Abstract
In this paper, a novel intelligent method to identify gear fault pattern was approached based on morphological filter, harmonic wavelet package and grey incidence. At first, the line structure element was selected for morphological filter to denoise the original signal. Secondly, different gear fault signals were decomposed into eight frequency bands by harmonic wavelet package in three levels; and energy distribution of each band was calculated. Finally, these energy distributions could serve as the feature vectors, the grey incidence of different gear vibration signals was calculated to identify the fault pattern and condition. Practical results show that this method can be used in gear fault diagnosis effectively.
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.
