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Thermal Error Forecasting for Motorized Spindle Based on Hybrid Model


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Thermal Error Forecasting for Motorized Spindle Based on Hybrid Model
LEI Chunli 12RUI Zhiyuan 12LI Emin 12
1.MOE Key Laboratory of Digital Manufacturing Technology and Application; 2.School of Mechanical and Electronic Engineering,Lanzhou University of Technology,Lanzhou 730050,China
motorized spindlesthermal errorscombined modelsforecastingradial basis functionautoregressive analysisgray system
Aiming at the complicated thermal deformation generation mechanisms of motorized spindles of numerical control machines,a combined prediction model based on radial basis function neural network is proposed to forecast their change trends.According to the measured data of thermal deformation of motorized spindles,the thermal errors of spindles are predicted by means of the autoregressive analysis model,gray system model and combination forecasting model respectively.Experimental results show that the prediction precision of the combined prediction model for motorized spindle thermal errors is the highest among the three kinds of forecasting models,and its relative forecast precision is about 3% above other single prediction models.


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Last Update: 2012-12-29