Development of Dissolved Gas Analysis Analyzing Program using Visual Studio Program

Taecharoen, Punnita; Kunagonniyomrattana, Pechet; Chotigo, S.

doi:10.1109/gtdasia.2019.8715892

Cited by 5 publications

(1 citation statement)

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“…Generally, conventional diagnostic methods using dissolved gases can be divided into three main categories: key gas, graphical and gas ratio methods [8]. The key gas method is based on the correlation of key gases generated with the fault type.…”

Section: Introductionmentioning

confidence: 99%

Interpreting dissolved gases in transformer oil: A new method based on the analysis of labelled fault data

Nanfak

Eke

Kom

et al. 2021

IET Generation Trans & Dist

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In this contribution, a new dissolved gas analysis (DGA) method combining key gases and ratio approaches for power transformer fault diagnostic is presented. It is based on studying subsets and uses the five main hydrocarbon gases including hydrogen (H 2 ), methane (CH 4 ), ethane (C 2 H 6 ), ethylene (C 2 H 4 ), and acetylene (C 2 H 2 ). The proposed method uses 475 samples from the dataset divided into subsets formed from the maximum and minimum(s) concentrations of the whole dataset. It has been tested on 117 DGA sample data and validated on the International Electrotechnical Commission (IEC) TC10 database. The performance of the proposed diagnostic method was evaluated and compared with the following diagnostic methods: IEC ratios method, Duval's triangle (DT), three ratios technique (TRT), Gouda's triangle (GT), and self-organizing map (SOM) clusters. The results found were analysed by computer simulations using MATLAB software. The proposed method has a diagnosis accuracy of 97.42% for fault types, as compared to 93.16% of TRT, 96.58% of GT method, 97.25% of SOM clusters method and 98.29% of DT method. However, in terms of fault severity, the proposed method has a diagnostic accuracy of 90.59% as compared to 78.90% of SOM clusters method, 83.76% of TRT, 88.03% of DT method, and 89.74% of GT method.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%