Abstract:

Existing train bearing trackside acoustic diagnosis methods mostly focus on doppler effect removal and spatial filter optimization, while ignoring the impact noise and cyclostationary noise in the trackside environment. To address this problem, a trackside acoustic diagnosis method combining beamforming and target band selection for train axlebox is proposed in this study. The proposed method acquires train bearing array acoustic signals by microphone array, corrects the signal distortion by time domain interpolation resampling method, extracts the target bearing direction signal using beamforming spatial domain filter, selects the optimal demodulation band and extracts the band-pass signal using ICS2gram, and the envelope analysis of the band-pass signal is carried out to realize bearing diagnosis. The experimental results show that the proposed method can effectively avoid the influence of impact noise and cyclostationary noise in the trackside sound field environment, accurately extract the target bearing signals and diagnose the bearing faults, showing better effect when compared with the existing methods.

Key words: bearing fault diagnosis, acoustic diagnosis, optimal frequency band selection, beam forming, track side diagnosis, cyclostationary, envelope analysis, Doppler effect