• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.169-177
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• 2021

Recently, the use of electric and electronic control systems is increasing in the automobile industry. This increase in the electric and electronic control system greatly increases the complexity of designing a vehicle, which leads to an increase in the malfunction of the system, and a safety problem due to the malfunction is becoming an issue. Based on IEC 61508 relating to the functional safety of electrical/electronic/programmable electronics, the ISO 26262 standard specific to the automotive sector was first established in 2011, and a revision was published in 2018. Malfunctions due to system failure are covered by ISO 26262, but ISO/PAS 21448 is proposed to deal with unintended malfunctions caused by changes in the surrounding environment. ISO 26262 sets out safety-related requirements for the entire life cycle. Functional safety analysis includes FTA (Fault Tree Analysis), FMEA (Failure Mode and Effect Analysis), and HAZOP (Hazard and Operability). These analysis have limitations in dealing with failures or errors caused by complex interrelationships because it is assumed that a failure or error affecting the risk occurs by a specific component. In order to overcome this limitation, it is necessary to apply the STPA (System Theoretic Process Analysis) technique.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2001년도 학술대회논문집
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• pp.51-58
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• 2001

This paper gives a type and high-frequency waves analysis of in-rush current cab be flowed into distribution automatic machine to be installed in distribution line in order to use minimizing operation error of failure indicator to have been issue recent with obtaining high-frequency component that can be different from current. The in-rush and fault current data studied in this paper is to be surveyed actually in USA distribution system substation line of Bryan Power Company near Texas A. M University, to be occurred high impedance fault.

• 전기학회논문지
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• 제60권9호
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• pp.1788-1794
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• 2011

The mold transformer is a complex and critical component of DC substations in Metro system. In this paper, a cost effective and intelligent condition monitoring system for mold transformers in DC substations was developed. This paper also provides an overview of the management program using PD (partial discharge) data on mold transformers. Prior to application of the proposed system to Metro DC substations, experiments were performed at the metro line substation located in Seoul and presented case studies for the use of the intelligent condition monitoring system for mold transformer in DC substations. The experiment results indicated that the developing system can be need in helping mange the risk of unexpected failure of mold type transformers.

• 대한전기학회논문지:전력기술부문A
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• 제49권8호
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• pp.390-398
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• 2000

Leakage impulse current of the contaminated insulators by using experiment data were studied. The impulse current in phase-time relationship was analyzed on line post insulators. Also, frequency components and crest factor of the leakage current were investigated to provide a scheme for an early detection of insulator incipient failure. The study shows that the phase-time characteristic is non-stationary and random and, non-harmonic component and crest factor can be promising parameters for detecting insulator leakage currents.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1406-1416
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• 2017

In complex and large-scale industries, properly designed fault detection and identification (FDI) systems considerably improve safety, reliability and availability of target processes. In thermal power plants (TPPs), generating units operate under very dangerous conditions; system failures can cause severe loss of life and property. In this paper, we propose a bagged auto-associative kernel regression (AAKR)-based FDI approach for steam boilers in TPPs. AAKR estimates new query vectors by online local modeling, and is suitable for TPPs operating under various load levels. By combining the bagging method, more stable and reliable estimations can be achieved, since the effects of random fluctuations decrease because of ensemble averaging. To validate performance, the proposed method and comparison methods (i.e., a clustering-based method and principal component analysis) are applied to failure data due to water wall tube leakage gathered from a 250 MW coal-fired TPP. Experimental results show that the proposed method fulfills reasonable false alarm rates and, at the same time, achieves better fault detection performance than the comparison methods. After performing fault detection, contribution analysis is carried out to identify fault variables; this helps operators to confirm the types of faults and efficiently take preventive actions.

• 전기학회논문지P
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• 제64권1호
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• pp.29-34
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• 2015

DC bus electrolytic capacitors are used in variety of equipments as smoothing element of the power converters because it has high capacitance for its size and low price. It is responsible for frequent breakdowns of many static converters and inverter drive systems. Therefore it is important to diagnosis monitoring the condition of an electrolytic capacitor in real-time to predict the failure of power converter. In this paper, the on-line remote diagnosis monitoring system for DC BUS electrolytic capacitors of power converter using low-cost type Zigbee communication modules is developed. To estimate the health status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The capacitor ESR is estimated by using RMS computation using AC coupling method of DC link ripple voltage/current. The Zigbee communication-based experimental results show that the proposed remote DC capacitor diagnosis monitoring system can be applied to DC/DC converter and UPS successfully.

• 전기학회논문지P
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• 제60권3호
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• pp.114-119
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• 2011

Large Power transformer is a complex and critical component of power plant and consists of cellulosic paper, insulation oil, core, coil etc. Insulation materials of transformer and related equipment break down to liberate dissolved gas due to corona, partial discharge, pyrolysis or thermal decomposition. The dissolved gas kinds can be related to the type of electrical faults, and the rate of gas generation can indicate the severity of the fault. The identities of gases being generated are using very useful to decide the condition of transformation status. Therefore dissolved gas analysis is one of the best condition monitoring methods for power transformer. Also, on-line multi-gas analyzer has been developed and installed to monitor the condition of critical transformers. Rogers method, IEC method, key gas method and Duval Triangle method are used to failure diagnosis typically, and those methods are using the ratio or kinds of dissolved gas to evaluate the condition of transformer. This paper analyzes the reliability of transformer diagnostic methods considering actual dissolved gas concentration. Fault diagnosis is performed based on the dissolved gas of five transformers which experienced various fault respectively in the field, and the diagnosis result is compared with the actual off-line fault analysis. In this comparison result, Diagnostic methods using dissolved gas ratio like Rogers method, IEC method are sometimes fall outside the ratio code and no diagnosis but Duval triangle method and Key gas method is correct comparatively.

• 한국자기학회지
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• 제12권5호
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• pp.168-173
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• 2002

본 연구에서는 인체모델(humman body model; HBM)을 터널링 자기저항(tunneling magneto resistance; TMR)소자에 연결하여 정전기에 대한 방전특성을 연구하였다. 이를 위해 제조된 TMR 시편을 전기적 등가회로 바꿔 HBM에 연결하여 PSPICE를 이용해 시뮬레이션 하였다. 이러한 등가회로에서 접합부분의 모델링 요소들의 값을 변화시켜 방전특성을 관찰할 수 있었다. 그 결과 시편의 저항과 정전용량 성분의 값이 다른 요소들에 비해 수배에서 수백 배까지 커서 정전기 방전(electrostatic discharge; ESD) 민감도를 좌우하는 주요한 요소임을 알 수 있었다. 여기에서 ESD현상에 대한 내구성을 향상시키기 위해서는 정전용량을 증가시키는 것 보다 접합면과 도선의 저항값을 줄이는 것이 유리하다. 그리고 직류 전압에 대해 절연층의 전위 장벽이 낮아져 많은 전류가 흐르게 되는 항복(breakdown)전압과 셀의 물리적 구조 및 성질이 변형되어 회복되지 못하는 파괴(failure)전압을 측정하여 DC 상태에서의 내구성을 연구하였다. 이 결과를 HBM 전압에 대한 파괴 전압으로 간주하여 TMR 소자가 견딜 수 있는 HBM 전압을 예측할 수 있었다.

• 대한안전경영과학회지
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• 제15권3호
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• pp.105-112
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• 2013

To meet the growing needs from a variety of stakeholders, the development of modern systems is getting more complex and thus, the systems failure in the actual operations can potentially become more serious. This is why several international or military standards on systems safety have been published. In spite of the importance of meeting those standards such as IEC 61508 and ISO 26262 in the systems development, the associated practical methods seem deficient since those standards do not provide them. The objective of this paper is to present a method to identify potential hazards in fulfilling the requirements of the safety standards. In particular, the approach taken here is based on applying the functional analysis that covers several levels of the system under development. Note, however, that in the most of the conventional methods for hazards identification, the analysis has been focused on the failure at or underneath the component level of the system. The hazards identification method in this paper would cover the level up to the system by utilizing the functions-oriented approach. The case study of the safety enhancement for locomotive cabs is also discussed.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.533-538
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• 2014

Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. I t designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick's second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.