Model Prediction and Numerical Simulation on Melt Temperature Distribution in Process of Polymer Eztrusion
Polymer dynamic extrusion is a complicated MIMO nonlinear system with time-varying, and the melt temperature is one of key parameters to measure and control. In order to improve the predicting accuracy of melt temperature distribution under the influence of multi-variable coupling, a ridge regression method based on Gaussian RBF GRBF-RR) is presented. The model fulfill the nonlinear mapping and reconstruction of high-dimension feature space from multi-variable input samples, and is superior to least square method in eliminating potential multicollinearity of variables new-produced. The simulation results show that the GRBK-RR model makes a full characterization of internal laws of melt temperature in process of polymer dynamic extrusion. The numerical simulation based on the GRBF-RR model illuminates the coupling influence of input variables on the melt temperature distribution, and provides decision support for the optimization quality control of plastic product machining.
Polymer Melt temperature Nonlinear transform Model prediction Dynamic eztrusion Numerical Simulation
Yang Yanjuan Zhang Dongzhi Cai Jun
School of Mechanical and Automotive Engineering South China University of Technology Guangzhou,Guangdong,510640,China
国际会议
上海
英文
1711-1715
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）