Frequency slice wavelet transform (FSWT) is a new time-frequency analysis method，and the noise in the signal will reduce frequency resolution of the FSWT. In order to improve the accuracy of analysis，a method based on morphological filtering and delayed autocorrelation analysis was proposed and applied to the bearing fault diagnosis successfully. In this method，a multi-structure element difference morphological filtering and time-delayed autocorrelation method was used to reduce the noise，and the bearing vibration signal was decomposed by applying frequency slice wavelet transform，and then time and frequency slice interval was selected for detailed analysis according to the bearing fault characteristic frequency to extract fault characteristics. Simulation signal and bearing fault diagnosis analysis of examples demonstrate the effectiveness of the method.