Iodine Aiming at the fault diagnosis of rolling element bearings, propose a method for fine diagnosis of bearings based on wavelet transform and one-dimensional convolutional neural network.First use wavelet transform to decompose the experimental data; Use the resulting low-frequency signal as a one-dimensional convolutional neural network input, bearing fault identification.The experiment uses the deep groove ball bearing of Case Vitamin A Western Reserve University as the research object, Use this method to identify the normal and outer ring faults of the bearing.the result shows: This method can be effectively applied to the precise identification of bearings.