• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.436-444
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• 2016

Oil-paper insulation of valve-side windings in converter transformers withstand electrical stresses combining with AC, DC and strong harmonic components. This paper presents the physical mechanisms and experimental researches on partial discharge (PD) of oil-paper insulation at pulsating DC voltage. Theoretical analysis showed that the phase-resolved distributions of PDs generated from different insulated models varied as the increase of the applied voltages following a certain rule. Four artificial insulation defect models were designed to generate PD signals at pulsating DC voltages. Theoretical statements and experimental results show that the PD pulses first appear at the maximum value of the applied pulsating DC voltage, and the resolved PD phase distribution became wider as the applied voltage increased. The PD phase-resolved distributions generated from the different discharge models are also different in the phase-resolved distributions and development progress. It implies that the theoretical analysis is suitable for interpretation of PD at pulsating DC voltage.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1665-1667
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• 2002

In this paper, a comparative study of time-frequency distributions by partial discharge(PD) kinds was made. The PD kinds were to be classified into the corona, the surface discharge and the void discharge in this paper. As a result, the distributions of the PD kinds were different, and using neural network, the PD pattern recognizing rate was about 85[%].

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1930-1932
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• 2000

PD in defects of solid insulation system is very harmful since it leads to deteriorate insulation system by. the discharge electrons and ions bombarding the insulation surface and the action of chemical products that are formed by discharges. PD is used to detect and recognize defects and degradation of insulation system However, there are still marked difficulties to recognize defects by PD methode. In this paper, we investigated properties of PD of defects in solid insulation by using statical methods and classified PD patterns of surface discharge, electrical tree and void discharge with source of discharge, we used specific distributions such as $H_n(q)$, $H_{an}(\phi)$, $H_n(\phi)$, $H_a(\phi)$ to recognize defects of solid insulation system.

• Korean Journal of Hydrosciences
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• v.3
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• pp.97-104
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• 1992

To design the minor structures in the small watersheds, it is required to calculate the peak discharge. For these calculations the simple peak flow prediction equations, the unit hydrograph method. the syntheic unit hydrograph methods or the runoff simulation models are adopted. To use these methods it is generally requried to know the amount and the distributions of the design rainfall; which are the uniform distribution, the trangular distribution, the trapezoidal distribution, or the Huff type distribution. In this study, the peak discharges are calculated by the different rainfall distributions and the results are compared.

• Journal of Magnetics
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• v.21 no.2
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• pp.222-228
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• 2016

Correlation between coil configurations and the discharge characteristics such as plasma density and the electron temperature in a newly designed magnetized inductively coupled plasma (M-ICP) etcher were investigated. Radial and axial magnetic flux density distributions as well as the magnetic flux density on the center of the substrate holder were controllable by placing multiple circular coils around the etcher. The plasma density increased up to 60.7% by arranging coils (or optimizing magnetic flux density distributions inside the etcher) properly although the magnetic flux density on the center of the substrate holder was fixed at 7 Gauss.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.3
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• pp.138-142
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• 2005

In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1927-1929
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• 2000

PD indicates the inception and progress of degradation of solid insulation system, so it has been used to determine degradation of insulation. PD provides means for detection and recognition of defects. However, there is still marked difficult to recognize defects by PD methods. In this paper, we investigated properties of PD in solid insulation by using statistical method with surface discharge, electrical tree and void discharge with source of discharge, we used statistical parameters of PD distributions specified such as $H_n(q)$, $H_{an}(\phi)$, $H_n(\phi)$, $H_a(\phi)$. The parameters induced from its specified distributions are average discharge, average repetition rate, Skewness, Kurtosis, asymmetry and correlation. From the parameters, we classified PD patterns and built up DB(data-base).

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.6
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• pp.223-227
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• 2005

Insulation failure of traction motor stator coil depends on the continuous stress imposed on it and knowing its insulation condition is an issue of significance for proper safety operation. In this paper, application of the NN (Neural Network) as a scheme of the off-line PD (partial discharge) diagnosis method that occurs at the stator coil of a traction motor was studied. For PD data acquisition, three defective models were made; internal void discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from a PD detector. Statistical distributions and parameters were calculated to perform recognition between model discharge sources. These statistical distribution parameters are applied to classify PD sources by the NN with a good recognition rate on the discharge sources.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.12
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• pp.1055-1059
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• 1998

The correlation between the propagation of electrical tree and distributions of partial discharge(PD) pulses accompanying with electrical tree of bush type in low density polyethylene were discussed. We measured the growth of electrical tree by using optical microscope and PD data simultaneously. The PD data detected and analyzed were PD magnitude, repetition rate, average discharge power, average phase angle, and $\psi$-q-n distribution pattern. The average discharge power and repetition rate of PD had good linear relation with area of tree. Repetition rate and peak discharge magnitude and width of discharge phase angle increased with the tree.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.296-299
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• 2005

Time series of spring discharge data in Jeju island can provide abundant information on the spatial groundwater system. In this study, the classification based on time series of spring discharge was performed with clustering analysis: discharge rate and EC. Peak discharges are mainly observed in august or september. However, double peaks and late peaks of discharge are also observed at a plenty of springs. Based on results of clustering analysis, it can be deduced that GH model is not appropriate for the conceptual model of Groundwater system in Jeju island. EC distributions in dry season are also support the conclusion.