A Hybrid Domain Degradation Feature Extraction Method for Motor Bearing Based on Distance Evaluation Technique
Joint Authors
Wang, Yu-kui
Yu, He
Li, Hong-ru
Chen, Baiyan
Source
International Journal of Rotating Machinery
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The vibration signal of the motor bearing has strong nonstationary and nonlinear characteristics, and it is arduous to accurately recognize the degradation state of the motor bearing with traditional single time or frequency domain indexes.
A hybrid domain feature extraction method based on distance evaluation technique (DET) is proposed to solve this problem.
Firstly, the vibration signal of the motor bearing is decomposed by ensemble empirical mode decomposition (EEMD).
The proper intrinsic mode function (IMF) component that is the most sensitive to the degradation of the motor bearing is selected according to the sensitive IMF selection algorithm based on the similarity evaluation.
Then the distance evaluation factor of each characteristic parameter is calculated by the DET method.
The differential method is used to extract sensitive characteristic parameters which compose the characteristic matrix.
And then the extracted degradation characteristic matrix is used as the input of support vector machine (SVM) to identify the degradation state.
Finally, It is demonstrated that the proposed hybrid domain feature extraction method has higher recognition accuracy and shorter recognition time by comparative analysis.
The positive performance of the method is verified.
American Psychological Association (APA)
Chen, Baiyan& Li, Hong-ru& Yu, He& Wang, Yu-kui. 2017. A Hybrid Domain Degradation Feature Extraction Method for Motor Bearing Based on Distance Evaluation Technique. International Journal of Rotating Machinery،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1169494
Modern Language Association (MLA)
Chen, Baiyan…[et al.]. A Hybrid Domain Degradation Feature Extraction Method for Motor Bearing Based on Distance Evaluation Technique. International Journal of Rotating Machinery No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1169494
American Medical Association (AMA)
Chen, Baiyan& Li, Hong-ru& Yu, He& Wang, Yu-kui. A Hybrid Domain Degradation Feature Extraction Method for Motor Bearing Based on Distance Evaluation Technique. International Journal of Rotating Machinery. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1169494
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169494