![](/images/graphics-bg.png)
Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification
Joint Authors
Li, Pengfei
Jiang, Yongying
Xiang, Jiawei
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC) is proposed.
The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band.
Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC.
The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples.
American Psychological Association (APA)
Li, Pengfei& Jiang, Yongying& Xiang, Jiawei. 2014. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1048463
Modern Language Association (MLA)
Li, Pengfei…[et al.]. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1048463
American Medical Association (AMA)
Li, Pengfei& Jiang, Yongying& Xiang, Jiawei. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1048463
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048463