• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.109-109
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• 2023

지구 온난화 등 기상이변으로 추정되는 단시간 동안 특정지역에 집중되는 국지성 집중호우가 빈번해지고 있으며, 내수침수가 홍수재해의 주된 원인이 되고 있다. 내수침수의 원인으로는 하수관로의 통수능력 부족(39%), 저지대 침수(37%), 내수배제불량(16%) 및 기타(8%)로 조사된 바 있으며, 이중 하수관로의 경우 용량 및 통수능 부족, 구배불량, 토사퇴적에 의한 배수 불량 등으로 이에 대처하기 위해서는 기초자료의 조사가 우선 되어야 한다. 하수관로의 문제로 인한 내수침수의 원인으로 첫째 하수관로 내·외부 불량으로 인한 통수능 저하로 측구 및 빗물받이에 토사 등 장애물, 관로내부 장애물, 관로내부 불량(뿌리침임, 영구장애물, 관붕괴, 관파손, 관변형, 내피생성, 토사퇴적 등)이 있으며, 두 번째로 하수관로 구배불량과 마지막으로 외수위(또는 해수위) 상승으로 인한 내수침수로 구분될 수 있다. 이러한 하수관로의 문제점은 많은 부분이 불탐지역으로 조사가 매우 어려워서 대안 없이 방치되는 실정이다. 금회 연구에서는 이러한 불탐지역의 조사를 위한 장비의 개발 및 정밀조사를 통해서 하수관로를 진단하고 내수침수 예방을 위한 대책을 찾고자 하였다. 특히, 계단부 관로조사용 내시경 VR장비, 준만관 조사용 부유식 VR장비, 가스 및 안전위험 지역 조사용 지하 드론 장비를 개발하여 시험검증을 하고자 하였다. 또한, 스마트 하수관로 체계에 빅데이터를 기반으로 한 하수관로 토탈 솔류션(nPASS) 시스템으로 내수침수대응 및 하수관로 유지관리를 위한 시스템의 필요성을 규명하고자 하였다. 하수관로의 선진화를 통한 내수침수예방의 시작은 불탐지역 하수관로 조사를 통한 정확한 원인 파악이며, 조사 및 축적되는 빅데이타를 기반으로 하수관로 토탈 유지관리 시스템의 구축을 제안하고자 하였다.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.19-27
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• 2024

Geotechnical structures such as dams, tunnels, and slopes require regular inspection and monitoring to ensure stability. Domestically, drones and accelerometers have become common tools for inspecting and monitoring various structures. However, drones have difficulty identifying internal changes in structures and the subsurface, and accelerometers generally serve for seismic design or strain measurement purposes. Therefore, this paper proposes to utilize accelerometers to monitor the internal information of the ground on a real-time or periodic basis. The proposed method utilizes a part of the analysis technique from the SASW test to monitor the stability and state changes of geotechnical structures. Cases where SASW was used to evaluate the safety of geotechnical structures, such as slopes, dams, and tunnels, were reviewed to verify the suitability of the technology. To make the proposed method more practical, the study considered using only the first-step analysis to derive the dispersion curve rather than the second-step analysis to determine the shear wave velocity profile, which requires complex analysis. The proposed technique is expected to enable the continuous monitoring and inspection of geotechnical structures by utilizing accelerometers.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.230-237
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• 2023

Self-driving is a key technology of the fourth industry and can be applied to various places such as cars, drones, cars, and robots. Among them, localiztion is one of the key technologies for implementing autonomous driving as a technology that identifies the location of objects or users using GPS, sensors, and maps. Locilization can be made using GPS or LIDAR, but it is very expensive and heavy equipment must be mounted, and precise location estimation is difficult for places with radio interference such as underground or tunnels. In this paper, to compensate for this, we proposes an image retrieval using attention module and image segmentation maps using color images acquired with low-cost vision cameras as an input.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.462-469
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• 2015

This study carried out a topographic survey at a small-scale open-pit limestone mine in Korea (the Daesung MDI Seoggyo office) using a popular rotary-wing unmanned aerial vehicle (UAV, Drone, DJI Phantom2 Vision+). 89 sheets of aerial photos could be obtained as a result of performing an automatic flight for 30 minutes under conditions of 100m altitude and 3m/s speed. A total of 34 million cloud points with X, Y, Z-coordinates was extracted from the aerial photos after data processing for correction and matching, then an orthomosaic image and digital surface model with 5m grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 5 ground control points measured by differential global positioning system and those determined by UAV photogrammetry revealed that the root mean squared errors of X, Y, Z-coordinates were around 10cm. Therefore, it is expected that the popular rotary-wing UAV photogrammetry can be effectively utilized in small-scale open-pit mines as a technology that is able to replace or supplement existing topographic surveying equipments.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.451-463
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• 2022

Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.427-436
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• 2016

Due to disasters such as earthquakes and landslides in urban areas, persons have been buried inside collapsed buildings and structures. Rescuers have mainly utilized detection equipment by applying sound, video and electric waves, but these are expensive and due to the directional approaches onto the collapsed site, secondary collapse risk can arise. In addition, due to poor utilization of such equipment, new human detection technology with quick and high reliability has not been utilized. To address these issues, this study develops a wireless signal-based human detection module that can be loaded into an Unmanned Aerial Vehicle (UAV). The human detection module searches for the 3D location for buried persons by collecting Wi-Fi signal and barometer sensors data transmitted from the mobile phones. This module can gain diverse information from mobile phones for buried persons in real time. We present a development framework of the module that provides 3D location data with more reliable information by delivering the collected data into a local computer in the ground. This study verified the application feasibility of the developed module in a real collapsed area. Therefore, it is expected that these results can be used as a core technology for the quick detection of buried persons' location and for relieving them after disasters that induce building collapses.