• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.288-290
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• 2007

This paper presents a visualization application using 3D-graphics for effective maintenance of power equipment. The maintenance algorithm implemented in the application is based on Condition-Based Maintenance (CBM) and Reliability -Centered Maintenance (RCM). The main frame of the developed application was made up based on Windows Application Programming Interface (API) and Microsoft Fundamental Classes (MFC). In order to develop the interactive 3D application, the WorldToolKit (WTK) library based on Open GL was used. Also Text-to-Speech (TTS) technology was used to enhance the efficiency of operators. The developed application can help the power system operators to intuitively recognize the present state and maintenance information of the equipment.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.357-359
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• 2006

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.246-248
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• 2006

This paper presents a visualization application using 3D-graphics for effective maintenance of power equipments. The maintenance algorithm implemented in the application is based on Condition-Based Maintenance (CBM) and Reliability-Centered Maintenance (RCM). The main frame of the developed application was made up based on visual C++ (MFC). In order to develop the interactive 3D application, the WorldToolKit library based on Open GL was used. The developed application can help the power system operators to intuitively recognize the present state and maintenance information of the equipments.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.486-493
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• 2007

In the field of maintenance of domestic high-speed railroad which has cost a great deal more than any other fields since it was opened; 1) We found out the conditions of current domestic railroad by understanding the status of track maintenance and analyzing operative processes of track maintenance. 2) The main factors in track maintenance of high-speed railroad, that is, the elements for success to help decision-support in track maintenance were derived from a research on literature about the condition of railroad R&D in these days and about the prediction of the irregular progresses of track. 3) We derived the order of priority and weights from AHP analysis which was based on the survey regarding elements for success.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.886-891
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• 2004

The process of determining whether, when, where and how to intervene, of deciding on optimum allocation of resources and minimizing the cost is a very complex problem: different track sections tend to behave differently under the effects of loading; decision-making processes for maintenance work are closely interrelated technically and economically; decision-making for maintenance plans is based on a large quantity of technical and economic information, extensive knowledge and above all experience. For that reason, It is considered very important to develope objective and computer-aided decision-making support system for track maintenance plan. On this paper, we made a survey of the state-of-art of decision-making support systems for track maintenance which were developed and used abroad and reviewed requirements of system and present the plan of develope decision-making support system for track maintenance appropriate to local condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1457-1465
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• 2016

A RCM approach to maintenance of the catenary system of electric railway is proposed. The proposed RCM approach provides a maintenance-oriented FMECA procedure to derive critical failure modes by analyzing failure effects and a RCM decision logic tree to suggest optimal maintenance works for the derived failure modes. By applying the proposed RCM procedures to the catenary system of high speed railway, it is suggested that strand breaks of dropper and voltage equalizing wire, and trolly wire wear-out are the critical failure modes for whom maintenance works based on condition monitoring should be applied instead of conventional time-based preventive maintenance. It is also proposed by reliability analysis that replacement time of dropper can be reduced from 18 years to 10 years. These results show that the proposed RCM approach can optimize the maintenance procedures of catenary system.

• Journal of KIBIM
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• v.8 no.4
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• pp.34-40
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• 2018

As the number of aged bridges increases, the development of efficient bridge maintenance techniques is becoming more important. Particularly, there have been many studies on digital-twin models of bridges for maintenance and SHM (Structure Health Monitering). However, in order to use the digital-twin model for maintenance of the bridge, the model updating process that matches the structural response between the real bridge and the digital-twin bridge model must be done. This study presents a model updating method that adjusts bridge's stiffness and boundary condition with genetic algorithm (GA) using static displacements and verified proposed updating method through field test on PSC girder bridge. This study also proposes a conceptual idea to construct an efficient bridge maintenance system by applying the updated numerical analysis model to the digital-twin model.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.1
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• pp.6-10
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• 2023

Only about 10% of selected equipment in nuclear power plants are monitored by wiring to address failures or problems caused by vibration. The purpose is primarily for preventive maintenance, not for predictive maintenance. This paper shows that vibration monitoring and diagnosis using Industrial 4.0 enables the complete predictive maintenance for all vibrating equipments in nuclear power plants with the convergence of internet of things; wireless technology, big data through periodic collection and artificial intelligence. Predictive maintenance using wireless technology is possible in all areas of nuclear power plants and in all systems, but it should satisfy regulatory guides on electromagnetic interference and cyber security.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.2
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• pp.4-9
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• 2013

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.18 no.2
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• pp.36-42
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• 2014