A fine spectral negentropy(ASNE)method based on empirical wavelet transform(EWT)is proposed to solve the problems that it is difficult to determine the central frequency of the resonance sideband and the determination of the bandwidth is susceptible to noise when extracting fault features of rolling bearings. The proposed method constructs a filter bank by using the characteristics of empirical wavelet filter to reali-e the scanning filter in frequency domain. Then
the filtered components are screened by combining the feature of spectral negentropy in time domain
and it is easier to detect periodic impulse components in signals. The accurate central frequency and bandwidth are obtained after two scanning cycles. Then the optimum fault feature components are extracted through EWT
and the fault feature information of the bearing is finally obtained through envelope demodulation. The method is validated by the experimental signals of inner and outer races of rolling bearing. The result
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references
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