• 한국지구물리탐사학회:학술대회논문집
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• 2010.10a
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• pp.69-74
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• 2010

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.3
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• pp.275-283
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• 2002

To detect the position and depth of buried underground utilities, method of Ground Penetrating Radar(GPR) survey is the most commonly used. However, the skin-depth of GPR is very shallow, and in the places where subsurface materials are not homogeneous and are compose of clays and/or salts and gravels, GPR method has limitations in application and interpretation. The aim of this study is to overcome these limitations of GPR survey. For this purpose the site where the GPR survey is unsuccessful to detect the underground big pipes is selected, and soil tests were conducted to confirm the reason why GPR method was not applicable. Non-destructive high-frequency electromagnetic (HFEM) survey was newly developed and was applied in the study area to prove the effectiveness of this new technique. The frequency ranges $2kHz{\sim}4MHz$ and the skin depth is about 30m. The HFEM measures the electric field and magnetic field perpendicular to each other to get the impedance from which vertical electric resistivity distribution at the measured point can be deduced. By adopting the capacitive coupled electrodes, it can make the measuring time shorter, and can be applied to the places covered by asphalt an and/or concrete. In addition to the above mentioned advantages, noise due to high-voltage power line is much reduced by stacking the signals. As a result, the HFEM was successful in detecting the buried underground objects. Therefore this method is a promising new technique that can be applied in the lots of fields, such as geotechnical and archaeological surveys.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.6
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• pp.616-624
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• 2003

The exhaustion of our water resource due to the leakage of waterworks renders it urgent to detect water leakage effectively. In the paper, the detection of water leakage makes use of a pound-penetrating radar(GPR). The region of water leakage is implemented by an acryl box filled with methanol, and then the scale-down experiments are performed by using the GPR system developed in our laboratory. The validity of GPR experiments is assured by showing that the measured data agree well with those finite-difference time-domain(FDTD) simulated results in the same situation. The feasibility of GPR system for the detection of water leakage is investigated by displaying B-scan images according to the distribution of water leakage.

• Journal of the Korean Geophysical Society
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• v.6 no.4
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• pp.261-268
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• 2003

Lots of various utilities are buried under the surface. The effective management of underground utilities is becoming the very important subject for the harmonious administration of the city. Ground Penetrating Radar(GPR) survey including other various underground survey methods, is mainly used to detect the position and depth of buried underground utilities. However, GPR is not applicable, under the circumstances of shallow depth and places, where subsurface materials are inhomogeneous and are composed of clay, salt and gravels. The aim of this study is to overcome these limitations of GPR and other underground surveys. High-frequency electromagnetic (HFEM) method is developed for the non-destructive precise deep surveying of underground utilities. The method is applied in the site where current underground surveys are useless to detect the underground big pipes, because of poor geotechnical environment. As a result, HFEM survey was very successful in detecting the buried shallow and deep underground pipes and in obtaining the geotechnical information, although other underground surveys including GPR were not applicable. Therefore this method is a promising new technique in the lots of fields, such as underground surveying and archaeology.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.135-138
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• 2007

A novel technique to estimate the dielectric constant of ground material by means of air launching GPR is proposed. The technique is an application of SAR algorithm. A laboratory experiment was conducted to examine the technique.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.47-53
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• 2017

Accurate exploration of the risk factors of the ground subsidence is needed to predict and evaluate the subsidence of the surrounding ground due to the excavation of the ground. In this study, we analyzed the distribution of soil relaxation area by analyzing the behavior around the ground excavation site and simulated the GPR exploration under various conditions. As a result, Although there are some differences according to the water content, distribution of the strata and the distribution of the relaxation region were confirmed in the unsaturated soil, and it was found that there was a difficulty in the GPR exploration in the saturated soil.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.430-439
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• 2018

Purpose: The purpose of this study is to verify the effectiveness of maintenance method using GPR exploration by buried detective materials in the ground for efficient maintenance of recovered cavities. Method: EMI sheet, EMI paint, and ferronickel slag were used as the detection materials, and the experiment was conducted by varying the size and depth of the buried detectable material. Results: As a result of the exploration, Detectable influence range by GPR exploration was found depending on the size and depth of buried detectable material in all materials, and the possibility of using it as a detection material was confirmed.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.171-184
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• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

• Journal of the Korean Geophysical Society
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• v.4 no.1
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• pp.1-10
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• 2001

A number of tangible cultural properties have been left to suffering damage without any scientific conservation or maintenance. We conducted nondestructive geophysical explorations around the Western pagoda of the Iksan Mireuksa Temple for the purpose of preparing the counterplan of its conservation and maintenance and of utilizing the geophysical information for the design of repair. Geophysical image of the shallow subsurface around the construct resulting from electric resistivity, seismic refraction, and GPR methods carried out along 6 lines in the site was used to investigate the relationship between the foundation characteristics and the structural safety. Tilting of the pagoda southwest towards seems to result from the low resistivity zones found in the southwestern part. The GPR and seismic surveys revealed a boundary at depth of 3.3～3.5m dividing into two layers, compacted overlaid soil and the original ground. The boundary appears to dip southwest. The artificial layer as a foundation does not covers as much as the bottom area of the pagoda. This top soil dipping southwest seems to result in tilting of foundation southwestward towards. Our geophysical result suggests ground reinforcement in the western part of the survey area for the conservation of the construct.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.