• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.937-943
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• 2012

Most of faults occurred in transmission lines are single-phase to ground faults and transient faults. Single-phase auto reclosing is an appropriate scheme to maintain the system stability and restore the system effectively when those faults are occurred. In single-phase auto reclosing scheme, the secondary arc is generated after faulted phase is tripped to eliminate the fault and it is sustained by the capacitive and inductive coupling to the healthy phases. It is important to reclose the faulted phase after fully extinction of secondary arc because of the damage applied to system. Therefore, it is necessary to research on the detection of secondary arc extinction to ensure high success rate of reclosing. In this step, firstly, the accurate modelling of secondary arc should be performed. In this paper, the modelling of secondary arc is performed by using EMTP-RV and the simulation results show that the implemented model is correct and effective.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.43-51
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• 2001

As the density of memories increases, unwanted interference between cells and coupling noise between bit-lines are increased. And testing high-density memories for a high degree of fault coverage can require either a relatively large number of test vectors or a significant amount of additional test circuitry. So far, conventional test algorithms have focused on faults between neighborhood cells, not neighborhood bit-lines. In this paper, a new test algorithm for neighborhood bit-line sensitive faults (NBLSFs) based on the NPSFs(Neighborhood Pattern Sensitive Faults) is proposed. And the proposed algorithm does not require any additional circuit. Instead of the conventional five-cell or nine-cell physical neighborhood layouts to test memory cells, a three-cell layout which is minimum size for NBLSFs detection is used. Furthermore, to consider faults by maximum coupling noise by neighborhood bit-lines, we added refresh operation after write operation in the test procedure(i.e.,$write{\rightarrow}\;refresh{\rightarrow}\;read$). Also, we show that the proposed algorithm can detect stuck-at faults, transition faults, coupling faults, conventional pattern sensitive faults, and neighborhood bit-line sensitive faults.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.423-430
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• 2009

Recently as the inactive response characteristics of the existing RCD used on low voltage power distribution system, so control of overload and electric short circuit faults, major causes of electrical fires, are not enough. Therefore, this paper confirms the unreliability of the existing RCD by electrical fault simulator and proposes a EFDPD by using semiconductor switching devices and a high precision current sensor (namely, reed switch) for the prevention of electrical disasters in low voltage power distribution system caused by overload or electric short circuit faults. The sensitive reed switch in the proposed EFDPD exactly detects the increased magnetic flux with the overload or the short current caused by a number of electrical faults, and the following, the self circuit breaker in EFDPD rapidly cuts off the system. The proposed EFDPD confirms the excellent characteristics in response velocity and accuracy in comparison with the conventional circuit breaker through various operation performance analysis. The proposed EFDPD can also prevent electrical disasters, like as electrical fires, which resulted from the malfunction and inactive response characteristics of the existing RCD.

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1663-1665
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• 1998

The power distribution system is 22.9 kV-y neutral point multi-ground one in our country. So, if conducting materials contacted, to the power line electrical equipment faults or stoppage of electrical power supply happened in the line. contacts are caused by magpie or its nest materials, especially, electrical power incidents by magpie from February to May, season layed egg, is high as 30% as. It is important to electrical power supplier to protect electrical power equipment caused by magpie. From now, KEPCO have tried to protect electrical power equipment faults caused by magpie using several methods, but have not acquired good results and continued to withdraw the nest. Recently, nature environment protection expand to around country and KEPCO also changed the nest withdrawal method to new pre-protection method coexisted with magpie, "Environmental Affinitive Pre-protection Counterplan". Therefore, we planned environmental affinitive pre-protection equipment, set test line. Also, after analyzed its effects during 1 year, we satisfied with results, and then expanded to other test lines and regions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.82-87
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• 2013

Electrical leakage happens when faults in electrical apparatus or power lines occur. It causes electrical fires and electric shocks. In order to reduce accidents caused by electrical leakage current, it is important to detect faults effectively and shut off the power. In this paper, firstly we analyzed statistics of electrical fires and electric shocks caused by electrical leakage current. Secondly, standards of allowable leakage current and body impedance models were analyzed. Lastly, effective application methods for breaking electrical leakage current were suggested. The results will provide useful preventive measures of electrical fires and electric shocks caused by electrical leakage.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.952-954
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• 1998

This paper presents an artificial neural network approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. The proposed algorithm is used to detect faults with or without cellulose involved. Several neural network topologies have been considered. Good diagnosis accuracy is obtained with the proposed approach.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1353-1355
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• 1996

This paper presents classification of high impedance fault pattern using linear prediction coefficients. A feature of neutral phase current is extracted by the linear predictive coding. This feature is classified into faults by a multilayer perceptron neural network. Neural network successfully classifies test data into three faults and one normal state.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1007-1016
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• 2007

In power system, substation facilities have become too complex and larger according to an extended power system. Also, customers require the high quality of electrical power system. However, some facilities become old and often break down unexpectedly. The unexpected failure may cause a break in power system and loss of profits. Therefore it is important to prevent abrupt faults by monitoring the condition of power systems. Among the various power facilities, power transformers play an important role in the transmission and distribution systems. In this research, we develop intelligent diagnosis technique for predicting faults of power transformer by FCM(Fuzzy c-means) and Euclidean based distance measure. The proposed technique make it possible to measures the possibility and degree of aging as well as the faults occurred in transformer. To demonstrate the validity of proposed method, various experiments are performed and their results are presented.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1376-1385
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• 2017

This paper proposes a method for estimating the expected frequency of voltage swells caused by asymmetrical faults in a power system. Although voltage swell is less common than voltage sag, repeated swells can have severe destructive impact on sensitive equipment. It is essential to understand system performance related to voltage swells for finding optimal countermeasures. An expected swell frequency at a sensitive load terminal can be estimated based on the concept of an area of vulnerability (AOV) and long-term system fault data. This paper describes an effective method for calculating an AOV to voltage swells. Interval estimation for an expected swell frequency is also presented for effective understanding of system performance. The proposed method provides long-term performance evaluation of the frequency and degree of voltage swell occurrences.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.36-39
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• 2000

This paper presents the technology of condition diagnosis & life estimation on insulation system of the traction motor. In the non-destructive methods for diagnosis of coil insulation state, residual dielectric strength is estimated by the D-map which consist of the partial discharge quantity Q and average degradation degree $\Delta$. In the operating history of machine, the N-Y life estimation method is based on the stop-starting numbers and operating times with considering each degradation factor by the thermal, electrical and heat-cycle stress. With the on-line conditioning monitoring on the currents of traction motors, detecting the abnormal operating state due to bearing faults, stator or armature faults, eccentricity related faults and broken rotor bars can be performed.