Abstract
Rolling bearing components are broadly utilized in major mechanical fabricating businesses and guaranteeing the secure and steady operation of rolling heading could be a basic necessity of the fabricating prepare. Engineering for intelligent manufacturing has grown significantly in importance during the past several years in the manufacturing sector. The method for identifying mechanical faults based on “frequency domain analysis plus intelligent model” has developed rapidly. In this study, methods such as envelope spectrum analysis and spectral kurtosis are applied to process and analyze fault data to improve the service life of rolling bearing production equipment. In addition, we perform grid search tuning of the hyperparameters in spectral kurtosis, enabling faster frequency band selection for envelope spectral bandpass filtering.
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.
