• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.08a
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• pp.142-145
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• 2002

This paper describes an influence of system voltage harmonics on arrester deterioration diagnostic techniques based on leakage current measurement because the resistive current is composed of two components caused by nonlinear characteristics of arrester and by system voltage harmonics. Resistive leakage currents of arresters, which can be evaluated by the third harmonic component of total leakage currents, increase with its deterioration progress. In this paper, we developed a PSpice model for ZnO arrester to simulate the harmonics' effect described above. In simulation, pure sinusoidal voltage and the $3^{rd}$ harmonic voltage are applied to the model, and the leakage current changes are compared. The simulation results showed that the magnitudes of resistive leakage current depend not only on the phase of system voltage harmonics but also on the magnitude of it.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.711-716
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• 2012

To assess the insulation deterioration of stator windings, diagnostic and AC breakdown tests were performed on the eleven high voltage (HV) motors rated at 6kV. After completing the diagnostic tests, the AC overvoltage test was performed by gradually increasing the voltage applied to the stator windings until electrical insulation failure occurred, to obtain the breakdown voltage. Stator winding of motors 1, 3, and 8 failed at above rated voltage at 14 kV, 13.8kV, and 16.4kV, respectively. The breakdown voltage of three motors was higher than expected for good quality windings in 6kV motors. Based on deterioration evaluation criteria, the stator winding insulation of eleven HV motors are confirmed to be in good condition. The turning point of the current, $P_{i2}$, in the AC current vs. voltage characteristics occurred between 5kV and 6kV, and the breakdown voltage was low between 13.8kV and 16.4kV. There was a strong correlation between the breakdown voltage and various electrical characteristics in diagnostic tests including Pi2.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.1
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• pp.42-46
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• 2003

Arresters are deteriorated by overvoltages or impulse currents, and the resistive leakage current of arresters increases as the deterioration of the arrester progresses, showing an increase in the 3$^{rd}$ harmonic component of the leakage current. In this reason, arrester diagnostic techniques based on the 3$^{rd}$ harmonic leakage current as a reference parameter of deterioration are widely used. The technique, however, includes an error due to the harmonics of power system voltage. Therefore, the influence of the harmonics on arrester diagnostics should be considered. In this paper, we designed a PSpice ZnO arrester model to simulate the influence of the voltage harmonics described above. A pure sinusoidal voltage and its the 3r harmonic voltage were applied to the model, and the leakage current components were analyzed. From the simulation results, it is confirmed that the peak value of resistive leakage current depends not only on the phase of the 3$^{rd}$ harmonic voltage but also on the magnitude of it. Consequently, the errors caused 1)y the harmonic voltage could be minimized by correcting the magnitude of leakage current upon analyzing the harmonics.cs.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.280-285
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• 2014

In order to evaluate the insulation deterioration in the stator windings of five gas turbine generators(137 MVA, 13.8 kV) which has been operated for more than 13 years, diagnostic test and AC dielectric breakdown test were performed at phases A, B and C. These tests included measurements of AC current, dissipation factor, partial discharge (PD) magnitude and capacitance. ${\Delta}I$ and ${\Delta}tan{\delta}$ in all three phases (A, B and C) of No. 1 generator stator windings showed that they were in good condition but PD magnitude indicated marginally serviceable and bad level to the insulation condition. Overall analysis of the results suggested that the generator stator windings were indicated serious insulation deterioration and patterns of the PD in all three phases were analyzed to be internal, slot and spark discharges. After the diagnostic test, an AC overvoltage test was performed by gradually increasing the voltage applied to the generator stator windings until electrical insulation failure occurred, in order to determine the breakdown voltage. The breakdown voltage at phases A, B and C of No. 1 generator stator windings failed at 28.0 kV, 17.9 kV, and 21.3 kV, respectively. The breakdown voltage was lower than that expected for good-quality windings (28.6 kV) in a 13.8kV class generator. In the AC dielectric breakdown and diagnostic tests, there was a strong correlation between the breakdown voltage and the voltage at which charging current increases abruptly ($P_{i1}$, $P_{i2}$).

• Journal of the Korean Society of Safety
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• v.27 no.4
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• pp.13-19
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• 2012

The purpose of this study is to extract the major factors related to the deterioration mechanism of white organic light-emitting diodes(WOLED) by performing accelerated testing of temperature, voltage, time, etc., and to develop an accelerated life test(ALT) model. The measurement results of the brightness of the WOLED exhibited that their average brightness tended to increase as the operating voltage increased and that the half-life period of the brightness appeared after approximately 400 hours when the operating voltage was 20V and the ambient temperature was $85^{\circ}C$. It could be seen that although the WOLED showed comparatively the same brightness when the initial acceleration began after the operating voltage was applied to it, its brightness changed excessively after the WOLED's thermal storage had been made. In addition, it was observed that the half-life period was reduced as the ambient temperature and applied voltage increased. The strength of the WOLED which had been maintained in the range of visible light at the maximum load was reduced by the deterioration of the organic light emitting material due to the influence of the operating voltage and temperature, and the reduction of emitted light was small at low voltage and temperature. It could be seen that the failure of the WOLED during the ALT was caused by wear due to load accumulation over time, and that Weibull distribution was appropriate for the life distribution and acceleration was established between test conditions. From the WOLED analysis, it is thought that factors influencing the brightness deterioration are voltage, temperature, etc., and that comprehensive analysis considering discharge control, dielectric tangent margin, etc., would further increase the reliability.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.323-328
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• 1989

In this paper, we studied the diagnostic method of insulation deterioration for 22.9kV CNCV cable using D.C potential decay component. At first, arbitrary D.C high voltage is appeied the CNCV cable for two minutes and switched off in vacuum. And then D.C potential decay components is measured for ten minutes. It is detecting source for cable insulation deterioration that its gradient is. Provisionally, we decided the criterion voltage and select the high voltage meter and S.W.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.400-405
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• 2008

Motor is energy converting system to generate mechanical force from electrical power and there are various typed motors in home, office, factory, vehicles, aircraft, shipping, etc. Recently in compliance with performance and reliability and the applications of variable speed motors with invert driver are expanded. Almost high power inverter have IGBT and IGBT's fault cause motor system fault. If we can calculate and foresee troubles of IGBT, we can protect accident caused by motor system fault. In this paper, the deterioration test method of IGBT devices is proposed and the test results of proposed method are shown by evaluated equipment. The basic concept of proposed method is current-voltage characteristic curve test between drain and source of IGBT in open state. The applied voltage type is ramp and it is confirmed that the current-voltage curvet pattern of IGBT in open state represents IGBT's deterioration state.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1954-1956
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• 2000

In this paper, when void of XLPE was existed, electrical tree was growth in branch-type, and it was growth in bush-type when void of XLPE was not existed. Moreover, charge magnitude of partial discharge by deterioration time of XLPE sample was about proportion to output voltage of AE signals. When void was existed, charge magnitude of partial discharge, the output voltage Vp-p value of AE signals were increased with increasing deterioration time. However, when void were not existed, charge magnitude of partial discharge, the output voltage Vp-p value of AE signals were increased in fast deterioration time, but it were decreasing at after in middle deterioration time. Frequency spectrum response of AE signal was about 100-250[kHz].

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.10
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• pp.635-640
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• 2016

This paper dealt with the deterioration characteristics and an on-line diagnosis equipment for SPDs (surge protective devices). An accelerated aging test was carried out using a $8/20{\mu}s$ standard lightning impulse current to analyze the changes of electrical characteristics and to propose the diagnostic parameters and the criterion for deterioration of ZnO varistor which is the core component of SPDs. Based on the experimental results, an on-line diagnosis equipment for SPD was fabricated, which can measure the total leakage current, reference and clamping voltage. The leakage current measurement circuit was designed using a low-noise amplifier and a clamp type ZCT. A linear controller, the leakage current measurement part and a HVDC were used in the measurement of reference voltage. The measurement circuit of clamping voltage consisted of a surge generator and a coupling circuit. In a calibration process, measurement error of the prototype equipment was less than 3%.