Radial basis function neural network is a type of three-layer feedforward non-linear network. It has many good properties

such as powerful ability for function approximation

classification. In this paper

in the light of the merit of radial basis function neural network and on the basis of the feature analysis of vibration signal of rolling bearing

AR model is presented by using time series method. Radial basis function neural networks is established based on AR model parameter. In the light of the theory of radial basis function neural networks

fault pattern of rolling bearing is recognized correspondingly. Theory and experiment shows that the recognition of fault pattern of rolling bearing based on AR model and radial basis function neural networks theory is available and its precision is high.