• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.1
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• pp.5-9
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• 2003

The waveforms of partial discharges (PDs) imply physical and structural properties of PD sources, so analyzing them give us information on the kind of PD sources and the location. Waveforms of PD as a time series function have variable amplitudes but sustain a certain uniform shape, which shows well the characteristics of the waveforms and frequency region. They can also be used as parameters having time and frequency information of PD signals and applied to classification of multiple PDs sources via Artificial Neural Network with back propagation (BP) learning.

• Proceedings of the KIEE Conference
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• 2004.11a
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• pp.107-109
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• 2004

It is well known that on-site corona and various noises make severe problems on the PD(partial discharge) measurement. In this paper, for the improvement of the on-site PD measuring performance, the applicability of TF(Time-Frequency) map was investigated. For the purpose, PDs that can be generated from the defect in the power cables as well as corona discharges and ground noises were measured. And through the TF analysis for the measured data, we have tried to distinguish the real PDs, corona discharges and noises. As a result, it is confirmed that the data of PDs can be clustered themselves separable from other data such as corona and noises on the TF map.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.251-256
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• 2012

This study deals with the location of partial discharges(PDs) for power cables and GIS using 2 PD sensors and long coaxial signal cables. Throughout the experiments by use of simulated PD pulses and corona discharges in the power cable system, it is found out that the impedance matching between the coaxial signal cable and the measuring equipment should be done for good S/N ratio and the on-site measurement using more than 100m-long coaxial signal cable is possible. In addition, new PD location algorithm with the polarities of PD pulses and the arrival time difference between two pulses was proposed and was proved through the partial discharge experiments for the cable joint defect and artificial void defect.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.9
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• pp.727-731
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• 2012

This paper dealt with the measurement and analysis of electromagnetic waves radiated from a partial discharge (PD) source in insulation oil to apply condition monitoring of oil-immersed transformers. Two types of narrow-band monopole antennas with the resonant frequency of a 500 MHz and a 1 GHz were designed and fabricated. Also, a needle-plane electrode system was manufactured to simulate PDs and the curvature radius of the needle is 10 ${\mu}m$ and the diameter of the plane is 60 mm. Electromagnetic wave was measured by the PD measurement system with the monopole antennas. Detection sensitivity of the fabricated antenna was compared for the same PD magnitude; 620 $mV_{peak}$ for the 500 MHz antenna and 960 $mV_{peak}$ for the 1 GHz antenna to the PD magnitude of 74 pC. Consequently, the 1 GHz monopole antenna is more effective to detect PDs in oil-immersed transformers.

• Journal of electromagnetic engineering and science
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• v.18 no.2
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• pp.94-100
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• 2018

Partial discharges (PDs) are electrical sparks that occur inside insulation between two conducting electrodes and can lead to the disastrous failure of insulation systems. To determine the location of a PD, a distributed array of UHF PD sensors is used to detect the electromagnetic (EM) signals emitted from the PD source, and the localization of the PD source can be estimated using the time difference of arrival (TDOA) between EM signals captured by the UHF PD sensor array. There are four popular methods to estimate the TDOA-the first peak method, the cross-correlation method, the energy criterion method, and the average time window threshold method. In this work, we numerically investigate the influence of noise on estimating the TDOA for the four different methods. Numerical results show that the energy criterion method is more robust against noise than other methods.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.9
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• pp.786-791
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• 2009

Transformer failures are mostly due to partial discharges (PDs) caused by the deteriorated insulation. It is, therefore, important to monitor PD occurrence in insulation system and prevent their deterioration. The presented paper deals with a PD detection method by a capacitive probe, which easily apply to cast - resin dry - type transformers. The PD detection system consists of a capacitive probe and a low noise amplifier having the frequency bandwidth of 500 $Hz{\sim}30$ MHz. In the experimental set-up, sensitivity of the system is 7.16 mV/pC.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.2
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• pp.95-101
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• 2003

In this paper, partial discharges(PDs), lift off and breakdown voltage were measured when metal particles existed in a model GIS coated with epoxy resin on its bottom electrode, and the measured results were analyzed after comparing with the model DIS not coated. In order to presume the various fault case in GIS, we measured the experimental values with changing some experimental factors, such as the mixture ratio of SF$\_$6//N$_2$, the pressure of the gases, the kinds and diameter of the metal particles, and the coating thickness of the epoxy resin. As a result, the PDIV increased with the thickness of the epoxy resin, while the magnitude of PDs decreased at the same condition. The lift off voltages of steel alloy particles were higher than that of copper particles, and increased wit diameter of particles. Futhermore, the lift off voltages in the case of the electrode coated with epoxy resin were higher than that in the case of the uncoated one. In addition, the thicker the thickness of the epoxy resin was, the higher the breakdown voltage were. Thus, it was confirmed that the GIS coated with epoxy resin on its inner surface could be improved in insulation performance.

• Journal of the Korean Vacuum Society
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• v.18 no.1
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• pp.66-72
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• 2009

The detection methods are required to monitor and diagnose the abnormality on the insulation condition inside a gas-insulated switchgear (GIS). Due to a good sensitivity to the products decomposed by partial discharges (PDs) in $SF_6$ gas, the development of a SWNT gas sensor is actively in progress. However, a few numerical studies on the diffusion mechanism of the $SF_6$ decomposition products by PD have been reported. In this study, we modeled $SF_6$ decomposition process in a chamber by calculating temperature, pressure and concentration of the decomposition products by using a commercial CFD program in conjunction with experimental data. It was assumed that the mass production rate and the generation temperature of the decomposition products were $5.04{\times}10^{-10}$ [g/s] and over 773 K respectively. To calculate the concentration equation, the Schmidt number was specified to get the diffusion coefficient functioned by viscosity and density of $SF_6$ gas instead rather than setting it directly. The results showed that the drive potential is governed mainly by the gradient of the decomposition concentration. A lower concentration of the decomposition products was observed as the sensors were placed more away from the discharge region. Also, the concentration increased by increasing the discharge time. By installing multiple sensors the location of PD is expected to be identified by monitoring the response time of the sensors, and the information should be very useful for the diagnosis and maintenance of GIS.