• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1511-1516
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• 2011

The maintenance of the turnout is composed of signal field and track field on business, the electrical and mechanical field on system. adjustment and maintenance carry forward through coordination with these fields. In the case of turnout equipment used in a first phase of Seoul-Busan high-speed train, it is treated by classifying as mechanical adjustments and electrical adjustments. Mechanical adjustment is conducted with focus on fine adjustment to meet maintenance standards limits(1mm or less) about interval of basic rail and tongue rail about each part of track transition equipment. This refers to mechanical adjustments performed mainly with physical changes and movement characteristics between basic rail and tongue rail by considering the overall environment surrounding track side of section installed track transition equipment. However, these series of maintenance are conducted in state that high-speed train is not in the process from 1 am to 4 am at night, but common workers for maintenance are not familiar with the operation and checking about various situation, and the workers are even insufficient. Maintenance training using mixed reality is conducted in the place of business, we tried to overcome several problems of safety and time reduction through this training.

• Computers and Concrete
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• v.17 no.4
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• pp.499-521
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• 2016

In this paper, a probabilistic- and finite element-based approach to evaluate and predict the lifetime performance of reinforced concrete (RC) bridges undergoing various maintenance actions is proposed with the time-variant system reliability being utilized as a performance indicator. Depending on their structural state during the degradation process, the classical maintenance actions for RC bridges are firstly categorized into four types: Preventive type I, Preventive type II, Strengthening and Replacement. Preventive type I is used to delay the onset of steel corrosion, Preventive type II can suppress the corrosion process of reinforcing steel, Strengthening is the application of various maintenance materials to improve the structural performance and Replacement is performed to restore the individual components or overall structure to their original conditions. The quantitative influence of these maintenance types on structural performance is investigated and the respective analysis modules are written and inputted into the computer program. Accordingly, the time-variant system reliability can be calculated by the use of Monte Carlo simulations and the updated the program. Finally, an existing RC continuous bridge located in Shanghai, China, is used as an illustrative example and the lifetime structural performance with and without each of the maintenance types are discussed. It is felt that the proposed approach can be applied to various RC bridges with different structural configurations, construction methods and environmental conditions.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.10
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• pp.1398-1406
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• 2016

In general, the seminiferous tubule basement membrane (STBM), comprising laminin, collagen IV, perlecan, and entactin, plays an important role in self-renewal and spermatogenesis of spermatogonial stem cells (SSCs) in the testis. However, among the diverse extracellular matrix (ECM) proteins constituting the STBM, the mechanism by which each regulates SSC fate has yet to be revealed. Accordingly, we investigated the effects of various ECM proteins on the maintenance of the undifferentiated state of SSCs in pigs. First, an extracellular signaling-free culture system was optimized, and alkaline phosphatase (AP) activity and transcriptional regulation of SSC-specific genes were analyzed in porcine SSCs (pSSCs) cultured for 1, 3, and 5 days on non-, laminin- and collagen IV-coated Petri dishes in the optimized culture system. The microenvironment consisting of glial cell-derived neurotrophic factor (GDNF)-supplemented mouse embryonic stem cell culture medium (mESCCM) (GDNF-mESCCM) demonstrated the highest efficiency in the maintenance of AP activity. Moreover, under the established extracellular signaling-free microenvironment, effective maintenance of AP activity and SSC-specific gene expression was detected in pSSCs experiencing laminin-derived signaling. From these results, we believe that laminin can serve as an extracellular niche factor required for the in vitro maintenance of undifferentiated pSSCs in the establishment of the pSSC culture system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.114-121
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• 1998

This paper describes th on-line maintenance system with integrated graphic environment for building electrical equipments. This system is based on the pre-defined troubleshoot knowledgebase with maintenance information. And this system utilizes the database and knowledgebase for the diagnosis of facility and runs on the operator's requirement and response. The operator is possible of a detailed observation, an early detection of abnormal state, a properly operation and a rapidly arrangement of electrical equipments. Especially, this system is developed using the maintenance of equipments, if needed, be operated by non-expertise.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1174-1181
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• 2011

This paper investigates the current established preventive maintenance and its corresponding data on a point machine among railway signalling facilities and suggests a part of considerable plans when the policy of the preventive maintenance is modified. It is not appropriated to apply the optimized preventive replacement period considered with the cost simply. In that case, it is suggested that the reliability should be analyzed failure mode and effects through collecting the on-site failure data sufficiently. Then, that result can be proposed to adjust the proper criteria into the rational way by comparing the initial maintenance criteria. In this paper, the alternative way to determine the feasibility of the inspection period using failure probability is introduced.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.51-61
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• 2014

Preventive maintenance of buildings has increased the importance of interest in that it is able to maintain the performance building has and to prevent a problem occurred in future. For improved preventive maintenance work, it should be performed to select works order clearly and preceded the accurate measurement for the state of works order. when measuring the conditions, measurement of the state of work order considering the various criteria is more effective than to measure by only criterion. But, there are something hard to evaluate exactly between the criteria because of decision-maker's subjective judgments. To solve these problems, this research proposes decision making support model to determine preventive maintenance works order using Fuzzy-sets. By using Fuzzy-sets when measuring state of work objects, it can be reduced vagueness of judgments by decision-makers. This model can be used as a tool for objective evaluation of preventive maintenance work orders and offer the guideline to perform decision-making.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.662-666
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• 2005

Using data gathered from expert opinion of plant and equipment professionals; this paper presents the key variables that may constitute a maintenance proficient plant operator. The Multivariate Discriminant Analysis (MDA) was applied to generate data and was tested for sensitivity analysis. Results showed that the MDA model was able to classify plant operators' proficiency at 94.10 percent accuracy and determined nine (9) key variables of a maintenance proficient plant operator. The key variables included: i) number of years of experience as equipment operator (PQ1); ii) eye-hand coordination (PQ9); iii) eye-hand-foot coordination (PQ10); iv) planning skills (TE16); v) pay/wage (MQ1); vi) work satisfaction (MQ4); vii) operator responsibilities as defined by management (MF1); viii) clear management policies (MF4); and ix) management pay scheme (MF5). The classification procedure of nine variables formed the general model with the equation viz: OMP (general) = 0.516PQ1 + 0.309PQ9 + 0.557PQ10 + 0.831TE16 + 0.8MQ1 + 0.0216MQ4 + 0.136MF1 + 0.28MF4 + 0.332MF5 - 4.387

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.149-154
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• 2008

Service life of bridges should be evaluated by physical life considering damage/deterioration. But it is difficult to identify optimal maintenance scenario due to insufficient research related to that. To identify optimal maintenance scenario, it is needed to develope life cycle profile model of condition state variation by deterioration factor. The LCP model has been developed in consideration of regression analysis and survey in this study. It is expected that the LCP model could help to achieve HBMS system improvement.

• Journal of applied mathematics & informatics
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• v.39 no.5_6
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• pp.851-858
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• 2021

In general, secondary batteries are widely used as an electric energy source. Among them, the state of energy storage of mobile devices is very important information. As a method of estimating a state, there is a method of estimating the state by integrating the current according to an energy storage state of a battery, and a method of designing a state estimator by measuring a voltage and estimating a charge amount based on a battery model. In this study, we designed the state estimator using an extended Kalman filter to increase the precision of the state estimation of the charge amount by including the error of the system model and having the robustness to the noise.