Intelligent Analysis Method of Gear Faults Based on FRWT and SVM
Joint Authors
Chen, Hongfang
Sun, Yanqiang
Shi, Zhaoyao
Lin, Jiachun
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
An intelligent analysis method for gear faults based on fractional wavelet transform (FRWT) and support vector machine (SVM) is proposed.
Based on this method, FRWT is used to eliminate noise from the gear vibration signal, and the vibration signal after noise elimination is carried thought wavelet packet decomposition and reconstruction.
A sequence corresponding to the signal is constructed consisting of the module with the highest level wavelet coefficients after decomposition and feature vectors corresponding to the energy sequence which were obtained by calculation.
Then, a particle optimization method is used to optimize SVM parameters, and the feature vectors as training samples are input into SVM for training while the test samples are input for fault recognition.
Experimental results show that the gear fault analysis method proposed in this paper is able to effectively extract the weak fault signal.
The accuracy rate for identification of the type of gear fault reached 96.7%.
American Psychological Association (APA)
Chen, Hongfang& Sun, Yanqiang& Shi, Zhaoyao& Lin, Jiachun. 2016. Intelligent Analysis Method of Gear Faults Based on FRWT and SVM. Shock and Vibration،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118810
Modern Language Association (MLA)
Chen, Hongfang…[et al.]. Intelligent Analysis Method of Gear Faults Based on FRWT and SVM. Shock and Vibration No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1118810
American Medical Association (AMA)
Chen, Hongfang& Sun, Yanqiang& Shi, Zhaoyao& Lin, Jiachun. Intelligent Analysis Method of Gear Faults Based on FRWT and SVM. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1118810
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118810