• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05c
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• pp.199-202
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• 2002

During normal operation, partial discharge(PD) tests were performed using turbine generator analyzer(TGA) in high voltage motor. Epoxy-mica couplers are installed at motor terminal and analyzed PD signal using TGA. #A motor stator insulation is good because small partial discharges are detected. PD pattern show that PD occurs in insulation. PD of #B motor is larger than that of #A motor and PD pattern show that positive PD larger than negative PD. It means that PD occurs between insulation and slot. And A phase PD magnitude of #B motor is large and high compare with any other phase. Therefore wedge, core and slot of #B motor need to check and repair.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.5
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• pp.177-181
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• 2003

Partial discharge pulse shapes from variable PD (partial discharge) sources sustain many characteristics such as types of PD. Ultra high frequency antennas have wide bandwidth from 30KHz to 2㎓. Therefore, signals taken from a UHF antenna have important attributes (rising time, falling time, shape factor, etc.) for electromagnetic sources, such as PD sources. We investigated PD pulse shapes from several PD sources using a UHF antenna and the results were used for classification of PD sources. Features for discrimination are extracted from frequency distribution and LPC (Linear Prediction Coefficient) of time signal. RBFN are used for investigating the possibility of classification of multi-PD sources.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2021_2022
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• 2009

Partial discharges(PD) is a important factor to evaluate the insulation state in high voltage electric machinery. However, measuring PD under the circumstances of power plant is occasionally impossible due to the relatively high magnitude of noise which is emanated from the operating machinery. In some case, the instrument measuring PD can not even perform a calibration that initializes tools and enhance the accuracy. This paper presents that we devised a noise reduction method and demonstrated the usefulness in acquiring reliable PD signals. We attached a series of filter and transformer at the input of power source of the instruments which refrains high noise signals from incoming to the instruments. We experimented the efficiency of noise reduction applying the device into the Dangjin Power Plant and Factory. As a result of testing with the filter and transformer, we can easily calibrate the PD signal compared to the case without the device. Additionally, we can detect the small PD signal which was unperceived with a normal device.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.1
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• pp.51-56
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• 2013

PID control systems are significantly utilized in industrial fields because of its multiple advantages. Many researches about more effective PID controllers to enhance control system performances have been addressed so far. This paper proposes a novel PI-PD control system with a pre-compensator which is configured with a pre-compensator and PD controller in PIcontrol system. The normal method is applied to the proposed control system for obtaining a simple first-order controller from cancelation of poles and zeros. We design a pre-compensator and PD controller by using parameters of PI controller and the transfer function of a plant. Computer simulation is carried out to demonstrate effectiveness of the proposed control system.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.1
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• pp.25-34
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• 2003

Gas insulated switchgear(GIS) is an important equipment in a substation. It is highly desirable to measure a partial discharge(PD) in GIS which is a symptom before insulation breakdown occurs. The issue is that the PD signal is weak and sensitive to external noise. In this paper, the algorithm for detection of PD in GIS using wavelet transform is proposed. The wavelet transform provides a direct quantitative measure of spectral content, "dynamic spectrum", in the time-frequency domain. The recommended mother wavelet is 'Daubechies' wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, can be used most properly in disturbance phenomena which occurs rapidly for a short time. Through the procedure of wavelet transform, noise extraction and reconstruction, the signal is Analyzed to determine the magnitude of PD in GIS. In experimental results, we can know that partial discharge is exactly detected in combination of Dl and D2 using wavelet transform.transform.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.2052-2053
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• 2007

Recently, the importance of supplying the reliable electric power is increasing. Breaking insulation of stator winding is major cause of fault in rotator machine. On-line PD detecting is useful technique to diagnose rotator machine. However, interpretation of its results in time domain is very complex because of the mixed results with PD(Partial Discharge) and noise signal. Therefore, the results were analyzed in frequency domain by FFT (Fast Fourier Transform) to detect precise PD signals. The purpose of this paper is to describe the optimal frequency range to discriminate the PD and noise signal.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1963-1966
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• 2004

An ultra wide band ultra-high frequency (UHF) signal processing module was designed for on-line UHF partial discharge (PD) monitoring systems for gas-insulated switchgears (GIS). Major advantage of the unit is an improved PD detection sensitivity through minimizing the effect of surrounding interference signals. The detection sensitivity of the unit was <-60 dBm that is sufficient to detect UHF PD signals as low as 1 pC. Precise detection of PD occurred in the GIS, due to internal defects, is possible by using the signal processing unit.

• Proceedings of the KIEE Conference
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• 2004.05b
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• pp.128-131
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• 2004

An ultra wide band ultra-high frequency (UHF) signal processing module was designed for on-line UHF partial discharge (PD) monitoring systems for gas-insulated switchgears (GIS). Major advantage of the unit is an improved PD detection sensitivity through minimizing the effect of surrounding interference signals. The detection sensitivity of the unit was <-60 dBm that is sufficient to detect UHF PD signals as low as 1 pC. Precise detection of PD occurred in the GIS, due to internal defects, is possible by using the signal processing unit.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.10
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• pp.895-900
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• 2007

Partial discharge(PD) test can be performed either when the rotating machine is not operating(off-line) or during normal machine operation(on-line). This paper presents an on-line and off-line PD test on a large hydro-generator and induction motor using the same PD acquisition system(PDAS) and ceramic coupler(CC) sensor. PD signal characteristics of CC sensor proved similar with that of epoxy mica coupler(EMC) sensor as a results of PD test for simulated defect winding and frequency response test. A comparison of on-line and off-line PD test for PD characteristic parameters-phase resolved PD(PRPD), maximum PD value(Qmax) and PD occurrence energy(POE)-indicated that on-line PD test could reliably and effectively diagnose insulation conditions which were verified by off-line PD test.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.7
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• pp.332-338
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• 2005

PD(Partial Discharge) signal emitted from PD sources has their intrinsic features in the region of time and frequency STFT(Short Time Fourier Transform) shows time-frequency distribution at the same time. 2-Dimensional matrices(33$\times$77) from STFT for PD pulse signals are a good feature vectors and can be decreased in dimension by wavelet 2D data compression technique. Decreased feature vectors(13$\times$24) were used as inputs of Back-propagation ANN(Artificial Neural Network) for discrimination of Multi-PD sources(air discharge sources(3), surface discharge(1)). They are a good feature vectors for discriminating Multi-PD sources in the air.