• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.417-423
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• 2001

This paper proposes a technique for fault detection and classification for both LIF(Low Impedance Fault)s and HIF(High Impedance Fault)s using Adaptive Network-based Fuzzy Inference System(ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square(RMS) values of 3-phase currents and zero sequence current. The performance of the proposed technique is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classily faults including (LIFs and HIFs) accurately within half a cycle.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.491-498
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• 2009

This paper presents the design method of an impedance matching network using an isolation transformer and the Chebyshev filter function for the high efficiency and the flat power driving of an underwater acoustic piezoelectric transducer. The proposed impedance matching network is designed for minimizing the reactance component of transducer and having the flat power response in the wide frequency range. We design a low pass filter with ladder-type circuit using the Chebyshev function as standard prototype filter function. In addition, we design the impedance matching network which is suitable for the equivalent circuit of transducer and the turn ratio of transformer through the bandpass frequency transformation. The proposed method is applied to the simulated dummy load of the tonpilz-type transducer operating in the middle frequency range. The simulation results are compared with the measured characteristics and the validity of the proposed method is verified.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.2
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• pp.130-134
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• 2020

Metal oxide varistors (MOVs) protect circuits and devices from transient overvoltages in electric power systems. However, a MOV continuously deteriorates owing to manufacturing defects or repetitive protective operations from transient overvoltages. A deteriorated MOV may result in a short circuit or a line-ground accident. Previous studies focused on the analysis of deterioration mechanisms and condition diagnosis techniques for MOVs owing to their recent growth of use. An accelerated deterioration experiment under the same conditions in which a MOV operates is essential. In this study, we designed and fabricated a surge generator that can apply a surge current to a MOV connected to AC mains. The coupling network operates at a low impedance against the surge current from the surge generator and transfers the surge current to the MOV under test. It also acts as a high impedance against AC mains for the AC voltage not to be applied to the surge generator. The decoupling network operates at a high impedance against the surge current and blocks the surge current from AC mains. It also acts as a low impedance against AC mains for the AC voltage to be applied to the MOV under test. The prototype surge generator can apply the 8/20 us up to 15 kA on AC voltages in the approximate range of 110~450 V, and it fully operates on a LabVIEW-based program.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.3
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• pp.305-316
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• 1998

The impedance matching network with the simplfied real frequency technique (SRFT) is proposed as a method for bandwidth enhancement of microstrip antenna. The validity of the technique is based on the relative frequency insensitivity of the radiation pattern and gain characteristics as compared to the resonant behaviour of the input impedance. The most significant feature of this technique is that there is no need to find any analytical description of the antenna and generator, and it only utilizes directly real frequency generator and load data over the prescribed frequency band. Furthermore, it is not necessary to invent an analytic form of the system transfer function to assume a matching network topology in advance. In this paper, the transmission line model is used to investigate the rectangular microstrip antenna, and based on the Fano's bandwidth-enlargement theory, the SRFT is introduced to design the matching networks of microstrip antennas in order to obtain a constant gain over the frequency band of interest. Two representative microstrip antnnas with different structure are fabricated and tested. From these procedures, it is obtained that the proposed impedance matching networks of microstrip antenna improve the impedance bandwidth nearly three times compared to the antenna without them.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.278-286
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• 2000

A new large-scale network geometric analysis is introduced. For a large-scale circuit, it must be analyzed with a geometric diagram and figure. So many equations are induced from a geometric loop-node diagram. The results are arranged into a simple matrix, of course. In case of constructing a network diagram, it is not easy to handle voltage and current sources together. Geometric loop analysis is related to voltage sources, and node analysis is to current sources. The reciprocal transfer is possible only to have series or parallel impedance. If not having this impedance, in order to obtain equivalent circuit, many equations must be derived. In this paper a loop-reduction method is proposed. With this method current source branch is included into the other branch, and disappears in circuit diagram. So the number of independent circuit equations are reduced as much as that of current sources. The number is not (b-n+1), but (b-n+1-p). Where p is the number of current sources. The reduction procedure is verified with a geometric principle and circuit theory. A resultant matrix can be constructed directly from this diagram structure, not deriving circuit equations. We will obtain the last results with the help of a computer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.459-462
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating. so it is well hon that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.666-671
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• 2010

Multi-layer perceptron neural networks have been constructed to classify four types of defects in steam generator tubes. Three features are extracted from the signals of the eddy current testing method. These include maximum impedance, phase angle at the point of maximum impedance, and an angle between the point of maximum impedance and the point of half the maximum impedance. Two hundred sets of these features are used for training and assessing the networks. Two approaches are involved to train the networks and to classify the defect type. One is the conjugate gradient method and the other is the Broydon-Fletcher-Goldfarb-Shanno method which is recognized as the most popular algorithm of quasi-Newton methods. It is found from the computation results that the training time of the Broydon-Fletcher-Goldfarb-Shanno method is much faster than that of the conjugate gradient method in most cases. On the other hand, no significant difference of the classification performance between the two methods is observed.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.897-899
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• 1997

The analysis of distribution line faults is essential to the proper protections of the power system. A high impedance fault does not make enough current to cause conventional protective devices. It is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. This paper describes an algorithm using back-propagation neural network for pattern recognition and detection of high impedance faults. Fractal dimensions are estimated for distinction between random noise and chaotic behavior in the power system. The fractal dimension of the line current is also used as a indication of the high impedance fault.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.788-795
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• 2000

In this paper, a method for the precise impedance measurement of coaxial loads using an offset open and short as the reflection standards and reference air lines with different lengths as the impedance standards is proposed. Measured input impedances of power sensors and thermistor mounts obtained from SWR bridges(5~400MHz) and a vector network analyzer(100~1,000MHz) are presented in the frequency range of 5MHz to 1,000 MHz.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.366-368
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• 2000

When faults occur in transmission lines, the classification of faults is very important. If the fault is HIF(High Impedance Fault), it cannot be detected or removed by conventional overcurrent relays (OCRs), and results in fire hazards and causes damages in electrical equipment or personal threat. The fast discrimination of fault needs to effective protection and treatment and is important problem for power system protection. This paper proposes the fault detection and discrimination algorithm for LIFs(Low Impedance Faults) and HIFs(High Impedance Faults). This algorithm uses artificial neural networks and variation of 3-phase maximum currents per period while faults. A double lines-to-ground and line-to-line faults can be detected using Neural Network. Also, the other faults can be detected using the value of variation of maximum current. Test results show that the proposed algorithms discriminate LIFs and HIFs accurately within a half cycle.