Ternary binary fractal wavelet sparse diagnosis method for rolling bearing fault

Abstract

The invention discloses a ternary binary fractal wavelet sparse diagnosis method for rolling bearing faults, and relates to a mechanical fault diagnosis method. The method comprises: carrying out multi-scale iterative decomposition on the vibration acceleration signal by adopting a finite impulse response filter bank to obtain 3.2J-1 wavelet subspaces; and testing the response function of each subspace through the unit pulse function, and reordering each wavelet subspace by calculating the frequency spectrum energy center of gravity of the response function. On each scale, a transition subspace is constructed by adding non-endpoint adjacent subspaces, so that a new ternary binary fractal wavelet frequency-scale division grid is realized. In order to carry out self-adaptive quantitative identification on potential periodic impact fault characteristics in each subspace, a periodic sparsity evaluation index is provided and is used for calculating the specific gravity of characteristic frequency multiplication energy in the signal envelope demodulation amplitude spectrum of each subspace in the total energy of the signal. And the type and the position of the fault can be determined according to the characteristic frequency corresponding to the maximum value of the periodic sparse characteristic index.

Description

technical field [0001] The invention relates to a mechanical fault diagnosis method, in particular to a ternary method for rolling bearing faults that extracts periodic fault characteristic components from bearing vibration acceleration signals, quantitatively calculates the energy ratio of the fault components in the signal, and automatically determines the fault type. Binary fractal wavelet sparse diagnostic methods. Background technique [0002] Rolling bearings are essential mechanical parts in complex electromechanical equipment, carrying most of the energy of the mechanical transmission system. Due to the long-term operation of rolling bearings in high-temperature, alternating heavy-load, and highly corrosive working environments, it is easy to induce fatigue failure of its components and further cause failures. In the early stage of fatigue failure, the metal surface of the parts will peel off and corrode, and the periodic transient impact component will be generated...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a ternary binary fractal wavelet sparse diagnosis method for rolling bearing faults for feature extraction and fault type automatic identification of rolling bearing faults

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