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2009 WRI World Congress on Computer Science and Information Engineering
Thermal Error Compensation on Machine Tools Using Rough Set Artificial Neural Networks
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
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.
Index Terms:
artificial neural network, rough set, optimal modeling, machine tool, thermal error compensation
Citation:
Huanglin Zeng, Yong Sun, Haiyan Zhang, "Thermal Error Compensation on Machine Tools Using Rough Set Artificial Neural Networks," csie, vol. 5, pp.51-55, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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