Jeong-Tae Kim

Partial Discharge Pattern Recognition Using Fuzzy-Neural Networks (FNNs) Algorithm

In order to develop reliable on-site partial discharge (PD) pattern recognition algorithm, the fuzzy set-based fuzzy neural network (FNN) was investigated and designed. Using PD data measured from laboratory defect models, this algorithm was designed and tested. Considering the on-site situation where it is not easy to obtain voltage phases in PRPDA (phase resolved partial discharge analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithm. The result of the proposed FNN algorithm was compared with that of conventional BP-NN (back propagation neural networks) algorithm using same data. The FNN algorithm proposed in this study was appeared to have better performance than BP-NN algorithm.

An analysis of the partial discharge pattern related to the artificial defects introduced at the interface in XLPE cable joint using laboratory model

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

A study on the oscillating wave voltage test as an after-laying test for distribution power cables

In this study, experimental investigation has been carried out for the defect detecting capability of two different way of the OW (oscillating wave) voltage test, such as with-cable-charging and without-cable-charging method. For this purpose, two types of OW voltage tests have been performed at the laboratory on the 22.9 kV CN/CV cables in which artificial needle-type and knifecut-type defects were well integrated. Based on the test results, it could be remarked that the with-cable-charging method is more appropriate to the after laying test due to its consistency of the test condition regardless of the cable length under testing.

Characteristics of partial discharge by AC and DC

Partial discharge(PD) characteristics by AC and DC voltage were studied using the laboratory models. PPLP butt gap in oil, void in solid insulation, surface discharge in solid/air interface, and corona were adopted as the artificial PD models. Using these models, PD pulse wave shapes and the time sequential characteristics were investigated according to the AC and DC voltage application.

Partial discharge location using 2 sensors and optical fibers

In the long electric equipment such as cables and GIS, it is very important to find out the location of the partial discharge(PD) source. In this study, PD location method was studied using arrival time difference and polarity of the pulses obtained from separately installed 2 sensors. For the purpose, pulse arrival time and pulse polarity analysis algorithm were developed. From the experiment for the long power cable, the proposed algorithm and the system were verified. Also, for the case of long cable system, the optical fiber transmission system including E/O and O/E module was composed and its performance was investigated through the PD experiments.

A study on the correlation between the PD pattern and the aspect of electrical trees propagation in the XLPE insulation of the underground power transmission cable

In this work, the correlation between the PD patterns and the electrical tree propagation has been investigated by use of the specimen removed from the insulation of the real 154 kV XLPE underground power cables. As a result, it could be deduced that the PD pattern regarding electrical trees depends on their types which could be classified into three different distinct groups such as branch, bush and branch-bush mixed. Considering the results of our investigation, if the partial discharge magnitude is only considered for the diagnosis of the cable system, it is possible to draw a wrong decision. Therefore, it is possible to propose that time characteristics of PD pattern should be taken into account for the diagnosis of the cable system in addition to the conventional /spl phi/-q-n characteristics.

Correlation between DC electric field intensity and electrical breakdown of butt gap in LN2/PPLP composite insulation system

In the design of DC superconducting cables, the electrical insulation design is a critical factor in the cables performance and reliability. To evaluate the insulation design of DC superconducting cables, DC electric field analysis and experimental verifications should be performed. Wrapped polypropylene laminated paper (PPLP) tape has generally been used to insulate superconducting cable. During the wrapping process, butt gaps are inevitably introduced, and these are filled with liquid nitrogen (LN2) during normal operating conditions. Therefore, the insulation characteristics of the resulting combination of PPLP and liquid insulation should be carefully verified. The objective of this work was to determine the DC electric field transitions when a butt gap is present in a LN2/PPLP composite insulation system. DC electric field distribution and transition were simulated by using COMSOL Multiphysics® software. Also, to verify the characteristics of DC electric field transitions, two kinds of breakdown tests were performed: a ramp voltage breakdown test and a step voltage breakdown test. In both the experimental and analytical works, it was observed that the electric field distributions were totally different while the DC field transition. And, due to the different distributions of electric field, the breakdown characteristics of LN2/PPLP composite insulation systems could be altered.

Design of optimized radial basis function neural networks classifier with the aid of fuzzy clustering and data preprocessing method

In this paper, we introduce a new architecture of optimized RBF neural network classifier with the aid of fuzzy clustering and data preprocessing method and discuss its comprehensive design methodology. As the pre-processing part, LDA algorithm is combined in front of input layer and then the new feature samples obtained through LDA are to be the input data of FRBF neural networks. In the hidden layer, FCM algorithm is used as receptive field instead of Gaussian function. The connection weights of the proposed model are used as polynomial function. PSO algorithm is also used to improve the accuracy and architecture of classifier. The feature vector of LDA, the fuzzification coefficient of FCM, and the polynomial type of RBF neural networks are optimized by means of PSO. The performance of the proposed classifier is illustrated with several benchmarking data sets and is compared with other classifier reported in the previous studies.

A Study on the Partial Discharge Location Method using 2 Sensors

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.

Analysis of Partial Discharge Inception Voltages for the Wrong Positioning Defects in the Joint of Distribution Power Cables

In order to find out partial discharge (PD) phenomena in the cable joint due to the poor workmanship during the installation, the relationship between PD inception voltages and joint defects was investigated. For the purpose, in the joint of 22.9kV CNCV cables, electric fields were calculated for various semiconductive layer wrong positioning (WP) defects. And, PDIV were investigated through the experiments and compared with the results of electric field analysis. In all WP defect cases, the PD inception field calculated using measured PDIVs was similarly shown to be the average value of 1.84kV/mm. In addition, the calculated PDIV and the measured PDIV were almost equal, from the PDIV calculation using maximum electric fields and the measured PDIV for the normal case. Throughout this study, it is possible to analyze WP defects due to the poor workmanship and to establish better joint design for the distribution grade extruded cable system.