• Title/Summary/Keyword: 비접촉식 탐지

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The Design and Test of the Stand-off Surface Chemical Contaminant Detection System based on Raman Spectroscopy (비접촉식 지표면 화학 오염 탐지용 라만 분광시스템 설계 및 성능확인)

  • Koh, Young Jin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.3
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    • pp.433-440
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    • 2019
  • In order to detect toxic chemical spread on field ground, we developed stand-off Raman spectrometer system which employed a deep UV laser. In this paper, the design and specification of various components in the spectrometer system are described. Some results when the detection system was tested on the outdoor roads are shown, which may help researching stand-off chemical detectors based on Raman spectroscopy.

Non-contact Impact-Echo Based Detection of Damages in Concrete Slabs Using Low Cost Air Pressure Sensors (저비용 음압센서를 이용한 콘크리트 구조물에서의 비접촉 Impact-Echo 기반 손상 탐지)

  • Kim, Jeong-Su;Lee, Chang Joon;Shin, Sung Woo
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.15 no.3
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    • pp.171-177
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    • 2011
  • The feasibility of using low cost, unpowered, unshielded dynamic microphones is investigated for cost effective contactless sensing of impact-echo signals in concrete structures. Impact-echo tests on a delaminated concrete slab specimen were conducted and the results were used to assess the damage detection capability of the low cost system. Results showed that the dynamic microphone successfully captured impact-echo signals with a contactless manner and the delaminations in concrete structures were clearly detected as good as expensive high-end air pressure sensor based non-contact impact-echo testing.

Architectural Cultural Heritage Crack Detection Techniques Using Object Detection (객체 탐지를 이용한 건축 문화재 크랙 탐지 기법)

  • Kim, Inki;Lim, Hyunseok;Kim, Beom-Jun;Gwak, Jeonghwan
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.649-652
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    • 2021
  • 본 논문에서는 노후화된 목조·석조 건축물의 균열을 탐지하는 기법을 소개한다. 본 기법의 목적은 석조·목조 문화재의 시간의 흐름에 따른 관리 소홀, 균열(벌레, 날씨, 기온 등), 배부름 현상에 의한 문화재의 손상을 사전에 방지하기 위함이다. 기존에 존재하는 목조·석조 건축물의 균열, 노후, 배부름 등 다양한 결함과 변형의 탐지 방법은 접촉식 센서를 이용하여 탐지를 해왔지만, 문화재 자체의 미관을 해칠 뿐 아니라 문화재를 추가로 훼손할 가능성이 있다는 문제점이 제시되었다. 이 문제를 해결하기 위해 문화재 비 접촉형 탐지 기법을 사용한다. CCTV 및 DSLR과 같은 관측장비로 촬영한 영상정보를 기반으로 문화재의 결함과 변형을 AI 영상분석 기반 방법으로 판단하는 문제를 제안한다.

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Development of Post-Processing Software for Flow Measurement Results Analysis using RQ-30 (RQ-30을 활용한 유량 측정 결과 분석을 위한 후처리 소프트웨어 개발)

  • Geunsoo Son;JungHwan Chun;Seongcheol Kang;Youngbeen Kwon;Youngsin Roh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.420-420
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    • 2023
  • 하천의 유량 자료는 하천 관리에 필수적인 요소로, 지속적인 유량측정을 위해 국가 유량 측정망을 구성하여 주요 지점을 대상으로 유량 측정을 수행하고 있다. 측정된 유량자료는 일반적으로 수위-유량 관계곡선식을 개발하여 제공되고 있으며, 홍수파와 배수 영향 등으로 인해 수위-유량 관계곡선식에서 발생하는 산포로 인한 신뢰도에 문제가 우려되는 경우에는 실시간의 정확한 유량자료를 제공하기 위해 H-ADCP를 설치하여 지표유속법 기반의 실시간 유량 자료 생산하여 제공하고 있다. 그러나 H-ADCP를 이용한 유량 측정 방법은 장비의 한계로 인해 상대적으로 규모가 작고 수심이 얕은 하천에 적용하기 어려운 문제가 있다. 따라서, 최근에는 자동유량관측소 지점 확대를 위해 비접촉식 유속계를 활용한 자동유량관측소 운영이 점차 고려되고 있다. 이에 따라 비접촉식유속계를 이용한 유량 측정 결과의 검증 및 유지 관리를 위한 소프트웨어가 필요하다. 이에 본 연구에서는 비접촉식유속계 중 전자파를 이용하여 수표면의 표면유속을 측정할 수 있는 장비인 RQ-30의 측정결과를 분석하기 위해 Microsoft Visual Studio(C#) 사용하여 측정결과의 검토 및 자료 관리를 위한 후처리 소프트웨어를 개발하였다. 개발한 소프트웨어는 측정 원시자료를 읽고, 도시하여 측정 결과를 확인할 수 있으며, 머신러닝 기반의 알고리즘을 적용하여 수위 및 유속 시계열 자료에서 발생하는 이상치를 탐색할 수 있도록 개발하였다. 그리고 탐지된 이상치에 대한 보정을 위해 선형보간, LOESS, SuperSmoother를 사용하여 이상치를 보정하여 결과를 도출할 수 있도록 개발하였다. 추후 본 연구를 통해 개발된 프로그램을 활용하여 측정 자료의 유지 관리 효율성을 증대시킬 수 있을 것으로 기대되며, 지속적인 프로그램의 개선을 통해서 실무적으로 활용이 가능할 것으로 판단된다.

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Denoising Autoencoder based Noise Reduction Technique for Raman Spectrometers for Standoff Detection of Chemical Warfare Agents (비접촉식 화학작용제 탐지용 라만 분광계를 위한 Denoising Autoencoder 기반 잡음제거 기술)

  • Lee, Chang Sik;Yu, Hyeong-Geun;Park, Jae-Hyeon;Kim, Whimin;Park, Dong-Jo;Chang, Dong Eui;Nam, Hyunwoo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.24 no.4
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    • pp.374-381
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    • 2021
  • Raman spectrometers are studied and developed for the military purposes because of their nondestructive inspection capability to capture unique spectral features induced by molecular structures of colorless and odorless chemical warfare agents(CWAs) in any phase. Raman spectrometers often suffer from random noise caused by their detector inherent noise, background signal, etc. Thus, reducing the random noise in a measured Raman spectrum can help detection algorithms to find spectral features of CWAs and effectively detect them. In this paper, we propose a denoising autoencoder for Raman spectra with a loss function for sample efficient learning using noisy dataset. We conduct experiments to compare its effect on the measured spectra and detection performance with several existing noise reduction algorithms. The experimental results show that the denoising autoencoder is the most effective noise reduction algorithm among existing noise reduction algorithms for Raman spectrum based standoff detection of CWAs.

Radiant Energy Filtering to Enhance High Temperature Measurement by a Thermography System (고온 계측 열화상 시스템 구현을 위한 복사에너지 필터링 연구)

  • Yoon, Seok Tae;Cho, Yong Jin;Jung, Ho Seok
    • Journal of the Korean Society for Nondestructive Testing
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    • v.36 no.6
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    • pp.466-473
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    • 2016
  • In a shipbuilding process, thermal damage to the ship structure at the rear end results from an excessive heat input and conduction during welding process. To prevent such damage, appropriate control of the heat input, based on welding temperature measurement, is required. For temperature measurement, contact and non-contact methods are available; the thermography system is a popular non-contact temperature measurement. When the intensity of radiation from a high-temperature object is excessive, however, detecting the sensors of ordinary thermography systems leads to an inability in measuring the temperature due to saturation. Hence, this study suggests use of a neutral density filter that prevents an excessive amount of radiation from being accumulated in a thermography system, and thus makes it possible to quantitatively measure an object's temperature as high as $3000^{\circ}C$.

3-dimensional Coordinate Measurement by Pulse Magnetic Field Method (자기적 방법을 이용한 3차원 좌표 측정)

  • Im, Y.B.;Cho, Y.;Herr, H.B.;Son, D.
    • Journal of the Korean Magnetics Society
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    • v.12 no.6
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    • pp.206-211
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    • 2002
  • We have constructed a new kind of magnetic motion capture sensor based on the pulse magnetic field method. 3-orthogonal magnetic pulse fields were generated in turns only one period of sinusoidal waveform using 3-orthogonal magnetic dipole coils, ring counter and analog multiplier. These pulse magnetic fields were measured with 3-orthogonal search coils, of which induced voltages by the x-, y-, and l-dipole sources using S/H amplifier at the time position of maximum induced voltage. Using the developed motion capture sensor, we can measure position of sensor with uncertainty of ${\pm}$0.5% in the measuring range from ${\pm}$0.5 m to ${\pm}$1.5 m.

A Study on the Shape Evaluation using Non-contact Electromagnetic Measurement System (비접촉식 전자기 측정 시스템에서 자성물체의 형상판정에 관한 연구)

  • Kim, Jae-Min;Yun, Seung-Ho;Won, Hyuk;Park, Gwan-Soo
    • Journal of the Korean Magnetics Society
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    • v.20 no.2
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    • pp.45-51
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    • 2010
  • We suggest the algorithm that it detects volume and shape according with a variation of magnetic field in non-contact electromagnetic measurement system. It is possible to assess an object shape through a variation of magnetic field. The basic idea is compared a length difference with a variation of magnetic field in a detected object and a circle which modeled equivalent area. And the shape is detected to many calibration process that it is similar to signal pattern between a length difference and a variation of magnetic field in object and equivalent circle. This is the shape detection algorithm that use only the variation of magnetic field. In this paper, it has application to the shape detection algorithm about the object as hexagon, pentagon, rectangle, trigon. we can detect the object shape easily because the shape detection algorithm is only used to the variation of magnetic field.

Estimation of Bridge Vehicle Loading using CCTV images and Deep Learning (CCTV 영상과 딥러닝을 이용한 교량통행 차량하중 추정)

  • Suk-Kyoung Bae;Wooyoung Jeong;Soohyun Choi;Byunghyun Kim;Soojin Cho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.3
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    • pp.10-18
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    • 2024
  • Vehicle loading is one of the main causes of bridge deterioration. Although WiM (Weigh in Motion) can be used to measure vehicle loading on a bridge, it has disadvantage of high installation and maintenance cost due to its contactness. In this study, a non-contact method is proposed to estimate the vehicle loading history of bridges using deep learning and CCTV images. The proposed method recognizes the vehicle type using an object detection deep learning model and estimates the vehicle loading based on the load-based vehicle type classification table developed using the weights of empty vehicles of major domestic vehicle models. Faster R-CNN, an object detection deep learning model, was trained using vehicle images classified by the classification table. The performance of the model is verified using images of CCTVs on actual bridges. Finally, the vehicle loading history of an actual bridge was obtained for a specific time by continuously estimating the vehicle loadings on the bridge using the proposed method.

A Terrestrial LiDAR Based Method for Detecting Structural Deterioration, and Its Application to Tunnel Maintenance (터널 유지관리를 위한 지상 LiDAR 기반의 구조물 변상탐지 기법 연구)

  • Bae, Sang Woo;Kwak, Jae Hwan;Kim, Tae Ho;Park, Sung Wook;Lee, Jin Duk
    • The Journal of Engineering Geology
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    • v.25 no.2
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    • pp.227-235
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    • 2015
  • In recent years, owing to the frequent occurrence of natural disasters, the inspection and maintenance of structures have become increasingly important on a national scale. However, because most structural inspections are carried out manually, and due to the lack of objectivity in data acquisition, quantitative data are not always available. As a result, researchers are seeking ways to collect and standardize survey data using terrestrial laser scanning, thereby bypassing the limitations associated with visual investigations. However, field data acquired using a laser scanner have been required to measure changes in structure geometry resulting from passive deterioration. In this study, we demonstrate that it is possible to identify the processes of structural deterioration (e.g., efflorescence, leakage, delamination) using intensity data from terrestrial laser scanning. Additionally, we confirm the viability of automated classification of alteration type and objectification of the polygon area by establishing intensity characteristics. Finally, we show that our method is effective for structural inspection and maintenance.