The application of neural networks to the analysis of dissolved gases in insulating oil used in transformers
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Data
2000-01-01
Autores
da Silva, I. N. [UNESP]
Imamura, M. M. [UNESP]
de Souza, A. N. [UNESP]
Título da Revista
ISSN da Revista
Título de Volume
Editor
Institute of Electrical and Electronics Engineers (IEEE)
Resumo
The state of insulating oils used in transformers is determined through the accomplishment of physical-chemical tests, which determine the state of the oil, as well as the chromatography test, which determines possible faults in the equipment. This article concentrate on determining, from a new methodology, a relationship among the variation of the indices obtained from the physical-chemical tests with those indices supplied by the chromatography tests.The determination of the relationship among the tests is accomplished through the application of neural networks. From the data obtained by physical-chemical tests, the network is capable to determine the relationship among the concentration of the main gases present in a certain sample, which were detected by the chromatography tests.More specifically, the proposed approach uses neural networks of perceptron type constituted of multiple layers. After the process of network training, it is possible to determine the existent relationship between the physical-chemical tests and the amount of gases present in the insulating oil.
Descrição
Palavras-chave
Chromatographic analysis, Computer simulation, Insulating oil, Oil filled transformers, Dissolved gas analysis, Neural networks
Como citar
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, v. 4, p. 2643-2648.