Rolling bearing fault diagnosis method based on calculation order tracking and spectral kurtosis

Abstract

The invention relates to a rolling bearing fault diagnosis method based on calculation order tracking and spectral kurtosis, and the method comprises the following steps: (1), carrying out tree-shapeddecomposition filtering of a time domain vibration signal, obtaining a signal of each frequency band, calculating the spectral kurtosis, drawing a spectral kurtosis graph, and obtaining the central frequency and optimal demodulation bandwidth of the optimal demodulation bandwidth of filtering through calculation; (2) performing band-pass filtering on the time domain vibration signal according tothe optimal demodulation bandwidth, and performing Hilbert envelope demodulation on the filtered signal to obtain an envelope signal containing fault impact; (3) setting a rotating speed pulse threshold value, obtaining a pulse generation moment, solving an angle domain time quadratic equation coefficient, and solving an angle domain stable signal; and (4) performing fast Fourier transform on theangular domain stationary signal, setting a sampling frequency as an angular domain sampling rate, and obtaining a fault diagnosis conclusion. The method can effectively extract bearing fault featureorder components under variable working conditions.

Description

technical field [0001] The invention relates to the technical field of equipment operation monitoring and vibration monitoring, in particular to the monitoring and fault diagnosis of rolling bearings. Background technique [0002] Rolling bearings, as one of the important parts of rotating machinery, are used to support the rotating shaft and its load and components, and maintain the rotation accuracy and working position of the shaft. Rolling bearings are vulnerable parts. According to incomplete statistics, about 30% of the failures of rotating machinery are caused by the failure of rolling bearings. Therefore, it is of great significance to carry out condition monitoring and fault diagnosis of rolling bearings. [0003] The working conditions of rolling bearings can be divided into stable working conditions and variable working conditions according to the degree of speed change. When the speed of the bearing is stable or slightly fluctuating, it can be regarded as being...

AI Technical Summary

Problems solved by technology

This also brings challenges to the application of traditional spectrum analysis in rolling bearing fault diagnosis

Images