• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.283-292
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• 2020

Current sensors that use a Hall element and Hall IC to measure the magnetic fields generated in steel silicon core gaps do not distinguish between direct and alternating currents. Thus, they are primarily used to measure direct current (DC) in industrial equipment. Although such sensors can measure the DC when installed in expensive equipment, ascertaining problems becomes difficult if the equipment is set up in an unexposed space. The control box is only opened during scheduled maintenance or when anomalies occur. Therefore, in this paper, a method is proposed for facilitating the safety management and maintenance of equipment when necessary, instead of waiting for anomalies or scheduled maintenance. A Bluetooth 4.0 low-energy current-sensor system based on near-field communication is used, which compensates for the nonlinearity of the current-sensor output signal using a piecewise linear model. The sensor is controlled using its generic attribute profile. Sensor nodes and cell phones used to check the signals obtained from the sensor at 50-A input currents showed an accuracy of ±1%, exhibiting linearity in all communications within the range of 0 to 50 A, with a stable output voltage for each communication segment.

• Smart Structures and Systems
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• v.13 no.3
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• pp.407-418
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• 2014

The purpose of this paper is to present an Integrated Life Cycle Bridge Information Modeling that can be used throughout different phases of the bridge life cycle including: design, construction, and operation and maintenance phases. Bridge Information Modeling (BrIM) has become an effective tool in bridge engineering and construction. It has been used in obtaining accurate shop drawings, cost estimation, and visualization. In this paper, BrIM is used as an integrated tool for bridges life cycle information modeling. In the design phase, BrIM model can be used in obtaining optimum construction methods and performing structural advanced analysis. During construction phase, the model selects the appropriate locations for mobile cranes, monitors the status of precast components, and controls documents. Whereas, it acts as a tool for bridge management system in operation and maintenance phase. The paper provides a detailed description for each use of BrIM model in design, construction, and operation and maintenance phases of bridges. It is proven that BrIM is an effective tool for bridge management systems throughout their life phases.

• Journal of Applied Reliability
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• v.17 no.1
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• pp.58-65
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• 2017

Different from general operating policies applied for various waiting line situations, two complementary dyadic operating policies are applied alternatingly to a single server maintenance service center model. That is, either of the two dyadic Min (N, T) or Max (N, T) policy is applied to operate such center first and the other operating policy should be applied later, and then the same sequence of both operating policies is followed repeatedly. This operating policy is denoted by the Minimax (N, T) policy. Purpose: Because of the newly introduced operating policy, important system characteristics of the considered service center model such as the expected busy and idle periods, the expected number of customers in the service center and so on should be derived to provide necessary information for determination of the optimal operating policy. Methods: Based on concepts of the newly introduced Minimax (N, T) policy, all necessary system characteristics should be redefined and then derived by constructing appropriate relations between complementary two dyadic operating policies. Results: Desired system characteristics are obtained successfully using simple procedures developed by utilizing peculiar structure of the Minimax (N, T) policy. Conclusion: Applying Minimax (N, T) operating policy is equivalent to applying the simple N and T operating policies alternatingly.

• Journal of Korean Society of societal Security
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• v.1 no.4
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• pp.41-49
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• 2008

As bridges have been longer and bigger recently, lots of bridge management systems (BMS) have been developed for each bridge. However, the differences among the data models developed by different system developers give a serious problem in integrated information management for national security. The aim of this study is to develop a common data model which can be referred in development of the BMS. The existing BMS and work process by laws are carefully analyzed. Based on the analysis results, the bridge management and maintenance process is categorized into the four basic activity types. In addition, common data models for each the unit activity type are defined.

• 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 Korean Society for Quality Management
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• v.47 no.1
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• pp.87-96
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• 2019

Purpose: The purpose of this paper is to determine an optimal production time for economic production quantity model with preventive maintenance and random defective rate as the function of a machinery deteriorates. Methods: If a machinery shifts from "in-control" state to "out-of-control" state, a proportion of defective items being produced increases. It is assumed that time to state shift is a random variable and follows an arbitrary distribution. The elapsed time until process shift decreases stochastically as a production cycle repeats and quasi-renewal process is used to implement for production facilities to deteriorate. Results: When the exponential parameter for exponential distribution increases, the optimal production time increases. When Weibull distribution is considered, the optimal production time is closely affected by the shape parameter of Weibull distribution. Conclusion: A mathematical model is suggested to find optimal production time and optimal number of production cycles and numerical examples are implemented to validate the patterns for changes of optimal times under different parameters assumptions. The real application is implemented using the proposed approach.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1472-1479
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• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.33-40
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• 2024

This study analyzes the impact of regular preventive maintenance (PM) on reducing the failure rate and occurrence of falling accidents of industrial overhead doors. A reliable safety device model with an additional safety device, which is installed to replace a defective one, is proposed. The research methodology involves collecting breakdown and falling accident records, comparing and analyzing data before and after regular PM implementation, and experimenting with two types of retrofittable safety devices. Key findings are as follows. 1. Regular PM implementation significantly reduces the failure rate of old overhead doors. 2. A parallel structured model with two alternative safety devices can minimize falling accident risks. The study's contributions include the following. 1. The positive impact of PM on extending overhead door lifespan is quantified. 2. A general safety device model that can be retrofitted and used as replacement with a fail-safe function is proposed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.107-114
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• 2008

Currently, each managing agencies are enforcing the maintenance against the cutting slopes, but the universality and objectivity are insufficient, because the evaluation item and model are various, the access method is not mutual-supplementary. Consequently, this study will lead the approach for a rational model development, by the analysis against the existing cutting slope evaluation technique, excavate a collapse primary reason and a factor, by the collapse example analysis, and make out evaluation table to decide a investigation priority of the existing cutting slope in the Investigation Evaluation step using AHP.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.349-375
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• 2016

The tension of an arch bridge hanger is estimated using a number of experimentally identified modal frequencies. The hanger is connected through metallic plates to the bridge deck and arch. Two different categories of model classes are considered to simulate the vibrations of the hanger: an analytical model based on the Euler-Bernoulli beam theory, and a high-fidelity finite element (FE) model. A Bayesian parameter estimation and model selection method is used to discriminate between models, select the best model, and estimate the hanger tension and its uncertainty. It is demonstrated that the end plate connections and boundary conditions of the hanger due to the flexibility of the deck/arch significantly affect the estimate of the axial load and its uncertainty. A fixed-end high fidelity FE model of the hanger underestimates the hanger tension by more than 20 compared to a baseline FE model with flexible supports. Simplified beam models can give fairly accurate results, close to the ones obtained from the high fidelity FE model with flexible support conditions, provided that the concept of equivalent length is introduced and/or end rotational springs are included to simulate the flexibility of the hanger ends. The effect of the number of experimentally identified modal frequencies on the estimates of the hanger tension and its uncertainty is investigated.