Pattern recognition of chatter gestation based on hybrid somidhmm architecture

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.