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Issue title: The 6th International Multi-Conference on Engineering and Technology Innovation 2017 (IMETI2017)
Guest editors: Wen-Hsiang Hsieh
Article type: Research Article
Authors: Li, Chao | Guo, Yu; * | Xiao, Zhengming; * | Wu, Xing | Liu, Tao
Affiliations: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, P.R. China
Correspondence: [*] Corresponding author. Yu Guo and Zhengming Xiao, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, 727 South Jingming Road, Kunming, 650500, P.R. China. E-mails: kmgary@163.com and 5636482@qq.com.
Abstract: One of the challenges for the fault feature extraction of a planetary gearbox is that the weak gear fault related vibration feature is often buried by the strong background noise in the gearbox. The minimum entropy deconvolution (MED) method for weak impulsive feature enhancement has been successfully applied to the feature extraction of gears and bearings in fixed-axis gearboxes. However, it is often failed if the result is converged to a single pulse rather than a periodic pulse sequence which corresponding to the gear or the bearing localized fault. In order to address this issue, the multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is employed in this paper to extract the vibration feature related to an individual planet gear with tooth-crack fault in a planetary gearbox. The effectiveness and advantages of the method are verified by experiments.
Keywords: Fault feature extraction, minimum entropy deconvolution, multipoint optimal minimum entropy deconvolution adjusted, planetary gearbox, planet gear, tooth-crack fault
DOI: 10.3233/JIFS-169871
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 943-953, 2019
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