关键词: 神经网络, BP算法, 动态隧道技术, 电力变压器, 油中溶解气体分析, 故障诊断

Abstract: Dissolved Gas-in-oil Analysis （DGA） plays an important role in fault diagnosis of power transformers.BP （Back Propagation） algorithm is used to classify for insulation fault diagnosis in this paper.But typical BP algorithm has some defects，such as converging slowly and immersing in local vibration frequently.The algorithm using dynamic tunneling technique to train BP Neural Networks has been proved to have good performances in avoiding the local trap.So this paper adopts BP artificial neural network with dynamic tunneling technique in fault diagnosis of power transformers. A mass of fault samples are analyzed in the algorithm and the results are compared with those obtained by the traditional BPNN.The comparison result indicates that the algorithm using the dynamical tunneling technique has better classifying capability for single-fault samples as well as high diagnosis precision.

Key words: neural network, BP algorithm, dynamic tunneling technique, power transformer, Dissolved Gas-in-oil Analysis（DGA）, fault diagnosis