• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1376-1378
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• 1999

Most conventional protection relays are based on processing information in the spectrum that is close to or at power frequency. It is, however, widely known that faults on transmission lines produce frequency components of a wide range In this respect, this paper describes the basis of a Protection technique for transmission lines which utilises high-frequency components. Fault-generated signals caused by post-fault and the signal derived from stack tuner is connected to the coupling capacitor of CVT. Digital signal processing is then applied to the captured information to determine whether the fault is inside or outside the Protected zone, and to discriminate the fault type on transmission line.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1465-1467
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• 1999

An Algorithm is devised to discriminate power distribution faults from other activites utilizing the arc activity and changes in the loading. This scheme intends to determine the cause of the transients and identify them. the discrimination algorithm was tested using recorded event data.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.458-460
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• 2007

RBF 네트워크의 중간층은 클러스터링 하는 층으로 주어진 자료 집합을 유사한 클러스터들로 분류하는 것이다. 여기서 유사하다는 것은 입력 데이터들에 대한 특징 벡터 공간사이에서 한 클러스터내의 벡터들 간에 거리를 측정하여 정해진 반경 내에 존재하면 같은 클러스터로 분류하고 정해진 반경 내에 존재하지 않으면 다른 클러스터로 분류한다. 그러나 정해진 반경 내에서 클러스터링 하는 것은 잘못된 클러스터를 선택하는 단점을 가지게 된다. 그러므로 중간층을 결정하는 것은 RBF 네트워크의 전반적인 효율성에 큰 영향을 준다. 따라서 본 논문에서는 효율적으로 중간층을 결정하기 위한 방법으로 퍼지 C-Means 클러스터링 알고리즘을 이용하고자 하였다. 그리하여 본 논문에서는 고장 전류의 특성을 해석하여 그 원인을 판단, 분류하기 위하여 전력계통의 고장 기록 장치로부터 얻어지는 선로의 전류 데이터를 FCM을 이용 분류하여 다양한 고장 모드를 판별할 수 있었다.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.210-212
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• 2003

Conventional PDC relaying with 2nd harmonic restraint makes some doubt in reliability. It can contain second harmonic component to a large extent even during internal fault, and shows a tendency of relative reduction because of the advancement of transformer's core material. It is, therefore, necessary to develop a new algorithm as well as a new technique for the effective and accurate discrimination. This paper deals with advanced algorithm, fuzzy logic based relaying by using flux differential, and a new fault detection criterion logic scheme by using wavelet transform. To comparative analysis of proposed techniques, the paper constructs power system model including power transformer, utilizing the EMTP, and collects data through simulation of various internal faults and magnetizing inrush.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.172-172
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• 2009

In this study, we presented comparative discrimination methods to identify various line and planar defects observed in nonpolar a-GaN epilayers on r-sapphire substrates. Unlike the case of conventional c-GaN, which is dominated by perfect threading dislocations, systematic identification of undistinguishable defects using transmission electron microscopy (TEM) is necessary to suppress the propagation of defects in nonpolar GaN epilayers. Cross-sectional TEM images near the [0001] zone axis revealed that perfect mixed and pure screw type dislocations are visible, while pure edge, partial dislocations, and basal stacking faults (BSFs) are not discernible. In tilted cross-sectional TEM images along the [$1\bar{2}10$] zone axis, the dominant defects were BSFs and partial dislocations for the $g=10\bar{1}0$ and 0002 two-beam images, respectively. From plan view TEM images taken along the [$11\bar{2}0$] axis, it was found that the dominantpartial and perfect dislocations were Frank-Shockley with b=${\pm}1/6$<$20\bar{2}3$> and mixed type without an 1 component including b=${\pm}1/3$<$1\bar{2}10$> and ${\pm}1/3$<$\bar{2}110$>, respectively. Prismatic stacking faults were observed as inclined line contrast near the [0001] zone axis and were visible as band contrast in the two-beam images along the [$1\bar{2}10$] and [$11\bar{2}0$] zone axes.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.329-336
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• 2008

The facilities with new technologies in the recent power plants become larger and need a lot of high cost for maintenance due to stop operations and accidents from the operating machines. Therefore, it claims new systems to monitor the operating status and predict the faults of the machines. This research classifies the normal/abnormal status of the machines into 5 levels which are normal-level/abnormal-level/care-level/dangerous-level/fault and develops the new system that predicts faults without stop operation in power plants. We propose the regional segmentation technique in the frequency domain from the data of the operating machines and generate the Peak-codes similar to the Bar-codes, The high efficient and economic operations of the power plants will be achieved by carrying out the pre-maintenance at the care level of 5 levels in the plants. In order to be utilized easily at power plants, we developed the algorithm appling to a notebook computer from signal acquisition to the discrimination.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.3
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• pp.75-81
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• 2007

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to Fourier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the Fast Fourier Transform(FFT).

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1697-1708
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• 2017

This paper proposes an algorithm for the differential protection of an Indirect Symmetrical Phase Shift Transformer (ISPST) by considering the different behaviors of the compensated differential current under internal fault and magnetizing inrush conditions. In this algorithm, a criterion function is defined which is based on the difference of amplitude of the wavelet transformation over a specific frequency band. The function has been used for the discrimination between three phase magnetizing inrush and internal fault condition and requires less than a quarter cycle after disturbance. This method is independent of any coefficient or threshold values of wavelet transformation. The merit of this algorithm is demonstrated by the simulation of different faults in series and excitation unit and magnetizing inrush with varying switching conditions on ISPST using PSCAD/EMTDC. Due to unavailability of in-field large interconnected transformers for such a large number of destructive tests, the results are further verified by Real Time Digital Simulator (RSCAD/RTDS). The proposed algorithm has been compared with the conventional harmonic restraint based method that justifies the application of wavelet transform for differential protection of ISPST. The proposed algorithm has also been verified for different rating of ISPSTs and satisfactory results were obtained.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.4
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• pp.179-188
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• 2003

Percentage differential characteristic scheme has been recognized as the principal basis for large transformer protection. Nowadays, relaying signals can contain second harmonic component to a large extent even in a normal state, and second harmonic ratio indicates a tendency of relative reduction because of the advancement of transformer's core material. And then, conventional second harmonic restraint differential relaying exposes some doubt in reliability. It is, therefore, necessary to develop a new algorithm for the effective and accurate discrimination. This paper deals with advanced fuzzy logic based relaying by using flux differential, and a new fault detection criterion logic scheme by using wavelet transform. To comparative analysis of proposed techniques, the paper constructs power system model including power transformer, utilizing the EMTP, and collects data through simulation of various internal faults and magnetizing inrush. The proposed fuzzy relaying and a new fault detection scheme were tested. The former, fuzzy relaying, was proven to be faster and more reliable than the latter.