Tools&rsquo;wear state recognition based on support vector machine and particle filtering#br#

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Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (17) : 48-55.

Tools’wear state recognition based on support vector machine and particle filtering#br#

CHENG Can 1 LI Jianyong 1,2 XU Wensheng 1,2 NIE Meng 1,2

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Abstract

To improve the accuracy of tools’wear recognition under the case of small samples,a tools’wear recognition method based on support vector machine (SVM) and particle filtering was proposed. Aiming at difficult problems of SVM’s feature selecting and parametric selecting,a bi-level programming model for SVM’s input features and parametric optimization was developed and solved using the genetic algorithm and the artificial bee colony algorithm. Then,the particle filtering method was used to modify tools’wear recognition results obtained using the regression algorithm of SVM. Test results showed that under the case of small samples,the tools’wear recognition method based on SVM and particle filtering has a good learning capability and can recognize tools’wear precisely.

Key words

tools&rsquo / wear / support vector machine (SVM) / bi-level programming / genetic algorithm / artificial bee colony algorithm / particle filtering

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CHENG Can 1 LI Jianyong 1,2 XU Wensheng 1,2 NIE Meng 1,2. Tools’wear state recognition based on support vector machine and particle filtering#br#[J]. Journal of Vibration and Shock, 2018, 37(17): 48-55

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