VMD and FastICA combined rolling bearing fault diagnosis method

Abstract

The invention relates to a VMD and FastICA combined rolling bearing fault diagnosis method comprising the steps that the original vibration signals of a rolling bearing are acquired by using the present data acquisition equipment; VMD decomposition is performed on the acquired original vibration signals of the rolling bearing; the original vibration signals are decomposed into k modal components through VMD decomposition, and three continuous modal components act as a sequence combination to perform FastICA analysis so as to obtain reconstruction fault signals; and Hilbert transform is performed on the reconstruction fault signals to obtain the envelope spectrum of the reconstruction fault signals, the characteristic frequency, the modulation characteristic frequency and the side band under each fault characteristic are extracted from the obtained envelope spectrum and thus occurrence of the fault in the rolling bearing and the fault type are judged according to the extracted characteristic frequency component.

Description

technical field [0001] The invention relates to a rolling bearing fault diagnosis method, in particular to a rolling bearing fault diagnosis method combining VMD and FastICA. Background technique [0002] Rolling bearings are one of the core components of rotating machinery such as gearboxes and turbomachinery, and their failure will directly affect the stable operation of mechanical equipment. Affected by the working environment, the original vibration signal of the rolling bearing is generally non-stationary and nonlinear, and the signal is often mixed with noise, resulting in a decrease in the signal-to-noise ratio of the vibration signal, which brings difficulties to the fault feature extraction and fault diagnosis of the rolling bearing. Contents of the invention [0003] In view of the above problems, the purpose of the present invention is to provide a rolling bearing fault diagnosis method combining VMD and FastICA, which can effectively reduce the interference noi...

AI Technical Summary

Problems solved by technology

Affected by the working environment, the original vibration signal of the rolling bearing is generally non-stationary and nonlinear, and the signal is often mixed with noise,...

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