• 전기학회논문지
• /
• 제65권10호
• /
• pp.1780-1785
• /
• 2016

This paper presents few case studies of state diagnosis of XLPE cables using very low frequency techniques. The power cables of 22.9kV which have installation fault were assessed using VLF technique in addition to other techniques like insulation resistance and DC voltage withstand test. From the experimental results, The dielectric loss($tan{\delta}$) values of degradation of the cable(joint, knife, needle) at $U_0$ were 5.839, 5.526 and 6.251, respectively and all values were "further study advised". VLF PD measurement was also found defective portion. These method was effective in defect to fault in the degradation of the cable. However, the breakdown did not occur in the degradation of the cable because of properties of XLPE insulation. Few case studies of using VLF $tan{\delta}$ diagnosis for fault are measured and analyzed. The $tan{\delta}$ values at $U_0$ were "further study advised" or "action required".

• Structural Engineering and Mechanics
• /
• 제34권6호
• /
• pp.755-778
• /
• 2010

Near-fault ground motion with directivity or fling effects is significantly influenced by the rupture mechanism and substantially different from ordinary records. This class of ground motion has large amplitude and long period, exhibits unusual response spectra shapes, possesses high PGV/PGA and PGD/PGA ratios and is best characterized in the velocity and the displacement time-histories. Such ground motion is also characterized by its energy being contained in a single or very few pulses, thus capable of causing severe damage to the structures. This paper investigates the characteristics of near-fault pulse-like ground motions and their implications on the structural responses using new proposed measures, such as, the effective frequency range, the energy rate (in time and frequency domains) and the damage indices. The paper develops also simple mathematical expressions for modeling this class of ground motion and the associated structural responses, thus eliminating numerical integration of the equations of motion. An optimization technique is also developed by using energy concepts and damage indices for modeling this class of ground motion for inelastic structures at sites having limited earthquake data.

• 한국지능시스템학회논문지
• /
• 제18권4호
• /
• pp.518-523
• /
• 2008

본 논문에서는 저압 배선 진단 시스템 개발에서 핵심 파트 중 하나인 지능형 차단 시스템 구축을 목표로 한다. 제안된 진단 시스템은 TFDR (Time-Frequency Domain Reflectometry) 알고리즘을 바탕으로 하여 실제 전압이 흐르는 배선에 대해 이상 거리 측정을 하게 된다. 그리고 배선으로부터 얻은 정보를 바탕으로 배선 이상의 종류를 분석하는 것이 지능형 차단 시스템의 목표이다. 효율적인 분석을 위해, 본 논문에서는 퍼지-베이시안 (Fuzzy-Bayesian) 알고리즘을 바탕으로 하여 시스템을 구성하였다. 실제 저압 배선에서 실험된 데이터를 바탕으로 한 실험을 통해 제안된 기술의 우수성을 입증하고자 한다.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권12호
• /
• pp.1492-1497
• /
• 1999

High impedance fault(HIF) is defined as fault the general overcurrent relay can not detect or interrupt. Especially when HIF occur in residential areas, energized high voltage conductor results in fire hazard, equipment damage or personal threat. This paper proposes the model of the high impedance fault in transmission line using the ZnO arrester and resistance to be implemented within EMTP. The performance of the proposed model is tested on a typical 154[kV] korean transmission line system under various fault conditions. Wavelet transform is efficient and useful for the detection of high impedance fault in power system, because it uses variable windows according to frequency. In this paper, HIF detection method using wavelet transform can distinguish HIF form similar fault like arcfurance load, capacitor bank switching and line switching.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권1호
• /
• pp.16-21
• /
• 1999

The analysis of distribution line faults is essential to the proper protections of the power system. A high impedance fault test, which was carried in Korean electric power systems, it was found that a arcing phenomenon occurred during the high level portion of conductor voltage in each cycle. In this paper, we propose a new method for detection of high impedance faults, which uses the arcing fault current difference during high voltage and low voltage portion of conductor voltage waveform. To extract this difference, we diveded one cycle fault current into equal spanned four data windows according to the magnitude of voltage waveform and applied fast fourier transform(FFT) to each data window. The frequency spectrum of current wavefrom in each portion are used as the inputs of neural network and is trained to detect high impedance faults. The proposed method shows improved accuracy when applied to staged fault data and fault-like load.

• 조명전기설비학회논문지
• /
• 제21권9호
• /
• pp.109-113
• /
• 2007

In this paper, an arc current controller was designed for the interruption of arc fault currents occurred in a low voltage network. Arc in an electrical network represents the characteristics of low current, high impedance, and high frequency. Conventional controllers do not have arc current interrupt functions. Thus, an arc current controller was designed for the interruption of arc fault currents.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 제38회 하계학술대회
• /
• pp.1700-1701
• /
• 2007

DC Arc Fault Current is an electric discharge which is occurred in two opposite electrode. In this paper, DC arc detection device is designed for the display of DC arc fault current which is occurred in the local electric network with DC Power. This DC arc is one of the main causes of electric fire. Arc fault in electrical network has the characteristics of low current, high impedance and low frequency. DC Arc current detection device is designed for the display of arc fault current which has the modified arc characteristics.

• 전기학회논문지
• /
• 제56권7호
• /
• pp.1183-1190
• /
• 2007

This paper proposes the improved fault decision algorithm using DWT(Discrete Wavelet Transform) and ANNs for the FRTU(Feeder Remote Terminal Unit) on the feeder in the power distribution system. Generally, the FRTU has the fault decision scheme detecting the phase fault, the ground fault. Especially FRTU has the function for 2000ms. This function doesn't operate FI(Fault Indicator) for the Inrush current generated in switching time. But it has a defect making it impossible for the FI to be operated from the real fault current in inrush restraint time. In such a case, we can not find the fault zone from FI information. Accordingly, the improved fault recognition algorithm is needed to solve this problem. The DWT analysis gives the frequency and time-scale information. The neural network system as a fault recognition was trained to distinguish the inrush current from the fault status by a gradient descent method. In this paper, fault recognition algorithm is improved by using voltage monitoring system, DWT and neural network. All of the data were measured in actual 22.9kV power distribution system.

• Earthquakes and Structures
• /
• 제5권2호
• /
• pp.129-142
• /
• 2013

Linear and nonlinear time history analyses have been becoming more common in seismic analysis and design of structures with advances in computer technology and earthquake engineering. One of the most important issues for such analyses is the selection of appropriate acceleration time histories and matching these histories to a code design acceleration spectrum. In literature, there are three sources of acceleration time histories: artificial records, synthetic records obtained from seismological models and accelerograms recorded in real earthquakes. Because of the increase of the number of strong ground motion database, using and scaling real earthquake records for seismic analysis has been becoming one of the most popular research issues in earthquake engineering. In general, two methods are used for scaling actual earthquake records: scaling in time domain and frequency domain. The objective of this study is twofold: the first is to discuss and summarize basic methodologies and criteria for selecting and scaling ground motion time histories. The second is to analyze scaling results of time domain method according to ASCE 7-05 and Eurocode 8 (1998-1:2004) criteria. Differences between time domain method and frequency domain method are mentioned briefly. The time domain scaling procedure is utilized to scale the available real records obtained from near fault motions and far fault motions to match the proposed elastic design acceleration spectrum given in the Eurocode 8. Why the time domain method is preferred in this study is stated. The best fitted ground motion time histories are selected and these histories are analyzed according to Eurocode 8 (1998-1:2004) and ASCE 7-05 criteria. Also, characteristics of both near fault ground motions and far fault ground motions are presented by the help of figures. Hence, we can compare the effects of near fault ground motions on structures with far fault ground motions' effects.

• 한국소음진동공학회논문집
• /
• 제22권12호
• /
• pp.1227-1236
• /
• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.