• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.158-161
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• 2002

Many methods were proposed for insulation degradation diagnosis to High voltage and capacity Transformer in live. IDD is difficult by those methods because insulation degradation circumstances and characteristics of electrical plant are different with other Therefore, it is necessary to design diagnosis algorithms fitting for each. In this paper, We develop IIDS that used diagnosis algorithm with fuzzy model and hardware with MCU.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.191-193
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• 2002

Insulation aging diagnosis system provides early warning in regard to electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. For solving this problem, many researchers proposed a method that diagnose power plant by using partial discharge. In this paper, we design the intelligent sensor to diagnose insulation degradation state that uses a Microprocessor and Al. Proposed sensor has MCU that is used to diagnose insulation degradation and communicate with main IDD system. And we use a fuzzy model to diagnose insulation degradation.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.3
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• pp.208-214
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• 2011

In this thesis, the partial discharge according to applied voltage and variations of cross-sectional area and length of the conductor related to general condition for using cable was measured in order to study degradation diagnosis for 2-Core cable of the PVC insulator used in industrial fields for other safety installations. Also the thermal degradation conditions under various installation circumstances of cables were studied by assuming degradation conditions with each different degradation rate (50%, 67%, 100%) such as variation in degradated temperature, thermal exposure time, normal state, partially degradated state and overall degradated state for thermal degradation diagnosis. The quantity of electric discharge (V-Q) according to applied voltage was measured for measurement of inception voltage and extinction voltage. The quantity of electric discharge and the number of electric discharge (Q-N) were measured with applied voltage kept constantly. In addition, pictures were taken using SEM (scanning electron microscope) to compare the surface of external insulator to degradated state of internal insulator according to thermal degradation temperature and also compare the surface of external insulator to degradated surface state of internal insulator according exposure time of cables to thermal stress.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.25-28
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• 2000

In this paper, the technology for accelerating degradation & life estimation on the traction motor was introduced with the stator form-winding sample coils of the 200 Class insulation system The accelerative degradation was performed in 10 cycles, which were composed of thermal stress, fast rising surge voltage, vibration, water immersion and overvoltage applying. After aging of 10 cycles, condition diagnosis test such as insulation resistance & polarization index, capacitance & dielectric loss and partial discharge properties were investigated in the temperature range of $20{\sim}160^{\circ}C$. Relationship between degradation conditions and diagnosis results were analyzed to find an dominative degradation factor at the end-life point

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.1
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• pp.93-101
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• 2002

In this study, the stator form-winding sample coils based on silicone resin and polyimide were made for fault prediction and reliability estimation on the C-Class(200$\^{C}$ ) insulation system of traction motors. The complex accelerative degradation was periodically performed during 10 cycles, which was composed of thermal stress, fast rising surge voltage, vibration, water immersion and overvoltage applying. After aging of 10 cycles, the condition diagnosis test such as insulation resistance '||'&'||' polarization index, capacitance '||'&'||' dielectric loss and partial discharge properties were investigated in the temperature range of 20 ∼ 160$\^{C}$. Relationship among condition diagnosis tests was analyzed to find a dominative degradation factor and an insulation state at end-life point.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.763-766
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• 2000

In this paper, stator form-winding sample coils based on silicone resin and polyimide were made for fault prediction and reliability estimation on the 200 Class insulation system of traction motors. The complex accelerative degradation was performed by periods during 10 cycles, which was composed of thermal stress, fast rising surge voltage, vibration, water immersion and overvoltage applying. After aging of 10 cycles, condition diagnosis test such as insulation resistance & polarization index, capacitance & dielectric loss and partial discharge properties were investigated in the temperature range of 20∼160$^{\circ}C$. Relationship among condition diagnosis test was analyzed to find an dominative degradation factor and an insulation state at end-life point.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.642-648
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• 2008

In order to analyze the causes of fossil power plant facilities due to a degradation and corrosion, artificial degraded materials composed of the facilities were manufactured. Various experiment were performed based on mechanical test, microstructure observation, hardness test, electrochemical potentiokinetic reactivation test(EPR) and corrosion scale thickness measurement test. The master curves were write out using Larson-Miller parameter to evaluate the degree of degradation with the above diagnosis methods. These data were applied to materials database of fossil power plant diagnosis. Finally expert system on the fossil power plant diagnosis was developed using the master curves and diagnosis algorithms.

• The Journal of Information Technology
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• v.2 no.2
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• pp.13-22
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• 1999

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime by introduction a neural network. In the proposed method, we use AE(acoustic emission) sensing system and calculate a quantitative statistic parameter by pulse number and amplitude. Using statically parameters such as the center of gravity(G) and the gradient if the discharge distribute(C), we analyzed the early stage and the middle stage. the quantitative statistic parameters are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05a
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• pp.61-65
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• 2001

The conventional tracking testing as IEC-60587 is widely used in surface aging measurement of outdoor insulator because those testing can carry out very short time in Lab-testing. Also IEC-60587 testing is able to offer the standard judgement of relative degradation level of outdoor HV machine/system. Therefore it is very useful method compare to previous conventional tracking testing method and effective Lab-testing method. But surface discharges(SD) have very complex characteristics of discharge pattern so it is required estimation research to development of precise analysis method. In recent, the study of IRR-camera is carrying out discover of temperature of power equipment through condition diagnosis and system development of degradation diagnosis. In this study, SD occurred from procelain insulator, used 22.9[KV] distribution, is measured with partial temperature distribution in real time, the degradation grade of SD is analyzed through produced patterns in SD concentration according to applied time.

• Journal of the Korean institute of surface engineering
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• v.55 no.4
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• pp.231-235
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• 2022

As environmental pollution becomes more serious, the demand for electric vehicles (EVs) and lithium-ion batteries for electric vehicles is rapidly increasing worldwide. Accordingly, the amount of waste batteries is also increasing, and a technology for recycling and reusing them is required. In order to reuse a used battery, it is necessary to non-destructively diagnose the deterioration condition of the battery. Therefore, in this study, we investigate the diagnosis of degradation for parallel-connected lithium-ion battery cells through non-constructive electrochemical approach. As the number of parallel-connected cells increased, in addition to linear degradation, abrupt step-like degradation occurred, which is attributed to the predominant degradation of specific cells. In addition, it is confirmed that deteriorated cells among multiple cells can be distinguished through a simple measurement of open circuit voltage (OCV).