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Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition
Joint Authors
Li, Yifan
Liu, Jianxin
Wang, Yan
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-04-06
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This study explores the capacity of the improved empirical mode decomposition (EMD) in railway wheel flat detection.
Aiming at the mode mixing problem of EMD, an EMD energy conservation theory and an intrinsic mode function (IMF) superposition theory are presented and derived, respectively.
Based on the above two theories, an improved EMD method is further proposed.
The advantage of the improved EMD is evaluated by a simulated vibration signal.
Then this method is applied to study the axle box vibration response caused by wheel flats, considering the influence of both track irregularity and vehicle running speed on diagnosis results.
Finally, the effectiveness of the proposed method is verified by a test rig experiment.
Research results demonstrate that the improved EMD can inhibit mode mixing phenomenon and extract the wheel fault characteristic effectively.
American Psychological Association (APA)
Li, Yifan& Liu, Jianxin& Wang, Yan. 2016. Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition. Shock and Vibration،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1119222
Modern Language Association (MLA)
Li, Yifan…[et al.]. Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition. Shock and Vibration No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1119222
American Medical Association (AMA)
Li, Yifan& Liu, Jianxin& Wang, Yan. Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1119222
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1119222