Aiming at the problem that the rolling bearing fault under strong noise is weak and the characteristic frequency is difficult to extract, which makes it impossible to diagnose the fault accurately, a fault diagnosis method based on trisection EMD fusion Autogram threshold algorithm is proposed. EMD is used to reduce the noise of the signal, and a trisection method based on M index is proposed. EMD reconstructs all IMF into three components (Write M1, M2, M3), and M2 is the required fault component; The Autogram algorithm is used to process the M2 component to determine the resonance frequency band, and the resonance signal is processed by the threshold envelope spectrum to obtain three threshold spectra. The fault type of rolling bearing is diagnosed according to the fault characteristic frequency in the threshold spectrum. In this paper, the simulation signals and the measured data of the inner and outer rings of rolling bearings are used to prove the effectiveness of this method. Experimental results show that the fault diagnosis rate of this method is over 95%