The application of neural networks to the analysis of dissolved gases in insulating oil used in transformers

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. The article concentrates 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 of determining 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 comprising multiple layers. After the process of network training, it is possible to determine the existing relationship between the physical chemical tests and the amount of gases present in the insulating oil