The study of variant DGA feature neural network multilayer diagnostic model

Selecting appropriate features has vital effect on the effectiveness of fault diagnosis, and DGA is widely used in transformer fault diagnosis, so this paper, using ANN as method and 5 gas concentrations as available features, studies the the key feature gases according to fault types, and their roles in fault diagnosis. Based on this, this paper provides the variant feature neural network multilayer diagnosis model.