• 제목/요약/키워드: Rebar Detection

검색결과 33건 처리시간 0.025초

RC 구조물의 Eddy Current 기반 철근부식 감지 센서에 관한 실험적 연구 (Experimental Study on Eddy Current based-on Corrosion Detection Sensor for RC structure)

  • 양현민;이한승
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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    • pp.260-261
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    • 2019
  • Corrosion of rebar embedded reinforced concrete is the main cause of collapse and degradation of reinforced concrete structure that many researches are recently focused on these works. Methods of evaluating rebar corrosion are divided into physical and electrochemical methods. However, the result of Conventional methods are less reliable due to effect of internal and external environments. In this study, rebar corrosion detection sensor for embedded rebar of RC structures is evaluated through immersion test in NaCl solustion for 160hours. From the results, Rebar corrosion was ongoing and corrosion products are produced on rebar surface. The voltage is decreased as amount of corrosion production increased.

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다중 코일에 의한 콘크리트내의 철근 탐지 시 신호 특성 (Signal Characteristics of Multi-coil Probe for the Test of Reinforcement Embedded in Concrete)

  • 김영주;이승석;윤동진
    • 비파괴검사학회지
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    • 제20권4호
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    • pp.285-289
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    • 2000
  • 본 연구는 콘크리트내의 철근의 굵기와 깊이를 동시에 측정할 수 있는 기술 개발에 관한 것이다. 개발된 탐촉자는 기존의 철근 탐지기와 다른 구조를 지니는데 감지 코일이 세 개로 구성되어 있다. 따라서 세 가지 신호를 동시에 측정하여 분석함으로써 철근의 굵기와 깊이를 분석하도록 되어 있다. 탐촉자 내 코일의 전압과 위상 변화를 임피던스 분석기를 이용하여 조사하고 그 전달함수의 괘적을 분석하였다. 여기 코일 내부에 장착된 감지 코일은 알려진 바와 같이 단순한 변화 형태를 나타내었으나 여기 코일 밖에 장착된 코일의 경우 변화 곡선이 복잡하였다. 실제 철근탐지 실험은 일반 와전류 탐상기를 이용하였는데 여러 가지 철근의 굵기와 깊이에 대하여 실험하였다. 철근 깊이에 따른 신호 변화는 임피던스 분석기에 의한 전달함수 변화에서 나타낸 것과 비슷한 경향을 나타내었으며 감지 코일마다 다른 전압의 변화를 이용하여 철근의 굵기와 깊이의 동시 측정이 가능하였다.

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BIM-Based Simulator for Rebar Placement

  • Park, U-Yeol
    • 한국건축시공학회지
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    • 제12권1호
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    • pp.98-107
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    • 2012
  • Reinforcing bars (rebar) comprise an integral part of a concrete structure, and play a major role in the safety and durability of the building. However, the actual placement or installation of rebar is not planned and controlled by the detailer. Recently, 4D simulations, using 3D model and scheduling software, have been used to improve the efficiency of the construction phrase. However, 4D simulators have not been introduced at the detailed level of work, such as rebar placement. Therefore, this paper suggests a BIM-based simulator for rebar placement to determine the sequence with which rebar is placed into the form. The system using Autodesk Revit API automatically generates rebar placement plans for a building structure, and labels the placement sequence of each individual bar or set of bars with ascending numbers. The placement sequence is then visualized using Autodesk Revit Structure 2012. This paper provides a short description of a field assessment and limits.

전기화학적 부식촉진 기법을 이용한 철근 콘크리트 부식의 영향평가 (Application of Electrochemical Accelerated Corrosion Technique to Detection of Reinforcing Corrosion in Concrete)

  • 이수열;이재봉;정영수
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 1999년도 학회창립 10주년 기념 1999년도 가을 학술발표회 논문집
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    • pp.675-678
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    • 1999
  • Rebar corrosion in concrete containing both chloride ions and calcium nitrite inhibitors were investigated by the various electrochemical methods. Rebar corrosion was accelerated by applying the impressed current to the rebar in concrete. Effect of chloride content and inhibitors on rebar corrosion were evaluated. Accelerated corrosion technique is the method to measure the time to the initiation of cracks of reinforced concretes, by applying constant voltage between rebar and the stainless steel cathedes. The increase of concentration of chloride ions in concrete result in the increase in anodic currents and the reduction of time to crack. However addition of inhibitors did not improve corrosion resistance of rebar in concrete. Rebar corrosion in concrete with chloride ions and inhibitors was also analyzed by the immersed tests though the mesurement of corrosion potentials.

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Rebar Spacing Fixing Technology using Laser Scanning and HoloLens

  • Lee, Yeongjoo;Kim, Jeongseop;Lee, Jin Gang;Kim, Minkoo
    • 한국건설관리학회논문집
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    • 제25권2호
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    • pp.69-80
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    • 2024
  • Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

Automatic assessment of post-earthquake buildings based on multi-task deep learning with auxiliary tasks

  • Zhihang Li;Huamei Zhu;Mengqi Huang;Pengxuan Ji;Hongyu Huang;Qianbing Zhang
    • Smart Structures and Systems
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    • 제31권4호
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    • pp.383-392
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    • 2023
  • Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

On the use of numerical models for validation of high frequency based damage detection methodologies

  • Aguirre, Diego A.;Montejo, Luis A.
    • Structural Monitoring and Maintenance
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    • 제2권4호
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    • pp.383-397
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    • 2015
  • This article identifies and addresses current limitations on the use of numerical models for validation and/or calibration of damage detection methodologies that are based on the analysis of the high frequency response of the structure to identify the occurrence of abrupt anomalies. Distributed-plasticity non-linear fiber-based models in combination with experimental data from a full-scale reinforced concrete column test are used to point out current modeling techniques limitations. It was found that the numerical model was capable of reproducing the global and local response of the structure at a wide range of inelastic demands, including the occurrences of rebar ruptures. However, when abrupt sudden damage occurs, like rebar fracture, a high frequency pulse is detected in the accelerations recorded in the structure that the numerical model is incapable of reproducing. Since the occurrence of such pulse is fundamental on the detection of damage, it is proposed to add this effect to the simulated response before it is used for validation purposes.

다중벽 탄소나노튜브를 이용한 철근 부식 검출 센서 제작 연구 (A study on the Corrosion Detection Sensor using Multi-Wall Carbon Nanotube)

  • 박수빈;김성연;이수정;최문정;홍영준;권성준;유봉영;윤상화
    • 한국표면공학회지
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    • 제54권4호
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    • pp.194-199
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    • 2021
  • In this study, rebar corrosion detection sensor was fabricated using multi-walled carbon nanotubes (MWCNTs). MWCNTs were pre-treated in the acid electrolytes to attach the carboxylic acid to the surface of MWCNTs. The fabricated sensor was attached on the surface of rebar and it detected the corrosion of steel using LCR meter with variation of capacitance. The surface morphology and electrical properties were characterized using scanning electron microscope (SEM) and electrical test equipment, respectively. To verify the corrosion detection characteristics, comparison experiment using plastic bar was performed. Moreover, mechanism of corrosion detection sensor was discussed.