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《Machine Tool & Hydraulics》 2011-11
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Research on Dynamic Grey Optimization Modeling for Thermal Error in Numerical Control Machine

LI Yimin(Department of Mechanical and Electrical Engineering,Nanjing College of Information Technology,Nanjing Jiangsu 210046,China)  
To reduce thermal error's influence on machining accuracy,a grey GM(0,N)model was presented for predicting CNC machine's thermal error with the aim of lowering compensation cost,simplifying data collection process and improving compensation accuracy.The GM(0,N)optimized model was established,which could optimize data allocation,improve system dynamic character and enhance robustness.Intelligent temperature sensors and displacement sensors were used to collect temperature data and spindle's thermal displacement information in the three directions of precise horizontal machining centre MCH63.Thermal error model was built up with the collected data.The experimental results show that the GM(0,N)modeling method is simple with less data,short operation time and higher predication accuracy,and the optimal model can modify itself due to input new data on line with high accuracy,good robustness and general usage,which is fit for modelling on line.
【Fund】: 江苏省自然科学基金资助项目(BK200606060)
【CateGory Index】: TG659
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