• Title/Summary/Keyword: 예측유지보수

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Prediction Model of Remaining Service Life of Concrete for Irrigation Structures by Measuring Carbonation (중성화 측정을 통한 콘크리트의 잔존수명 예측 모델)

  • Lee, Joon-Gu;Park, Kwang-Soo;Kim, Han-Joung;Lee, Joung-Jae
    • Journal of the Korea Concrete Institute
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    • v.15 no.4
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    • pp.529-540
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    • 2003
  • Recently, the researches on the durability design of concrete structures have been studied. As the examples, models to evaluate the service life prediction of the structure have been developed. The purpose of this article is to develop the model for predicting remaining service life. The final aim is to provide the user time for repairing the concrete structures. In addition, it makes possible to maintain the concrete structure economically. 70 reservoirs out of the inland concrete structures were selected and concrete structures of their components were surveyed. Two methods were used for measuring carbonation; TG/DTA method and Phenolphtalein indicator and, the value of pH was measured by the pH meter, After deriving correlations of calcium carbonate and used year, duration from completion year to 2002, pH value, and concrete cover depth the model was developed for predicting remaining service life by measuring data as small as possible. The conventional models had been developed on the basis of experiment data obtained from the restricted lab environment like as carbon gas exposure. On the other hand this model was developed on the basis of measuring data obtained from the real field that the complex deterioration actions are occurred such as freezing and thawing, carbonation, steel corrosion, and so on. The reliability of the developed model will be evaluated high in this point and this model can help to maintain concrete structures economically by providing the manager time to repair the deteriorated concrete structures in site of facility management.

Study on Performance Evaluation Model of River Infrastructures for Life-Cycle Management (생애주기관리를 위한 하천 시설물 성능평가모델에 관한 연구)

  • Yun, Gwan Seon;Kim, Boram;Kim, Hyung-Jun;Yoon, Kwang Seok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.298-298
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    • 2020
  • 하천 혹은 그 인근에 설치된 시설물은 수문, 통문, 제방, 댐, 보, 배수펌프장, 상·하수도, 하구둑 등이 존재한다. 이러한 하천 시설물은 홍수나 가뭄 등 수해를 저감하는 역할을 한다. 그러나 많은 하천 시설물은 노후화, 기후변화, 하천환경변화 등으로 구조적 혹은 기능적 안정성의 저하가 우려되는 실정이다. 시설물 유형별 고령화율을 살펴보면, 댐, 하천, 상하수도 순으로 조사되었으며, 준공연수가 30년을 초과한 하천 시설물은 약 40%를 넘어섰다. 그럼에도 불구하고 하천시설물의 관리 구조는 시설물 설치단계까지만 치중되었으며, 이후 계획 재수립 단계까지의 평가 및 모니터링, 유지관리, 정보관리 등에 이르는 선순환 구조가 미흡한 실정이다. 시설물의 노후화에 따라 유지관리 비용이 증가하며, 대형사고로 이어질 수 있기 때문에 적절한 시기에 시설물 점검 및 유지보수가 매우 중요하다. 우리나라의 경우 시설물의 안전 및 유지관리에 관한 특별법에 따라 국가주요시설물은 안전점검을 실시하고 있으며, 시설물통합정보관리시스템(Facility Management System; FMS)에 안전등급을 제공하고 있다. 본 연구에서는 FMS의 하천 시설물 안전등급 현황을 기반으로 시설물의 효과적인 생애주기관리를 위해 하천 시설물의 성능평가모델을 제안하였다. 성능평가모델은 하천 시설물의 사용연수에 따른 안전등급의 예측이 가능하며, 관리자 측면에서 예산투입 등의 의사결정 시 활용이 가능할 것으로 판단된다.

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Study of The Performance Analysis of a Solar Power Utility with 1.3MW (1.3MW급 태양광 발전소 성능 분석에 관한 연구)

  • Park, Jaegyun;Yun, Jungnam;Lee, Somi;Yun, Kyungshick
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.06a
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    • pp.71.1-71.1
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    • 2010
  • 본 연구는 1.3 MW급 태양광 발전소에서 기온 및 일사량에 따른 발전성능이 유지 보수 및 사후관리에 따라 성능이 향상될 수 있음을 실측자료를 통해 입증하는데 목적이 있다. 실측자료는 2008년 5월 전북 부안에 설치된 태양광 발전소에서 측정된 기온 및 일사량에 따른 발전량을 이용하였으며, 측정기간은 2009년 1월~2009년 12월까지 1년간 모니터링을 한 데이터를 기반으로 분석하였고, 발전소 성능 지표인 PR(Performance Ratio)을 계산하여 자료로 활용하였다. 또한, 실측자료는 PVSYST를 이용하여 실측자료와 동일한 조건에서 예측된 시뮬레이션 발전량 및 PR값과 비교 분석하였다. 실측자료와 해석결과의 비교에서 월단위로 측정된 실측 발전량과 예측 발전량은 유사한 경향을 나타냈으며, 실측 발전량은 예측 발전량 대비 약 5% 낮게 나타났다. 또한, 실측 PR값은 예측 PR값보다 약 4.97% 높게 나타났는데, 이는 해석을 위해 적용되는 일사량(기상청)과 실측 일사량이 다르고, Team Function 방식으로 구동되는 인버터와 시뮬레이션에서의 인버터 구동방식의 차이 때문인 것으로 판단된다. 한편, 일조량의 증가에 따른 1.3MW급 태양광 발전소의 발전량은 비례적으로 증가하는 경향을 나타냈으며, 7월의 경우 기후특성으로 인하여 국부적으로 감소하는 특성을 나타낸다.

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A Condition Rating Method of Bridges using an Artificial Neural Network Model (인공신경망모델을 이용한 교량의 상태평가)

  • Oh, Soon-Taek;Lee, Dong-Jun;Lee, Jae-Ho
    • Journal of the Korean Society for Railway
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    • v.13 no.1
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    • pp.71-77
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    • 2010
  • It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

Analysis of Influences on the Coast Construction Facilities depending on Sea Level Rise (해수면 상승에 따른 연안 건설시설물의 영향 분석)

  • Park, Jun-Young;Bu, Yang-Su;Lee, Dong-Wook
    • Proceedings of the KAIS Fall Conference
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    • 2009.05a
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    • pp.825-828
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    • 2009
  • 기후변화는 기상재해뿐만 아니라 지속적인 해수면 상승의 원인이 되고 있으며, 자연 생태계화 인간의 사회, 경제시스템 전반에 걸쳐 영향을 미치고 있으며, 건설분야도 이와 무관하지 않다. 특히 기후변화는 해수면 상승으로 이어져 사회기반시설인 항구, 연안도로, 철도, 빌딩 등과 연안산업인 석유 및 석유화학공장, 그리고 서비스업인 관광에 대한 위협으로 나타나고 있다. 이러한 해수면 상승은 토지 및 건물의 재산 가치 하락과 해수면 상승에 따른 보호비용 증대, 구조물의 급속한 노후화에 따른 유지관리비용의 증가뿐만 아니라 정치적 제도적 불안 및 사회동요 등을 유발할 수 있다. 우리나라의 경우, 지난 100년간 6대 도시 평균기온이 약 $1.5^{\circ}C$ 상승하였으며, 해수면(제주기준)은 40년간 22cm가 상승하였다. 특히 제주의 경우 매년 5mm씩의 해수면 상승을 보이고 있으며 이는 전 지구 해수면 상승률보다 3배 높은 수치이다. 본 연구는 해수면의 상승에 따른 건설분야의 영향을 분석하기 위한 선도적인 연구로서, 연구의 범위를 제주지역에 국한하였으며, 해수면 상승에 따른 영향 지역을 추출하고, 영향 지역 내 건설시설물 정보를 추출하기 위한 절차를 규명하였다. 본 연구 결과는 유지보수 및 시설물 이설에 따른 공사비 산출의 근거가 될 뿐만 아니라 관련 예산 확보에 대한 근거 자료로 활용될 수 있을 것이다. 향후 관련 지역의 유지보수 및 이설 공사비 정보의 추출 및 DB 구축을 통해 연안 건설 시설물의 이설에 따른 공사비를 예측할 수 있을 것이다.

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Probability Based Resistance Model of Steel Girder Bridges Based on Field Testing (현장계측결과를 이용한 강거더교의 확률적 저항모델)

  • Eom, Jun-Sik
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.12 no.4
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    • pp.195-202
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    • 2008
  • Underestimation of the capacity can have serious economic consequences, as deficient bridges must be posted, repaired or replaced. Accurate prediction of bridge behavior may allow for more bridges to remain in service with or without minor repairs. The presented research is focused on the reliability evaluation of the actual load carrying capacity of existing bridges based on the field testing. Reliability analysis is performed on 17 previously tested bridges. Bridges are first evaluated based on the code specified values and design resistance. However, after the field testing program, it is possible to apply the experimental results into the bridge reliability evaluation procedures. The girder distribution factors obtained from the tests are also applied in the reliability calculation. The results indicate that the reliability indices of selected bridges can be significantly increased due to the reduction of uncertainties without sacrificing the safety of structures, by including the result of field measurement data into calculation.

Condition-Based Model for Preventive Maintenance of Armor Units of Rubble-Mound Breakwaters using Stochastic Process (추계학적 확률과정을 이용한 경사제 피복재의 예방적 유지관리를 위한 조건기반모형)

  • Lee, Cheol-Eung
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.28 no.4
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    • pp.191-201
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    • 2016
  • A stochastic process has been used to develop a condition-based model for preventive maintenance of armor units of rubble-mound breakwaters that can make a decision the optimal interval at which some repair actions should be performed under the perfect maintenance. The proposed cost model in this paper based on renewal reward process can take account of the interest rate, also consider the unplanned maintenance cost which has been treated like a constant in the previous studies to be a time-dependent random variable. A function for the unplanned maintenance cost has been mathematically proposed so that the cumulative damage, serviceability limit and importance of structure can be taken into account, by which a age-based maintenance can be extended to a condition-based maintenance straightforwardly. The coefficients involved in the function can also be properly estimated using a method expressed in this paper. Two stochastic processes, Wiener process and gamma process have been applied to armor stones of rubble-mound breakwaters. By evaluating the expected total cost rate as a function of time for various serviceability limits, interest rates and importances of structure, the optimal period of preventive maintenance can easily determined through the minimization of the expected total cost rate. For a fixed serviceability limit, it shows that the optimal period has been delayed while the interest rate increases, so that the expected total cost rate has become lower. In addition, the gamma process tends to estimate the optimal period more conservatively than the Wiener process. Finally, it is found that the more crucial the level of importance of structure becomes, the more often preventive maintenances should be carried out.

A Study on Improved Inspection Method of the Foundation Scouring and Establishment of 3D Underwater Surface Map (개선된 교량 기초세굴 점검방법 및 3D 하상지도 구축 연구)

  • Choi, Hyun-Chul;Ko, Jun-Young
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.5
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    • pp.161-170
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    • 2022
  • The maintenance of bridges installed in rivers is carried out through facility safety inspection and repair & reinforcement procedures according to the results. Many studies have been so far conducted on the safety check of the bridge upperstructure because of the ease of access. However as it is impossible to directly investigate whether the pier foundation installed in the river has been scoured. Management of underwater foundations has remained based on theory. In this study, the scour of the bridge foundation installed in such a river was realized in 3D form by using an echo sounder and VRS. This made it possible to predict the scour pattern through comparison and analysis with the ground height of the riverbed at the time of the bridge installation. Based on these results, if the pier foundation is used as an initial data to determine whether or not local scour is present and to predict long-term scouring, bridge collapse due to foundation scour can be prevented.

Prediction Method about Power Consumption by Using Utilization Rate of Resources in Cloud Computing Environment (클라우드 컴퓨팅 환경에서 자원의 사용률을 이용한 소비전력 예측 방안)

  • Park, Sang-myeon;Mun, Young-song
    • Journal of Internet Computing and Services
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    • v.17 no.1
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    • pp.7-14
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    • 2016
  • Recently, as cloud computing technologies are developed, it enable to work anytime and anywhere by smart phone and computer. Also, cloud computing technologies are suited to reduce costs of maintaining IT infrastructure and initial investment, so cloud computing has been developed. As demand about cloud computing has risen sharply, problems of power consumption are occurred to maintain the environment of data center. To solve the problem, first of all, power consumption has been measured. Although using power meter to measure power consumption obtain accurate power consumption, extra cost is incurred. Thus, we propose prediction method about power consumption without power meter. To proving accuracy about proposed method, we perform CPU and Hard disk test on cloud computing environment. During the tests, we obtain both predictive value by proposed method and actual value by power meter, and we calculate error rate. As a result, error rate of predictive value and actual value shows about 4.22% in CPU test and about 8.51% in Hard disk test.

Modelling on the Carbonation Rate Prediction of Non-Transport Underground Infrastructures Using Deep Neural Network (심층신경망을 이용한 비운송 지중구조물의 탄산화속도 예측 모델링)

  • Youn, Byong-Don
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.4
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    • pp.220-227
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    • 2021
  • PCT (Power Cable Tunnel) and UT (Utility Tunnel), which are non-transport underground infrastructures, are mostly RC (Reinforced Concrete) structures, and their durability decreases due to the deterioration caused by carbonation over time. In particular, since the rate of carbonation varies by use and region, a predictive model based on actual carbonation data is required for individual maintenance. In this study, a carbonation prediction model was developed for non-transport underground infrastructures, such as PCT and UT. A carbonation prediction model was developed using multiple regression analysis and deep neural network techniques based on the actual data obtained from a safety inspection. The structures, region, measurement location, construction method, measurement member, and concrete strength were selected as independent variables to determine the dependent variable carbonation rate coefficient in multiple regression analysis. The adjusted coefficient of determination (Ra2) of the multiple regression model was found to be 0.67. The coefficient of determination (R2) of the model for predicting the carbonation of non-transport underground infrastructures using a deep neural network was 0.82, which was superior to the comparative prediction model. These results are expected to help determine the optimal timing for repair on carbonation and preventive maintenance methodology for PCT and UT.