Technology, Faculty of Civil Engineering, Warsaw, Poland
autor
- Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
- Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
autor
- Warsaw University of Technology, Faculty of Civil Engineering, Warsaw, Poland
autor
- Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
autor
- Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland
Bibliografia
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- [6] J. Li, T. Guo, H. Leung, H. Xu, L. Liu, B. Wang, and Y. Liu, “Locating Underground Pipe Using Wideband Chaotic Ground Penetrating Radar”, Sensors, vol. 19, no. 13, 2019, doi: 10.3390/s19132913.
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- [11] M.S. Sudakova, M. Sadurtdinov, A. Tsarev, A. Skvortsov, and G. Malkova, “Ground-Penetrating Radar for Studies of Peatlands in Permafrost”, Russian Geology and Geophysics, vol. 60, no. 7, pp. 793-800, 2019.
- [12] T. Yamaguchi, T. Mizutani, M. Tarumi, and D. Su, “Sensitive Damage Detection of Reinforced Concrete Bridge Slab by ‘Time-Variant Deconvolution’ of SHF-Band Radar Signal”, IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 3, pp. 1478-1488, 2019, doi: 10.1109/TGRS.2018.2866991.
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- [15] M. Ramya, K. Balasubramaniam, and M. Shunmugam, “On a reliable assessment of the location and size of rebar in concrete structures from radargrams of ground-penetrating radar”, Insight - Non-Destructive Testing and Condition Monitoring, vol. 58, no. 5, pp. 264-270, 2016, doi: 10.1784/insi.2016.58.5.264.
- [16] K. Dinh, N. Gucunski, and T. Duong, “Migration-based automated rebar picking for condition assessment of concrete bridge decks with ground penetrating radar”, NDT & E International, vol. 98, pp. 45-54, 2018, doi: 10.1016/j.ndteint.2018.04.009.
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- [18] Z. Xiang, G. Ou, and A. Rashidi,37 “An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database”, in Construction Research Congress 2020: Computer Applications. ASCE, 2020, pp. 86-95, doi: 10.1061/9780784482865.010.
- [19] K. Agred, G. Klysz, and J. Balayssac, “Location of reinforcement and moisture assessment in reinforced concrete with a double receiver GPR antenna”, Construction and Building Materials, vol. 188, pp. 1119-1127, 2018, doi: 10.1016/j.conbuildmat.2018.08.190.
- [20] M.R. Shaw, S. G. Millard, T.C.K. Molyneaux, M.J. Taylor, and J.H. Bungey, “Location of steel reinforcement in concrete using ground penetrating radar and neural networks”, NDT & E International, vol. 38, no. 3, pp. 203-212, 2005, doi: 10.1016/j.ndteint.2004.06.011.
- [21] Z. Xiang, A. Rashidi, and G. (Gaby) Ou, “An Improved Convolutional Neural Network System for Automatically Detecting Rebar in GPR Data”, in Computing in Civil Engineering 2019: Data, Sensing, and Analytics. ASCE, 2019, pp. 422-429, doi: 10.1061/9780784482438.054.37
- [22] P. Wiwatrojanagul, R. Sahamitmongkol, S. Tangtermsirikul, and N. Khamsemanan, “A new method to determine locations of rebars and estimate cover thickness of RC structures using GPR data”, Construction and Building Materials, vol. 140, pp. 257-273, 2017, doi: 10.1016/j.conbuildmat.2017.02.126.
- [23] H. Rathod, S. Debeck, R. Gupta, and B. Chow, “Applicability of GPR and a rebar detector to obtain rebar information of existing concrete structures”, Case Studies in Construction Materials, vol. 11, art. no. e00240, 2019, doi: 10.1016/j.cscm.2019.e00240.
- [24] Z. Xiang, A. Rashidi, and G. Ou, “States of Practice and Research on Applying GPR Technology for Labeling and Scanning Constructed Facilities”, Journal of Performance of Constructed Facilities, vol. 33, no. 5, 2019, doi: 10.1061/(ASCE)CF.1943-5509.0001313.
- [25] F. Zhou, Z. Chen, H. Liu, J. Cui, B.F. Spencer, and G. Fang, “Simultaneous Estimation of Rebar Diameter and Cover Thickness by a GPR-EMI Dual Sensor”, Sensors, vol. 18, no. 9, 2018, doi: 10.3390/s18092969.
- [26] W. Mukupa, G.W. Roberts, C.M. Hancock, and K. Al-Manasir, “A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures”, Survey Review, vol. 49, no. 353, pp. 99-16, 2017, doi: 10.1080/00396265.2015.1133039.
- [27] H. Li, S. Qi, X. Yang, X. Li, and J. Zhou, “Geological Survey and Unstable Rock Block Movement Monitoring of a Post-Earthquake High Rock Slope Using Terrestrial Laser Scanning”, Rock Mechanics and Rock Engineering, vol. 53, no. 10, pp. 4523-4537, 2020, doi: 10.1007/s00603-020-02178-0.
- [28] N. Lercari, “Monitoring earthen archaeological heritage using multi-temporal terrestrial laser scanning and surface change detection”, Journal of Cultural Heritage, vol. 39, pp. 152-165, 2019, doi: 10.1016/j.culher.2019.04.005.
- [29] X. Liang, et al., “Terrestrial laser scanning in forest inventories”, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 115, pp. 63-77, 2016, doi: 10.1016/j.isprsjprs.2016.01.006.
- [30] C. Wu, Y. Yuan, Y. Tang, and B. Tian, “Application of Terrestrial Laser Scanning (TLS) in the Architecture, Engineering and Construction (AEC) Industry”, Sensors, vol. 22, no. 1, 2022, doi: 10.3390/s22010265.
- [31] T. Saarenketo, “Electrical properties of road materials and subgrade soils and the use of Ground Penetrating Radar in traffic infrastructure surveys”, PhD thesis, University of Oulu, Finland, 2006.
- [32] X. Han, “Experimental Study on Dielectric Properties of Pavement Structure Layer Based on Radar Image”, Chemical Engineering Transactions, vol. 66, pp. 883-888, 2018, doi: 10.3303/CET1866148.
- [33] J. Karczewski, Ł. Ortyl, and M. Pasternak, Zarys Metody Georadarowej. Kraków, Poland: Wydawnictwa AGH, 2011.
- [34] Z. Tong, D. Yuan, J. Gao, Y. Wei, and H. Dou, “Pavement-distress detection using ground-penetrating radar and network in networks,” Construction and Building Materials, vol. 233, art. no. 117352, 2020, doi: 10.1016/j.conbuildmat.2019.117352.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-eecf1ffe-a48e-473c-b084-5df14d535c02