Bearing Fault Enhancement Detection Based On Spectral Kurtosis And Minimum Entropy Deconvolution

Rolling bearing is one of the key components widely used in the transmission system,and plays an important role in ensuring the normal operation of the system.Bearing often runs under the condition of changing working and high noise,and the weak fault signals are often overwhelmed by noise.To extract the bearing fault feature effectively,this paper carried out the research of fault enhancement detection for rolling bearings under variable working conditions.In this paper,the method for fault enhancement detection of rolling bearing is studied based on spectral kurtosis method and minimum entropy deconvolution.The main research contents include:(1)The characteristic frequency and vibration feature of rolling bearing is researched,and an improved bearing failure model is established.The model can especially simulate the variable speed bearing fault signal,which lays the data verification foundation for the follow-up study.(2)The spectral kurtosis method is chosen to select the best band of the envelop demodulation,the principle and realization process of this method are studied.Then the correctness and validity of the method are verified by using the simulation signal,so the foundation for further research on feature extraction is laid.(3)Because of the repetitive impact and high frequency modulation characteristics of bearing fault signal,the principle and implementation process of multipoint optimal minimum entropy deconvolution adjusted(MOMEDA)method aimed at bearings are studied.The envelop signal is enhanced by combining the MOMEDA method with the envelop analysis,and the effectiveness of the proposed fault enhancement method is verified by the processing results of the simulation signals.(4)Rolling bearing fault experiments are carried out and a series of vibration signals with different fault types under different working conditions are obtained.The proposed method is verified by measured signals.Finally,the integrated software is established and used to display the processing result.The simulation signal and experimental signal processing results show that the method studied in this paper can effectively enhance the bearing fault signal,and the fault enhancement method proposed in this paper is more effective than the existing methods.These researches lay the foundation for condition monitoring and fault diagnosis of rolling bearings.