Aiming at the problem that weak early fault of rolling bearing is not easy to be detected under strong noise interference.A rolling bearing early weak fault anomaly detection method based on combining variational mode decomposition and maximum correlation kurtosis deconvolution optimized by sparrow search algorithm integrating sine-cosine and Cauchy mutation(SCSSA-VMD-MCKD)was proposed.Firstly,the VMD parameters including α and K were optimized by sparrow search algorithm integrating sine-cosine and Cauchy mutation(SCSSA),the rolling bearing fault signal was adaptively decomposed,and the effective modal components screened by weighted envelope spectrum peak factor(WEPF)indexes were reconstructed to obtain the reconstructed signal.Then,the MCKD parameters including T、L and M were optimized by the SCSSA,and the reconstructed signal was processed by the MCKD in order to enhance the fault shock component.Finally,the envelope spectrum of the MCKD-enhanced signal was analyzed to extract the characteristic frequency and frequency doublings of rolling bearing faults.The fault anomaly detection method was verified and analyzed by bearing fault simulation signal and test signal.The research result show that comparing with the signal decomposed and reconstructed by SCSSA-VMD,the method can effectively reduce noise and adaptively enhance the fault impact component,the signal-to-noise ratio of fault simulation signal and actual test signal is respectively increased by 102.6%and 81.3%,and the root-mean-square error is respectively reduced by 26.7%and 33.3%.The amplitudes of bearing fault characteristic frequency and frequency doublings of inner and outer ring are more prominent,and the method can realize the early weak fault anomaly detection of rolling bearings under strong noise background.Comparing with the SSA-VMD-MCKD method,the superiority of the method is better emphasized.
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