• Journal of Electrical Engineering and information Science
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• 제1권2호
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• pp.52-57
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• 1996

Detection of arcing high impedance faults has been a perplexing in the power distribution protection. Transient analysis of distribution disturbances for fault discrimination from other normal events is important for a secure protection of the power system. A simple parameter of wave form distortion quantification is used to analyze the behaviors of arcing faults and normal distribution disturbances. Theoretical perspectives of the transients were studied and actual disturbances were examined. From this investigation, a discrimination guideline based on the revised crest factor is developed. The discrimination method has a high potential to enhance the reliability and security for the distribution system protection.

• 대한전기학회논문지:전력기술부문A
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• 제49권8호
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• pp.405-411
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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 propolsed 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.619-621
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• 2004

This paper presents the rapid and accurate algorithm for fault discrimination in transmission lines. When faults occur in transmission lines, fault discrimination is very important. If high impedance faults occur in transmission lines, it cannot be detected by overcurrent relays. The method using current and voltage cannot discriminate high impedance fault. Because of this reason this paper uses voltage and zero sequence current, and the proposed algorithm uses fuzzy logic method. This algorithm uses voltage and zero sequence current per period in case of faults. Single line ground fault and three-phase fault can be detective using voltage. Two-line ground fault and line to line fault and high impedance can be detected using zero sequence current. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• 전기학회논문지
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• 제58권7호
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• pp.1294-1303
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• 2009

This paper presents a new numerical algorithm for fault discrimination and fault location estimation when occur to arcing ground and arcing line to line on transmission lines. The object of this paper is developed from new numerical algorithm to calculate the fault distance and simultaneously to make a distinction between transient and permanent faults. so the first of object for propose algorithm would be distinguish the permanent from the transient faults. This arcing fault discrimination algorithm is used if calculated value of arc voltage amplitude is greater than product of arc voltage gradient and the length of the arc path, which is equal or greater than the flashover length of a suspension insulator string[1-3]. Also, each algorithm is separated from short distance and long distance. This is difference to with/without capacitance between short to long distance. To test the validity of the proposed algorithms, the results of algorithm testing through various computer simulations are given. The test was simulated in EMTP/ATP simulator under a number of scenarios and calculate of algorithm was used to MATLAB.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.924-931
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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. High frequency signals caused by sudden changes in system voltage that occurs in the immediate post-fault period are generally outside the bandwidth of receptibility of most protection scheme. In this respect, a specially designed stack tuner is connected to the coupling capacitor of CVT, in order to capture the high frequency signals. 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. In this paper, modal transform is not applied to fault generated signals, because signals which are converted by modal transform are not have an information of each phase any longer. Instead, using peak voltage value of data windows is able to discriminate fault type. The paper concludes by presenting fault detection and discrimination of various faults on transmission line which are based on extensive simulation studies carried out on a typical 154kV Korean transmission line, using the EMTP software.

• 대한전기학회논문지:전력기술부문A
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• 제50권5호
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• pp.211-217
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• 2001

This paper proposes a new fault detection criterion logic that extracts the features of magnetizing inrush and internal faults by making use of Daubechies Wavelet Transform which analyzes distinct features. To prove the effectiveness of proposed method, the paper constructs power system model including power transformer by using EMTP, and collects data through simulation using various fault inception angle and magnetizing inrush. The conclusions implemented by the C program and the Wavemenu of MATLAB Toolbos are more effective and simpler to distinguish inter-turn faults from magnetizing inrush states.

• 전기학회논문지
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• 제57권11호
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• pp.2102-2107
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• 2008

This paper demonstrates a enhanced FCM to identify the causes of ground faults in power distribution systems. The discrimination scheme which can automatically recognize the fault causes is proposed using Fuzzy RBF networks. By using the actual fault data, it is shown that the proposed method provides satisfactory results for identifying the fault causes.

• 대한전기학회논문지:전력기술부문A
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• 제52권2호
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• pp.134-141
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• 2003

The power transformer is one of the very important electric facilities in power systems. Recently, current differential relay is widely used to protect such power transformer But if inrush occurs in transformer, relay can be tripped by judging like internal fault. Therefore the correct discrimination between internal winding fault, inrush and overexcitation should be performed. This paper presents a new protective relaying algorithm which discriminates inrush, internal faults and overexcitation of transformer modelled using BCTRAN and HYSDAT of EMTP. Discrimination between internal winding fault and inrush is revealed in simulation within 1/2 cycle after fault. Accordingly, it is evaluated that the proposed algorithm has better discrimination characteristics in various cases thin the current relaying for protection of transformer.

• Journal of Mechanical Science and Technology
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• 제18권9호
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• pp.1537-1548
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• 2004

This paper presents a novel diagnostic technique for monitoring the system conditions and detecting failure modes and precursors based on wavelet-packet analysis of external noise/vibration measurements. The capability is based on extracting relevant features of noise/vibration data that best discriminate systems with different noise/vibration signatures by analyzing external measurements of noise/vibration in the time-frequency domain. By virtue of their localized nature both in time and frequency, the identified features help to reveal faults at the level of components in a mechanical system in addition to the existence of certain faults. A prima-facie case is made via application of the proposed approach to fault detection in scroll and rotary compressors, although the methods and algorithms are very general in nature. The proposed technique has successfully identified the existence of specific faults in the scroll and rotary compressors. In addition, its capability of tracking the severity of specific faults in the rotary compressors indicates that the technique has a potential to be used as a prognostic tool.