Research on Chatter Prediction and Monitor Based on DHMM Pattern Recognition Theory

Author

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

Author_Institution

Dalian Nationalities Univ., Dalian

fYear

2007

fDate

18-21 Aug. 2007

Firstpage

1368

Lastpage

1372

Abstract

A new method of chatter prediction based on discrete hidden Markov models (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, and these code books are introduced to DHMM 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; feature extraction; hidden Markov models; learning (artificial intelligence); machining chatter; pattern classification; process monitoring; self-organising feature maps; vibration control; vibrations; DHMM pattern recognition theory; FFT vectors; SOM; chatter gestation; chatter prediction; cutting process; discrete hidden Markov models; fast Fourier transform; features extraction; machine learning; self-organising map; vibration signal; Books; Fault diagnosis; Feature extraction; Hidden Markov models; Monitoring; Pattern classification; Pattern recognition; Signal processing; Stochastic processes; Vibrations; Chatter; Discrete Hidden Markov Model (DHMM); Dynamic Pattern Recognition; Prediction; Vector Quantification;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2007 IEEE International Conference on

Conference_Location

Jinan

Print_ISBN

978-1-4244-1531-1

Type

conf

DOI

10.1109/ICAL.2007.4338783

Filename

4338783