Bearing fault detection method and system

Abstract

The invention relates to a bearing fault detection method and system. The method includes the following steps that: original vibration signals are collected, the original vibration signals are calculated with a particle swarm algorithm, so that decomposition parameters can be obtained; the decomposition parameters are optimized, so that parameter combination information can be obtained, and the original vibration signals are decomposed into mode decomposition information according to the parameter combination information; coupled input signals in the mode decomposition information are extracted; and a bistable stochastic resonance system is optimized with the particle swarm algorithm, and stochastic resonance processing is performed on the coupled input signals, so that fault characteristic signals can be obtained. With the bearing fault detection method and system of the invention adopted, the technical problems of poor signal processing effect and low detection precision of weak fault signals in the prior art can be solved.

Description

technical field [0001] The invention relates to a mechanical fault signal detection method, in particular to a bearing fault detection method and system. Background technique [0002] The stochastic resonance signal enhancement method uses the nonlinear vibration theory to convert the random noise energy in the signal into the energy of a specific signal, so as to achieve the purpose of enhancing the signal strength and performing effective detection. [0003] Variational mode decomposition is an adaptive signal decomposition method based on the three concepts of classical Wiener filtering, Hilbert transform and frequency mixing. Compared with the recursive 'screening' mode of the empirical mode decomposition algorithm and local mean decomposition, the variable mode decomposition algorithm transforms the signal decomposition into a non-recursive and variational decomposition mode, which is essentially multiple adaptive Wiener filter banks. Unlike empirical mode decompositio...

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Problems solved by technology

However, the variable mode decomposition algorithm needs to set the parameters of the variable mode decomposition in advance when processing the signal, and the simple use of the mode decomposition algorithm cannot accurately extract the weak fault information in the strong noise environment, which makes the mode decomposition algorithm have certain limitations in practical applications. limitation

[0004] In summary, the fault signal enhancement method in the prior art has the technical problems of poor signal processing effect and low detection accuracy of weak fault signals

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