Prediction of Cutting Chatter Based on Hidden Markov Model

Abstract:

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Self-chatter is a serious problem in cutting process. This paper aims to solve the problem by establishing time series model of vibration acceleration signal in cutting process based on Hidden Markov Model (HMM) technology and achieve the purpose of chatter recognition and prediction. Features which can indicate cutting state are extracted from the acceleration signal. HMM parameters are obtained by model training, and the reference models database is built. Then cutting state recognition is performed according to the feature matching level. Simulations and experiments are conducted, and the results show that the proposed method is feasible and it could get high recognition

Info:

Periodical:

Key Engineering Materials (Volumes 353-358)

Edited by:

Yu Zhou, Shan-Tung Tu and Xishan Xie

Pages:

2712-2715

DOI:

10.4028/www.scientific.net/KEM.353-358.2712

Citation:

Z. H. Yao et al., "Prediction of Cutting Chatter Based on Hidden Markov Model", Key Engineering Materials, Vols. 353-358, pp. 2712-2715, 2007

Online since:

September 2007

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Price:

$35.00

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