• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제55권6호
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• pp.308-312
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• 2006

Partial Discharge (PD) phenomena occurred by different nature of insulating defects has been regarded as a random process by which Phase Resolved Partial Discharge Analysis(PRPDA) has been proposed and then commercially accepted for the diagnosis of the power apparatus since more than three decades. Moreover, for the same purpose, a novel approach based on the Chaotic Analysis(CAPD) has been proposed since 2000, in which Partial Discharge(PD) phenomena is suggested to be considered as a deterministic dynamical process. In this work, for the diagnosis of Gas Insulated Transformer(GITr), four different types of specimen were fabricated as a model of the possible defects that might possibly cause its sudden failures such as turn to turn insulation, inter coil insulation, free moving particle and protrusion. For this purpose, these defects are introduced into the Gas Insulated Transformer(GITr) mock-up and experimental investigations have been carried out in order to analyze the related Partial Discharge(PD) patterns by means of both Phase Resolved Partial Discharge Analysis(PRPDA) and Chaotic Analysis(CAPD) respectively and then their comparisons are made systematically.

• KIEE International Transactions on Electrophysics and Applications
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• 제2C권5호
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• pp.239-245
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• 2002

In this work, in order to realize the possible defects at the cable joint interface, four different types of artificial defects are provided : conducting, insulating substances, void and scratches. The analysis related to the PD patterns has been performed by means of conventional Phase Resolved Partial Discharge Analysis (PRPDA) and Chaotic Analysis of Partial Discharge (CAPD) as well which was proposed by our previous communication. As a result, it could be pointed out that each defect has shown particular characteristics in its pattern respectively and that the nature of defect causing partial discharge could be identified more distinctively when the CAPD is combined with the conventional statistic method, PRPDA.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 연구회
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• pp.221-224
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• 2001

In connection with the monitoring of insulation degradation of large power apparatus in order to predict their unexpected service failures, a statistical treatment, such as phase resolved partial discharge analysis(PRPDA), has been established for the on-line monitoring system during the past decades. However, this method has shown some inconveniences to distinguish the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis(CAPD) is proposed describing the fundamental ideas, outcomes and different view points from conventional PRPDA. In order to make a model for the possible defects causing sudden failures in service, several types of specimen were prepared. And partial discharge signals, originated from those samples, were measured and analysed by means of PRPDA and CAPD respectively. Throughout this paper, it seems that the correlation between the consecutive PD pulses depending on the nature of PD could be investigated by CAPD. Therefore, it could be considered that the nature of PD source can be distinguished more distinctively when the PRPDA is combined with CAPD.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.975-979
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• 2001

In connection with the monitoring of the insulation degradation of large power apparatus in order to predict their expected service failures, a statistical treatment, such as phase resolved partial discharge analysis (PRPDA), has been established for the on-line monitoring system during the past decades. However, this method has shown some inconveniences to identify the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis (CAPD) is proposed describing the fundamental ideas, outcomes and different viewpoints from the conventional PRPDA. As a model for the possible defects causing sudden failures in service, three types of specimen are prepared. And partial discharge signals, originated from those samples, are measured and analyzed by means of CAPD. Throughout this work, it seems that the correlation between the consecutive PD pulses, depending on the nature of PD, could be clarified by CAPD. Thereffre, it could be considered that the nature of PD source can be identified more distinctively when the CAPD is combined with PRPDA.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전기물성,응용부문
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• pp.226-228
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• 2003

This paper deals with the improvement of indefiniteness in PRPDA(Phase Resolved Partial Discharge Analysis) through analyzing the relation between PRPDA and PSA(Pulse Sequence Analysis). For the analysis we adopted PD data from artificial defects in XLPE HV cable systems and performed PRPDA and PSA. As a results, we confirmed that PSA was more useful than PRPDA in classifying PD patterns with the degradation stages. Therefore, it is possible to improve the indefiniteness of PD pattern recognition using the relation between PRPDA and PSA.

• 전기학회논문지
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• 제58권8호
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• pp.1615-1623
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• 2009

In order to develop reliable on-site partial discharge (PD) pattern recognition algorithm, we introduce Type-2 Fuzzy Neural Networks (T2FNNs) optimized by means of Particle Swarm Optimization(PSO). T2FNNs exploit Type-2 fuzzy sets which have a characteristic of robustness in the diverse area of intelligence systems. Considering the on-site situation where it is not easy to obtain voltage phases to be used for PRPDA (Phase Resolved Partial Discharge Analysis), the PD data sets measured in the laboratory were artificially changed into data sets with shifted voltage phases and added noise in order to test the proposed algorithm. Also, the results obtained by the proposed algorithm were compared with that of conventional Neural Networks(NNs) as well as the existing Radial Basis Function Neural Networks (RBFNNs). The T2FNNs proposed in this study were appeared to have better performance when compared to conventional NNs and RBFNNs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기설비전문위원
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• pp.109-112
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• 2004

In this study, the applicability of SOM(Self Organizing Map) algorithm to partial discharge pattern recognition have been investigated. For the purpose, using acquired data from the artificial defects in GIS, SOM 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. As a result, basically BP algorithm was found out to be better than SOM algorithm. Therefore, it is needed to apply SOM algorithm in combination with BP algorithm in order to improve on-site applicability using the advantages of SOM. Also, for the pattern recognition by use of PRPDA(Phase Resolved Partial Discharge Analysis) it is required the normalization of the PRPDA graph. However, in case of the normalization both BP and SOM algorithm have shown worse results, so that it is required further study to solve the problem.

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

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 C
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• pp.1606-1608
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• 2001

In connection with the monitoring of the insulation degradation of the large power apparatus, a statistical treatment, such as phase resolved partial discharge analysis (PRPDA) has been established for the on-line monitoring system during the past two decades. However, it has shown some inconveniences to distinguish the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis(CAPD) is proposed describing the fundamental ideas, outcomes and different view points from conventional PRPDA. In order to make a model for the possible defects causing sudden failures in service, several types of specimen were prepared. And partial discharge signals, originated from those samples, were measured and analyzed by means of PRPDA and CAPD respectively. In this paper, it seems that the correlation between the consecutive PD pulses depending on the nature of PD could be investigated by CAPD. Therefore, it could be considered that the nature of PD source can be distinguished more distinctively when the PRPDA is combined with CAPD.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 추계학술대회 논문집 Vol.17
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• pp.327-330
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• 2004

Because of its effectiveness for the PD(partial discharge) pattern recognition, PSA(Pulse Sequence Analysis) has been considered as a new analytic method instead of conventional PRPDA(Phase Resolved Partial Discharge Analysis). However, PSA has a big problem that can misanalyze patterns in case of data missing resulting from poor sensitivity because it analyses the correlation between sequential pulses, which leads to hesitate to apply it to on-site. Therefore, in this paper, the problems of PSA such as data missing and noise adding cases were investigated. For the purpose, PD data obtained from various defects including noise adding data were used and analysed, The result showed that both cases can cause fatal errors in recognizing PD patterns. In case of the data missing, the error depends on the kinds of defect and the degree of degradation. Also, it could be noticed that the error due to adding noises was larger than that due to some data missing.