• 전기의세계
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• v.46 no.8
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• pp.34-40
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• 1997

케이블 시스템의 사고는 예방 진단에 근거한 정확한 진단으로 피할 수 있으며, 잔여수명 예측 기술은 진단 방법의 체계적인 적용에 의해 향상될 수 있다. 따라서 본 고에서는 케이블 시스템 진단 방법의 체계적인 개발을 위해서 60 kV급 이상의 종이 절연 혹은 고분자 절연 전력 케이블과 그 접속 자재에 대해서만 진단 방법을 개략적으로 소개만하고 있으며 수트리에 관련된 열화, 절연체의 열화를 제외한 모든 열화현상과 DC 케이블에 대해서는 언급을 하지 않았다. 회전기 고체절연체의 열화에 의해 야기되는 변화는 회전기 진동을 발생 시키고, 진동은 기계에 심각한 손상을 발생시킨다. 회전기의 절연열화 진단은 유전손실, 유전율, 음향 등의 측정/분석으로 가능하고 적용 방법은 on-line/off-line으로 가능하다. 절연 시스템의 열화정도 판정은 회전기의 적절한 보수시기의 판단을 가능하게 하여 유지 보수비의 절감 및 회전기의 수명연장을 가능하게 할 것이다.

• Journal of Platform Technology
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• v.6 no.2
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• pp.19-25
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• 2018

Existing Photovoltaic(PV) monitoring system monitors the current, past power generation, all values of environmental sensors. It is necessary to predict solar power generation for efficient operation and maintenance on the power plant. We propose a method for estimating the generation of PV data based PV monitoring system with data accumulation. Through this, we intend to find the failure prediction of the photovoltaic power plant in proportion to the predicted power generation. As a result, the administrator can predict the failure of the system it will be prepared in advance.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.3-11
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• 2012

The most of domestic bridge has an used life under 30 years, Future maintenance budgets can be expected to increase. However, because of bridge maintenance budgets are limited, demand for asset management being performed to achieve required performance within available budget is increasing. To perform effective asset management of bridges should be made the best use of information to occur in all phase of construction project. Therefore, the development of system and DB is required to support asset management by effective information management. The objective of this study is the development of the BIM-based bridge asset management model. Through previous research survey, BIM capabilities and asset management components were established and mutual linkages were examined. Bridge asset management model was composed of alternate assessment model. In addition, BIM-based asset management model was performed case studies to verify feasibility and applicability. The proposed model can be applied to a current bridge maintenance procedures and supported to perform effective bridge maintenance tasks within a limited budget.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.765-778
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• 2008

Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

• Journal of the Korean Society for Railway
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• v.17 no.1
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• pp.52-58
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• 2014

Plastic deformation of roadbed influences the stability and maintenance of concrete slab track. Long-term plastic deformation in a railway roadbed is generated primarily due to accumulated inelastic strains caused by repeated passing of trains. Prediction of cumulative plastic deformation is important in cost-effective maintenance of railway tracks as well as for the safe operation of trains. In this study, the vertical displacements in railway roadbeds with different thicknesses of reinforced roadbed were computed. Parameters of the power model for cumulative plastic strain were calibrated by using the data from triaxial tests and full-scale loading tests. Results of three-dimensional finite element analyses of standard roadbed sections provide us with design guidelines for the selection of the thickness of reinforced roadbed.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1656-1664
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• 2007

This paper introduces a study of improvement for a defect diagnosis of the UM71C track circuit using on HSL. The track circuit on HSL has long operation section. Therefore, when the worker maintain, many times and efforts are spent. So, periodically, we have operated a inspection car. However, we don't know exactly the state changed of the inspection data when track circuit has defect. Actually, We fixed a sample area within operation section on HSL and performed the simulations for short circuit current that is reflected characteristic impedance and propagation factor. We compared the measuring data with the result of the simulation. Using verified simulation program, we estimated inspection data as the malfunction number and the change of capacity of compensation capacitor. These study need to secure of the safety as the train operation. Also, It needs to make a criteria of analysis for the maintenance through comparison simulation data and inspection data.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.3
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• pp.31-40
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• 2012

The irregularity of railway track affects not only the comfort of ride such as noise or vibration but also the safety of train operation. For this reason, it is an interesting research area to design a reliable and sustainable railway track system and to analyze the train movement mechanism based on systematic approaches considering reasons of track irregularity possible in a specific local environment. Irregularity data inspected by EM-120, an railway inspection system in Korea includes unavoidable incomplete and erratic information, so it is encountered lots of problem to analyse those data without appropriate pre-data-refining processes. In this research, for the efficient management and maintenance of railway system, progress rate of standard deviation of irregularity is quantified. During the computation, some important components of railways such as rail joint, ballast, roadbed, and fastener have been considered. Probabilistic distributions of irregularity growth with respect to time are computed to predict the remaining service life of railway track and to be adapted for the safety assessment.

• Journal of the Korean Geotechnical Society
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• v.36 no.3
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• pp.5-14
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• 2020

The railway concrete track has been increasingly adopted for high-speed train such as KTX due to its high running stability, improved ride quality for the passengers, and low maintenance cost. However, excessive settlement of the railway concrete track has been monitored at embankment sections of the ◯◯ High-speed Line, resulting in the concerns on the safety of railway operation. In order to establish an effective maintenance plan for the concrete track railway exceeding the allowable residual settlement, it is essential to reasonably predict their long-term settlement behavior during the public period. In this study, we developed a model for predicting the long-term settlement behavior of concrete track using recurrent neural network (RNN) and examined the applicability of the developed model.