Short-Sampled Blind Source Separation of Rotating Machinery Signals Based on Spectrum Correction
Joint Authors
Huang, Xiangdong
Jin, Xukang
Fu, Haipeng
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-18
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Nowadays, the existing blind source separation (BSS) algorithms in rotating machinery fault diagnosis can hardly meet the demand of fast response, high stability, and low complexity simultaneously.
Therefore, this paper proposes a spectrum correction based BSS algorithm.
Through the incorporation of FFT, spectrum correction, a screen procedure (consisting of frequency merging, candidate pattern selection, and single-source-component recognition), modified k -means based source number estimation, and mixing matrix estimation, the proposed BSS algorithm can accurately achieve harmonics sensing on field rotating machinery faults in case of short-sampled observations.
Both numerical simulation and practical experiment verify the proposed BSS algorithm’s superiority in the recovery quality, stability to insufficient samples, and efficiency over the existing ICA-based methods.
Besides rotating machinery fault diagnosis, the proposed BSS algorithm also possesses a vast potential in other harmonics-related application fields.
American Psychological Association (APA)
Huang, Xiangdong& Jin, Xukang& Fu, Haipeng. 2016. Short-Sampled Blind Source Separation of Rotating Machinery Signals Based on Spectrum Correction. Shock and Vibration،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1120132
Modern Language Association (MLA)
Huang, Xiangdong…[et al.]. Short-Sampled Blind Source Separation of Rotating Machinery Signals Based on Spectrum Correction. Shock and Vibration No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1120132
American Medical Association (AMA)
Huang, Xiangdong& Jin, Xukang& Fu, Haipeng. Short-Sampled Blind Source Separation of Rotating Machinery Signals Based on Spectrum Correction. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1120132
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1120132