• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.667-669
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• 2005

지중배전선로에 설치되어 있는 23kV 수동개폐기의 고장표시 상태를 단말장치와 소출력 RF 통신을 이용하여 배전자동화 주장치에서 FII(Fault Indicator)로 고장 판단할 수 있는 시스템 구성에 대해 논하고자 한다.

• 한국정밀공학회지
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• 제32권7호
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• pp.611-617
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• 2015

In the development of a vibration-based condition monitoring system in gearbox, one of the most important research topics is a quantitative analysis and test of the effect of gear damage on vibration of gearbox. This paper presents the evaluation result of vibration condition indicator according to the gear tooth damage through the vibration test of gearbox. The dynamic load test was performed with high speed railway (KTX)'s gearbox. The vibration of gearbox was measured according to a rotational speed change with the common gear fault modes, such as pitting and tooth breakage. The characteristics and the possibility of applying of vibration condition indicator on condition monitoring system were analyzed. As a result, the value of most condition indicator is gradually increased with the severity of gear faults. The NA6 indicator shows a low variation with the rotational speed change and high sensitivity in accordance with the gear fault.

• 한국지능시스템학회논문지
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• 제17권3호
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• pp.374-379
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• 2007

본 논문은 전력계통의 배전계통시스템에서 FRTU(Feeder remote terminal unit)의 고장검출 알고리즘의 개선에 관한 연구이다. FRTU는 상과 지락에 관한 고장검출을 할 수 있다. 특히 고장픽업 기능과 돌입억제기능은 일반적인 부하전류로부터 고장전류를 구별할 수 있다. FRTU는 돌입전류 또는 설정값을 초과한 고장전류가 발생하면 고장표시기(FI)로 고장을 발생한다. 짧은 시간 푸리에 변환(STFT) 분석은 주파수와 시간에 관한 정보론 제공하고, 퍼지 중심 평균 클러스터링(FCM) 알고리즘은 고조파의 특성을 추출한다. 고장 검출기의 신경회로망 시스템은 최급강하법을 이용하여 고장상태로부터 돌입전류를 구별하도록 학습된다. 본 논문에서는 FCM과 신경회로망을 이용하여 고장검출기법을 개선하였다. 검증에 사용된 데이터는 22.9KV 배전계통 시스템에서 실제 측정된 데이터이다.

• 제어로봇시스템학회논문지
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• 제9권11호
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• pp.874-882
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• 2003

The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.39-47
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• 2016

In this paper, we propose vehicle SoC fault diagnosis platform using FlexRay protocol in order to detect the faults of semiconductor control chip even after vehicle production. Before FlexRay protocol by sending NFI (Null Frame Indicator) bit among the header segment and a specific identifier in the payload segment of FlexRay frame, this technique can be distinguishable from normal mode and test mode. By using this technique, it is possible to detect the faults such as performance degradation of vehicle network system caused by the aging or several problems of vehicle semiconductor chip. Also high reliability and safety of vehicle can be maintained by using structural test for vehicle SoC fault detection.

• 한국전기전자재료학회논문지
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• 제33권1호
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• pp.65-69
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• 2020

The aim of this study is to improve the fault decision ability of FRTU (Feeder remote terminal unit) in DAS (Distribution automation system). FRTU uses the FI (Fault indicator) algorithm based on fault current pickup and operation of the protection device. Even if the inrush current flows or the protection device is sensitive to the transient current, FRTU may indicate incorrect fault information. To address these problems, we propose an improved fault recognition algorithm that can be applied to FRTU. We will detect a specific wave that is indicative of a fault, and use this information to identify a fault wave. The specific wave-detection algorithm is based on the duration and periodicity of the voltage, current, and harmonic variations. In addition, we propose fault recognition algorithms using voltage factor variation analysis and DWT (Discrete wavelet transform). All the wave data used in this study were actual data stored in FRTU.

• 전기학회논문지
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• 제64권10호
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• pp.1418-1425
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• 2015

In this paper, an filtering method of FI(Fault Indication) information generated by FRTU(Feeder Remote Terminal Unit)s is proposed for the present DAS(Distribution Automation System). In order to find fault area, correct FI information should be generated. But when a single line-to-ground fault occurs, FI information is generated in downside of the fault in some circumstance because existing FI algorithm considers only magnitude. These wrong FI information can be removed by changing existing algorithm. An improved algorithm considers both the direction of zero-sequence current and the phase of three-phase current&voltage. But many FRTUs are distributed in DAS and Changing the algorithm all of FRTU will spend a lot of time and cost. On the other hand, an filtering algorithm proposed in this paper can substitute for it. The filtering algorithm also considers both the direction of zero-sequence current and the phase of three-phase current&voltage. In case study, the proposed method has been shown the reasonability in filtering the fault indication information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.32.6-32
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• 2002

The damage localization of the structural system using the natural frequency measurement only is proposed. The existing methods use the changes of mode shape, strain mode shape or curvature mode shape before and after the damage occurrence as these shapes carry the geometric information of the structure. Basically, the change of natural frequencies of the structure can be used as the indicator of the damage occurrence but not as the indicator of the damage location as the natural frequency changes does not carry the geometric information of the structure. In this research, the feedback scope method that measures the natural frequency changes of the structure with and without the feedback Ioo...

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.125-127
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• 1999

We generally use Yes-No algorithms for feeder automation algorithm. This logic determines the faulty section by fault current detection information of the fault indicators of each switches in distribution feeder. This paper presents the data acquisition method such as breaker's open status in fault and the determination method of faulty section using fault indicator's information of each switches.

• 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.