• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제53권10호
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• pp.523-529
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• 2004

Faults of cellulosic insulations greatly affect the life span of oil immersed transformers because their performance recovery is impossible. Therefore, the reliable diagnosis technologies are needed for detection of the faults. Dissolved gas analysis technologies using CO and $CO_2$ gases have been widely used for fault diagnosis of cellulosic insulations. In this research, we described Degradation diagnosis of insulation paper CO and $CO_2$ gases in oil immersed Transformers using. We considered the distribution characteristics of CO, $CO_2$ gases' concentrations and ratios of $CO_2$/CO not only in serviced transformers but in experiments with typical fault causes such as heat, partial discharge and moisture. As result, the reliability of diagnosis results for the cellulosic insulations can be improved when the concentrations of CO, $CO_2$ and the ratio of CO/$CO_2$ satisfy each diagnosis criterion at a tim

• 전기학회논문지P
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• 제60권3호
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• pp.114-119
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• 2011

Large Power transformer is a complex and critical component of power plant and consists of cellulosic paper, insulation oil, core, coil etc. Insulation materials of transformer and related equipment break down to liberate dissolved gas due to corona, partial discharge, pyrolysis or thermal decomposition. The dissolved gas kinds can be related to the type of electrical faults, and the rate of gas generation can indicate the severity of the fault. The identities of gases being generated are using very useful to decide the condition of transformation status. Therefore dissolved gas analysis is one of the best condition monitoring methods for power transformer. Also, on-line multi-gas analyzer has been developed and installed to monitor the condition of critical transformers. Rogers method, IEC method, key gas method and Duval Triangle method are used to failure diagnosis typically, and those methods are using the ratio or kinds of dissolved gas to evaluate the condition of transformer. This paper analyzes the reliability of transformer diagnostic methods considering actual dissolved gas concentration. Fault diagnosis is performed based on the dissolved gas of five transformers which experienced various fault respectively in the field, and the diagnosis result is compared with the actual off-line fault analysis. In this comparison result, Diagnostic methods using dissolved gas ratio like Rogers method, IEC method are sometimes fall outside the ratio code and no diagnosis but Duval triangle method and Key gas method is correct comparatively.

• 조명전기설비학회논문지
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• 제21권9호
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• pp.87-94
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• 2007

This paper presents new criteria for DGA(Dissolved Gases Analysis) using CDF(Cumulative Distribution Function) obtained from the data from the diagnosis of transformers operated in KEPCO over a period of 16 years. Because of differences in operating environments, construction type, oil volume, and other factors, the interpretative criteria of DGA at KEPCO differs from other standards such as IEC-60599, or Rogers and Doernenburg. To suggest the most appropriate criteria, the DGA data from transformers under normal conditions as well as from developing fault transformers were collected. Using these data, this study suggests the limitative gas level of transformers under normal operating conditions and verifies the suitability of the criteria. Because the application of this new criterion to transformers at KEPCO increases the detectable ratio of incipient faults and reduces unnecessary follow-up sampling and analysis, the new criteria yields a more reliable prediction of transformer condition.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 추계학술대회 논문집
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• pp.275-278
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• 2007

Dissolved gases analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. Criteria interpreting DGA result is the most important. Because of difference of operation environment, construction type, oil volume, and etc, the interpretative criteria of DGA at KEPCO must be different with other standard like IEC-60599, Rogers and Doernenburg. In this paper, we collected the DGA data of the normal condition transformers and the incipient fault transformer to suggest the most appropriate criteria. Using these data, this paper suggests appropriate condition classification algorithm. Suggested algorithm can help to detect incipient fault earlier without unnecessary sampling.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.95-96
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• 2007

Dissolved gas analysis (DGA) is one of the most widely used diagnostic tools for detecting and evaluating faults in electrical equipment. However, interpretation of DGA results is often complex and should always be done with care, involving experienced insulation maintenance personnel. KEPCO (Korea Electric Power Cooperation) has been using DGA technique since KEPCO established the criteria of DGA in 1985. In this paper, we introduce the DGA criteria of KEPCO and analyze the result of DGA. Also we sort pattern in result of DGA. Then, relation between pattern and inner inspection was studied. 67 DGA data was used for analyzing pattern. Some patterns have something to do with cause of incipient fault.

• 한국안전학회지
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• 제38권6호
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• pp.1-8
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• 2023

The health state of the oil transformer is evaluated by the age of use and the state of internal defects. Mineral Oil, used as an insulator for oil transformers, creates specific gases and compounds through chemical reactions caused by heat, moisture, and partial discharge inside the transformer. It is possible to determine the aging and defect of the transformer through these gases and compounds. So, it is an important indicator to evaluate the health of a transformer. In this study, factors for assessing the health of transformers were hierarchically categorized, and key factors for each hierarchy were selected for design weighting. These weights were determined through surveys conducted with experts in the fields of transformer design, operation, and quality. For the health of a transformer, defect-related factors are approximately three times more important than factors related to aging. Additionally, defect-related factors showed a higher weighting for gases generated at high temperatures. Furthermore, Furan was determined to have a high weight, directly associated with insulating paper aging. Based on these findings, a health index was proposed, and a comparative analysis was conducted by categorizing 40 operational transformers into normal and comparison groups to evaluate and validate it.

• 한국해양학회지:바다
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• 제27권3호
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• pp.144-157
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• 2022

비활성기체는 화학적, 생물학적 반응을 하지 않는 보존적인 특성을 가지고 있어 해양에서 수온과 염분 변화, 기체 주입, 해수의 혼합과 빙하 융해수의 분포와 같은 물리적인 변화의 추적자로 활용되고 있다. Ne, Ar과 Kr을 정밀하게 분석하기 위해 사중극자 질량 분석기, 고진공 전처리 라인, 초저온 냉각 트랩과 동위원소 표준기체로 구성된 분석 시스템을 제작했다. 고진공 라인은 시료의 용존 기체를 추출하여 동위원소 표준기체와 혼합하는 시료추출부, 합금 물질을 이용하여 반응성 기체를 제거하고 초저온 냉각 트랩으로 비활성기체를 기화점에 따라 분별 증류하는 기체 준비부, 비활성기체를 원소별로 측정하는 기체 측정부로 구성하였다. 기체준비부에 결합한 초저온 냉각 트랩은 질량분석기 내 Ar와 CO₂의 부분압을 현저히 낮추어 Ne 동위원소 분석의 오차를 감소시켰다. 동위원소 표준기체는 ²²Ne, ³⁶Ar과 ⁸⁶Kr를 혼합하여 제작하였고, 혼합 표준 기체의 원소별 양은 대기를 반복 측정하여 역동위원소 희석법으로 결정했다. 대기 평형수 반복 분석의 상대 오차는 Ne, Ar과 Kr에 대해 각각 0.7%, 0.7%, 0.4%이었다. 반복 측정한 대기 평형수의 농도와 포화 농도의 차이로 확인한 분석시스템의 정확도는 Ne, Ar, Kr에 대해 각각 0.5%, 1.0%, 1.7%이었다.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.830-839
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• 2017

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

• 조명전기설비학회논문지
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• 제13권3호
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• pp.56-63
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• 1999

전력계통의 변전소 설비들은 계통의 확장에 따라 점점 복잡하고 거대해지고 있다. 또한, 몇몇 장비들은 점점 노후되고, 종종 예상치 않은 고장을 일으킨다. 변전소 설비들 중 변압기의 신뢰도를 증가시키기 위해서, 변압기의 진단기법 개발이 매우 필요하다. 본 연구에서는, 전력용 변압기의 용해 가스들을 근거로 KSOM(Kohonen Self Organizing Map)에 의한 열화정도와 원인의 분석기법을 개발하였다. KOSM은 용해가스에 의해 구성된 다차원 패텅을 이차원 평면에 지형학적 맵핑이 가능하다. 그리고 정장변압기에 대한 열화의 정도와 잠재적인 열화의 가능성을 제안된 정량적 지표에 의해 제시하였다. 아울러, 변압기의 열화과정을 제안된 지표를 근거로 특정한 변압기에 대해 분석하였다. 제안된 방법의 타당성을 입증하기 위해서 사례연구가 수행되고, 그 결과를 제시하였다.

• 전기학회논문지
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• 제59권5호
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• pp.912-917
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• 2010

It was known that oil-filled transformer's life depended on insulating paper which was applied to transformers for insulating of transformer. Therefore when paper was aged, its electrical, mechanical and chemical characteristics were changed. Especially if operating temperature was high, paper was quickly damaged. As cellulose paper which was mainly used for solid insulation of transformers was degraded, the cellulose polymer chains broke down into shorter lengths and gases such as CO, $CO_2$, $CH_4$, $C_2H_4$ and so on were produced from paper. Also by-product known as furan compounds were producted from paper and it were dissolved within insulating oil. In this paper accelerating aging cell was aged during 60 hours at 100, 150, 180 and $200^{\circ}C$, respectively, so evaluating the chemical characteristics of cellulose paper by thermal. An it were performed analysis such as tensile strength(TS), dissolved gas analysis(DGA) and high performance liquid chromatography(HPLC). Also for analyzing of correlation between insulating degradation characteristics, it was performed linear regression method as statistical treatment.