Vibration Signal Processing and Fault Diagnosis of Bearing Based on MCKD Algorithm
In order to improve the anti-interference ability of bearing vibration signal,a bearing vibration signal processing and fault diagnosis method based on maximum correlation kurtosis deconvolution(MCKD)algorithm is designed.The correlation-Kurtosis method is used to determine IMF1 and IMF2 and complete the reconstruction noise reduction process.The MCKD algorithm is used to realize the noise reduction of the reconstructed signal,and the demodulation analysis is completed by the envelope spectrum.The research results show that there is a more obvious wave crest at the position of 105.5Hz,which forms the same result as the theoretical value of the fault frequency of the rolling element,and still forms an obvious double frequency wave crest,which proves that the MCKD algorithm has a more obvious advantage in the initial fault diagnosis of rolling bearings.This research is helpful to improve the fault identification ability of bearings,and can also be extended to other mechanical transmission fields.
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