• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1685-1687
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• 2001

변전소 및 전력계통에 지락사고가 발생하면 변전소의 접지망에 사고전류가 유입하게 된다. 이 유입전류는 가공지선이나 변압기 중성선 그리고 기타 접지 망에 연결되어 있는 접지시스템에 의해 분류되는데, 모델변전소의 지락전류 흐름도를 모델화하여 Pspice 프로그램으로 대략적인 분류율을 계산하고, 실측치를 통해 지락사고시의 가공지선 분류율을 비교 평가하였다.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.952-954
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• 1998

This paper presents an artificial neural network approach to diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. The proposed algorithm is used to detect faults with or without cellulose involved. Several neural network topologies have been considered. Good diagnosis accuracy is obtained with the proposed approach.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.511-517
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• 2016

Current oil-type potential transformers for trains are filled with insulating oil, which could have problems like explosions due to rising inner pressure during train operation. Therefore, mold and dry-type potential transformers are being developed to prevent explosions. One problem in manufacturing mold-type transformers is preventing void formation around the coiled core inside the mold during epoxy filling, which could cause an electrical spark. Micro voids can remain in the resin after filling, and macro voids can occur due to the structure shape. A transformer that is being developed has a cavity at the junction of the core and the coil for better performance, and when highly viscous epoxy flows inside the cavity channel, macro voids can form inside it. Therefore, in this study, the free-surface flow of the mold filling procedure was analyzed numerically by applying the VOF method. The results were used to understand the phenomena of void formation inside the cavity and to modify the process conditions to reduce voids.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.2035_2036
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• 2009

This paper is purpose to understand the dissipation factor properties of the oil-filled large transformer according to the oil filtering. In order to know the insulation characteristic change by insulating oil filtering, we carried out the insulation diagnostic test for the same transformer before oil filtering and after. The insulation diagnosis tests are consist of the megger, the polarization index, the AC current test, the dissipation factor test and the partial discharge test, Especially we took notice of dissipation factor change, we analyzed and made a comparison of the two cases test result.

• Proceedings of the KIEE Conference
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• summer
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• pp.578-580
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• 2004

Substation facilities have become large and complex in the electric power systems. Development of condition monitoring and diagnosis techniques have been very important to improve the security of substation transformers. This paper presents a method to analyze the cause and the degree of aging of power transformers by Self organizing map(SOM). Dissolved gas data were non-linearly transformed by sigmoid function to make determination of SOM close to that of human. Potential of a failure and the degree of aging of a normal transformer are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.1
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• pp.41-46
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• 2016

It has been proven that the dissolved gas analysis (DGA) is the most effective and convenient method to diagnose the transformers. The DGA is a simple, inexpensive, and non intrusive technique. Among the various diagnosis methods, IEC 60599 has been widely used in transformer in service. But this method cannot offer accurate diagnosis for all the faults. This paper proposes a fault diagnosis method of oil-filled power transformers using IEC code based neuro-fuzzy model. The proposed method proceeds two steps. First, IEC 60599 method is applied to diagnosis. If IEC code can't determine the fault type, neuro-fuzzy model is applied to effectively classify the fault type. To demonstrate the validity of the proposed method, experiment is performed and its results are illustrated.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2011.10a
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• pp.69-69
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• 2011

본 논문에서는 유입변압기의 절연진단을 위한 기초연구로 유중 부분방전에 의해 발생하는 전자파의 검출과 분석에 대하여 기술하였다. 유중 방사전자파 측정에는 공진주파수가 1 GHz인 모노폴 안테나를 제작하였다. 절연유 내부에 침-평판 전극계를 설치하고 0~50 kV까지 고전압을 인가시키면서 유중 부분방전의 발생을 모의하였다. 실험결과, 92.3 pC의 부분방전 발생시 1.28 V의 신호가 검출되었다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.96-99
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• 2003

In this paper, ageing diagnostics in the large capacity oil transformer are investigated. Following items are investigated for the ageing diagnostic in transformer oils (leakage current of sensor, power consumption and temperature of transformer oil). All temperature data are gathered from daily report in the substation. The power consumption of transformer are gathered output report of APIS(Airport Power Information System). Especially, data of sensor leakage current are accumulated from the online diagnostic system for transformer oil. The temperature of transformer oils major change factor was ambient temperature and capacity of power load. The leakage current are change by oil temperature. The leakage current ware not more than 2 [nA] in summer,

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.12
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• pp.546-552
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• 2005

In this paper, a present condition with gas-in-oil diagnosis which used to condition analysis for oil insulated transformer is investigated and reason why hydrogen used to basic diagnosis for the transformer is described. This paper gives an overview of background knowledge that should to consider as moisture detecting of oil immersed paper and how could we approach to life expectancy of oil insulated transformer through detecting furfural compound.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.374-376
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• 2001

In this paper, we developed the fault diagnostic expert system of silicone-immersed transformer using dissolved gas analysis. The knowledge base module consists of the knowledge using the rule: if Then . The inference engine uses the fuzzy rule for the management of uncertainty of the boundary and rule and derivate the Belief and Plausibility of the normality and fault using Dempster-Shafer theory. The expert system is connected to the database and it can manages the history of gas-data of the transformer.