• 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[%].

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.1
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• pp.10-14
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• 2003

The occurrence of partial discharge (PD) in solid dielectrics is very harmful because it leads to the deterioration of insulation by electrical, chemical, and thermal reactions as a combined action of the discharged ions bombarding the surface and by the action of chemical compounds that are formed by the discharge. Consequently, if any defects are present in the solid insulation system, performance decreases until the system breaks down. Therefore, removing or suppressing the defect is very important. Voids are a typical defect in the solid insulation system and are very harmful because they deteriorate insulation. As a basic step, studying the properties of PD in voids is important because an accurate knowledge of these properties is required to estimate the deterioration of voids. In this paper, the correlation between the size of voids and internal PD is discussed as a function of the time of the applied voltage and its magnitude. Magnitude, repetition rate, average discharge power, and average discharge current of PD in specimens with large voids were found to be larger than the others in this experiment. The smaller specimens had voids when the magnitude and number of PDs were reduced.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.468-470
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• 1997

This paper presents an estimation method of the number of partial discharge(PD) sources and their locations in power transformer. To identify multiple PD sources and their locations, the directions-of-arrival estimation algorithm is employed. The results of simulations shows that the proposed method could be accurately detect the number of PD sources and their locations in power transformer.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1924-1926
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• 2000

This paper deals with the multiresolution analysis of wavelet transform for partial discharge(PD).PD is an electrical discharge that only partically bridges the insulation performance of electrical equipment in high voltage. PD signal is very sensitive and difficult to suppress strong noises such as narrow-band radio frequency noise and random noise. In recently, wavelet transform has become a powerful tool to analysis and process signals in various science and technology fields. In this paper, daubechies family is adopted for the research of the characteristics of PD signals. The results show that the kurtosis is increased with discharge process and skewness is decreased with discharge process, but when PD occured positive range then skewness is increased. Segment 7, 8, 9, 10, 11 values is increased with discharge process, so phase distribution is characterized by 210$\sim$330 ranges.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05a
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• pp.50-54
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• 2000

Recently, the HFPD measurement testing is widely used in partial discharge measurement of HV machines because HFPD measurement testing receives less influence of external noise and has a merit of good sensitivity. Also HFPD testing is able to offer the judgement standard of degradation level of HV machine and can detect discharge signals in live-line. Therefore it is very useful method compare to previous conventional PD testing method and effective diagnosis method in power transformer that requires live-line diagnosis. But partial discharges have very complex characteristics of discharge pattern so it is required continuous research to development of precise analysis method. In recent, the study of partial discharge is carrying out discover of initial defect of power equipment through condition diagnosis and system development of degradation diagnosis using HFPD(High Frequency Partial Discharge) detection. In this study, simulated transformer is manufactured and HFPD occurred from transformer is measured with broad band antenna in real time, the degradation grade of transformer is analyzed through produced patterns in simulated transformer according to applied voltages.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1461-1466
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• 2014

GIS(Gas Insulated Switchgear) is important power apparatus which have strong dielectric strength, supply electric power and is a part of the power system. Most substation type is configured as GIS. Recently, because of continuous increasement of GIS demand resulted from high quality & big capacity of electric power, the necessity of the preventive & diagnosis system is being expanded gradually. GIS partial discharge occurred on the UHF band is detected effectively by the method to IEC 60270 that recommend to be able to detect the apparent minimum discharge, 5 pC. Additionally, the UHF sensor should be installed to detect PD signal if Partial discharge signal, 5 pC occur in every part of GIS. Currently PD diagnosis system applying UHF sensor for GIS with various voltage level like 154 kV, 345 kV, 765 kV have been operated. And it is necessary to measure and analyze insulation breakdown phenomenon of inside GIS exactly. In this paper, we proposed Fat-dipole patch UHF sensor that is developed and more sensitive, excellent wide-range characteristic than the exising UHF sensor. And we performed KERI (Korea Electrotechnology Research Institute) reference test, which showed the excellent result for the all tests.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1381_1382
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• 2009

Nondestructive tests were performed on two 4.16kV motors. Epoxy-mica coupler(80pF) was connected to 4.16 kV motor stator windings. The voltage applied to the stator windings was 2.4 kV, 3.0kV, 3.5kV and 4.16kV, respectively. Digital partial discharge detector(PDD) and turbine generator analyzer(TGA) were used to measure partial discharge(PD) activity. TGA summarizes each plot with two quantities such as the normalized quantity number(NQN) and the peak PD magnitude(Qm). The PD levels in pC were measured with PDD. PD patterns of stator windings were indicated the internal discharge. PD patterns are consistent with the result of measurement using PDD and TGA.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.4
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• pp.166-171
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• 2006

In this paper, we have studied for analysis of the partial discharge(PD) signal in underground transmission line. The PD signal has estimated as detected signal accumulation of a PRPDA method by using Labview, and analyzed with fuzzy algorithm. In our algorithm, we developed system configuration that detected accumulating PD signal using by Labview and programmed fuzzy algorithm can be analyzed the PD signal using with Matlab. With practical PD logic implementation of theoretical detected system and hardware implementation, the device for Hipotronics Company's 50kV setup has generated and then has applied with $15k{\sim}17kV$ with 1:1 time probe. It's also used the LDPE 0.27mmt (scratch error 0.05mmt) to sample for making PD. In conclusion, Our new class of PD detected algorithm has also compared with previous PRPDA or Fuzzy algorithm. which has diagnose more conveniently by adding numerical values.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.214-221
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• 2003

In view of the fact that gas insulated switchgear (GIS) is an important piece of equipment in a substation, it is highly desirable to continuously monitor the state of equipment by measuring the partial discharge (PD) activity in a GIS, as PD is a symptom of an insulation weakness/breakdown. However, since the PD signal is relatively weak and the external noise makes detection of the PD signal difficult, it therefore requires careful attention in its detection. In this paper, the algorithm for detection of PD in the GIS using the wavelet transform (WT) is proposed. The WT provides a direct quantitative measure of the spectral content and dynamic spectrum in the time-frequency domain. The most appropriate mother wavelet for this application is the Daubechies 4 (db4) wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, is very well suited to detecting high frequency signals of very short duration, such as those associated with the PD phenomenon. The proposed algorithm is based on utilizing the absolute sum value of coefficients, which are a combination of D1 (Detail 1) and D2 (Detail 2) in multiresolution signal decomposition (MSD) based on WT after noise elimination and normalization.