Hybrid KPCA-SVM Method for Pattern Recognition of Chatter Gestation

Qiang Shao; Chang Jian Feng; Wen Long Li

doi:10.4028/www.scientific.net/AMM.69.88

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 69Hybrid KPCA-SVM Method for Pattern Recognition of...

Hybrid KPCA-SVM Method for Pattern Recognition of Chatter Gestation

Abstract:

To distinguish chatter gestation, chatter recognition method based on hybrid KPCA(Kernel Principal Compenent Analysis) and SVM(Support Vector Machine) 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 introduced to KPCA-SVM 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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Periodical:

Applied Mechanics and Materials (Volume 69)

Pages:

88-92

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.69.88

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Online since:

July 2011

Authors:

Qiang Shao, Chang Jian Feng, Wen Long Li

Keywords:

Chatter Gestation, KPCA, Pattern Recognition, Support Vector Machine (SVM)

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