• Title/Summary/Keyword: 터널영상

Search Result 160, Processing Time 0.025 seconds

Application of Borehole Radar to Tunnel Detection (시추공 레이다 탐사에 의한 지하 터널 탐지 적용성 연구)

  • Cho, Seong-Jun;Kim, Jung-Ho;Kim, Chang-Ryol;Son, Jeong-Sul;Sung, Nak-Hun
    • Geophysics and Geophysical Exploration
    • /
    • v.9 no.4
    • /
    • pp.279-290
    • /
    • 2006
  • The borehole radar methods used to tunnel detection are mainly classified into borehole radar reflection, directional antenna, crosshole scanning, and radar tomography methods. In this study, we have investigated the feasibility and limitation of each method to tunnel detection through case studies. In the borehole radar reflection data, there were much more clear diffraction signals of the upper wings than lower wings of the hyperbolas reflected from the tunnel, and their upper and lower wings were spreaded out to more than 10m higher and lower traces from the peaks of the hyperbolas. As the ratio of borehole diameter to antenna length increases, the ringing gets stronger on the data due to the increase in the impedance mismatching between antennas and water in the boreholes. It is also found that the reflection signals from the tunnel could be enhanced using the optimal offset distance between transmitter and receiver antennas. Nevertheless, the borehole radar reflection data could not provide directional information of the reflectors in the subsurface. Direction finding antenna system had a advantage to take a three dimensional location of a tunnel with only one borehole survey even though the cost is still very high and it required very high expertise. The data from crosshole scanning could be a good indicator for tunnel detection and it could give more reliable result when the borehole radar reflection survey is carried out together. The images of the subsurface also can be reconstructed using travel time tomography which could provide the physical property of the medium and would be effective for imaging the underground structure such as tunnels. Based on the results described above, we suggest a cost-effective field procedure for detection of a tunnel using borehole radar techniques; borehole radar reflection survey using dipole antenna can firstly be applied to pick up anomalous regions within the borehole, and crosshole scanning or reflection survey using directional antenna can then be applied only to the anomalous regions to detect the tunnel.

Deep learning algorithm of concrete spalling detection using focal loss and data augmentation (Focal loss와 데이터 증강 기법을 이용한 콘크리트 박락 탐지 심층 신경망 알고리즘)

  • Shim, Seungbo;Choi, Sang-Il;Kong, Suk-Min;Lee, Seong-Won
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.23 no.4
    • /
    • pp.253-263
    • /
    • 2021
  • Concrete structures are damaged by aging and external environmental factors. This type of damage is to appear in the form of cracks, to proceed in the form of spalling. Such concrete damage can act as the main cause of reducing the original design bearing capacity of the structure, and negatively affect the stability of the structure. If such damage continues, it may lead to a safety accident in the future, thus proper repair and reinforcement are required. To this end, an accurate and objective condition inspection of the structure must be performed, and for this inspection, a sensor technology capable of detecting damage area is required. For this reason, we propose a deep learning-based image processing algorithm that can detect spalling. To develop this, 298 spalling images were obtained, of which 253 images were used for training, and the remaining 45 images were used for testing. In addition, an improved loss function and data augmentation technique were applied to improve the detection performance. As a result, the detection performance of concrete spalling showed a mean intersection over union of 80.19%. In conclusion, we developed an algorithm to detect concrete spalling through a deep learning-based image processing technique, with an improved loss function and data augmentation technique. This technology is expected to be utilized for accurate inspection and diagnosis of structures in the future.

A Study on Automatic Classification of Characterized Ground Regions on Slopes by a Deep Learning based Image Segmentation (딥러닝 영상처리를 통한 비탈면의 지반 특성화 영역 자동 분류에 관한 연구)

  • Lee, Kyu Beom;Shin, Hyu-Soung;Kim, Seung Hyeon;Ha, Dae Mok;Choi, Isu
    • Tunnel and Underground Space
    • /
    • v.29 no.6
    • /
    • pp.508-522
    • /
    • 2019
  • Because of the slope failure, not only property damage but also human damage can occur, slope stability analysis should be conducted to predict and reinforce of the slope. This paper, defines the ground areas that can be characterized in terms of slope failure such as Rockmass jointset, Rockmass fault, Soil, Leakage water and Crush zone in sloped images. As a result, it was shown that the deep learning instance segmentation network can be used to recognize and automatically segment the precise shape of the ground region with different characteristics shown in the image. It showed the possibility of supporting the slope mapping work and automatically calculating the ground characteristics information of slopes necessary for decision making such as slope reinforcement.

Selecting a Landmark for Repositioning Automated Driving Vehicles in a Tunnel (자율주행 차량의 터널내 측위오차 보정 지원시설 선정)

  • Kim, Hyoungsoo;Kim, Youngmin;Park, Bumjin
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.17 no.5
    • /
    • pp.200-209
    • /
    • 2018
  • This study proposed a method to select existing facilities as a landmark in order to reset accumulated errors of dead reckoning in a tunnel difficult to receive GNSS signals in automated driving. First, related standards and regulations were reviewed in order to survey 'variety' on shapes and installation locations as a feature of facilities. Second, 'recognition' on facilities was examined using image and Lidar sensors. Last, 'regularity' in terms of installation locations and intervals was surveyed through related references. The results of this study selected a fire fighting box / lamp (50m), an evacuation corridor lamp (300m), a lane control system (500m), a maximum / minimum speed limit sign and a jet fan as a candidate landmark to reset positioning errors. Based on those facilities, it was determined that error correction was possible. The results of this study are expected to be used in repositioning of automated driving vehicles in a tunnel.

A case study of ground subsidence analysis using the InSAR technique (InSAR 기술을 이용한 지반침하분석 사례연구)

  • Moon, Joon-Shik;Oh, Hyoung-seok
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.24 no.2
    • /
    • pp.171-182
    • /
    • 2022
  • InSAR (Interferometry SAR) technique is a technique that uses complex data to obtain phase difference information from two or more SAR image data, and enables high-resolution image extraction, surface change detection, elevation measurement, and glacial change observation. In many countries, research on the InSAR technique is being conducted in various fields of study such as volcanic activity detection, glacier observation in Antarctica, and ground subsidence analysis. In this study, a case of large ground settlement due to groundwater level drawdown during tunnelling was introduced, and ground settlement analyses using InSAR technique and numerical analysis method were compared. The maximum settlement and influence radius estimated by the InSAR technique and numerical method were found to be quite similar, which confirms the reliability of the InSAR technique. Through this case study, it was found that the InSAR technique reliable to use for estimating ground settlement and can be used as a key technology to identify the long-term ground settlement history in the absence of measurement data.

Delineation of a fault zone beneath a riverbed by an electrical resistivity survey using a floating streamer cable (스트리머 전기비저항 탐사에 의한 하저 단층 탐지)

  • Kwon Hyoung-Seok;Kim Jung-Ho;Ahn Hee-Yoon;Yoon Jin-Sung;Kim Ki-Seog;Jung Chi-Kwang;Lee Seung-Bok;Uchida Toshihiro
    • Geophysics and Geophysical Exploration
    • /
    • v.8 no.1
    • /
    • pp.50-58
    • /
    • 2005
  • Recently, the imaging of geological structures beneath water-covered areas has been in great demand because of numerous tunnel and bridge construction projects on river or lake sites. An electrical resistivity survey can be effective in such a situation because it provides a subsurface image of faults or weak zones beneath the water layer. Even though conventional resistivity surveys in water-covered areas, in which electrodes are installed on the water bottom, do give high-resolution subsurface images, much time and effort is required to install electrodes. Therefore, an easier and more convenient method is sought to find the strike direction of the main zones of weakness, especially for reconnaissance surveys. In this paper, we investigate the applicability of the streamer resistivity survey method, which uses electrodes in a streamer cable towed by ship or boat, for delineating a fault zone. We do this through numerical experiments with models of water-covered areas. We demonstrate that the fault zone can be imaged, not only by installing electrodes on the water bottom, but also by using floating electrodes, when the depth of water is less than twice the electrode spacing. In addition, we compare the signal-to-noise ratio and resolving power of four kinds of electrode arrays that can be adapted to the streamer resistivity method. Following this numerical study, we carried out both conventional and streamer resistivity surveys for the planned tunnel construction site located at the Han River in Seoul, Korea. To obtain high-resolution resistivity images we used the conventional method, and installed electrodes on the water bottom along the planned route of the tunnel beneath the river. Applying a two-dimensional inversion scheme to the measured data, we found three distinctive low-resistivity anomalies, which we interpreted as associated with fault zones. To determine the strike direction of these three fault zones, we used the quick and convenient streamer resistivity.

Pixel-level Crack Detection in X-ray Computed Tomography Image of Granite using Deep Learning (딥러닝을 이용한 화강암 X-ray CT 영상에서의 균열 검출에 관한 연구)

  • Hyun, Seokhwan;Lee, Jun Sung;Jeon, Seonghwan;Kim, Yejin;Kim, Kwang Yeom;Yun, Tae Sup
    • Tunnel and Underground Space
    • /
    • v.29 no.3
    • /
    • pp.184-196
    • /
    • 2019
  • This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.

An Extended Multicast Connectivity Solution for Remote Multi-party Collaborative Environment (원격 다자간 협업 환경을 위한 확장된 멀티캐스트 연결성 솔루션)

  • Kim, Nam-Gon;Kim, Jong-Won
    • 한국HCI학회:학술대회논문집
    • /
    • 2007.02a
    • /
    • pp.262-267
    • /
    • 2007
  • 다자간 분산형 협업 시스템인 Access Grid(AG)는 IP 멀티캐스트 네트워크상에서 여러 사용자들 간에 영상, 음성 및 다양한 데이터의 공유를 통해 상호 의사소통이 가능한 공동 작업환경을 제공하기 위해 개발되었다. 멀티캐스트를 사용함으로써 AG는 대역폭 효율적으로 다수 사용자 사이의 의사소통 환경을 제공하고 있다. 그러나 IP 멀티캐스트의 설정 및 관리상 복잡성으로 인해 이를 지원하지 않는 네트워크가 다수 존재한다. 이는 AG를 이용한 협업 서비스를 이용하는 데에 큰 장애물이 되고 있다, 본 논문에서는 이러한 멀티캐스트 연결성 문제에 대한 해결책으로 응용 계층의 멀티캐스트 터널링 프로토콜인 UMTP (UDP multicast tunneling protocol) 를 확장한 멀티캐스트 연결성 솔루션인 AG Connector를 제안한다.

  • PDF

Investigation of Concrete Flaw Using Seismic First Arrival (탄성파 초동주시를 이용한 콘크리트 구조물의 결함 탐지)

  • 서백수;장선웅;김석현;서정희
    • Tunnel and Underground Space
    • /
    • v.11 no.2
    • /
    • pp.120-121
    • /
    • 2001
  • The purpose of this study is to investigate concrete flaw using seismic first arrival and various inversion method. Seismic wave propagation was calculated using finite element method in theoretical modelling and tomogram was made using various inversion methods in theoretical and experimental modelling. Five steps of seismic first arrival were selected from FEM results and these data were used to calculate seismic velocity section. According to the results, exact seismic first arrival picking method was proposed and experimental modelling was conducted.

  • PDF

Development of Vision-Based Inspection System for Detecting Crack on the Lining of Concrete Tunnel (비젼센서를 이용한 콘크리트 터널 라이닝 균열검사 시스템의 개발)

  • 고봉수;조남규
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.20 no.12
    • /
    • pp.96-104
    • /
    • 2003
  • To assess tunnel safety, cracks in tunnel lining are measured by inspectors who observe cracks with their eyes. A manual inspection is, however, slow and subjective. This paper, therefore, proposes vision-based inspection system for measuring cracks in the tunnel lining that inspects cracks fast and objective. The system is consisted of an on-vehicle system and a lab system. An on-vehicle system acquires image data with line CCD camera. A lab system extracts crack then inform their thickness, length and orientation by using image processing. To improve accuracy of crack recognition the geometric properties of a crack was applied to image processing. The proposed system were verified with experiments in both laboratory and field environment.