Abstract
The vibration signal of roller bearings contains important information, but the strong background noise makes fault diagnosis difficult. In this paper, inspired by the idea of a block-matching 3D algorithm, using local and nonlocal correlation of vibration signal, a patch-matching 2D (PM2D) denoising method is proposed for the first time to suppress noise in vibration signals. The proposed denoising method constructs similarity matrices of component modules, which are used for threshold processing to determine the coefficients of the 2D discrete cosine transform, so as to achieve optimal denoising performance. Then, empirical mode decomposition and envelope analysis are employed to perform fault diagnosis. The proposed PM2D denoising method and fault diagnosis strategies are applied to both simulated and measured signals. A comparison study shows the superiority of the proposed method over the other existing denoising methods.
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.
