Abstract
To distinguish chatter gestation, a new method of chatter prediction 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.
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Kang, J., Feng, Cj., Shao, Q., Hu, Hy. (2007). Prediction of Chatter in Machining Process Based on Hybrid SOM-DHMM Architecture. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_104
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DOI: https://doi.org/10.1007/978-3-540-74205-0_104
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