Abstract
Since the thermal error modeling of CNC machine tools has characters of small sample and discrete data, the variable-weight combined modeling method was presented by integrating time series analysis and least squares support vector machines. Taking minimum sum of error square of prediction model as the optimization criterion, optimal weights in different time were calculated. Using grey GM (1, 1) model to predict the variable weights, the prediction result of thermal error was obtained as well. Application of the grey variable-weight combined model on a five axis vertical machining center indicated that it can get higher prediction accuracy than single modeling method. Therefore online error compensation to CNC machine tools will become more effective.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
