• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.2
• /
• pp.109-118
• /
• 2022

GPR (Ground Penetrating Radar), developed as a technology for geotechnical investigations such as sinkhole exploration, was used limitedly as a method to resolve undetectable lines in underground facility exploration. To improve the accuracy of underground facility data, the government made it possible to explore underground facilities using a non-metallic pipeline probe from July 2022. However, GPR has a problem in that the exploration rate is lowered in the soil with high moisture content, such as soft soil, such as clay layer, and there is a lot of variation in long-term accuracy. In this study, as a way to improve the accuracy of exploration considering the characteristics of GPR and the environment of underground facilities, we propose a GPR exploration method for underground facilities using permittivity constant correction and pattern analysis of GPR image data. Through this study, the accuracy of underground facility exploration and high reproducibility were derived as a result of field verification applying GPR frequency band and heterogeneous GPR.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.2 no.4
• /
• pp.148-158
• /
• 1998

Determining the thickness if concrete lining and detecting of the cavity where is located behind tunnel lining plays an important role in the safety diagnosis of tunnel structure and the quality control. In this study, we made use of GPR and seismic method in order to find the cavity or flaw. Although GPR is very useful method in the concrete lining without rebar, it is difficult to detect the cavity in the reinforced concrete lining. We applied mini-seismic method to the reinforced concrete lining. The obtained seismic data was processed by means of seismic section in time domain and image section of power spectrum in frequency domain using Impact-Echo method as well. The proposed method can accurately show the location and depth of the cavity in the reinforced concrete lining.

• 한국지구물리탐사학회:학술대회논문집
• /
• 1999.08a
• /
• pp.65-91
• /
• 1999

More than 6 years passed until GPR was introduced to our country. GPR method is now widely used in construction site because of its various applicability, convenient handling and low cost. We discussed the characteristics and limits of GPR method with various case study.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.197-206
• /
• 2021

GPR data is used for underground exploration. The data gathered are interpreted by experts based on experience as the underground facilities often reflect GPR. In addition, GPR data are different in the noise and characteristics of the data depending on the equipment, environment, etc. This often results in insufficient data with accurate labels. Generally, a large amount of training data have to be obtained to apply CNN models that exhibit high performance in image classification problems. However, due to the characteristics of GPR data, it makes difficult to obtain sufficient data. Finally, this makes neural networks unable to learn based on general supervised learning methods. This paper proposes an image classification method considering data characteristics to ensure that the accuracy of each label is similar. The proposed method is based on semi-supervised learning, and the image is classified using clustering techniques after extracting the feature values of the image from the neural network. This method can be utilized not only when the amount of the labeled data is insufficient, but also when labels that depend on the data are not highly reliable.

• Geomechanics and Engineering
• /
• v.30 no.6
• /
• pp.489-502
• /
• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Journal of Korea Soil Environment Society
• /
• v.1 no.1
• /
• pp.29-38
• /
• 1996

Among many geophysical prospecting methods, GPR(Ground Penetration Radar) and electrical resistivity method have been applied to a open waste dumping landfill for measuring of the site area and depth. The surveying was limited to a boarder of the site and inside area because of the field situation. The data of GPR were recorded by 50MHz antenna, and dipole array was used for electrical resistivity survey in the same survey line for the integrated interpretation. The result of GPR clearly indicated the horizontal boarder of site. However, the data of GPR did not have enough to measure the depth of site clearly. The electrical resistivity method may show the effective information by integrated interpreation. These results coincided with results of the boring test. Therefore, a combination of GPR and electrical resistivity is a good method for surveying of suspective open waste dumping landfill area and it's depth.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.1
• /
• pp.61-67
• /
• 2018

The effects of subsurface inhomogeneities on the detection of buried metal pipes in ground-penetrating radar(GPR) signals are investigated numerically. To model the electrical properties of the subsurface inhomogeneities, the continuous random media(CRM) generation technique is introduced. For the electromagnetic simulation of GPR signals, the finite-difference time-domain(FDTD) method is implemented. As a function of the standard deviation and the correlation length of the relative permittivity distribution for a randomly inhomogeneous ground, the GPR signals of the buried metal pipes are compared using numerical simulations. As the subsurface inhomogeneities increase, the GPR signals of the buried pipes are distorted because of the effect of the subsurface clutter.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.3
• /
• pp.32-40
• /
• 2021

Underground information is difficult to visually check, which can lead to a huge accident in the event of a safety accident. Recently, the Ministry of Land, Infrastructure and Transport intends to reduce safety accidents caused by the aging or damage of underground facilities through the Special Act on Underground Safety Management. GPR is increasingly being used as a technology to acquire information in underground spaces that are difficult to see with the naked eye. However, GPR's location information is corrected by checking images of CCTV and GPS information acquired during exploration. This method has an average error of about 2 meters. In this works, We used LiDAR to calibrate the GPR information and found that the error was reduced from at least 7cm to up to 40cm. If accurate GPR information collected in the future is analyzed quickly using AI, etc., it will be able to collect and utilize underground information faster than it is now to secure safety.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.6
• /
• pp.82-92
• /
• 2012

This study proposed a new non-destructive evaluation method for concrete bridge deck deterioration using ground penetrating radar (GPR). To calculate dielectric constant of the concrete bridge deck, an extended common mid-point (XCMP) method was developed for a two-layered structure using an air-coupled GPR antenna setup. The deterioration conditions of the concrete bridge deck such as deterioration depth was evaluated based on the dielectric constant and surface-to-average dielectric constant ratio of the concrete bridge deck. A GPR field test was conducted on an old concrete bridge with asphalt concrete surfacing to validate the new evaluation method. The test results showed that the newly proposed method estimated pavement thickness and deterioration depth of the concrete deck in a reasonable level.

• Journal of the Korean Geosynthetics Society
• /
• v.17 no.3
• /
• pp.47-55
• /
• 2018

Recently, increasing number of urban ground subsidence occurrences has been identified. This situation is mainly due to the increased number of underground cavities. This study is intended to develop the method that prevents ground settlement caused by deteriorated or damaged sewers, which are the main cause of land subsidence. To that end, GPR exploration was conducted using CCTV monitoring of deteriorated sewer at the location with high settlement potential. Through such CCTV monitoring and GPR investigation, abnormal ground behavior was monitored at the site where sewer was damaged, joint was cracked and soil was deposited. According to site investigation in this study, evaluation method using correlation analysis of CCTV monitoring and GPR investigation results is expected to prevent ground settlement attributable to damaged sewer.