• Proceedings of the KIEE Conference
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• 2003.10a
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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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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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.

• Proceedings of the KIEE Conference
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• 2001.07c
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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.

• Proceedings of the IEEK Conference
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• 2001.09a
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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.

• KIEE International Transactions on Electrophysics and Applications
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• v.2C no.5
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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.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.6
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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.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1015-1018
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• 2005

In this paper, we introduce about a new class to analysis of partial discharge signal based on Fuzzy model. We can early diagnose life of power cable through detection of partial discharge signal. However, partial discharge signal detector is difficult because of partial discharge signal is very non-linear. Also, it is very difficult work that separate partial discharge signal from noise. We constructed partial discharge accumulation detection system that use Labview for detection of non-linear partial discharge signal. And analyzed partial discharge signal that is detected by Labview system utilizing Fuzzy model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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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.

• 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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• 2006.10a
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• pp.224-226
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• 2006

In this paper, we have studied for analysis of the partial discharge(PD) signal in power transmission line. The PD signal has estimated as detected signal accumulation of a PRPDA method by using Labview, and analyzed with neuro-fuzzy algorithm. With practical PD logic implementation of theoretical detected system and hardware implementation, the device for Hipotronics Company's 22.9kV or 154kV setup has generated and then has applied with 18kV,20kV with 1:1 time probe. It's also used the LDPE O.27mmt (scratch error O.05mmt) to sample for making PD. 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.