• Journal of the Society of Disaster Information
• /
• v.15 no.3
• /
• pp.391-401
• /
• 2019

Purpose: In this study, the location and history information of the cavity identified in the cavity exploration, such as repacking of the pavement, is not known. Therefore, it is to review the field applicability of RFID(Radio Frequency Identification) systems that enable anyone to accurately identify information. Method: Basic experiments were conducted for field applicability for cavity recognition distance, recognition and recognition rate, tag performance and tag type, reader interference, communication, underground burial impact, and duplicate recognition by RFID system. Results: As a result of the depth of tag and reader recognition, the electronic tag chips and readers applied in the basic experiment are judged to be effectively applicable in the field environment where the road cavity is located. Conclusion: The RFID tags for field application of the pavement management system store various information such as location and size of cavity, identification date, cause of occurrence, and surrounding underground facilities to maximize cavity management effect with a system that can be computerized and mobile utilization.

• Journal of the Society of Disaster Information
• /
• v.16 no.3
• /
• pp.449-457
• /
• 2020

Purpose: The Seoul Metropolitan Government classifies the cavity risks into emergency, priority, general, and observation grades in consideration of the cavity size, asphalt pavement thickness, and pavement depth based on the cavity management grade criteria of Seoul. In this study, the depth of cracking was measured at 17 cracks identified by checking the pavement condition of the cavity at 265 cavities found in the 2019 cavity investigation service. Method: In the first phase, crack width and depth were measured using a vernier caliper, taper gauge, and depth gauge to check the cracks of the identified cavities. In the second phase, the location of the largest crack in the upper road surface was confirmed, and A.C. was drilled to further measure the crack depth. Results: As a result, the cavity management level was raised in nine of the 17 test cavity identified. Therefore, in case of emergency and priority recovery, the grade should be adjusted according to the depth of pavement crack and the thickness of residual A.C. pavement. Conclusion: In the case of cracks in the upper part of the cavity, the crack progression must be determined through the perforation and the remaining asphalt concrete thickness must be determined to determine the cavity grade.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.173-183
• /
• 2020

In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.

• Geophysics and Geophysical Exploration
• /
• v.24 no.3
• /
• pp.113-130
• /
• 2021

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.189-200
• /
• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.3
• /
• pp.77-84
• /
• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.1
• /
• pp.39-45
• /
• 2024

Seismic safety of expansion joints for piping systems has been underscored by water pipe ruptures and leaks resulting from the Gyeongju and Pohang earthquakes. Metal bellows in piping systems are applied to prevent damage from earthquakes and road subsidence in soft ground. Designed with a series of corrugated segments called convolutions, metal bellows exhibit flexibility to accommodate displacements. Several studies have examined variations in convolution shapes and layers based on the intended performance to be evaluated. Nonetheless, the research on the seismic performance of complex bellows having multiple corrugation heights is limited. In this study, monotonic loading tests, cyclic loading tests, and fatigue tests were conducted to evaluate the shear performance in seismic conditions, of metal bellows with variable convolution heights. Single- and triple-layer bellows were considered for the experimentation. The results reveal that triple-layer bellows exhibit larger maximum deformation and fatigue life than single-layer bellows. However, the high stiffness of triple-layer bellows in resisting internal pressure poses certain disadvantages. The convolutions are less flexible at lower displacements and experience leakage at a rate related to the variable height of the convolutions in certain conditions. At lower deformation rates, the fatigue life is rated higher as the number of layers increase. It converges to a similar fatigue life at higher deformation rates.