• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 E
• /
• pp.2089-2092
• /
• 1999

Partial discharge(PD) tests were performed both when the pumped storage generator(rated 13.8kV and 220MVA) was on-line and off-line. This generator has been equipped with 12 bus coupler sensors in directional mode. PD tests were conducted using partial discharge analyzer(PDA), partial discharge meter(PDM) and digital partial discharge detector. PDA showed that the patterns of the normalized quantity number(NQN) and the partial discharge magnitude are in accord with on-line and off-line. The insulation condition was estimated by diagnostic tests(off-line) such as PD magnitude and dissipation factor.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
• /
• pp.221-222
• /
• 2005

In this paper, application of NN (Neural Network) as a method of pattern discrimination of PD(partial discharge) which occurs at the stator coil of traction motor was studied. For PD data acquisition, three defective models are manufactured such as internal discharge model, slot discharge model and surface discharge model. PD data for recognition were acquired from PD detector and DAQ board which is able to analysis the PD signal and perform the pattern discrimination. Statistical distributions and parameters are calculated to discriminate PD sources. And also these statistical distribution parameters are applied to classify PD sources by BP and has good recognition rate on the discharge sources.

• Journal of Electrical Engineering and Technology
• /
• 제9권1호
• /
• pp.293-300
• /
• 2014

This paper proposes a novel pattern recognition approach based on the radial basis function (RBF) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). Pattern recognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, pattern recognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of cast resin current transformer (CRCT) models. These tests used artificial defects created in order to produce the common PD activities of CRCTs by using feature vectors of field-test PD patterns. The significant features are extracted by using nonlinear principal component analysis (NLPCA) method. The experimental data are found to be in close agreement with the recognized data. The test results show that the proposed approach is efficient and reliable.

• Journal of Electrical Engineering and Technology
• /
• 제9권2호
• /
• pp.670-676
• /
• 2014

The objective of this research is to utilize the ultrasonic method to analyze the property of partial discharge (PD) which is generated by the winding of the insulation stator in the generator. Therefore, a PD measurement system is built based on ultrasonic and virtual instruments. Three types of PD models (internal PD model, surface PD model and slot PD model) have been constructed. With the analysis of these experimental results, this research has identified the ultrasonic signals of the discharges which were produced by three types of PD models. This analysis shows the different features among these PD types. Both the time domain and frequency domain of the ultrasonic signals are obviously different. In addition, an experiment based on a large rotating machine has been done to analyze ultrasonic noises. The result indicates that the ultrasonic noises can be wiped off by the filters and algorithms. The application of this system is convenient for the detection of early signs of insulation failure, which is an effective method for diagnosis of insulation faults.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2004년도 춘계학술대회 논문집 방전 플라즈마 유기절연재료 초전도 자성체연구회
• /
• pp.100-103
• /
• 2004

In this paper, BP learning algorithm is studied to apply as a PD source classification in GIS specimens. For occurred partial discharge, three defected models are made; floating particle, surface discharge of spacer, needle to plane. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• KIEE International Transactions on Electrophysics and Applications
• /
• 제5C권6호
• /
• pp.223-227
• /
• 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.

• 한국전기전자재료학회논문지
• /
• 제11권12호
• /
• pp.1055-1059
• /
• 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.

• Journal of Electrical Engineering and Technology
• /
• 제13권2호
• /
• pp.902-910
• /
• 2018

In recent times, development of nanofluid insulation for power transformers is a hot research topic. Many researchers reported the enhancement in dielectric characteristics of nano modified mineral oils. Considering the drawbacks of petroleum based mineral oil, it is necessary to understand the dielectric characteristics of nanofluids developed with natural ester based oils. Palm oil has better insulation characteristics comparable to mineral oil. However very few research reports is available in the area of nanofluids based on palm oil. Partial discharge (PD) is one of the major sources of insulation performance degradation of transformer oil. It is essential to understand the partial discharge(PD) characteristics by collecting huge data base of PD performance of nano modified palm oil which will increase its confidence level for power transformer application. Knowing these facts, in the present work, certain laboratory experiments have been performed on PD characteristics of nano $SiO_2$ modified palm oil at different electrode configurations. Influence of concentration of nano filler material on the PD characteristics is also studied. Partial discharge inception voltage, Phase resolved partial discharge (PRPD) pattern, PD signal time-frequency domain characteristics, PD signal equivalent timelength-bandwidth mapping, Weibull distribution statistical parameters of PRPD pattern, skewness, repetition rate and phase angle variations are evaluated at different test conditions. From the results of the experiments conducted, we came to understand that PD performance of palm oil is considerably enhanced with the addition of $nano-SiO_2$ filler at 0.01%wt and 0.05%wt concentration. Significant reduction in PD inception voltage, repetition rate, Weibull shape parameter and PD magnitude are noticed with addition of $SiO_2$ nanofillers in palm oil. These results will be useful for recommending nano modified palm oil for power transformer applications.

• 대한전기학회논문지:전기물성ㆍ응용부문C
• /
• 제54권5호
• /
• pp.198-205
• /
• 2005

Many precedent investigations hate been made for the reliable assessment of the insulation state of large power apparatus for which partial discharge detection is one of tile plausible way. In this work, experimental investigations have been carried out to make the comparison on the PD(partial discharge) pattern analysis related to the five different types of artificial defects such as SFMP (Single Free Moving Particle), MFMP (Multi Free Moving Particle), Void, CFP (Conductor-Fixed Protrusion), EP (Enclosure Protrusion). For each PD pattern, PD detection has been done by tee different types of PD sensors such as HFCT(High Frequency Current Transformer), AE(Acoustic Emission) and UHF(Ultra High Frequency). And, in addition, frequency spectrum by the UHF sensor has been also made for each defect respectively. As a result, it is observed that the possibility of obtaining PD pattern based on PRPD(Phase Resolved Partial Discharge) in connection with the defects tinder investigation is dependant on the type of the sensor while the spectrum analysis is always successful to be achieved for every defect. Therefore, it could be suggested that the nature of PD source can be identified more distinctively when the conventional PRPDA is combined with spectrum analysis.

• Journal of Electrical Engineering and Technology
• /
• 제10권3호
• /
• pp.1093-1101
• /
• 2015

Partial Discharge (PD) is a physical phenomenon, which causes defects and damages to the insulation. This phenomenon is regarded as the most important source of fault and defect in power transformers. Therefore, methods of high speed and precision are considered of special importance for the maintenance of transformers in localization of the origin of partial discharge. In this paper, the transformer winding is first modeled in a transient state by using RLC ladder network and multiconductor transmission line (MTL) models. The parameters of the two models were calculated by Ansoft Maxwell software, and the simulations were performed by Matlab software. Then, the PD pulses were applied to the models with different widths of pulses. With regard to the fact that the signals received after the application of PD had a variable frequency nature over time, and based on the wavelet transform and signal energy, a new method was presented for the localization of PD. Ultimately; the mentioned method was implemented on a 20 kV winding distribution transformer. Then, the performances of the models used in this paper, including RLC and MTL models, were compared in different frequency bands for the correct distinction of partial discharge location.