Given the existing signal denoising or reconstruction methods can not completely remove the noise, and the time-frequency representation has the problem of energy ambiguity, a method for rolling bearing fault diagnosis based on element analysis was proposed. Firstly, the proposed method constructs an elemental model to characterize the signal, then the Morse wavelet transform is applied to the elemental model and the impact point of the signal is calculated from the wavelet transform to obtain the characteristic defect frequency of the signal. Based on a small number of solitary points in the time or scale plane of the wavelet transform, the method is used to reconstruct the signal. In this paper, a set of simulated signal data and two sets of experimental data are used to estimate the performance of the method and compare it with other signal reconstruction methods and time-frequency analysis methods. The results demonstrate that the proposed method has a good performance in the identification and reconstruction of rolling bearing fault signals.