• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1891-1892
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• 2008

본 논문에서는 부분방전 패턴인식을 위한 퍼지뉴럴네크워크(Fuzzy-Nueral Network를 설계한다. 퍼지뉴럴네트워크의 구조에서 규칙의 전반부는 개별적인 입력 공간을 분할하여 표현하고, 규칙의 후반부는 다항식으로서 표현되며 오류역전파 알고리즘을 이용하여 연결가중치인 후반부 다항식의 계수를 학습한다. 또한, 유전자 알고리즘을 이용하여 각 입력에 대한 전반부 멤버쉽함수의 정점과 학습률 및 모멤텀 계수를 최적으로 동조한다. 제안된 네트워크는 부분방전 패턴인식을 위해 다중 출력을 가지며, 초고압 XLPE 케이블 절연접속함의 모의결함에 대해 부분방전 신호를 패턴인식한다. 부분방전 신호는 PRPDA 방법을 통해 256개의 입력 벡터와 4개의 출력 벡터를 가지며, 보이드 방전, 코로나 방전, 표면 방전, 노이즈의 4개 클래스를 분류하며, 패턴인식률로서 결과를 분석한다.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.4
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• pp.161-165
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• 2006

In this paper, we developed HPF (high pass filter) consists of lumped LC components to decrease the noises that are detected in PD (partial discharge) measuring test, and adapted it to field test. We tested it under laboratory circumstances like the fields, and measured the phase change properties of detected signal in UHF sensor with Lemke Probe and oscilloscope (TDS-3054, Tektronix). As a result, we obtained available data showing the decrease of noises in the experiments with the developed HPF from the joint box of 22.9kV distribution line. The result can be adapted to prevent the degeneration of the XLPE power cable, and to observe and diagnosis the underground power transmission cable at the ultra-high voltage.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.411-414
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• 2008

본 논문에서는 다중 출력을 가지는 퍼지 집합 기반 퍼지뉴럴네크워크(Fuzzy-Nueral Network; FNN)를 설계한다. 퍼지 집한 기반 퍼지뉴럴네트워크는 각 입력 변수에 따른 개별적인 입력 공간을 공간 분할함으로서 네트워크를 구성한다. 규칙의 전반부는 앞서 언급한 개별적인 입력 공간을 분할하여 표현하고, 규칙의 후반부는 다항식으로서 표현되며 오류역전파 알고리즘을 이용하여 연결가중치인 후반부 다항식의 계수를 학습한다. 또한, 각 입력에 대한 전반부 멤버쉽 함수의 정점과 학습률 및 모멤텀 계수를 유전자 알고리즘을 이용하여 최적 동조한다. 따라서 유전자 알고리즘을 이용하여 퍼지뉴럴네트워크를 최적 설계한다. 제안된 네트워크는 초고압 XLPE 케이블 절연접속함의 모의결함에 대해 부분방전 신호를 패턴인식한다. 부분방전 신호는 PRPDA 방법을 통해 200개의 입력 벡터와 4개의 출력 벡터를 가지며, 보이드 방전, 코로나 방전, 표면 방전, 노이즈의 4개 클래스를 분류한다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.453-454
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• 2007

전력설비에 대한 부분방전 패턴인식은 결함의 차이에 따라 다양한 패턴의 차이를 보이고 있으며, 신경회로망을 비롯한 다양한 패턴인식 기법들이 적용되고 있다. 본 논문에서는 이의 일환으로 퍼지 집합 기반 퍼지뉴럴네트워크를 설계하여 초고압 XLPE 케이블 절연접속함의 모의 결합에 대해 부분방전 신호를 패턴인식하고자 한다. 부분방전 신호는 보이드 방전, 코로나 방전, 노이즈의 3개 클래스로 분류하게 되며, PRPDA 방법을 통해 556개의 입력 벡터와 3개의 출력 벡터를 가지며 총 120개의 패턴수를 가진다.

• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1511-1512
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• 2006

In this paper, we measured PD signals from artificial surface defects and corona discharges under laboratory circumstances like the fields using both HFCT-sensor and UHF-sensor for MV grade XLPE cable with AMP, spectrum analyzer and oscilloscope. Also, detected signals were analyzed via PRPDA system in this paper. As a result, in this case of HFCT-sensor, the amount of background noise are larger than as compared to UHF-sensor. There is needed some hardware or software or software algorithm removing background noise effectively for diagnosis the underground power transmission cable in the case of HFCT-sensor.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.119-125
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• 2008

This work involves analyzing partial discharge (PD), which has estimated the detected signal accumulation based on Labview, and analyzing by Fuzzy algorithm. In algorithm, we developed system configuration that detected accumulating PD signal. With practical PD logic implementation of theoretical detected system and hardware implementation, the device for 50kV setup has generated and then has applied with 15k~17kV with 1:1 time probe. Our new class of PD detected algorithm has also compared with PRPDA or Fuzzy algorithm, which has diagnose more conveniently by adding numerical values.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1652-1654
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• 2002

The defects making partial discharge(PD) in a C-GIS(Cubicle Insulated Switchgear) initiate acoustic wave which can be detected using acoustic emission sensor placed outside or inside the C-GIS enclosure. In this paper, partial discharge property for 2 locations for AE sensor and 3 locations for defects in C-GIS are presented and PD waveforms were analyzed by PRPDA(Partial Resolved Partial Discharge Analysis). As a result, using post amplifier having gain of 10,000 and band pass filter having $20kHz{\sim}300kHz$, resolution of waveforms AE sensor signal by detected was good. Noise level was about 80 mV.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.1
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• pp.40-45
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• 2015

Electrode systems: a protrusion on conductor (POC), a protrusion on enclosure (POE), a crack in epoxy plate and a free particle (FP) were fabricated to simulate insulation defects in a gas insulated switchgear (GIS). $SF_6$ gas was filled in the electrode systems by 3 bar and/or 5 bar, respectively. Partial discharge (PD) pulses were detected through a $50{\Omega}$ non-inductive resistor. A calibration test was carried out according to IEC 60270, and the sensitivity was 0.25 pC/mV. PD pulses were distributed in the phase of $50^{\circ}{\sim}135^{\circ}$ and over 95% of them existed in the phase of $55^{\circ}{\sim}120^{\circ}$ for the POC. PD pulses were distributed in the phase of $230^{\circ}{\sim}310^{\circ}$ and over 90% of them existed in phase of $220^{\circ}{\sim}300^{\circ}$ for the POE. PD pulses occurred in the phase of $40^{\circ}{\sim}60^{\circ}$ and $220^{\circ}{\sim}300^{\circ}$ for the crack, and pulse counts were 25% higher in negative polarity than in positive polarity. PD pulses were distributed in every phase unlike to other three electrode systems and the peak magnitude was measured at $118^{\circ}$ and $260^{\circ}$ for the FP. As described above, PD pulses were observed in positive polarity for the POC, in negative one for the POE, in both one for the crack and the FP. In conclusion, it is expected that the identification rate of defect type can be improved by considering the polarity ratio of PD pulses on the PRPDA method.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1930-1932
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• 2004

SOM(Self Organizing Map) algorithm which has some advantages such as data accumulation ability and the degradation trend trace ability was compared with conventionally used BP(Back Propagation) algorithm. For the purpose, partial discharge data were acquired and analysed from the artificial defects in GIS. As a result, basically the pattern recognition rate of BP algorithm was found out to be better than that of SOM algorithm. However, SOM algorithm showed a great on-site-applicability such as ability of suggesting new-pattern-possibility. Therefore, through increasing pattern recognition rate it is possible to apply SOM algorithm to partial discharge analysis. Also, for the image processing method it is required the normalization of the PRPDA graph. However, due to the normalization both BP and SOM algorithm have shown worse results, so that it is required further study to solve the problem.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.939-944
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• 2002

PD phenomena can be regarded as a deterministic dynamical process where PD should be occurred if the local electric field be reached to be sufficiently high. And thus, its mathematical model can be described by either difference equations or differential equations using several state variables obtained from the time sequential measured data of PD signals. These variables can provide rich and complex behavior of detectable time series, for which Chaos theory can be employed. In this respect, a new PD pattern recognition method is proposed and named as 'Chaotic Analysis of Partial Discharges (CAPD)' for this work. For this purpose, six types of specimen are designed and made as the models of the possible defects that may cause sudden failures of the underground power transmission cables under service, and partial discharge signals, generated from those samples, are detected and then analyzed by means of CAPD. Throughout the work, qualitative and quantitative properties related to the PD signals from different defects are analyzed by use of attractor in phase space, information dimensions ($D_0$ and D2), Lyapunov exponents and K-S entropy as well. Based on these results, it could be pointed out that the nature of defect seems to be identified more distinctively when the CAPD is combined with traditional statistical method such as PRPDA. Furthermore, the relationship between PD magnitude and the occurrence timing is investigated with a view to simulating PD phenomena.