Subsurface object detection and characterization using Ground Penetrating Radar

被引:1
|
作者
Balasubramani, Divya Priya [1 ]
Gopalakrishnan, Venkatachalam [2 ]
机构
[1] Vellore Inst Technol, Sch Civil Engn, Vellore 632014, Tamil Nadu, India
[2] Mukesh Patel Sch Technol Management, Dept Civil Engn, Mumbai 400 056, India
关键词
GPR; Buried pipes; SVM; Subsurface characterization; ELECTRICAL-RESISTIVITY; GPR; CLASSIFICATION; PROPAGATION; RADIUS; CAIRO; AREA; SOIL;
D O I
10.1007/s41062-020-00352-5
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Subsurface characterization and information about buried utility infrastructure is an important issue affecting the public safety and progress of development projects. A heterogeneous subsurface environment is often insufficiently characterized by the data collected through various direct and indirect means, particularly in dense urban areas. The present study aims to detect the subsurface objects and map the stratigraphic environment in a city region using a non-invasive geophysical technique called Ground Penetrating Radar (GPR). In this study, antennas of central frequency 200 and 80 MHz have been used to identify the underground utilities and subsurface layer information, respectively. A methodology based on a geometrical approach using Support Vector Machines (SVM) is developed for computing the depth and radius of buried pipes. Also, the electrical discontinuities in the GPR profiles are identified through various processing techniques to extract the subsurface layer information. The results indicate that the 200-MHz antenna and SVM-based methodology estimate the buried pipe parameters with reasonable accuracy at various site combinations. It is found that the bistatic low-frequency 80-MHz antenna suitably characterizes the subsurface layers, which are in close agreement with the borehole data. The processed data illustrate a strong correlation between the radar signals and the characteristics of the strata resolving the uncertainty. The study highlights the capability of GPR in extracting the subsurface data and recommends a multi-frequency approach to map and interpret the complete subsurface environment at a specific site.
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页数:17
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