Earticle

연구목적: 터널구조물 유지관리계측의 현장점검 결과를 분석하여 개선방안을 제시한다. 연구방법: 도 심지에서 건설되고 있는 서울지하철○호선 14개 공구의 터널구조물을 대상으로 유지관리계측에 대한 다양한 항목의 문제점을 조사하고 분석을 실시하였다. 연구결과: 유지관리 계측 항목과 계측수량 및 설 치위치는 개착터널과 굴착터널로 구분하여 개선방안을 제시하였다. 계측기기의 내구연한은 각종 기준 을 검토하였고, 내구성 확인방법은 계측센서의 승인 및 검수, 검사 및 시험, 검정 및 교정 등의 개선방안 을 제시하였다. 결론: 터널구조물 유지관리계측의 개선방안을 건설현장에 적용하면 유지관리계측의 효율성이 증대되고 건설계측 기술발전에 기여할 것이다.

Purpose: Analyze the results of on-site inspection of the tunnel structure maintenance management monitoring and suggest improvement plans. Method: We investigate and analyze the problems of various items on maintenance monitoring of tunnel structure of 14 subway lines of Seoul subway in downtown area. Result: The maintenance monitoring items, measurement quantity and installation location are classified into open tunnel and excavation tunnel and improvement plans are suggested respectively. Various durability criteria of the measuring instruments were examined, and durability confirmation method suggested improvement measures such as approval, inspection, inspection and testing, calibration of monitoring sensors. Conclusion: Applying the improvement measures of the tunnel structure maintenance monitoring to the construction site will increase the efficiency of the maintenance monitoring and contribute to the development of construction monitoring technology.

경부고속철도 2단계구간 3개의 장대터널 유지관리 계측센서의 총 손망실율은 19.5%로이며, 터널별 손망실율이 높은 순서 는 원효터널 28.2%, 금정터널 19.5% 복안터널 8.0%순서로 나타났다. 8종류의 계측센서별 손망실율이 가장 큰 순서는 진동계와 사면변위계 100%, 전단면내공변위계 32.4%, 라이닝응력계 18.4%, 철근응력계 13.2%, 간극수압계 1.6%, 암반응력계와 건물경사계 0%로 나타났다.

수서평택고속철도 2개의 장대터널 유지관리 계측센서의 총 손망실율은 7.9%이며, 터널별 손망실율은 율현터널 8.2%, 통복 터널 2.2%로 나타났다. 8종류의 계측센서별 손망실율이 큰 순서는 전단면내공 변위계 10.6%, 토압계 8.3%, 철근응력계 7.3%, 라이닝응력계 7.1%, 간극수압계 3.3%, 종단면 침하계, 3D균열측정계, 부등침하계는 0%로 나타났다.

연구목적: 본 연구는 국내와 국외의 도시 및 고속철도터널 유지관리 계측센서의 손망실 현 황을 조사하고 분석을 실시하였다. 연구방법: 도시철도터널 유지관리 계측센서 설치 후 5년에서 6년의 손망실율은 서울 지하 철5,6,7,9호선은 14.2%에서 14.8%, 영국의 Channel tunnel은 13.9%로 거의 유사하게 나타나 5년 경과연수에서는 15%로 설정하는 것이 타당한 것으로 판단된다. 연구결과: 고속철도터널 유지관리 계측센서 설치 후 3년에서 5년의 손망실율은 호남고속 철 도1단계 에서 60.9%로 서울지하철5,6,7,9호선의 4배 이상 크게 나타났다. 결론: 8년에서 10년의 경부고속철도2단계에서는 66.8%로 나타나 5년에서 10년 사이에 급격 하게 증가하므로 향후 10년 이상 장기간의 경과연수에 따른 계측항목별 손망실율 연구가 필요할 것으로 판단된다.

Purpose: This paper investigates and analyzes the loss and damage ratio of maintenance monitoring sensor in metropolitan and high speed railroad tunnel in Korea and abroad. Method: After 5~6 years from the installation, the maintenance monitoring sensor on metropolitan transit tunnels showed the loss and damage ratio from 14.2% to 14.8% in Seoul metro line no. 5, 6, 7, 9, and 13.9% in UK channel tunnel. Based on the result, 15% is thought to be a proper set for the elapsed years, which is 5 years from the installation. Results: The maintenance monitoring sensor on high speed railroad tunnels showed the loss and damage ratio of 60.9% in Ho-Nam high speed railroad on 1 stage after 3 ~ 5 years from the installation, which was approximately 4 times as high as that of Seoul metro line no. 5, 6, 7, 9. Conclusion: Kyung-Bu high speed railroad on 2 stage, after 8~10 years from the installation, showed the loss and damage ratio of 66.8%. Based on the result, it can be inferred that the loss and damage ratio increases drastically after 5~10 years from the installation. Therefore, it is necessary to study on the loss and damage ratio of long term elapsed years, especially more than 10 years from the installation.

연구목적: 본 연구는 최근 들어 적용이 확대되고 있는 Shield 및 TBM터널의 유지관리계측 관리 기준을 설정하여 터널 유지관리계측 관리기술을 향상시키고자 한다. 연구방법: 국내 Shield 및 TBM터널인 서 울지하철 7호선, 9호선, 분당선, 국외의 프랑스, 일본, 영국의 채널터널 자료와 국내외의 터널 모형실험 사례를 종합적으로 분석하여 상호 비교를 실시한다. 연구결과: Shield 및 TBM 터널의 유지관리계측 단 면 중 단면설계나 단면해석 등의 수치해석 결과에 의한 설계 예상치가 없는 경우의 유지관리계측 관리 기준을 설정한다. 결론: 계측 관리기준 적용 시 각각의 계측항목 뿐만 아니라 전체 항목의 변화추이와 상관관계, 그리고 터널의 변상 등을 종합적으로 고려하여 안전성 여부를 판정하여야 한다.

Purpose: The objective of this study was to improve the tunnel maintenance and monitoring technology by establishing the maintenance, management, and monitoring standards for shield and TBM tunnels, which had been applied more in recent years. Method: This study comprehensively analyzed and compared the data and model simulations of Seoul Subway Lines 7 and 9 and Bundang Line, shield and TBM tunnels in South Korea, tunnels in France and Japan, and Channel Tunnel in the UK. Result: This study set maintenance and monitoring standards when there was no design estimate based on numerical analyses such as section design and section analysis regarding the maintenance and monitoring section of shield and TBM tunnels. Conclusion: It is necessary to determine safety by comprehensively considering not only each monitoring item but also the changing trend and correlation of all items and compensation of the tunnel.

트러스 구조에서 변형률계 설치위치는 상현재는 하단부, 하현재는 상단부, 사재는 하단부에 설치하여야 하고, 측정 단위는 (+)인장응력과 (-)압축응력이며, 압축부재의 허용응력은 허용 좌굴응력으로 분석하여야 하며, 토목구조물 계측관리기준은 1 차 안전, 2차 주의, 3차 정밀분석의 기준 적용이 일반적이다.

강아치 구조에서 변형률계 설치위치는 전체연장의 1/4~3/4 지점의 상부 좌우측 행어부와 하부 좌우측 거더부에 집중 설치하 여야 하고, 강아치교에 적용한 관리주의치(관리기준치의 75%), 관리경고치(관리기준치의 90%), 관리기준치(관리기준치의 100%)는 토목구조물 유지관리 계측관리기준을 적용하도록 한다.

한국형 항공위성서비스(KASS; Korea augmentation satellite system) 성능 유지감시 도구(PMMS; performance maintenance and monitoring system) 도구는 사용자에게 KASS 시스템에 대한 정보 제공을 위해 개발되었다. PMMS 도구는 상태감시, 성능감시, 교육시험, 운영관리 도구로 구성되며 각각의 도구는 KASS 메시지, SBAS(satellite based augmentation system) 메시지, 외부 데이터를 기반으로 KASS 시스템에 대한 정보 생성 및 성능분석을 수행한다. KASS PMMS 도구의 인터페이스는 요구사항을 만족하기 위해 내부 및 외부 인터페이스로 구성되며, 인터페이스 검증은 실시간 상태정보 표시 및 데이터 입출력과 관련된 도구의 기능을 중심으로 검증을 완료하였다.

Korea augmentation satellite system(KASS) performance maintenance and monitoring system(PMMS) tool was developed to provide information about the KASS system. Based on the KASS message, satellite based augmentation system(SBAS) message, external reference data, the PMMS tool consists of status monitoring tools, performance analysis and monitoring tools, training and test platform tool and operation and maintenance tools. Each tool generates information and performs performance analysis on KASS system. The interface of KASS PMMS tools has internal and external configurations depending on the interface requirements and interface verification was finished with a focus on the data transmission and real-time data display during the PMMS function test.

인공습지는 물순환, 생태, 수질정화, 경관, 심미적 기능 등의 융합적 기능을 가지고 있어 다양한 분야에서 적용되고 있다. 특히 기후변화와 토지이용의 고도화 문제를 해결할 수 있는 자연친화적 기술로 알려져 있으며, 전 세계적으로 활발한 연구가 이루어지고 있다. 국내에 조성된 인공습지는 다양한 형태와 목적으로 적용되고 있으나 설치, 운영 등에 대한 가이드라인이 체계적으로 제시되어 있지 않아 단순 토목, 조경 위주의 습지 조성으로 인공습지의 고유기능 발휘에 한계를 보이고 있다. 본 연구는 인공습지의 적정 설계, 유지관리 및 사후운영 방안 등을 제시하기 위해 국내에 조성된 인공습지에 대한 현장조사를 실시하였으며, 인공습지의 개념 정립 및 분류체계를 확립하기 위해 환경부 및 기타 기관에서 분류하고 있는 인공습지의 분류체계에 대하여 조사였다. 인공습지 현장조사는 2013년부터 2014년까지 43개 지점의 인공습지를 대상으로 실시되었다. 현장조사를 실시한 인공습지 중 우수사례로 꼽힌 인공습지는 공통적으로 수변공간 제공, 오염물질 정화기능, 생태서식처 제공 등의 다양한 기능을 발휘하고 있는 것으로 나타났으며, 식생, 퇴적물, 시설관리 등의 유지관리가 적절하게 수행되는 것으로 분석되었다. 현장조사 결과를 바탕으로 인공습지의 적정 설계 및 유지관리 방안을 제시하였으며 이러한 결과는 실제 현장에서 활용 가능할 것으로 판단된다.

Constructed wetlands (CWs) have been accepted as an attractive and economic alternative to a variety of pollution control and provided potentially valuable wildlife habitat in urban and suburban areas, as well as esthetic value within the local natural environment. CWs are known eco-friendly technology to solve the problem of the climate change and urbanization issues. Numerous studies have been published on the various aspects of a CW. However, there are current limitations about the CW operations such as few design guidelines, poor performance results regarding the simple construction. Therefore, the objective of this research was to suggest an appropriate design and maintenance guidelines for a CW by thorough investigation of site monitoring results. The research also concentrated in redefining and reclassifying CWs, based on literatures made by the Ministry of Environment (MOE) and other organizations. Investigation at 43 CWs in Korea was performed by using collected data and by performing site survey from 2013 to 2014. Based on the results, the best practices among the investigated CWs provided water treatment, wildlife habitat, environmental education, and leisure. Also these CWs conducted a regular maintenance such as vegetation, sediment dredging and cleaning of facilities. Results obtained are intended for use by academics and any organizations involved in CW management.

In order to supply the high-quality electric power, several researches have been conducted. For the high-quality power, it is necessary to inspect the power lines and insulators before the lines or insulators are disconnected or damaged. However, it is not enough to inspect all the power lines by human inspectors. In previous study, a power line inspection robot was developed to investigate the power lines and insulators. According to replace the human operators by the robot, the inspection robot has several advantages: the improved working conditions, machine accuracy, and the prevention of accident. However, the robot has some defects in its heavyweight. In this study, a lightweight inspection robot has been developed using a RP and a vacuum casting. And, this study developed a fault detection monitoring program for the high voltage equipment using a microphone which detects the location of fault and the thermal imaging and CCD cameras which verifies the fault and stores the image, respectively.

소규모로 널리 보급되고 있는 대부분의 가정용 태양광 발전 시스템은 간단한 단품의 조합만으로 구성되어 저비용 시 스템으로 공급되지만 발전 효율을 관리하고 유지 보수를 개선하기는 어렵다. 또한, 사용자에게 한정적인 데이터 제 공으로 태양광 발전시스템의 상태를 파악하고 문제가 발생할 경우 사용자가 대처하기 어려운 실정이다. 본 논문에서 는 가정용 태양광 발전시설과 같은 소규모 태양광 발전소의 발전 현황을 측정하고, 서버에 정보를 기록하며, 이상 발생시 소유자에게 경보를 보내는 시스템의 구축 방법을 제안 한다.제안하는 시스템은 인버터로부터 정보를 얻는 기 존의 발전량 모니터링 시스템과는 달리 태양광 모듈 단위의 발전 정보 계측, 전송과 저장을 특징으로 한다. 제안하 는 시스템은 태양광 모듈 상태 감지 보드, 게이트웨이, 데이터베이스, 서버, 모바일 APP 및 원격 모니터링 프로그 램으로 구성된다. 특히 안정성과 확장성의 증대를 위해 MQTT기반의 정보 전송시스템을 구현하며, 수집된 정보를 모니터링하고 사용자에게 이상발생에 대한 알람을 보낼 수 있도록 설계하여 발전소의 유지보수를 위한 플랫폼을 제 공하고자 한다. 실험을 통해 제안하는 시스템의 유효성을 확인하며, 이상 발생시 즉각 대응이 이루어질 수 있는 가 정용 태양광 발전 시스템의 유지관리 방법을 제안한다.

Most of the home PV(Photovoltaic) power generation systems, which are being widely distributed on a small scale, are supplied mainly on low-cost systems composed of simple single items, but it is difficult to manage power generation efficiency and improve maintenance. In addition, it is difficult to identify the state of the PV power generation system by providing limited data to the user and to cope with the user when a problem occurs. In this paper we propose a method for constructing a system that measures the power generation status, records information on a server, and sends an alert to the owner when an abnormality occurs in a small PV power plant, such as a home PV power facility. Unlike, in other studies, the power generation monitoring system that obtains information from the inverter, the proposed system is characterized by measuring, transmitting and storing the power generation information in the module unit. The proposed system consists of a PV module status detection board, gateway, database, server, mobile APP and remote monitoring program. In particular, the MQTT(Message Queuing Telemetry Transport)-based information transmission system is implemented to increase the stability and expansion, and it is designed to monitor the collected information and send an alarm to the user about the occurrence of an abnormality to provide a platform for power plant maintenance.

최근 교량의 장수명화와 이용자의 안전을 보장하기 위한 첨단IT기술을 이용한 유지관리 기법이 세계적으로 각광을 받고 있다. 이에 본 논문에서는 무선계측센서를 이용하여 교량의 정적 동적 데이터를 취득 및 분석하여 교량의 거동상태를 실시간으로 모니터링 할 수 있는 지능형 교량 구조 건전성 모니터링시스템을 개발하였다. 본 논문에서 개발한 모니터링 시스템은 교량의 주요 부재의 거동을 계측하기 위한 센서 및 계측데이터 전송을 위한 무선송수신시스템, 전체 시스템 관리를 위한 운영프로그램 및 데이터베이스로 구성되어 있다. 개발한 무선계측센서 기반의 모니터링 시스템의 성능검증을 위해 올림픽대교에 5종의 무선계측센서를 설치하였으며, 센서의 전원은 태양광 발전장치를 설치하여 자가 전원공급이 가능하도록 하였다. 성능검증을 위한 데이터는 시스템 구축완료 후 일주일간의 데이터를 활용하여, 유선시스템으로부터 취득된 데이터와 비교 분석하였으며, 이를 통행 지능형 구조 건전성 모니터링 시스템의 성능 및 실 교량 적용성을 검증하였다.

As structures' long term performances and users' safety have been highlighted, a new maintenance technique using IT has drawn attention around the globe. Therefore, throughout the paper, by analyzing bridge's static and dynamic data using wireless measuring sensor, a "real time smart bridge monitoring system" has developed. Smart bridge monitoring system is consists of three main parts a sensor that can measure major members' movement, a wireless system that informs the data from the sensor, and the database system that analysis the data. In order to test the performance of the system, five different were placed on the Olympic Bridge, Seoul. The power system of the sensors was replaced by self-sustain solar energy system. In order to validate data from the real time smart bridge monitoring system, the data was collected for a week from both wireless system and the wired system and the two data were compared to see the relevance.

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

In this study, an investigation of a damage detection methodology for global condition assessment is presented. A particular emphasis is put on the utilization of wireless sensors for more practical, less time consuming, less expensive and safer monitoring and eventually maintenance purposes. Wireless sensors are deployed with a sensor roving technique to maintain a dense sensor field yet requiring fewer sensors. The time series analysis method called ARX models (Auto-Regressive models with eXogeneous input) for different sensor clusters is implemented for the exploration of artificially induced damage and their locations. The performance of the technique is verified by making use of the data sets acquired from a 4-span bridge-type steel structure in a controlled laboratory environment. In that, the free response vibration data of the structure for a specific sensor cluster is measured by both wired and wireless sensors and the acceleration output of each sensor is used as an input to ARX model to estimate the response of the reference channel of that cluster. Using both data types, the ARX based time series analysis method is shown to be effective for damage detection and localization along with the interpretations and conclusions.

Urban rail transit is a critical infrastructure system that supports urban economic and social development. It has a significant mass transportation capacity while enables environmental benefits. Public transport is a way to resolve large-scale urban road traffic problems and contributes towards sustainable development. However, with the operations of railway vehicles on curves, unbalanced and undulated wears often appear on rails, especially on the low rail. This rail surface defect, so-called 'rail corrugation', directly affects the service life of rolling stocks and track components. The high-frequency vibrations caused by train-track interaction over rail corrugations also impair passenger ride comfort and generate excessive noises. In severe cases, the defects may even endanger the safe passage of a railway vehicle. In practice, rail corrugation has brought huge challenges to the reliable operations and maintenance of railway networks. With the continuous expansion of railway lines and the increasing traffic demands, any existing rail corrugation test method is not enough to meet the actual needs of track maintainers to promptly identify and mitigate rail surface defects. Therefore, this investigation aims to establish a new technique to prognose and classify rail corrugations efficiently and effectively. This study adopts D-track dynamic simulation package to obtain over thousands of vibration data in the form of axle box accelerations from train-track interactions under different conditions. Neural network models have been developed to recognize the rail corrugations and then classify their severity to aid the planning and prioritization of rail track maintenance activities. The models have been trained and tested using the vibration data, achieving the accuracy of over 90%. The optimal model has then been highlighted. The investigation has demonstrated the potential of the neural network to detect and classify rail corrugations, which can be used practically for curved track condition monitoring and maintenance planning.

This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

The optimal replacement problem was investigated for a multi-state deteriorated system for which the true internal state cannot be observed directly except when the system breaks down completely. The internal state was assumed to be monitored incompletely by a monitor that gives information related to the true state of the system. The problem was formulated as a partially observable Markov decision process. The optimal procedure was found to be a monotone procedure with respect to stochastic increasing ordering of the state probability vectors under some assumptions. Limiting the optimal procedure to a monotone procedure would greatly reduce the tremendous amount of calculation time required to find the optimal procedure.