Abstract
The distortion of signal caused by transmission path always brings great difficulties to feature extraction for bearing fault diagnosis. It is thus an important work to eliminate the influence of transmission path and recover impulsive features. A novel method called maximum correntropy criterion-based blind deconvolution (MCCBD) is presented in this paper and the strong analytical connection which holds for MOMEDA and MCCBD is revealed. Maximum correntropy criterion (MCC) is used as an objective function to reduce the influence of outliers and the coefficients of the optimal deconvolution filter can be obtained. Moreover, the proposed method adopts an autocorrentropy-based strategy to automatically evaluate the impulse period, hence it can enhance the fault impulses buried by noise without any prior knowledge. Finally, the superiority of MCCBD is exhibited by comparing with some existing methods on the simulated signal and two experimental datasets.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
