• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.627-639
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• 2002

Bridge construction is almost complete in many countries. Thus, the government and highway agencies change their focus from constructing to maintaining. Effectively maintaining bridges require predicting their lifespan using a system reliability viewpoint. Likewise, maintenance models based on the system reliability concept should be developed. Thus, this study developed maintenance models for preventive maintenance and essential maintenance using system reliability and lifetime distributions. The optimal maintenance strategy for an existing bridge was obtained using the developed maintenance models.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.6
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• pp.1-9
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• 2016

The paper aims at evaluating effects of preventive maintenance on life cycle cost(LCC) reduction of bridges. The preventive maintenance activities capable to delay bridge deteriorations can reduce overall maintenance costs and extend service life of a bridge by regularly providing maintenance activities and avoiding larger maintenance(repairs or rehabilitations) costs. Couple of prediction models were proposed in order to calculate LCC of a typical bridge: a health score model and repair rehabilitation cost model. In addition, the maintenance activities such as wash and painting were also suggested in order to consider effects of preventive maintenance in the analysis based on literature reviews. According to analysis results, new maintenance strategy(reactive maintenance + preventive maintenance) can save \0.5 billion per bridge for future life-cycle costs over 100 year analysis or \184 billion for entire HBMS(Highway Bridge Management System) inventory over 20 years. Small investments for preventive maintenance in improved bridge management can have a very significant return when considering the large bridge inventory.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.489-490
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• 2011

사회기반 시설물들의 노후화로 유지보수 비용이 급격하게 증가하고 있는 선진국뿐만 아니라 국내에서도 시설물을 체계적으로 관리하여 안전사고를 예방하고 유지관리 예산을 절감하고자 하는 관심이 날로 증대하고 있다. 해외의 뉴질랜드, 호주, 캐나다, 미국, 영국 등의 나라에서는 공공시설물 유지관리에 자산개념을 도입하여 관련 법과 제도를 정비하고 대웅적 유지관리방식보다 자산의 가치 중심의 예방적 유지관리로 전환하여 일정 부분 성과를 내고 있다. 국내에서도 시설물을 체계적으로 관리하여 안전사고를 예방하고 유지관리 예산을 절감하고자 하는 관심이 날로 증대하고 있다. 이에 IIMM의 자산관리 업무절차 모델과 국내에서 제시된 KTAM-40을 비교하여 공공시설물 자산관리 정보시스템의 설계방안을 제시하고자 한다.

• Journal of Korean Society of Steel Construction
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• v.14 no.3
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• pp.443-452
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• 2002

Construction of highway bridges is almost complete in many countries. Thus, the government and highway agencies are shifting their remaining life span from the viewpoint of system reliability. As such, it is necessary to develop maintenance models based on system reliability concept. In this paper, preventive and essential maintenance models were developed using system reliability and lifetime distribution.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.34-43
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• 2019

The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1373-1374
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• 2012

공공시설 자산관리는 기존의 대응적 유지보수 개념의 시설물유지관리체계에서 예방적 유지보수 개념으로 전환한 시설물 유지보수의 새로운 개념이다. 기존에 운영되고 있는 공공시설관리 시스템들을 효율적으로 관리하기 위해서는 자산관리 모형이 표준화되어 범정부EA 지원시스템에 목표아키텍처로 등록되고 더 나아가서는 범정부 표준시스템으로 만들어 필요한 기관에 보급할 필요가 있다. 이 연구에서는 공공시설 자산관리 정보시스템을 구축하는데 필수적인 참조모델을 시스템의 상호운영성과 정보의 호환성을 확보하기 용이하도록 범정부EA 관점에서 제시하였다. 제시한 자산관리 참조모델이 GEAP에 등록 관리 된다면 이것을 바탕으로 타 기관에서 향후 정보시스템을 구축할 때 사전에 파악하고 활용하도록 제안 할 수 있을 것이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.505-516
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• 2018

In order to establish an efficient bridge maintenance strategy, the future performance of a bridge must be estimated by considering the current performance, which allows more rational way of decision-making in the prediction model with higher accuracy. However, personnel-based existing maintenance may result in enormous maintenance costs since it is difficult for a bridge administrator to estimate the bridge performance exactly at a targeting management level, thereby disrupting a rational decision making for bridge maintenance. Therefore, in this work, we developed a representative performance prediction model for each bridge element considering uncertainty using domestic bridge inspection data, and proposed a bayesian updating method that can apply the developed model to actual maintenance bridge with higher accuracy. Also, the feasibility analysis based on calculation of maintenance cost for monitoring maintenance scenario case is performed to propose advantages of the Bayesian-updating-driven preventive maintenance in terms of the cost efficiency in contrast to the conventional periodic maintenance.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.701-704
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• 2006

산업 발전에 따라 생활은 점차 편리해지고 각종 질병들에 대한 위험도 점차 높아지고 있다. 인간의 생명을 위협하는 위험한 질병 중에는 사전에 예방하지 않으면 돌이킬 수 없는 사태로 확산되기도 하지만 바쁜 현태인들에게는 자신의 건강상태를 사전에 파악하고 관리하기 힘든 실정이다. 이에 유비쿼터스 환경에 접어든 IT기술을 바탕으로 의료진단 및 예방 시스템을 구축하여 실요자들이 센서를 통해 컴퓨터를 직접 이용하지 않더라도 자신의 건강상태를 유지 관리할 필요가 있다. 그러므로 본 논문에서는 이와 같이 유비쿼터스 환경으로 변화해가는 기술적 변화를 바탕으로 의료 진단 및 예방이 가능한 시스템 구축을 위한 모델로서 뇌혈관 질환에 대한 모델을 제시하고자 한다. 또한, 이를 통해 향후 구축하고자 하는 u-헬스 케어 의료진단 시스템 구축 모델에 활용하고자 하며, 본 모델을 통해 의료정보를 활용한 산업 발전과 인류의 편이성 증대 및 건강상태의 주기적 검사를 통해 향상된 복지문화를 유도할 수 있을 것이다.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.1-11
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• 2021

As the aging of large domestic SOC facilities accelerates, facility maintenance is also changing from safety evaluation based on the current condition to performance-oriented preventive and preemptive maintenance based on the prediction of the level of future obsolescence. In particular, in the case of bridges, class 1 and 2 bridges are systematically managed along with many studies, but for small and medium-sized class 3 bridges there is no collection and utilization of historical data presenting performance degradation during their service life. Therefore, in this study, 3D model-based demonstration DB system was designed and developed to intuitively check the damage change rate at the damage location by registering the maintenance history by life cycle for each member's exterior damage in the 3D bridge object and to enable API-based comprehensive performance evaluation.