Rolling bearing fault diagnosis method based on adaptive termination criterion OMP

Abstract

The invention discloses a rolling bearing fault diagnosis method based on an adaptive termination criterion OMP, and the method comprises the steps of calculating the theoretical fault characteristic frequency of a diagnosed bearing through combining the geometric parameters and rotating speed of the diagnosed bearing; analyzing the frequency spectrum of the fault signal, and observing the approximate interval of the high-frequency natural vibration frequency of the bearing; setting a Laplace wavelet parameter set of the initial dictionary; obtaining wavelet frequency and damping which are most matched with fault impact components in the fault signals through a correlation filtering method, and building a needed complete dictionary; using an adaptive termination criterion OMP algorithm to decompose the fault signal, searching the optimal algorithm iteration frequency, and rebuilding a fault impact component in the signal; and analyzing the envelope spectrum of the reconstructed signal, and extracting the fault characteristic frequency in the spectrum to complete fault mode diagnosis. According to the invention, the fault impact component can be reconstructed from the fault signal more accurately, the fault characteristic frequency is extracted, and fault diagnosis of the rolling bearing is realized.

Description

technical field [0001] The invention relates to the technical field of mechanical equipment fault diagnosis, in particular to a rolling bearing fault diagnosis method based on an adaptive termination criterion OMP. Background technique [0002] As a key part of rotating machinery, rolling bearings often work in harsh environments with high temperature, high speed, and heavy loads, so they are prone to failure. Once the rolling bearing fails, it will cause the equipment to be shut down for maintenance, and it will cause a major disaster. Therefore, the condition monitoring and fault diagnosis of rolling bearings in mechanical equipment have great engineering value. Bearing vibration signals can reflect the dynamic characteristics of faulty bearings in time and are very sensitive to bearing faults, so they are widely used in bearing fault diagnosis. When the rolling bearing at a constant speed fails, the local defects on the bearing surface and the periodic impact of the int...

AI Technical Summary

Problems solved by technology

However, in the application and research of the MP algorithm, it is found that the MP algorithm is very dependent on the setting of the iteration termination criterion, and the inaccurate termination criterion will lead to incomplete decomposition of the impact components in the signal and the decomposition of interference noise, which will affect the reconstruction results.

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