Traditional BP neural network is a typical mehtod to solve ECT system of flow pattern identification.It is applied to the simple problems in industrial applications，but there are many defects in solving complexindustrial problems. In this paper based on the analysis of deficiency of BP neural network，for reducing the erroroscillation，the adaptive learning rate adjustment factor and the additional momentum is introduced. In this method，the electrical capacitance values are input to train a network to identify the flow patterns. The simulation resultsshow the algorithm not only inherits the advantages of traditional BP neural network，but also improve slowconvergence and solve being prone to fall into local minimum problems in flow pattern identification of ECT system