RESEARCH ON ROLLING BEARING FAULT FEATURE EXTRACTION METHOD WITH SGMD-MOMEDA (MT)

RESEARCH ON ROLLING BEARING FAULT FEATURE EXTRACTION METHOD WITH SGMD-MOMEDA (MT)

Aiming at the problem that the vibration signal of rolling bearing is difficult to extract due to the characteristics of non-linear, non-stationary and low signal-to-noise ratio, a new fault extraction method based on symplectic geometry mode decomposition（SGMD） and multipoint optimal minimum entrop...

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Bibliographic Details
Main Authors: CAO YaLei, DU YingJun, WEI Guang, DONG XinMin, GAO LiPeng, LIU YuXi
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2022-01-01
Series:Jixie qiangdu
Subjects:
Symplectic geometry mode decomposition
Symplectic geometry component
Multipoint optimal minimum entropy deconvolution adjusted
Feature extraction
Rolling bearing fault diagnosis
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2022.06.02
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