In a wayside acoustic defective bearing detector system, bearing faults are detected through the analysis of the acoustic signal generated by the bearings of a passing vehicle. As vehicles pass by with high speeds, the acoustic signal recorded by the stationary microphone is disturbed by the Doppler effect. The reduction of the frequential structure disturbance of signals facilitates the efficient diagnosis of bearing faults. This study proposes a Doppler effect reduction scheme for the removal of the frequential structure disturbances of Doppler-shifted signals in the acoustic defective bearing detector system. First, the parameters, including the initial speed and the initial acceleration of the vehicle, are estimated by the acceleration-based Dopplerlet transform via the matching pursuit algorithm. Second, the time vector for resampling is calculated according to the estimated initial speed, the initial acceleration in the first step, the sound speed, and the measured geometric parameters of the ADBD system. Finally, the distorted signal is resampled through spline interpolation. Simulation and experimental cases are used to validate the effectiveness of the proposed scheme. Compared with the steady-motion-based method, the proposed scheme can better capture the true time-varying nature of Doppler-shifted signals. Moreover, this scheme is also robust to noise.