• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.7
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• pp.364-369
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• 2004

In this Paper, a flashover prediction method using the leakage current in the contaminated EPDM distribution polymer insulator is proposed. The leakage currents on the insulator were measured simultaneously with the different salt fog application such as 25g, 50g, and 75g per liter of deionized water. Then, the measured leakage currents were enveloped and transformed as the CDFS using the Hilbert transform and the level crossing rate, respectively. The obtained CDFS having different gradients(angles) were used as a important factor for the flashover prediction of the contaminated polymer insulator. Thus, the average angle change with an identical salt fog concentration was within a range of 20 degrees, and the average angle change among the different salt fog concentrations was 5 degrees. However, it is hard to be distinguished each other because the gradient differences among the CDFS were very small. So, the new weighting value was defined and used to solve this problem. Through simulation, it Is verified that the proposed method has the capability of the flashover prediction.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.759-761
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• 2010

In order to monitor operating performance of contaminated outdoor insulators, a wavelet-based flashover prediction method is proposed. In most cases, the low-frequency components, namely, fundamental, $3^{rd}$, and $5^{th}$ harmonic components have been mainly used for the sake of the spectral analysis of the leakage current. However, in this paper, the detail coefficients of wavelet transform representing high-frequency components are used as important information to predict a flashover in the contaminated insulator. Experimental results verify that the proposed method has a superior capability for flashover prediction.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1375-1384
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• 2014

Flashover of power transmission line insulators is a major threat to the reliable operation of power system. This paper deals with the flashover prediction of polymeric insulators used in power transmission line applications using the novel condition monitoring technique developed by PD signal time-frequency map and neural network technique. Laboratory experiments on polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. Partial discharge signals were acquired using advanced ultra wide band detection system. Salient features from the Time-Frequency map and PRPD pattern at different pollution levels were extracted. The flashover prediction of polymeric insulators was automated using artificial neural network (ANN) with back propagation algorithm (BPA). From the results, it can be speculated that PD signal feature extraction along with back propagation classification is a well suited technique to predict flashover of polymeric insulators.

• Journal of the Korea Construction Safety Engineering Association
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• s.46
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• pp.74-81
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• 2008

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1326-1336
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• 2018

This paper proposes a numerical approach to predict the critical flashover voltages of air gaps under lightning impulses. For an air gap, the impulse voltage waveform features and electric field features are defined to characterize its energy storage status before the initiation of breakdown. These features are taken as the input parameters of the predictive model established by support vector machine (SVM). Given an applied voltage range, the golden section search method is used to compute the prediction results efficiently. This method was applied to predict the critical flashover voltages of rod-rod, rod-plane and sphere-plane gaps over a wide range of gap lengths and impulse voltage waveshapes. The predicted results coincide well with the experimental data, with the same trends and acceptable errors. The mean absolute percentage errors of 6 groups of test samples are within 4.6%, which demonstrates the validity and accuracy of the predictive model. This method provides an effectual way to obtain the critical flashover voltage and might be helpful to estimate the safe clearances of air gaps for insulation design.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1677-1685
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• 2014

Major problem in the high voltage power transmission line is the flashover due to polluted ceramic insulators which leads to failure of equipments, catastrophic fires and power outages. This paper deals with the development of a better diagnostic tool to predict the flashover and pollution severity of power transmission line insulators based on the wavelet transform and fuzzy c-means clustering approach. In this work, laboratory experiments were carried out on power transmission line porcelain insulators under AC voltages at different pollution conditions and corresponding leakage current patterns were measured. Discrete wavelet transform technique is employed to extract important features of leakage current signals. Variation of leakage current magnitude and distortion ratio at different pollution levels were analyzed. Fuzzy c-means algorithm is used to cluster the extracted features of the leakage current data. Test results clearly show that the flashover and pollution severity of power transmission line insulators can be effectively realized through fuzzy clustering technique and it will be useful to carry out preventive maintenance work.

• 전기산업
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• v.15 no.8
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• pp.73-80
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• 2004

• Fire Science and Engineering
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• v.18 no.3
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• pp.30-38
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• 2004

An important characteristics during fire growth is the phenomena of flashover, which is the transition from the local combustion to the full-room fire. The aim of this study is to predict the flashover times, the ignition times and HRR(heat release rate) of flashover for building interior materials. By using the literature data and RSM(response surface methodology), the new equations for predicting the flashover time, the ignition time and the HRR of building interior materials are proposed. The A.A.P.E.(average absolute percent error) and the A.A.D.(average absolute deviation) of the reported and the calculated flashover times were 38.74sec and 51.24sec respectively, and the correlation coefficient was 0.975. The A.A.P.E and the A.A.D of the reported and the calculated ignition times were 10.96sec and 1.97sec, and the correlation coefficient was 0.962. Also the A.A.P.E and the A.A.D. of the reported and the calculated the HRR of flashover by means of times were 29.92 and 514, and the correlation coefficient was 0.830. The values calculated by the proposed equations were in good agreement with the literature data. Therefore, it is expected that this proposed equations will support the use of the research for other building interior materials.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.413-419
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• 2004

This paper describes a technique that can predict electric fires by detection of discharge voltage signals caused by the use of electric facilities. In the experiment, various discharge modes, a flashover or a surface discharge through insulation paper and a line to line short, were simulated to acquire electrical information for predicting electrical fire as discharge modes. From the experimental results, it is hewn that electorial discharges which are ranked as majority causes of electric fires generate characterized signals distinguished from power frequency. Finally. We designed a prototype discharge detector based on the experimental results, and the detector is applied to a power lines. This study showed that the prediction of electric fires is possible by monitoring discharge voltage signals in electric power lines.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.989-993
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• 2009

Triple junction which consists of three media(electrode, insulator, and gas) should be considered in designing of high voltage equipments due to the electric field enhancement. In this paper, positive lightning impulse breakdown voltage is predicted based on the streamer theory for simplified insulator models and 72.5kV spacer with varying the triple junction geometry and gas pressure, and the results are compared to the experimental results. The electric field coefficient concept is also applied in order to evaluate the partial discharge inception voltage and the surface flashover voltage from the streamer inception voltage. The application of this method using the constant electric field coefficient of 1.3 and 0.66 is possible for evaluating the triple-junction insulation of the simplified insulator and the 72.5kV spacer respectively. The error rate is under 10%.