%0 Electronic Article
%A Wei Wang
%A Lin Yan
%A Tao Jin
%A Hong Liu
%A Fan Hu
%A Dongxun Wu
%K real-time identification system
%K stability
%K neural network
%K operation state
%K power system
%K feature vectors
%K power transformer
%K wavelet packet reconstruction coefficients
%K recognition method
%K fault current signal
%K security
%K inrush current method
%X The transformer is an important equipment of power system; its operation state is directly related to the security and stability of the power system. Aiming at the problem that the differential protection of power transformer has been plagued by inrush current, a recognition method based on wavelet packet and the neural network is proposed. The inrush current and fault current signal are decomposed and reconstructed by using wavelet packet to extract wavelet packet reconstruction coefficients and calculate the energy of each band. These feature vectors are chosen as input values for the neural network. It has been shown by experiments that the inrush current and internal fault current can be accurately identified and the identification method can meet the requirement of the transformer inrush current real-time identification system.
%T Inrush current method of transformer based on wavelet packet and neural network
%B The Journal of Engineering
%D October 2018
%I Institution of Engineering and Technology
%U https://digital-library.theiet.org/;jsessionid=g6vlyza05zam.x-iet-live-01content/journals/10.1049/joe.2018.8847
%G EN