• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.199-204
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• 2007

This paper presents design of interleave configured dc-dc converter for high power distributed power system applications. The multi channel interleaving buck converter with small inductance has proved to be suitable for micro-grid, requiring medium output voltages, high output currents and fast transient response. Integrated magnetic components are used to reduce the size of the converter and improve efficiency. Unlike conventional methods, the distributed approach requires no centralized control, automatically accommodates varying numbers of converter cells, and is highly tolerant of subsystem failures. A general methodology for achieving distributed interleaving is proposed, along with a specific implementation approach. The design and simulation verification of switching frequency 10 kHz system is presented with interleaved clocking of the converter cells. The simulation (simulated by PSIM 6.1) results corroborate the analytical predictions and demonstrate the tremendous benefits of the distributed interleaving approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.241-249
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• 2005

ATM based MPLS(Multiprotocol Label Switching) is discussed for its provisioning QOS commitment capabilities, Traffic engineering and smooth migration for BcN in Korea. At this time, due to the comprehensive nature of ATM protocol, ATM has been adapted as the backbone system for carrying Internet traffic[1,2,3,4]. This paper presents preventive congestion control mechanisms for detecting HTR(Hard-To-Reach) LSP(Label Switched Path) in ATM based MPLS systems. In particular, we have introduced a HTR LSP detection method using network signaling information in an ATM layer. MPLS related studies can cover LSP failures in a physical layer fault, it can not impact network congestion status. Here we will present the research results for introducing HTR LSP detection methods and control mechanisms and this mechanism can be implementing as SOC for high speed processing a packet header. We concluded that it showed faster congestion avoidance abilities with a more reduced system load and maximized the efficiency of network resources by restricting ineffective machine attempts.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.487-492
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• 2006

Inverter driven induction motors with high speed switching and advanced PWM techniques are widely used for variable speed applications. Recently, the insulation failures of stator winding have attracted much concern due to high dv/dt of IGBT PWM inverter output. In this paper, the detailed insulation test results of 26 low-voltage induction motors are presented. Six different types of insulation techniques are applied to 26 motors. The insulation characteristics are analyzed with partial discharge, inception voltage, AC current, and dissipation factor tests. Also, breakdown tests by high voltage pulses are performed. From the above test data the effects due to different wires and insulation techniques on the insulation characteristics of low-voltage induction motors are compared and analyzed. The insulation technique to enhance the insulation strength is suggested from the test results.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.108-115
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• 2001

SDH-based SHR networks are the reconfiguration process in case of failure and APS protocol used. In this study, addresses the maximum allowed recovery time in two fiber bidirectional networks. We analyse the APS protocol and derive the Processing time domains of each n order to cope with the maximum reconfiguration time of 50㎳, as specified in the ITU-T standard. We finally analyze the interleaved failures. One is the signal degrade then the signal failure, the other is the signal failure then the signal failure. Any case analysis is carried out. reconfiguration time can be guaranteed.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.1-19
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• 2016

While previous studies on service failures mainly focused on general services, this study examines the effects of failed financial services on the psychological process and behavioral responses of consumers. The important factors of financial service (relational benefits, convenience, branch satisfaction, product diversity, company stability, and product profitability) are regarded as antecedents in our model. We study how each factor of failed financial service affects the negative emotions of consumers through the attribution process and how these arising emotions influence their behavioral responses. Through path analysis, this study shows that failure of service factors of relational benefits, branch satisfaction, and convenience induces disappointment, with the mediation effect of external attribution. Meanwhile, failure of service factors of product diversity and product profitability induces regret, with the mediation effect of internal attribution. Disappointment leads to complaint behavior, and regret leads to switching behavior. Unlike previous studies, the present one considers the important factors of financial service and their effects on the affective and behavioral responses of consumers.

• Journal of Power Electronics
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• v.11 no.6
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• pp.914-921
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• 2011

Commencing with incandescent light bulbs, every load today creates harmonics. Unfortunately, these loads vary with respect to their amount of harmonic content and their response to problems caused by harmonics. The prevalent difficulties with harmonics are voltage and current waveform distortions. In addition, Electronic equipment like computers, battery chargers, electronic ballasts, variable frequency drives, and switching mode power supplies generate perilous amounts of harmonics. Issues related to harmonics are of a greater concern to engineers and building designers because they do more than just distort voltage waveforms, they can overheat the building wiring, cause nuisance tripping, overheat transformer units, and cause random end-user equipment failures. Thus power quality is becoming more and more serious with each passing day. As a result, active power filters (APFs) have gained a lot of attention due to their excellent harmonic compensation. However, the performance of the active filters seems to have contradictions with different control techniques. The main objective of this paper is to analyze shunt active filters with fuzzy and pi controllers. To carry out this analysis, active and reactive current methods ($i_d-i_q$) are considered. Extensive simulations were carried out. The simulations were performed under balance, unbalanced and non sinusoidal conditions. The results validate the dynamic behavior of fuzzy logic controllers over PI controllers.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.5
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• pp.583-591
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• 2007

This paper reports the performance of a 150W PV-wave hybrid system with battery storage in buoy. This system was originally designed to meet a new hybrid ower system for buoy in Korea. In the case or lighted buoys and lighthouses, a light failure alarm system of wireless radio is attached so that light failures are immediately notified to the office. At lighthouse offshore fixed lights and light buoys where commercial electricity is not available, the power source depends on solar system and batteries. This power system has a various problems. Therefore energy derived from the sunshine, wind and waves has been used as the energy source lot aids to navigation. Recently a hybrid system of combining the solar, wind and the wave generator is a favorable system lot the ocean facilities like lighthouse and buoy. The hybrid system in this paper is intended for variable DC load like light, communication system in the buoy and includes a PV-wane generation system and battery. This is composed a high efficiency charging algorithm, switching converter and controller. This paper includes discussion on system reliability, power quality, and effects of hybrid system in the buoy. Simulation and experimental results show excellent performance.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.290-297
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• 2013

The increasing level of operation in high-tech industry is likely to require ever more complex structure in reliability problem. Furthermore, system failures are more significant on society as a whole than ever before. Reliability redundancy optimization problem (RROP) plays a important role in the designing and analyzing the complex system. RROP involves selection of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. Meanwhile, previous works on RROP dealt with system with perfect failure detection, which gave at most a good solution. However, we studied RROP with imperfect failure detection and switching. Using absorbing Markov Chain, we present not a good solution but the optimal one. In this study, the optimal system configuration is designed with warm and cold-standby redundancy for k-out-of-n system in terms of MTTF that is one of the performance measures of reliability.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.333-340
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• 2022

Recently, the use of large-capacity secondary batteries for electric vehicles is rapidly increasing, and accordingly, the demand for technologies and equipment for battery reliability evaluation is increasing significantly. The existing short circuit test equipment for evaluating the stability of the existing secondary battery consists of relays, MCs, and switches, so when a large current is energized during a short circuit, contact fusion failures occur frequently, resulting in high equipment maintenance and repair costs. There was a disadvantage that repeated testing was impossible. In this paper, we developed an electronic short circuit test device that realizes stable switching operation when a large-capacity power semiconductor switch is energized with a large current, and applied smart ICT technology to this electronic short circuit stability test system to achieve high speed and high precision through communication with the master. It is expected that the inspection history management system based on data measurement, database format and user interface will be utilized as essential inspection process equipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.