According to the problem of noise interference in the mechanical equipment fault signal acquisition,a novel mechanical equipment fault diagnosis method of wavelet shrinkage threshold based on Bayesian estimation combined with EMD is proposed. The fault signal denoising characteristics of different scales are considered in proposed method. The new threshold is suitable for the situation of noise distribution. The noise reduction can be gotten by improving the threshold function. The signal components decomposed and denoised by EMD is extracted with cross- correlation and kurtosis criterion to highlight the high- frequency resonance components,the blindness of IMF component selection is avoided. The results of analysis applied to simulated signal and the measured signal show that the equipment fault can be detected accurately.