• Journal of the Korean Society for Precision Engineering
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• v.22 no.2
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• pp.53-59
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• 2005

In this study, the isolation system for multi-mechanism HIF (high impulsive force) device has been investigated. For this purpose, parameter optimization process has been performed based on the simplified isolation system model under constraints of moving displacement and transmitted force. The design parameters for multi-mechanism HIF device have been derived with respect to HIF system I and HIF system II, respectively. In order to implement the dynamic absorbing system, the dual stage hydro-pneumatic damper and magnetorheological damper with semi-active control scheme are considered. Finally, the performance of the designed prototype isolation system has been evaluated by experimental works under actual operating conditions.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.107-112
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• 2005

In this study, the dynamic analysis is performed fur predicting the transmitted force to flexible human body induced by prototype HIF(High Impulsive force) device operation, which is partially assembled by major parts. A beam-mass model and a shear-structure model are used for the flexible mount structure and their dynamic behavior are investigated by experimental results under rigid/flexible mount conditions using a general purpose device. From the test result of prototype device in rigid mount condition, the transmitted force to human body which can not be measured directly, is estimated based on the proved mount structure model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.155-163
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• 2013

As the increasing HIF(High Impedance Fault) with the arc cannot be easily detected for the low fault current magnitude compared to actual load in distribution line. However, the arcing current shows that the magnitude varies with time and the signal is asymmetric. In addition, discontinuous changes occur at starting point of arc. Considering these characteristics, wavelet transformation of actual current data shows difference between before and after the fault. Althogh raw data(detail coefficient) of wavelet transform may not be directly applied to HIF detection logic in a device, there are several developing methods of HIF monitoring data using the original wavelet coefficients. In this paper, a simple and effective developing methods of HIF monitoring data were analized by using the signal data through an actual HIF experiment to apply them to economic devices. The methods using the sumation of the wavelet coefficient squares in one cycle of the fundamental frequency as the energies of the wavelet coefficeits and the sumation of the absolute values were compared. Besides, the improved method which less occupies H/W resouces and can be applied to field detection devices was proposed. and also Verification of this HIF detection method through field test on distribution system in KEPCO power testing center was performed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.817-826
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• 2023

In this paper, a fault determination methodology based on an artificial neural network was proposed to protect the system from faults on the lines in the smart grid distribution system. In the proposed methodology, first, it was designed to determine whether there is a low impedance line fault (LIF) based on the magnitude of the current RMS value, and if it is determined to be a normal current, it was designed to determine whether a high impedance ground fault (HIF) is present using Normal/HIF classifier based on artificial neural network. Among repetitive DSP module-based algorithm verification tests, the normal/HIF classifier recognized the current waveform as normal and did not show reclosing operation for the cases of normal state current waveform simulation test where the RMS value was smaller than the minimum operating current value. On the other hand, for the cases of LIF where RMS value is greater than the minimum operating current value, the validity of the proposed methodology could be confirmed by immediately recognizing it as a fault state and showing reclosing operation according to the prescribed procedure.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.191-197
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• 2003

Accurate detection and classification of faults on transmission lines is vitally important. In this respect, many different types of faults occur, such as inter alia low impedance faults (LIF) and high impedance faults (HIF). The latter in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if undetected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. Because of the randomness and asymmetric characteristics of HIFs, their modeling is difficult and numerous papers relating to various HIF models have been published. In this paper, the model of HIFs in transmission lines is accomplished using the characteristics of a ZnO arrester, which is then implemented within the overall transmission system model based on the electromagnetic transients program (EMTP). This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs 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 algorithm is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results demonstrate that the ANFIS can detect and classify faults including LIFs and HIFs accurately within half a cycle.

• 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.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.856-858
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• 1999

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. 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 neural network for pattern recognition and detection of high impedance faults. Wavelet transform analysis gives the time-scale information. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.38-43
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• 2003

In this study, the optimal dynamic absorbing system for the gas operated HIF (high implusive force) device has been investigated. For this purpose, firstly, the dynamic behavior of human body induced by impulsive disturbances has been analyzed through a series of experimental works using the devised test setup. The characteristics of linear impulse has been compared under some conditions of support system. In order to design the optimal dynamic absorbing system, the parameter optimization process has been performed based on the simplified isolation system model under constraints of moving displacement and transmitted force. Finally, the performance of the designed dynamic absorbing system has been evaluated by simulation in the actual operating condition.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.252-254
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• 2001

Accurate detection and classification of faults on transmission lines is vitally important. High impedance faults(HIF) in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if not detected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System(ANFIS). The performance of the proposed algorithm is tested on a typical 154[kV] Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classify faults including (LIFs and HIFs) accurately within half a cycle.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2525-2527
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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 known 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.