Ternary Binary Fractal Wavelet Sparse Diagnosis Method for Rolling Bearing Faults

Abstract

A ternary binary fractal wavelet sparse diagnosis method for rolling bearing faults relates to a mechanical fault diagnosis method. The multi-scale iterative decomposition of the vibration acceleration signal is carried out by using the finite impulse response filter bank, and 3·2 J‑1 wavelet subspace. The response function of each subspace is tested by the unit impulse function, and the wavelet subspaces are reordered by calculating the center of gravity of the spectrum energy of the response function. At each scale, the transitional subspace is constructed by adding the adjacent subspaces of the non-endpoints, so that the new ternary binary fractal wavelet "frequency-scale" grid is realized. In order to carry out self-adaptive and quantitative identification of the potential periodic impact fault characteristics in each subspace, an evaluation index of periodic sparsity is proposed, which is used to calculate the frequency multiplier energy of each characteristic frequency on the signal envelope demodulation amplitude spectrum of the subspace to the total energy of the signal proportion. The characteristic frequency corresponding to the maximum value of the periodic sparse characteristic index can determine the type and location of the fault.

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...

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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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