• 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.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1679-1681
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electromagnetic wave detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, inclued noise signal in detected PD signal is well elimiated. we can propose the true shape of PD signal.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.11
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• pp.616-621
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• 2000

This paper deals with the multiresolution analysis of wavelet transform for partial discharge(PD). Test arrangement is based on the needle-plane electrode system and applied AC high voltage. The measured PD signal was decomposed into "approximations" and "details". The approximation are the high scale, low-frequency components of the PD signal. The details are the low-scale, high frequency components. The decomposition process are iterated to 3 level, with successive approximation being decomposed in turn, so that PD signal is broken down into many lower-resolution components. Through the procedure of signal wavelet transform, signal noise extraction and signal reconstruction, the signal is analyzed to determine the magnitude of PD.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.5
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• pp.12-18
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• 2000

This paper describes the analysis of ultrasonic signal and partial discharge(PD) signal patterns for each location of particle in GIS. The characteristics of the ultrasonic signal and PD signal patterns for each location were as follows; in case of particle on the electrode, large ultrasonic signals and large PD signals occurred in positive half-cycle periodically; in case of particle on the spacer, ultrasonic signals and large PD signals occurred in negative half-cycle periodically; in case of the free moving particle, ultrasonic signals and large PD signals occurred by collision non-periodically. As a result, it was confirmed that particle in GIS could be located by the comparison and analysis of ultrasonic signal and PD signal patterns.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.4
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• pp.62-68
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• 2001

In this paper, As the wavelet transform has the properties of multi-resolution analysis and time-frequency domain localization, application of wavelet transform is used at partial discharge(PD) signal detected by electrical detection method to extract PD signal's various frequency component and its time domain. therefore we can analyzed PD signal's time-frequency domain simultaneously. On the other hand, using wavelet transform denoising process, included noise signal in detected PD signal is well eliminated. we can propose the true shine of PD signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.728-732
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• 2010

GIS(Gas insulated switching gear) is power equipment with excellent dielectric strength and is economy merit in high confidence and stability. Recently, because equipment of GIS was occurring problem of confidence used for a long time, partial discharge on-line diagnosis systems have been importantly recognized. Partial discharge (PD) detection is an effective means for monitoring and evaluation of dielectric condition of gas insulated system (GIS). The ultra-high-frequency (UHF) PD detection technique can detect and locate the PD sources inside GIS by detecting electromagnetic wave emitted from PD source. Therefore, real-time diagnostic system using UHF detection method has been developed for this application is being expanded gradually. However, the signal of partial discharge occurring in SF6 gas is very weak and susceptible to external noises which mainly consist of PD in air. Thus, it is important to distinguish the PD in SF6 gas more sensitively from the external noises. Unfortunately, these external noise signals and the partial discharge signals have very similar characteristics. Therefore, to solve this problem, we need the signal processing method for distinguish partial discharge signals with external noise signals for improvement of SNR(signal to noise ratio) and sensitivity. In this paper, we proposed internal signal processing method for removing external noise signals with built-in pre.amplifier and frequency conversion circuit.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.134-141
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• 2019

Radar systems are divided into the pulse Doppler (PD) radar and the frequency modulated continuous wave (FMCW) radar depending on the transmission waveform. In particular, the PD radar is advantageous for long-range target detection, and the FMCW radar is suitable for short-range target detection. In this paper, we present design and implementation results for a multi-mode radar signal processor (RSP) that can support both PD and FMCW radar systems to detect unmanned aerial vehicles (UAVs) at short distances as well as long distances. The proposed radar signal processor can be implemented based on Altera Cyclone-IV FPGA with 19,623 logic elements, 9,759 registers, and 25,190,400 memory bits. The logic elements and registers of the proposed radar signal processor are reduced by approximately 43% and 30%, respectively, compared to the sum of logic elements and registers of the conventional PD radar and FMCW radar signal processor.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.217-219
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• 2001

This paper presents new diagnosis technique for detecting a partial discharge(PD) using antenna. The wavelet transform is applied for the analysis of PD pulse signal because it is difficult to identify PD signal using electromagnetic waves detected by antenna. The capabilities of the proposed diagnosis methodology for detecting PD signal is verified on experiment in laboratory.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.56-59
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• 2008

We have designed 4 types(void in insulation paper, protrusion electrode, floating electrode, surface discharge) of partial discharge(PD) defect to simulate typical faults found in oil filled power transformers. Ultra-high frequency(UHF) radiation due to PD was measured using a UHF measuring system and a conventional PD measuring system, simultaneously. Electromagnetic radiation spectra of these defects show UHF radiation up to about 1.5-2 GHz range. The phase resolved partial discharge(PRPD) patterns of UHF radiation from the PD defects were also measured and the pattern reveals distinct feature for each defect types. The UHF measuring could be used to detect PDs in oil filled transformers and analysis of the PRPD pattern should provide useful information on origin of PD signal.