Optimal SES Selection Based on SVD and Its Application to Incipient Bearing Fault Diagnosis
Joint Authors
Li, Longlong
Cui, Yahui
Chen, Runlin
Liu, Xiaolin
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Rotating machinery has extensive industrial applications, and rolling element bearing (REB) is one of the core parts.
To distinguish the incipient fault of bearing before it steps into serious failure is the main task of condition monitoring and fault diagnosis technology which could guarantee the reliability and security of rotating machinery.
The early defect occurring in the REB is too weak and manifests itself in heavy surrounding noise, thus leading to the inefficiency of the fault detection techniques.
Aiming at the vibration signal purification and promoting the potential of defects detection, a new method is proposed in this paper based on the combination of singular value decomposition (SVD) technique and squared envelope spectrum (SES).
The kurtosis of SES (KSES) is employed to select the optimal singular component (SC) obtained by applying SVD to vibration signal, which provides the information of the REB for fault diagnosis.
Moreover, the rolling bearing accelerated life test with the bearing running from normal state to failure is adopted to evaluate the performance of the SVD-KSES, and results demonstrate the proposed approach can detect the incipient faults from vibration signal in the natural degradation process.
American Psychological Association (APA)
Li, Longlong& Cui, Yahui& Chen, Runlin& Liu, Xiaolin. 2018. Optimal SES Selection Based on SVD and Its Application to Incipient Bearing Fault Diagnosis. Shock and Vibration،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1215467
Modern Language Association (MLA)
Li, Longlong…[et al.]. Optimal SES Selection Based on SVD and Its Application to Incipient Bearing Fault Diagnosis. Shock and Vibration No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1215467
American Medical Association (AMA)
Li, Longlong& Cui, Yahui& Chen, Runlin& Liu, Xiaolin. Optimal SES Selection Based on SVD and Its Application to Incipient Bearing Fault Diagnosis. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1215467
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215467