Dynamic Model Based on Genetic Algorithms of Prediction for the Thermal Deformation of Machine Tools

Abstract:

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The compensation of thermal deformation is the most significant for the accuracy of a machine tool. This study proposes an approach based on genetic algorithms (GA) to build the dynamic model of the prediction for thermal deformation of a machine tool. GA is used to optimize the prediction accuracy by using appropriate number and locations of temperature sensors, the model order and the time delay between temperatures and thermal deformation. The compared results show that the proposed approach can improve the accuracy of prediction results and better than other methods.

Info:

Periodical:

Materials Science Forum (Volumes 505-507)

Edited by:

Wunyuh Jywe, Chieh-Li Chen, Kuang-Chao Fan, R.F. Fung, S.G. Hanson,Wen-Hsiang Hsieh, Chaug-Liang Hsu, You-Min Huang, Yunn-Lin Hwang, Gerd Jäger, Y.R. Jeng, Wenlung Li, Yunn-Shiuan Liao, Chien-Chang Lin, Zong-Ching Lin, Cheng-Kuo Sung and Ching-Huan Tzeng

Pages:

163-168

DOI:

10.4028/www.scientific.net/MSF.505-507.163

Citation:

C. W. Chang et al., "Dynamic Model Based on Genetic Algorithms of Prediction for the Thermal Deformation of Machine Tools", Materials Science Forum, Vols. 505-507, pp. 163-168, 2006

Online since:

January 2006

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Price:

$35.00

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