• 제목/요약/키워드: underground detection

검색결과 218건 처리시간 0.028초

GPR을 이용한 토조의 공동 탐사 (Cavity Detection of Chamber by GPR)

  • 이현호
    • 한국구조물진단유지관리공학회 논문집
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    • 제20권2호
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    • pp.86-93
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    • 2016
  • 본 연구에서는 토조에 설치한 관의 종류 및 매립 깊이, 공동 깊이 및 포장 조건 등에 대한 GPR(Ground Penetrating Radar) 탐사를 진행하여 매립관의 종류 및 공동 탐사 능력을 실험적으로 규명하였다. 아스팔트 포장 및 비포장의 경우, 콘크리트 포장 및 철근 콘크리트 포장 대비 매립관의 탐사가 용이한 것으로 평가되었다. 또한 공기 공동의 경우, 매립 깊이 1 m에서는 탐지가 가능한 것으로 평가되었다.

지하구조물 콘크리트 균열 탐지를 위한 semi-supervised 의미론적 분할 기반의 적대적 학습 기법 연구 (Adversarial learning for underground structure concrete crack detection based on semi­supervised semantic segmentation)

  • 심승보;최상일;공석민;이성원
    • 한국터널지하공간학회 논문집
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    • 제22권5호
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    • pp.515-528
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    • 2020
  • 통상적으로 콘크리트 지하 구조물은 수십 년 이상 사용할 수 있도록 설계되지만 최근 들어 구조물 중 상당수가 당초의 기대 수명에 근접하고 있는 실정이다. 그 결과 구조물 고유의 기능이 상실되고 다양한 문제가 야기될 수 있어 신속한점검과 보수가 요구되고 있다. 이를 위해 지금까지는 지하 구조물 유지관리를 위하여 인력 기반의 점검과 보수가 진행되었으나 최근에는 인공지능과 영상 기술의 융합을 통한 객관적인 점검 기술 개발이 활발하게 이루어지고 있다. 특히 딥러닝을 활용한 영상 인식 기술을 적용하여 지도학습 기반의 콘크리트 균열 탐지 알고리즘 개발에 관한 연구가 다양하게 진행되고 있다. 이러한 연구들은 대부분 지도학습 형태 영상 인식 기술로 많은 양의 데이터를 바탕으로 개발이 되는데, 그 중에도 많은 수의 라벨 영상(Label image)이 요구된다. 이를 확보하기 위해서는 현실적으로 많은 시간과 노동력이 필요한 실정이다. 본 논문에서는 이와 같은 문제를 개선하고자 적대적 학습 기법을 적용하여 균열 영역 탐지 정확도를 평균적으로 0.25% 향상시키는 방법을 기술하고자 한다. 이 적대적 학습은 분할(Segmentation) 신경망과 판별자(Discriminator) 신경망으로 구성되어 있고, 가상의 라벨 영상을 경쟁적인 구조로 생성하여 인식 성능을 높이는 알고리즘이다. 본 논문에서는 이 같은 방법을 활용하여 효율적인 심층 신경망 학습 방법을 제시하였고, 향후에 정확한 균열 탐지에 활용될 것으로 기대한다.

Energy and Air Quality Benefits of DCV with Wireless Sensor Network in Underground Parking Lots

  • Cho, Hong-Jae;Jeong, Jae-Weon
    • 국제초고층학회논문집
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    • 제3권2호
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    • pp.155-165
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    • 2014
  • This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

배관-유체 연성진동을 이용한 누수지점 탐지알고리듬 개발연구 (An Algorithm for Leak Locating using Coupled Vibration of Pipe-Water)

  • Lee, Yeong-Seop;Yun, Dong-Jin
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 춘계학술대회논문집
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    • pp.985-990
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    • 2004
  • Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

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배관-유체 연성진동을 이용한 누수지점 탐지 알고리듬 개발 연구 (An Algorithm for Leak Locating using Coupled Vibration of Pipe-Fluid)

  • 이영섭;윤동진
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 춘계학술대회
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    • pp.798-803
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    • 2004
  • Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband sound from a leak location and this sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

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시간지연 추정을 통한 누수위치 식별 연구 (Time Delay Estimation for the Identification of Leak Location)

  • 이영섭;윤동진;김치엽
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 추계학술대회논문집
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    • pp.327-332
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    • 2004
  • Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than loom.

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GPR 영상에서 딥러닝 기반 CNN을 이용한 배관 위치 추정 연구 (A Study on the Pipe Position Estimation in GPR Images Using Deep Learning Based Convolutional Neural Network)

  • 채지훈;고형용;이병길;김남기
    • 인터넷정보학회논문지
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    • 제20권4호
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    • pp.39-46
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    • 2019
  • 최근에 지하공동이나 배관의 위치 파악 등의 필요에 의해 금속을 포함하여 다양한 재질의 지하 물체를 탐지하는 일이 중요해지고 있다. 이러한 이유로 지하 탐지 분야에서 GPR(Ground Penetrating Radar) 기술이 주목을 받고 있다. GPR은 지하에 묻혀 있는 물체의 위치를 찾기 위하여 레이더파를 조사하고 물체로부터 반사되는 반사파를 영상으로 표현한다. 그런데 레이더 신호는 지하에서 여러가지 물체에서 반사되어 나오는 특징이 물체마다 유사한 경우가 많기 때문에 GPR 영상을 해석하는 것은 쉽지 않다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해서 영상 인식 분야에서 최근에 많이 활용되고 있는 딥러닝 기반의 CNN(Convolutional Neural Network)모델을 이용하여 임계값에 따른 GPR 영상에서의 배관 위치를 추정하고 그 실험 결과 임계값이 7 혹은 8 일 때 가장 확실하게 배관의 위치를 찾음을 증명하였다.

22.9kV 다중 접지 지중 전력 케이블의 가압 상태 진단에 관한 기초 연구 (A Study on Diagnosis of The Energized Status of 22.9kV Multigrounded Underground Power Cable)

  • 김창교;홍진수;정영호
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제48권10호
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    • pp.699-703
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    • 1999
  • An experimental study to identify the energized status of the 22.9kV underground power cable by the detection of vibration has been performed. We have derived that there exists vibration at double the line frequency in live cables by electromagnetic force. The relative amplitudes of the cable vibration according to the energized status of the cable were calculated by computer simulation. The cable vibration can also be picked up by accelerometer. A prototype was tested on the underground distribution system in Chonan substation, KEPCO. Comparison between simulation results and field test results was performed. The results showed that the energized status of the calble can be identified by measuring the vibration of the cable using accelerometer.

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화재 발생시 환기방식에 따른 지하공동구내 열유동 특성 연구 (Characteristics of Fire-induced Thermal-Flowfields in an Underground Utility Tunnel with Ventilation)

  • 김홍식;황인주;김윤제
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.1845-1850
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    • 2003
  • The underground utility tunnels are important facility as a mainstay of country because of communication developments. The communication and electrical duct banks as well as various utility lines for urban life are installed in the underground utility tunnel systems. If a fire breaks out in this life-line tunnel, the function of the city will be discontinued and the huge damages are occurred. In order to improve the safety of life-line tunnel systems and the fire detection, the behaviors of the fire-induced smoke flow and temperature distribution are investigated. In this study we assumed that the fire is occurred at the contact or connection points of cable. Numerical calculations are carried out using different velocity of ventilation in utility tunnel. The fire source is modeled as a volumetric heat source. Three-dimensional flow and thermal characteristics in the underground tunnel are solved by means of FVM (Finite Volume Method) using SIMPLE algorithm and standard ${\kappa}-{\varepsilon}$ model for Reynolds stress terms. The numerical results of the fire-induced flow characteristics in an underground utility tunnel with different velocity of ventilation are graphically prepared and discussed.

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상수도관로의 주변 지반침하 위험도 평가를 위한 안전감시 센서 (Safety Monitoring Sensor for Underground Subsidence Risk Assessment Surrounding Water Pipeline)

  • 곽필재;박상혁;최창호;이현동
    • 센서학회지
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    • 제24권5호
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    • pp.306-310
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    • 2015
  • IoT(Internet of Things) based underground risk assessment system surrounding water pipeline enables an advanced monitoring and prediction for unexpected underground hazards such as abrupt road-side subsidence and urban sinkholes due to a leak in water pipeline. For the development of successful assessment technology, the PSU(Water Pipeline Safety Unit) which detects the leakage and movement of water pipes. Then, the IoT-based underground risk assessment system surrounding water pipeline will be proposed. The system consists of early detection tools for underground events and correspondence services, by analyzing leakage and movement data collected from PSU. These methods must be continuous and reliable, and cover certain block area ranging a few kilometers, for properly applying to regional water supply changes.