In this paper, the feature vectors of the roller bearing signals are extracted on the basis of wavelet analysis and a fault diagnosis experiment is carried through wavelet neural network in detail. The method and the theory of fault diagnosis based on BP neural network and the radial basis function neural network are studied and the results of diagnosis based on relax-type neural - networks and close-type neural-networks are compared.Simulation results indicate that diagnosis based on close-type networks more effective.