Early Fault Detection And Initial Fault Estimation Of Rolling Element Bearing

Rolling element bearings are widely used in the field of mechanical and electrical equipment to support the operation of rotating components.Accordingly,due to the harsh working environment,the performance of bearing deteriorating over time,causes a cascade failure in the mechanical system leads to excessive maintenance costs and production delays.Early fault diagnosis is an effective strategy to avoid unexpected failures.Therefore,this thesis focuses on the development of such an algorithm to investigate the status of early bearing fault detection.A signal processing approach based on the combination of Variational Mode Decomposition(VMD)and Infogram followed by backtracking analysis is proposed in the thesis to estimate initial fault time of rolling element bearing.The main contents of this object as listed below.(1)An approach combining VMD and EEMD is proposed to denoise the original vibration signal of the rolling element bearing.The original vibration signal is decomposed by VMD,and the IMF obtained by VMD is further decomposed by EEMD based on the theory of VMD and EEMD algorithm.The denoised signal is obtained after the IMF with the largest kurtosis value,and the correlation coefficient is selected for reconstruction.The experimental results show that the combination of VMD and EEMD has good effects on noise reduction and highlight fault information.(2)The method for optimizing filter parameters of the resonance demodulation of the filtered vibration signal based on the Infogram is proposed.The spectral entropy is introduced to analyze the Infogram method.The spectral entropy of the square envelope of the reconstructed signal is calculated by Infogram,and the center frequency and bandwidth of the optimal resonance frequency band are determined.The analysis results show that Infogram has good ability for early faults diagnosis.(3)A hybrid signal processing method based on Infogram,VMD,and backtracking strategy are proposed to predict the initial failure time of rolling element bearings.The kurtosis value is used as the index of bearing performance degradation.The square envelope of the bearing signal is used to identify the fault characteristic frequency and fault type.The backtracking strategy is used to predict the initial fault time of rolling element bearings.