When the mechanical equipment is running,its vibration signal is often shown as non-stationary signal.When the traditional time-frequency analysis method is used to deal with the non-stationary signals with strong noise and strong modulation,it often shows some defects such as not obvious noise reduction effect and not accurate extraction of fault characteristic frequency.Therefor,a mechanical equipment fault diagnosis method based on multivariate variable mode decomposition was proposed.By establishing the constrained variational model expression,multiple signals were decomposed into the sum of the same number of inherent mode functions (IMF) at the same frequency scale,and each IMF was an FM/AM signal.In order to verify the effectiveness of the proposed method,the proposed method was applied to the analysis of bearing fault signals collected by multiple sensors.The results show that by using the proposed method,the noise of mechanical equipment vibration signals in complex environment can be effectively reduced and a better effect of fault feature extraction can be obtained,which verifies its reliability.