The Study and Analysis of Oil-immersed Power Transformer by Using Artificial Neural Network for Designing Program Apply in the Industry of Testing Oil-immersed Transformers

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dc.contributor.authorBoonsaner, Nutthaphan
dc.contributor.authorChancharoensook, Phop
dc.contributor.authorBunnag, Chisanucha
dc.contributor.authorSuwantaweesuk, Achirawit
dc.contributor.authorVongphanich, Kiattisak
dc.date.accessioned2026-08-06T10:29:58Z
dc.date.available2026-08-06T10:29:58Z
dc.date.issued2020-10-25
dc.description.abstractThis research presents the study and analysis of faults in the oil-immersed transformer. Abnormalities can be analyzed from the Dissolved Gas Analysis (DGA) test. The oil has a variety of compounds such as hydrocarbons, oxygen, nitrogen and hydrogen. The amount of gas in oil has distinctive characteristics that can indicate abnormalities in different types. This program is developed based on according to standard IEEE Std C57.104TM - 2019. This program is designed to detect for defects in oil-immersed transformers by using artificial neural networks (Artificial Neural Network: ANN). The program using MATLAB programs is prepared for maintenance planning and supports applications from basic learning to industrial sector.
dc.identifier.citationProceeding 8th International Conference on Condition Monitoring and Diagnosis Cmd 2020, 274-277, 2020
dc.identifier.doi10.1109/CMD48350.2020.9287230
dc.identifier.other2-s2.0-85108540337
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/11331
dc.sourceProceeding 8th International Conference on Condition Monitoring and Diagnosis Cmd 2020
dc.subjectDGA
dc.subjectDoernenburg ratio
dc.subjectDuval Triangle and App designers
dc.subjectGUI
dc.subjectMatlab
dc.subjectNeural network
dc.subjectRoger ratio
dc.titleThe Study and Analysis of Oil-immersed Power Transformer by Using Artificial Neural Network for Designing Program Apply in the Industry of Testing Oil-immersed Transformers
dc.typeConference Paper

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