Research on Fault Feature Extraction Method Based on FDM-RobustICA and MOMEDA
Joint Authors
Wang, Xiaodong
Li, Xuefeng
Wu, Limei
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-22
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
Aiming at the difficulty of extracting rolling bearing fault features under strong background noise conditions, a method based on the Fourier decomposition method (FDM), robust independent component analysis (RobustICA), and multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is proposed.
Firstly, the FDM method is introduced to decompose the single-channel bearing fault signal into several Fourier intrinsic band functions (FIBF).
Secondly, by setting the cross-correlation coefficient and kurtosis as a new selection criterion, it can effectively construct the virtual noise channel and the observation signal channel, which makes RobustICA complete the separation of the useful signal and noise well.
Finally, MOMEDA is introduced to enhance the periodic impact components in the denoised signal, and then the filtered signal is analyzed by the Hilbert envelope spectrum to extract the fault characteristic frequency.
Through the experimental analysis of the simulated signals and the actual bearing fault signals, the results show that the proposed method not only has the ability to suppress noise and accurately extract fault feature information but also has better performance than the traditional method of local mean decomposition (LMD) and intrinsic time-scale decomposition (ITD), highlighting its practicality in the fault diagnosis of rotating machinery.
American Psychological Association (APA)
Wang, Xiaodong& Li, Xuefeng& Wu, Limei. 2020. Research on Fault Feature Extraction Method Based on FDM-RobustICA and MOMEDA. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1197262
Modern Language Association (MLA)
Wang, Xiaodong…[et al.]. Research on Fault Feature Extraction Method Based on FDM-RobustICA and MOMEDA. Mathematical Problems in Engineering No. 2020 (2020), pp.1-23.
https://search.emarefa.net/detail/BIM-1197262
American Medical Association (AMA)
Wang, Xiaodong& Li, Xuefeng& Wu, Limei. Research on Fault Feature Extraction Method Based on FDM-RobustICA and MOMEDA. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1197262
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197262