• 전기학회논문지
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• 제59권7호
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• pp.1276-1281
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• 2010

To analyze the gas discharge phenomena in parallel-plane electrodes, the fully coupled finite element method (FEM) considering secondary electron emission effects in discharge column was adopted in this paper. Two coupled equations of the hydrodynamic diffusion-drift equations for three carriers and the Poisson's equation for electric scalar potential should be solved as a system equation. The proposed method including two secondary electron processes of the photoemission and background ionization has been successfully applied to evaluating the breakdown voltage in parallel-plane electrodes and is verified by comparing its numerical results with the experimental ones. From the obtained results, it is inferred that the proposed numerical scheme will be useful for predicting and understanding streamer transient phenomena.

• Transactions on Electrical and Electronic Materials
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• 제16권3호
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• pp.107-111
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• 2015

Our work is based on the development of a numerical model to develop a methodology for predicting the aging and breakdown in insulation due to the dynamics of space charge packets. The model of bipolar charge transports is proposed to simulate space charge dynamic for high DC voltage in law-density polyethylene (LDPE), taking into account the trapping and detrapping of recombination phenomena, this model has been developed and experimentally validation. Theoretical formulation of the physical problem is based on the Poisson, the continuity and the transport equations as well as on the appropriate models for injection. Numerical results provide temporal and local distributions of the electric field, the space charge density for the different kinds of charges, conduction and displacement current densities, and the external current.

• 대한조선학회논문집
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• 제56권6호
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• pp.473-479
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• 2019

Welding is one of the most popular joining methods and most welding quality estimation methods are executed using joined material. This paper propose welding quality estimation methods using dynamic current, voltage and resistance which are obtained during welding in real time. There are many kinds of welding method. Among them, we focused on the projection welding and gathered dynamic characteristics from two different types of projection welding. For image learning, graphs are drawn using obtained current, voltage and resistance, and the graphs are converted to images. The images are labeled with two sub-categories - normal and defect. For deep learning of images obtained from welding, Convolutional Neural Network (CNN) is applied, and Tensorflow was used as a framework for deep learning. With two resistance welding test datasets, we conclude that the Convolutional Neural Network helps in predicting the welding quality.

• 한국안전학회지
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• 제11권3호
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• pp.75-80
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• 1996

This paper presents a study on characteristics and safety for human body in ELF electric and magnetic fields using statistical method. The magnetic fields from a power line can be computed given a knowledge of the currents, voltage and geometry of the line. In this paper, a statistical method for predicting the magnetic fields given the inherent indetermination of the currents is presented. But the electric field is calculated given a knowledge of the voltage and geometry of the line. The effect of unexpected fluctuations in current is modeled by the Monte Carlo simulation. The suggested method is applied to the 345kV and 765kV transmission line system, the result shows that the maximum electric and magnetic field intensity is 6.8627kV/m and 284mG in 345kV system, 2. 5590kV/m and 35mG in 765kV system, respectively.

• 전력전자학회논문지
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• 제23권6호
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• pp.403-407
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• 2018

This study proposes a predictive direct power control method in a modular multilevel converter (MMC) high-voltage direct-current (HVDC) system. The conventional proportional integral (PI)-based control method uses a cascaded connection and requires an optimal gain selection procedure and additional decoupling scheme. However, the proposed control method has a simple structure for active/reactive power control due to the direct power control scheme and exhibits a fast dynamic response by predicting the future status of system variables and considering time delay. The effectiveness of the proposed method is verified by simulation results.

• 전력전자학회논문지
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• 제13권4호
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• pp.247-256
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• 2008

직류철도의 회생제동 시 발생되는 회생에너지는 급전선로의 직류가선전압의 상승에 의해 시스템의 오동작이나 차량 정류기의 파손, 또는 급전 시스템의 전력변환 장치의 고장을 일으키는 원인이 될 수 있다. 슈퍼 커패시터를 이용한 회생에너지 저장장치는 직류가선전압을 안정화 하게하는 방법이다. 본 논문에서는 슈퍼 커패시터 뱅크를 이용하여 직류철도 시스템의 에너지 저장장치를 구현하였고, 지하철 2호선 N역과 S역의 실측값을 이용하여 가선전압이 전동차에 의한 회생에너지 발생에 따른 동작 특성과 슈퍼 커패시터의 충 방전 특성을 확인하였다. 본 논문을 통하여 직류철도 시스템에 설치된 회생에너지 저장시스템용 슈퍼 커패시터 뱅크의 동작 특성을 알 수 있고, 향 후 직류철도 모든 변전소의 직류 가선전압 실측 데이터를 이용한다면, 특정 직류철도 운행 구간에 대한 회생에너지 저장장치의 운전특성과 슈퍼커패시터의 용량 및 수명 예측으로 가격을 절감 할 수 있고 전체 시스템의 안정도 와 신뢰성을 향상시킬 수 있다.

• Journal of Electrochemical Science and Technology
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• 제11권4호
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• pp.346-351
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• 2020

The removal characteristics of copper (Cu) from electrochemical surface by voltage-activated reaction were reviewed to assess the applicability of electrochemical-mechanical polishing (ECMP) process in three types of electrolytes, such as HNO₃, KNO₃ and NaNO₃. Electrochemical surface conditions such as active, passive, transient and trans-passive states were monitored from its current-voltage (I-V) characteristic curves obtained by linear sweep voltammetry (LSV) method. In addition, the oxidation and reduction process of the Cu surface by repetitive input of positive and negative voltages were evaluated from the I-V curve obtained using the cyclic voltammetry (CV) method. Finally, the X-ray diffraction (XRD) patterns and energy dispersive spectroscopy (EDS) analyses were used to observe the structural surface states of a Cu electrode. The electrochemical analyses proposed in this study will help to accurately control the material removal rate (MRR) from the actual ECMP process because they are a good methodology for predicting optimal electrochemical process parameters such as current density, operating voltage, and operating time before performing the ECMP process.

• International Journal of Korean Welding Society
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• 제1권2호
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• pp.36-44
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• 2001

To get the appropriate welding process variables, mathematical modeling in conjunction with many experiments is necessary to predict the magnitude of weld bead shape. Even though the experimental results are reliable, it has a difficulty in accurately predicting welding process variables for the desired weld bead shape because of nonlinear and complex characteristics of welding processes. The welding condition determined for the desired weld bead shape may cause the weld defect if the welding current/voltage/speed combination is improperly selected. In this study, the $2^{n-1}$ fractional factorial design method and correlation parameter were used to investigate the effect of the welding process variables on the fillet joint shape, and the multiple non-linear regression analysis was used for modeling the gas metal arc welding(GMAW）parameters of the fillet joint. Finally, a fuzzy rule-based method and a neural network method were proposed so that the complexity and non-linearity of arc welding phenomena could be effectively overcome. The performance of the proposed neuro-fuzzy system was evaluated through various experiments. The experimental results showed that the proposed neuro-fuzzy system could effectively check the welding conditions as to whether or not weld defects would occur, and also adjust the welding conditions to avoid these weld defects.

• 시스템엔지니어링학술지
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• 제4권1호
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• pp.35-43
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• 2008

Generally, in analysis of reliability of Design and Development Phase, reliability of electrical components is analyzed based on standards such as MIL-HDBK-217F, Bellcore Issue 4,5,6 by analyzing stress of architectural side (Power, Voltage, Current and quality level of components) of weapon system and stress of operational side (operational environment, operational temperature, Operational Profile). But the reliability of mechanical components is analyzed based on the data book of failure history of mechanical parts called NPRD-95(Nonelectronic Parts Reliability Data-95) without any analysis of above stress. However, even if it's the same mechanical parts, it might have different failure rate(fatigue, wear, corrosion) during operation depending on how weary(stress : pressure, vibration, temperature during operation) the parts are. Therefore, analyzing reliability using just data book can cause big difference in reliability instead of analyzing based upon stressfulness that parts might have, operational concept, and other various factors. Thus, This paper will guide the way of predicting reliability by organizing ways of predicting reliability for system organization and adopt ing NSWC-98/LE1(Naval Surface Warfare Center-98/LE1) for mechanical components.

• Journal of Power Electronics
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• 제4권2호
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• pp.102-111
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• 2004

This paper is concerned with a deadbeat current control implementation of shunt-type three-phase active power filter (APF). Although the one-dimensional deadbeat control method can attain time-optimal response of APF compensating current, one sampling period is actually required fur its settling time. This delay is a serious drawback for this control technique. To cancel such a delay and one more delay caused by DSP execution time, the desired APF compensating current has to be predicted two sampling periods ahead. Therefore an adaptive predictor is adopted for the purpose of both predicting the control error of two sampling periods ahead and bringing the robustness to the deadbeat current control system. By adding the adaptive predictor output as an adjustment term to the reference value of half a source voltage period before, settling time is made short in a transient state. On the other hand, in a steady state, THD (total harmonic distortion) of the utility grid side AC source current can be reduced as much as possible, compared to the case that ideal identification of controlled system could be made.