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Thermal Error Compensation on Machine Tools Using Rough Set Artificial Neural Networks

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3 Author(s)
Huanglin Zeng ; Sichuan Univ. of Sci. & Eng., Zigong, China ; Yong Sun ; Haiyan Zhang

This paper is a study of the application of rough set artificial neural networks to the problem of calculating thermal error compensation values for axis positioning on a machine tool. The primary focus is on the development of a rough set approach to reduce a thermal error compensation system which is composed of all of the temperature variables. One modeling of thermal error compensation on machine tools is presented by way of using artificial neural networks integrated rough sets. Positioning error compensation capabilities were tested using industry standard equipment and procedures, and the results obtained is validated for applicability to the problem.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:5 )

Date of Conference:

March 31 2009-April 2 2009