Separation Method of Trackside Acoustic Signals of Train Wheelset Bearings Based on Harmonic-Shock Doppler Modulation Composite Dictionary

Abstract

The invention discloses a method for separating rail-side acoustic signals of train wheel-set bearings based on a harmonic-shock Doppler modulation dictionary. Microphones installed on both sides of the rail and facing the train wheel-set bearings are used to collect the sound signals emitted by trains passing at high speed. The sound signal x(t) of the detection signal is processed as follows: (1) Construct an over-complete parameterized Doppler modulated complex harmonic-impact compound dictionary Datom3; (2) Use the matching pursuit algorithm to convert the track edge signal x (t) Sparse decomposition is performed in the constructed over-complete complex complex dictionary Datom3 to obtain the projection dictionary Datom4 and the projection coefficient K; (3) According to the bearing resonance frequency band and the geometric position relationship between the microphone and the wheel set bearing, the dictionary Datom4 is selected to meet the requirements The atoms form the dictionary Datom5 and perform linear combination to obtain the reconstructed fault signal sig. The invention realizes better time-frequency structure matching with the fault signal, achieves better sparse representation and signal reconstruction, and improves the sound source separation effect.

Description

technical field [0001] The present invention relates to the technical field of railside acoustic fault diagnosis of high-speed train wheelset bearings, in particular to a method for separating railside acoustic signals of train wheelset bearings based on a harmonic-shock Doppler modulation composite dictionary, which is used for separating trackside signals from the trackside signals The fault signal of the wheel set bearing is separated to eliminate noise and improve the accuracy of fault diagnosis. Background technique [0002] When the train is running at high speed, the sound signal from the wheel set bearing contains information closely related to its health status, and the trackside acoustic fault diagnosis has the characteristics of non-contact monitoring. However, trackside signals are mixed with sound signals from other parts of the train, wheel-rail contact sound and aerodynamic noise, etc., which brings difficulties to effective fault diagnosis. A common denoisin...

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved in the present invention is: to overcome the deficiencies of existing technologies and methods, to provide a method for separating acoustic signals of train wheel-set bearing rails based on harmonic-shock Doppler modulation compound dictionary, which has the ability to eliminate in-band noise and It overcomes the problem that single dictionary atoms cannot achieve optimal matching of signal components, and effectively improves the denoising effect and the accuracy of fault diagnosis

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