• 전기학회논문지
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• 제67권11호
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• pp.1542-1548
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• 2018

When any faults occurred in electrical railway system, operators need to analysis it quickly and accurately. Existing COMTRADE based analysis tools are not enough to analysis faults occurred in electrical railway system. In this paper, it presents some functions to fault analysis for electrical railway system based on fault data formatted COMTRADE. These functions are implemented in PSCAD/EMTDC and it can be shown that analyzed results against actual electrical fault cases which were occurred in the electrical railway power system.

• International Journal of Control, Automation, and Systems
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• 제6권3호
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• pp.339-350
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• 2008

A general active fault-tolerant control framework is proposed for nonlinear systems with sensor faults. According to their identifiability, all sensor faults are divided into two classes: identifiable faults and non-identifiable faults. In the healthy case, the control objective is such that all outputs converge to their given set-points. A fault detection and isolation module is firstly built, which can produce an alarm when there is a fault in the system and also tell us which sensor has a fault. If the fault is identifiable, the control objective remains the same as in the healthy case; while if the fault is non-identifiable, the control objective degenerates to be such that only the healthy outputs converge to the set-points. A numerical example is given to illustrate the effectiveness and feasibility of the proposed method and encouraging results have been obtained.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.485-487
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• 1997

Schemes for detecting and diagnosing faults are presented. Faults are detected when residuals change significantly and thresholds are exceed. Two stage artificial neural networks are applied to diagnose faults. The idealized steady state patterns of residuals are defined and learned by ANNs using back propagation algorithm. The first stage ANN is trained to classify the subsystem in which the various faults are located. The first stage ANN could be also used to detect faults with threshold, checking. The second stage ANNs are trained to discriminate the specific cause of a fault at the subsystem level.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.244-251
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• 1997

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전력기술부문
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• pp.37-39
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• 2007

In the faults of power line, single line ground and line-to-line fault make power system to unbalanced. These fault currents make unbalanced power system. This paper suggests the simulation results of dynamic characteristic of HTS cable system under unbalanced faults condition using EMTDC, Quench phenomenon and current limiting effects are observed. However, quench on the HTS is destroy cable system, coordination with SFCL has to be considered.

• 전기전자학회논문지
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• 제24권3호
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• pp.727-734
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• 2020

본 논문은 과도 고장을 가지는 비동기 순차 머신에 대한 내고장성 교정 제어를 다룬다. 본 논문에서 다루는 고장은 머신이 과도 상태 천이를 거칠 때 발현할 수 있으므로 비-기본 모드(non-fundamental mode)에서 원하지 않는 상태 천이를 일으킨다. 본 논문에서는 비동기 순차 머신의 비-기본 모드에서 발생하는 과도 고장을 탐지하고 극복할 수 있는 새로운 내고장성 제어 시스템을 제안한다. 교정 제어 이론의 틀 안에서 내고장성 제어기의 존재 조건과 설계 과정을 제시한다. 또한 제안된 제어 시스템의 효용성을 검증하기 위해 FPGA 실험을 실시한다.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• 조명전기설비학회논문지
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• 제22권3호
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• pp.52-58
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• 2008

The importance of. identifying the causes of electrical faults cannot be overstated because of the accidents caused by over-current that take place at the home, the office and electrical facilities due to misuse, poor products and system faults. It is necessary to gather objective, scientific data pertaining to electrical fault investigation in a product liability(PL) environment. To date, no database(DB) has been built concerning the accurate cause analysis of faultyfacilities. In this paper, accident hazard and arc scattering when over-current flows in copper wire was investigated. It was found that when over-current flows in a copper wire, the copper wire became heated and bent and beads were scattered around the wire with a flash. It was determinedthat the fusing current and time was related to the current rise per second. For example, when the current rise per second was largethe fusing current was higher than when the current rise per second was small, and the beads dispersed along a wide area. Fusing time, however, was shorter. The possibility of electrical fault became highest when the fusing current was higher. As the current rise per second is short, the dendrite structure is distributed in the surface of the copper wire. These experimental results can be utilized for a fault process DB system in the investigation and the prevention of electrical faults.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1074-1077
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• 1993

The objective of this paper is to develop a fuzzy logic based decision-making system to detect low current faults using multiple detection algorithms. This fuzzy system utilizes a fuzzy expert model which executes an operation without complicated mathematical models. This fuzzy system decides the performance weights of the detection algorithms. The weights and the turnouts of the detection algorithms discriminate faults from normal events. This system can also be a generic group decision-making tool for other areas of power system protection.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.156-158
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• 1993

This paper presents several techniques of power spectrum estimation for high impedance fault detection. High impedance faults are those faults with current too low to be reliably cleared by conventional overcurrent protection. So power spectrum estimation is required. AR and MA techniques require optimal order for good performance of power spectrum estimation because these techniques are unstable for order selection. ARMA and Extended techniches are stable for order selection and have very sharp response. So ARMA and Extended Prony techniques are suitable for our purpose.