Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks

Abstract:

Article Preview

Through analysis of the thermal errors affected NC machine tool, a new prediction model based on BP neural networks is presented, and ant colony algorithm is applied to train the weights of neural network model. Finally, thermal error compensation experiment is implemented, and the thermal error is reduced from 35μm to 6μm. The result shows that the local minimum problem of BP neural network is overcome, and the model accuracy is improved.

Info:

Periodical:

Materials Science Forum (Volumes 626-627)

Edited by:

Dongming Guo, Jun Wang, Zhenyuan Jia, Renke Kang, Hang Gao, and Xuyue Wang

Pages:

135-140

DOI:

10.4028/www.scientific.net/MSF.626-627.135

Citation:

Q. J. Guo and X.N. Qi, "Research on Thermal Error Modeling of NC Machine Tool Based on BP Neural Networks", Materials Science Forum, Vols. 626-627, pp. 135-140, 2009

Online since:

August 2009

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Price:

$35.00

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