Pattern recognition of chatter gestation based on hybrid somidhmm architecture

Author

Kang, Jing ; Feng, Chang-jian ; Qiang Shao ; Hu, Hong-ying

Author_Institution

Dalian Nationalities Univ., Dalian

Volume

3

fYear

2007

fDate

2-4 Nov. 2007

Firstpage

1161

Lastpage

1166

Abstract

To distinguish chatter gestation, chatter recognition based on hybrid SOM/DHMM is proposed for dynamic patterns of chatter gestation in cutting process. At first FFT features are extracted from the vibration signal of cutting process, then FFT vectors are presorted and coded into code book of integer numbers by SOM (self-organizing feature map), and these code books are introduced to DHMM (discrete hidden Markov models), for machine learning and classification. Finally the results of chatter gestation recognition and chatter prediction experiments are presented and show that the method proposed is effective.

Keywords

cutting; fast Fourier transforms; feature extraction; hidden Markov models; learning (artificial intelligence); machining chatter; pattern classification; production engineering computing; self-organising feature maps; vibrations; FFT features; chatter gestation; chatter recognition; classification; cutting process; discrete hidden Markov models; hybrid SOM/DHMM; machine learning; pattern recognition; self-organizing feature map; vibration signal; Notice of Violation; Pattern analysis; Pattern recognition; Wavelet analysis; Chatter; Discrete Hidden Markov Model (DHMM); Prediction; Self-Organizing Feature Map(SOM); Vector coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1065-1

Electronic_ISBN

978-1-4244-1066-8

Type

conf

DOI

10.1109/ICWAPR.2007.4421608

Filename

4421608