One of the most important characteristics of rolling bearing fault is that the fault components will induce the shock response of vibration. Aiming at the modulation characteristics of roller bearing fault vibration signals and the complex of traditional analysis method,the paper puts forward a rolling bearing fault feature extraction method based on extreme point probability density and auditory model. The method firstly conduct band-pass filtering with Gammatone filters,phase adjustment and extreme points extraction for signals,and then calculate the amplitude probabilitydensity of extreme points,Judging whether there is a transient impact composition by its derivation in filtered signals,then extractrelated extreme points to get the transient componentsat last. Considering the modulation characteristic of the vibration signal. The amplitude of impact is different over time. Sectional processing of the signal can extract the impact component that may be ignored because the amplitude is small.The method is applied to analysis the vibration signal of a certain type of wire cutting machine ’s rolling bearing. The experimental results show that this method can effectively extract the transient components from the rolling bearing fault signal.