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dc.contributor.authorTseng, P.C.en_US
dc.contributor.authorChen, S.L.en_US
dc.description.abstractThe geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80 mum to 3 mum. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from +/-10 mum to +/-3 mum.en_US
dc.relationJsme International Journal Series C-Mechanical Systems Machine Elements and Manufacturingen_US
dc.relation.ispartofseriesJsme International Journal Series C-Mechanical Systems Machine Elements and Manufacturing, Volume 45, Issue 2, Page(s) 470-478.en_US
dc.subjectthermal driften_US
dc.subjectcompensation technologyen_US
dc.subjectneural-fuzzy controlleren_US
dc.titleThe neural-fuzzy thermal error compensation controller on CNC machining centeren_US
dc.typeJournal Articlezh_TW
Appears in Collections:機械工程學系所


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