Car Bearing Vibration Signal Noise Reduction Based on MCKD-FDM Method
In order to improve the fault diagnosis accuracy of motor bearing,Fourier decomposition(FDM)method is selected to decompose the noise reduction signal,and the maximum correlation kurtosis deconvolution(MCKD)is used to reconstruct the signal envelope spectrum to diagnose the information fault,and simulation and experimental analysis are carried out.The results show that the test signals form obvious fault characteristic frequen-cy and frequency doubling of each order,and the amplitude of each order frequency doubling is reduced.By using the method presented in this paper,the fault impact components can be significantly highlighted,and rich bearing fault information can be extracted,which more clearly reflects the fault characteristic frequency and frequency dou-bling.The fault diagnosis method in this paper can meet the requirements of high-precision automotive transmission system fault detection.
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