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Proceedings Paper

Hybrid HMM/SVM method for predicting cutting chatter
Author(s): Yongtao Jiang; Chunliang Zhang
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Paper Abstract

According to the properties of cutting chatter, a new chatter forecast system has been developed based on Hidden Markov Model (HMM) and Support Vector Machine (SVM). This system uses HMM as the recognition method and SVM as the prediction method. At the same time, means like wavelet package decomposition are also employed to extract the cutting features. The basic idea and general steps of this method are as follow. Firstly, the cutting signals are analyzed step by step in the same interval using wavelet packet decomposition. Secondly, the energy in every spectrum section are calculated and scaled in order to get general property. As a result, the energy distribution information and energy transition curve of different spectrum section can be retrieved. Then, SVR algorithm is applied to predict the trend of energy transition. The results, after scalar quantized, at last are input into HMMs to determine whether in chatter period. Certainly, current state still needs to be distinguished. The simulation results indicate that the new predicting method has good discriminating performances and high forecast accuracy.

Paper Details

Date Published: 13 October 2006
PDF: 8 pages
Proc. SPIE 6280, Third International Symposium on Precision Mechanical Measurements, 62801Q (13 October 2006); doi: 10.1117/12.716150
Show Author Affiliations
Yongtao Jiang, Nanhua Univ. (China)
Chunliang Zhang, Nanhua Univ. (China)


Published in SPIE Proceedings Vol. 6280:
Third International Symposium on Precision Mechanical Measurements
Kuang-Chao Fan; Wei Gao; Xiaofen Yu; Wenhao Huang; Penghao Hu, Editor(s)

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