Rolling bearing fault diagnosis method based on VMD-FRFT (Variational Mode Decomposition-Fractional Fourier Transform)

Abstract

The invention discloses a rolling bearing fault diagnosis method based on VMD-FRFT (Variational Mode Decomposition-Fractional Fourier Transform), and relates to the technical field of the fault diagnosis method of a bearing. The method comprises the following steps that: extracting the vibration signal of a rolling bearing, and processing the vibration signal to obtain a multi-component LMF (Linear Frequency Modulation) vibration signal; carrying out VMD-FRFT on the multi-component LMF vibration signal to obtain the modal component of the vibration signal; according to the obtained modal component of the vibration signal, reconstructing the vibration signal; and carrying out wavelet transform on the reconstructed vibration signal to obtain an instantaneous frequency conversion curve, and according to the instantaneous frequency conversion curve, obtaining the fault information of the rolling bearing. The method which is put forward is successfully applied to rolling bearing inner ringfault data analysis, instantaneous fault characteristic frequency can be accurately extracted, and noise robustness is high.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis methods for rolling bearings, in particular to a rolling bearing fault diagnosis method based on fractional variational mode decomposition. Background technique [0002] Bearing is one of the core components of a locomotive. It has the characteristics of complex structure, high speed, and heavy load. It is a typical nonlinear system. There are various types of bearing faults, and they are prone to damage. According to statistics, 40% of the used locomotive bearings are tested every year, and 33% of the bearings need to be replaced. And any small failure of locomotive bearings may bring huge losses to the country and the people. In engineering practice, most of them use the analysis of bearing vibration signals for fault diagnosis. However, the vibration signals collected by sensors will be accompanied by a large number of interference signals, making the signals weak and unstable. Theref...

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Problems solved by technology

In the prior art, there is also an algorithm (EMD-FRFT) combining EMD and fractional Fourier transform (EMD-FRFT) to suppress high-power interference in tracking radar signals, which has achieved certain results, but the filtering effect is not good when the interference frequency is high. Obviously; an integrated empirical mode decomposition algorithm (EEMD-FRFT) based on fractional Fourier transform is also proposed in the prior art to detect and estimate parameters of multi-component chirp signals, but due to the integrated empirical mode decomposition Due to the limitations of the algorithm, the mode mixing problem has not been well solved

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