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Sparsity-Oriented Nonconvex Nonseparable Regularization for Rolling Bearing Compound Fault under Noisy Environment
Joint Authors
Li, Xiaocheng
Wang, Jingcheng
Wang, Hongyuan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-30
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Rolling bearing is widely used in rotating machinery and, at the same time, it is easy to be damaged due to harsh operating environments and conditions.
As a result, rolling bearing is critical to the safe operation of the machinery devices.
Compound fault of rolling bearing is not a simple superimposition of multiple single faults, but the coupling of multiple fault features, making the vibration signal, becomes complicated.
In our study, sparsity-oriented nonconvex nonseparable regularization (SONNR) method is proposed to rolling bearing compound fault diagnosis under noisy environment.
Firstly, a theoretical model of rolling bearing compound fault is established, and the vibration characteristics of rolling bearing compound fault are analyzed.
Secondly, four-layer structure of the SONNR method is proposed: input layer, nonconvex sparse regularization layer, signal reconstruction layer, and compound faults isolation layer.
Finally, the validity of the method is verified by simulation data and actual data, and it is compared with the traditional time domain diagnostic methods and artificial intelligence methods.
American Psychological Association (APA)
Li, Xiaocheng& Wang, Jingcheng& Wang, Hongyuan. 2020. Sparsity-Oriented Nonconvex Nonseparable Regularization for Rolling Bearing Compound Fault under Noisy Environment. Shock and Vibration،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1212688
Modern Language Association (MLA)
Li, Xiaocheng…[et al.]. Sparsity-Oriented Nonconvex Nonseparable Regularization for Rolling Bearing Compound Fault under Noisy Environment. Shock and Vibration No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1212688
American Medical Association (AMA)
Li, Xiaocheng& Wang, Jingcheng& Wang, Hongyuan. Sparsity-Oriented Nonconvex Nonseparable Regularization for Rolling Bearing Compound Fault under Noisy Environment. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1212688
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212688