A new method of wayside acoustic fault diagnosis for locomotive bearings is presented in this paper. In this method, firstly, time-domain Doppler effect correction is implemented for the bearing’s acoustic signal recorded by the wayside microphone. Such problems as frequency shift, frequency band expansion and amplitude modulation can be solved through this correction. Secondly, the Ensemble empirical mode decomposition (EEMD) method is applied to extract the Intrinsic Mode Functions (IMFs) which contains the fault signature of the bearings. Finally the envelope spectrum of the selected IMF is calculated to decide whether the bearing is defective. This method is applied to the feature extraction for a locomotive bearing with a single defect on the outer race and inner race, respectively. The results show that the proposed method can reduce the Doppler effect embedded in the bearing’s acoustic signal and can extract the fault signature of the locomotive bearings.