Considering the early fault feature information of rolling bearings is difficult to identify,and form the frequency bands after wavelet packet decomposition can not be effectively determined and adaptive to extract the resonance band,the concept of amplitude entropy of frequency band is proposed.On this basis,the wavelet packet transform and Teager energy spectrum was combined,a rolling bearing early fault feature extraction method is proposed based on wavelet packet transform adaptive Teager energy spectrum.Firstly,the vibration signal was decomposed by wavelet packet,and the frequency amplitude entropy of each subband was calculated.Then,on the basis of kurtosis index to determine the best entropy and the optimal decomposition level of wavelet packet,thus,the resonance band was extracted adaptively and effectively.Finally,the Teager energy spectrum analysis was performed to identify the frequency of the bearing fault.Through the signal simulation and experimental data analysis it verifies the effectiveness of the proposed method.