• 한국물환경학회지
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• 제29권3호
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• pp.343-353
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• 2013

Flow duration curve (FDC) can be developed by linking the daily flow data of stream flow monitoring network to 8-day interval flow data of the unit watersheds for the management of Total Maximum Daily Loads. This study investigated the applicable method for the development of long term FDC with the selection of the stream flow reference sites, and suggested the development of the FDC in 4 river basins. Out of 142 unit watersheds in 4 river basins, 107 unit watersheds were shown to estimate daily flow data for the unit watersheds from 2006 to 2010. Short term FDC could be developed in 64 unit watersheds (45%) and long term FDC in 43 unit watersheds (30%), while other 35 unit watersheds (25%) were revealed to have difficulties in the development of FDC itself. Limits in the development of the long term FDC includes no stream monitoring sites in certain unit watersheds, short duration of stream flow data set and missing data by abnormal water level measurements on the stream flow monitoring sites. To improve these limits, it is necessary to install new monitoring sites in the required areas, to keep up continuous monitoring and make normal water level observations on the stream flow monitoring sites, and to build up a special management system to enhance data reliability. The development of long term FDC for the unit watersheds can be established appropriately with the normal and durable measurement on the selected reference sites in the stream flow monitoring network.

• 한국구조물진단유지관리공학회 논문집
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• 제2권3호
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• pp.194-204
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• 1998

This study was performed to suggest the proper maintenance method for the deteriorated gerber type PC box girder bridge by using the long term displacement monitoring data. For this study, the monitoring system which can measure the long term displacement and the concrete surface temperature was designed and operated. From the measurement and structural analysis results, the cause of the permanent deformation which the bridge has already was estimated, and based on this result, the allowable permanent displacement value at the hinge was suggested. From this study, it was known that the long term monitoring system can be applied to the active maintenance of the deteriorated bridge and the suggested allowable permanent displacement could be used for the maintenance of the bridge.

• Journal of Advanced Marine Engineering and Technology
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• 제39권4호
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• pp.483-488
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• 2015

본 논문에서는 엔진유지관리 개선을 위해 Web 기반 선박엔진성능분석용 장기모니터링시스템을 구현하고자 한다. 이 시스템은 시뮬레이터, 다채널 A/D 변환기가 내장된 감시모듈, 모니터링 컴퓨터, 네트워크저장기(NAS), RS485 및 무선인터넷 통신시스템으로 구성된다. 기존 제품은 각 엔진마다 압력센서를 설치하고 이를 감시모듈에서 실시간으로 계측한 후 통신에 의해 현장 제어실 PC나 Web 상에서 모니터링이 가능하지만 많은 샘플링 압력데이터 용량으로 인해 통신전송속도가 느려지고, 장기모니터링에 오류가 발생할 수 있다. 이와 같은 문제점을 개선하기 위하여 본 논문에서는 각 실린더별 압력센서에서 받은 원본 압력데이터는 NAS에 저장하고, 원본 압력데이터를 구간별 다운샘플링을 하여 제어실에서 장기모니터링하고, Web에서의 장기모니터링을 위하여 다운샘플 데이터를 무선전송 한다. 제안한 방식에서는 전송량을 1/10로 하였으므로 작은 용량을 가진 메모리를 사용할 수 있고, 빠른 통신속도를 유지할 수 있어 통신비용이 절감되며, 화면전체에 약 30일간의 장기모니터링이 가능하여 엔진의 유지관리에 큰 기여를 할 수 있을 것으로 사료된다.

• Wind and Structures
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• 제27권6호
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• pp.357-368
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• 2018

For a long cable-stayed bridge, stay cables are its most important load-carrying components. In this paper, long-term monitoring of super-long stay cables of Sutong Bridge is introduced. A comprehensive data analysis procedure is presented, in which time domain and frequency domain based analyses are carried out. In time domain, the vibration data of several long stay cables are firstly analyzed and the standard deviation of the acceleration of stay cables, and its variation with time are obtained, as well as the relationship between in-plane vibration and out-plane vibration. Meanwhile, some vibrations such as wind and rain induced vibration are detected. Through frequency domain analysis, the basic frequencies of the stay cables are identified. Furthermore, the axial forces and their statistical parameters are acquired. To investigate the vibration deflection, an FFT-based decomposition method is used to get the modal deflection. In the end, the relationship between the vibration amplitude of stay cables and the wind speed is investigated based on correlation analysis. Through the adopted procedure, some structural parameters of the stay cables have been derived, which can be used for evaluating the component performance and corresponding management of stay cables.

• Smart Structures and Systems
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• 제31권1호
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• pp.45-56
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• 2023

Vibration-based structural health monitoring is used to ensure the safety of structures by installing sensors in structures. The peak picking method, one of the applications of vibration-based structural health monitoring, is a method that analyze the dynamic characteristics of a structure using the peaks of the frequency response function. However, the results may vary depending on the person predicting the peak point; further, the method does not predict the exact peak point in the presence of noise. To overcome the limitations of the existing peak picking methods, this study proposes a new method to automate the modal analysis process by utilizing long short-term memory, a type of recurrent neural network. The method proposed in this study uses the time series data of the frequency response function directly as the input of the LSTM network. In addition, the proposed method improved the accuracy by using the phase as well as amplitude information of the frequency response function. Simulation experiments and lab-scale model experiments are performed to verify the performance of the LSTM network developed in this study. The result reported a modal assurance criterion of 0.8107, and it is expected that the dynamic characteristics of a civil structure can be predicted with high accuracy using data without experts.

• 한국전산구조공학회논문집
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• 제29권3호
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• pp.219-227
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• 2016

이 연구에서는 현장타설 캔틸레버공법(free cantilever method)을 적용한 PSC(prestressed concrete) 교량에 콘크리트의 장기거동을 고려한 시공 중 계측분석 방법을 제안하였다. 콘크리트 박스 거더의 장기 거동에 따른 응력을 확인하기 위해 온도센서와 변형률계를 함께 설치하고 계측된 데이터를 이용하여 크리프계수를 산출하였다. 또한 크리프계수를 적용한 콘크리트 박스 거더의 시공 중 응력을 분석하고 설치된 온도 센서의 변화 데이터를 비교하여 세그먼트 시공에 따른 연직변위를 분석하였다. 연구결과, 교량의 장기 거동을 고려한 FCM 교량의 시공 중 계측은 레이저 변위계나 처짐계를 사용하지 않고 온도와 변위 데이터만을 이용하여 효율적인 분석이 가능한 것으로 나타났다.

• Geomechanics and Engineering
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• 제36권1호
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• pp.83-97
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• 2024

It is important to make reasonable prediction about the long-term deformation of high rockfill geostructures. However, the deformation is usually underestimated using the rockfill parameters obtained from laboratory tests due to different size effects, which make it necessary to identify parameters from in-situ monitoring data. This paper proposes a novel hybrid back-analysis method with a modified objective function defined for the time-dependent back-analysis problem. The method consists of two stages. In the first stage, an improved weighted average method is proposed to quickly narrow the search region; while in the second stage, an adaptive response surface method is proposed to iteratively search for the satisfactory solution, with a technique that can adaptively consider the translation, contraction or expansion of the exploration region. The accuracy and computational efficiency of the proposed hybrid back-analysis method is demonstrated by back-analyzing the long-term deformation of two high embankments constructed for airport runways, with the rockfills being modeled by a rheological model considering the influence of stress states on the creep behavior.

• Smart Structures and Systems
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• 제25권3호
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• pp.285-299
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• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• 한국농공학회논문집
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• 제49권1호
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• pp.67-76
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• 2007

Bioventing is commonly used for petroleum hydrocarbon (PHC) spills. This process provides better subsurface oxygenation, thus stimulating degradation by indigenous microorganisms. Therefore soil vapor monitoring points (VMPs) are extremely important in determining the potential effectiveness of bioventing and in long-term monitoring of bioventing progress. In this study in-situ soil gas monitoring well (GMW) was developed and presented the pilot test results which recover the contaminated site by bioventing method. The result of application was successful and it was expected that GMW developed could be applied to the evaluation procedure of bioventing effectiveness and long-term remediation potential.

• Structural Monitoring and Maintenance
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• 제5권1호
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• pp.51-65
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• 2018

A number of sensing techniques have been implemented for detecting defects in civil infrastructures instead of onsite human inspections in structural health monitoring. However, the issue of faults in sensors has not received much attention. This issue may lead to incorrect interpretation of data and false alarms. To overcome these challenges, this article presents a deep learning-based method with a new architecture of Stateful Long Short Term Memory Neural Networks (S-LSTM NN) for detecting sensor fault without going into details of the fault features. As LSTMs are capable of learning data features automatically, and the proposed method works without an accurate mathematical model. The detection of four types of sensor faults are studied in this paper. Non-stationary acceleration responses of a three-span continuous bridge when under operational conditions are studied. A deep network model is applied to the measured bridge data with estimation to detect the sensor fault. Another set of sensor output data is used to supervise the network parameters and backpropagation algorithm to fine tune the parameters to establish a deep self-coding network model. The response residuals between the true value and the predicted value of the deep S-LSTM network was statistically analyzed to determine the fault threshold of sensor. Experimental study with a cable-stayed bridge further indicated that the proposed method is robust in the detection of the sensor fault.