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Prediction System of Thermal Errors Implemented on Machine Tools with Open Architecture Controller  

Kim, Sun-Ho (동의대학교 메카트로닉스공학과)
Ko, Tae-Jo (영남대학교 기계공학부)
Ahn, Jung-Hwan (부산대학교 기계공학부)
Publication Information
Journal of the Korean Society for Precision Engineering / v.25, no.5, 2008 , pp. 52-59 More about this Journal
Abstract
The accuracy of the machine tools is degraded because of thermal error of structure due to thermal variation. To improve the accuracy of a machine tools, measurement and prediction of thermal error is very important. The main part of thermal source is spindle due to high speed with friction. The thermal error of spindle is very important because it is over 10% in total thermals errors. In this paper, the suitable thermal error prediction technology for machine tools with open architecture controller is developed and implemented to machine tools. Two thermal error prediction technologies, neural network and multi-linear regression, are investigated in several methods. The multi-linear regression method is more effective for implementation to CNC. The developed thermal error prediction technology is implemented on the internal function of CNC.
Keywords
Thermal error; Neural network; Multi linear regression; Open architecture controller;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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