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- W4309263311 abstract "Dissolved gas analysis (DGA) is the most common method used to diagnose faults in thermal power plant transformers by monitoring the concentration of various gas in transformer oil and using it to interpret the type of fault. In this study, neural networks using SGD and Adam optimizers are proposed to classify and predict electrical faults based on DGA analysis data due to the complicated interpretation of the data. Those data are obtained from IEC TC 10 databases combined with the data from a Jakarta Government's Steam Power Plant. The network designed produced a reliable fault detector for power transformer condition diagnosis." @default.
- W4309263311 created "2022-11-25" @default.
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- W4309263311 date "2022-10-06" @default.
- W4309263311 modified "2023-09-29" @default.
- W4309263311 title "Deep Learning Neural Networks Diagnosis of Power Transformer through Its DGA Data" @default.
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- W4309263311 doi "https://doi.org/10.23919/eecsi56542.2022.9946518" @default.
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