Aiming at the problem that the reliability of the diagnosis results of power transformer is not ideal when the gas content in oil is used as the fault characteristic,a transformer neural network fault diagnosis method based on modified PSO-BP algorithm is proposed.The initial particle search range of PSO-BP algorithm is modified to improve the conver-gence accuracy and stability of the algorithm.The transformer gas dissolution analysis(DGA)data is taken as input,and the improved PSO-BP algorithm is used to train the neural network.The diagnosis results are compared with those of the conventional PSO-BP fault diagnosis neural network,whose results show that the modified PSO-BP algorithm achieves improved accuracy of transformer fault diagnosis.
transformerdissolved gas analysisfault diagnosisneural networkparticle swarm optimization
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