Gear Pitting Corrosion Fault Diagnosis In Gearbox Based On Wavelet Analysis

Wavelet Analysis is a theory developed in recent years. It has been successfully used in image processing, telecommunication and Geophysics. In this paper, some research and application work with wavelet. And wavelet analysis, a new time-frequency analysis method, is used in the field of mechanical fault diagnosis.This paper comprises of the following parts:First, through multianalysis and studying of vibration theory of the gear, we could draw the conclusion: Effective time-frequency analysis is the inherent demand for analyzing the vibration signal of the gear;Singularity monitoring and filtering the signal or depressing noise are the main applications of wavelet to gear vibration signal analysis.Second, through studying gear vibration signal analysis course related to wavelet theory that arrives research, I explain with various wavelet project meanings and theoretical foundation. Comparing wavelet analysis and other common signal analytical methods, and on the basis of comparing every performance index, I choose Daubechies wavelet as the wavelet mother function for gear vibration signal.Third, we established the system of fault diagnosis on gearbox. Simulated experiment could be carried out. And gained artificial pitting corrosion fault vibration signal by the experiment on artificial pitting corrosion gear.Fourth, research on the application of wavelet analysis in depressing noise is conducted. And I gained the good result in depressing noise on simulation signal and real signal. Research on the application of wavelet analysis in singularity signal is conducted. It proved that wavelet analysis in processing these signal has a great advantage over fourier analysis. By using wavelet analysis, we successfully extracted artificial pitting corrosion fault feature of the gearbox ZQ350 which was made by Lanzhou Decelerator Factory, and from this effective method the same kind accidents can be avoided and the fault situation can be confirmed for the future.From above all, some important feature that can not be obtained by other methods can be obtained by wavelet analysis in mechanical fault diagnosis. A feasible and effective method is provided for detecting hidden trouble of equipment and analyzing fault.