A Hybrid Chatter Detection Method Based on WPD, SSA, and SVM-PSO
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-20
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
As a kind of self-excited vibrations, chatter vibration is extremely common in end milling, especially in high-speed cutting processes.
It affects the machining accuracy of products and decreases the processing efficiency of machine tools.
Thus it is very crucial to develop an effective condition monitoring system to extract the chatter feature before chatter vibration grows.
In this paper, a hybrid chatter detection method (HCDM) is proposed for chatter feature extraction and classification in end milling.
Firstly, wavelet packet decomposition is employed to decompose cutting vibration signals into a series of wavelet coefficients, and the signals of each frequency band are reconstructed.
Secondly, fast Fourier transform and singular spectrum analysis are chosen to obtain the chatter features.
Furthermore, the support vector machine model is optimized by particle swarm optimization to recognize the cutting states in end milling.
At last, cutting experiments of 300 M steel under different machining conditions are conducted, and the results indicate that the proposed HCDM can distinguish the stable, transition, and chatter states accurately and rapidly in end milling.
American Psychological Association (APA)
Wang, Erhua& Yan, Peng& Liu, Jie. 2020. A Hybrid Chatter Detection Method Based on WPD, SSA, and SVM-PSO. Shock and Vibration،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1210345
Modern Language Association (MLA)
Wang, Erhua…[et al.]. A Hybrid Chatter Detection Method Based on WPD, SSA, and SVM-PSO. Shock and Vibration No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1210345
American Medical Association (AMA)
Wang, Erhua& Yan, Peng& Liu, Jie. A Hybrid Chatter Detection Method Based on WPD, SSA, and SVM-PSO. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1210345
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210345