I. Introduction
The selection and design of the network model have an essential influence on the effectiveness and efficiency of the transformer fault diagnosis system. We need to conduct extensive research and analysis on the network model. This paper considers the network model’s basic concept, classification, characteristics, advantages, and disadvantages. Considering the characteristics and requirements of the oil chromatographic analysis method, the selection and design of the network model suitable for the transformer fault diagnosis system are discussed. Furthermore, this paper proposes a transformer fault diagnosis method based on deep learning. With deep learning’s feature extraction and classification capabilities, the transformer fault diagnosis is transformed into a multiple classifier problem, and a trained deep neural network model is used to accurately identify the error type.