![](/images/graphics-bg.png)
An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis
Joint Authors
Qiao, Zhicheng
Liu, Yongqiang
Liao, Yingying
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
When the vibration signals of the rolling bearings contain strong interference noise, the spectrum division of the vibration signals is seriously disturbed by the noise.
The traditional empirical wavelet transform (EWT) decomposes signals into a large number of components, and it is difficult to select suitable components that contain fault information.
In order to address the problems above, in this paper, we proposed the improved empirical wavelet transform (IEWT) method.
The simulation experiment proved that IEWT can solve the problem of a large number of EWT components and separate the impact component effectively which contains bearing fault information from noise.
The IEWT method is combined with the support vector machine (SVM) to diagnosis the fault of the rolling bearings.
The permutation entropy (PE) is used to construct feature vectors for its strong induction ability of dynamic changes of nonstationary and nonlinear signals.
The crucial parameter penalty factor C and kernel parameter g of SVM are optimized by quantum genetic algorithm (QGA).
Compared with traditional EWT and variational mode decomposition (VMD) methods, the effectiveness and advantages of this method are demonstrated in this study.
The classification prediction ability of SVM is also better than that of K-nearest neighbor (KNN) and extreme learning machine (ELM).
American Psychological Association (APA)
Qiao, Zhicheng& Liu, Yongqiang& Liao, Yingying. 2020. An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis. Shock and Vibration،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1209971
Modern Language Association (MLA)
Qiao, Zhicheng…[et al.]. An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis. Shock and Vibration No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1209971
American Medical Association (AMA)
Qiao, Zhicheng& Liu, Yongqiang& Liao, Yingying. An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1209971
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209971