An adaptive doppler effect reduction algorithm for wayside acoustic defective bearing detector system

Abstract

In the wayside Acoustic Defective Bearing Detector (ADBD) system, because of the high moving speed of the railway vehicle, the recorded acoustic signal will be severely distorted by the Doppler effect, which is a barrier that would badly reduce the effectiveness of online defect detection. This paper proposes an adaptive Doppler effect reduction algorithm for the ADBD system. In this algorithm, firstly, the narrow-band signal is got by the band-pass filter after the sensitive frequency band selection; Secondly, the parameters of the Doppler kinematic model are estimated by maximizing the Pearson’s correlation coefficient between the narrow-band signal and the Doppler atom; Finally, the Doppler-shifted signal is restored by the resampling method. The effectiveness of this method is verified by means of simulation studies and applications to diagnosis of train roller bearing defects.