Abstract:Aiming at the problem of low accuracy of current-lossing identification in main network by traditional methods, an intelligent identification method of current-lossing based on Back Propagation (BP) neural network is proposed. In this paper, make use of back-propagation neural network algorithm, through the mode of gradient descent to reverse the weights of each layer, the network output error is acceptable, and it has good self-learning ability for fault identification of current-lossing. According to the research of current-lossing fault in this paper, firstly construct indicators of continuous current-lossing and discontinuous current-lossing, build up the fault feature extraction system based on all indicators, finally BP network is established to fit current-lossing extraction system, Identify the data, then Set up the expert samples, and train BP neural network off-line, fix weight value after training. Through the test by example, this model is superior to the general classification model and has high discrimination of current-lossing fault recognition. It can provide a forceful basis for solving the problem.