Research On Fourier Decomposition Method And MSB In Bearing Fault Diagnosis

Rolling bearings are the core components of rotating machinery,and the causes of many mechanical failures are closely related to bearing failures.If the fault can be found early and accurately,the stability and safety of the equipment operation will be ensured to a large extent,and it will play a very important role in the normal operation of the rotating machinery.In this paper,the rolling bearing’s fault signal is taken as the research object,the Fourier decomposition method and of modulated signal bispectrum are used as the main analysis methods This paper first analyzes the research status of Fourier decomposition method(FDM)and Modulated signal bispectrum(MSB),and launches the following series of researches on the shortcomings.Aiming at the problem that the FDM was difficult to extract fault features accurately in a strong noisy environment.Taking the advantage of the FDM with orthogonality,completeness and locality,and the Teager energy operator can highlight the impulse features in the signal.The following method was proposed.First,the FDM was used to search for the Fourier intrinsic mode component signals in a high-frequency to low-frequency search mode.Then,the valid mode signals selected by the kurtosis criterion and the correlation coefficient were used to reconstruct.Next,Teager energy operator was used in the reconstructed signal to enhance the impulse features.Finally,the fault features were extracted in the spectrogram.This method was used to analyze analog and rolling bearing vibration signals,and bearing data provided by the University of Cincinnati was used as follow-up verification.The experimental results show that the method is significantly better than the FDM,which can accurately highlight the fault characteristic frequency and realize the fault diagnosis of the rolling bearing.However,FDM still has shortcomings in demodulating the modulated signal in an environment with strong noise interference.Therefore,a rolling bearing fault diagnosis method is proposed which combine FDM and MSB.First,the FDM was used to search for fourier intrinsic band functions by high frequency to low frequency,and the weighted kurtosis index was used as the criterion to get the best signal;then the new signal was demodulated by using MSB and finally the fault characteristic frequency was extracted through the composite slice spectrum.Finally,the analog signal and the fault signal of the rolling bearing outer ring are analyzed by the above method.The results show that the method can extract the fault characteristic effectively and compared with the conventional bispectrum to verify the superiority.In this paper,a series of researches were carried out around the FDM method,Teager energy operator and MSB analysis method.Through simulation signal analysis,laboratory data verification and generalization analysis of bearing data provided by the University of Cincinnati,the effectiveness of the method was verified.The research results have a certain guiding role in the field diagnosis of rolling bearing faults.