DocumentCode
3482024
Title
Pattern recognition of chatter gestation based on SVM — HMM method
Author
Shao, Qiang ; Shao, Cheng ; Qiang Shao ; LiNa, Guan
Author_Institution
Inst. of Adv. Control Technol., Dalian Univ. of Technol., Dalian, China
fYear
2009
fDate
5-7 Aug. 2009
Firstpage
1489
Lastpage
1494
Abstract
To distinguish chatter gestation, a new method of chatter gestation based on HMM-SVM method is proposed for dynamic patterns of chatter gestation in cutting process. At first, FFT features are extracted from the model signal of cutting process, then FFT vectors are introduced to HMM-SVM (hidden Markov model-support vector machine) for machine learning and classification. the vibration signal of cutting process is introduced to the HMM-SVM model. Finally, the results of chatter gestation recognition and chatter prediction experiments are presented and show that the method proposed is executable and effective.
Keywords
cutting; fast Fourier transforms; feature extraction; hidden Markov models; learning (artificial intelligence); machining chatter; vibrations; FFT; HMM-SVM method; chatter gestation; cutting process; feature extraction; hidden Markov model; machine learning; pattern recognition; support vector machine; vibration signal; Automation; Feature extraction; Hidden Markov models; Pattern recognition; Predictive models; Signal processing; Support vector machine classification; Support vector machines; Training data; Vibrations; HMM; SVM; chatter gestation; pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-4794-7
Electronic_ISBN
978-1-4244-4795-4
Type
conf
DOI
10.1109/ICAL.2009.5262734
Filename
5262734
Link To Document