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《Foundry Technology》 2017-10
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Application of RBF Neural Network in Prediction of Warm-Extrusion Forming of Connecting Rod Bushing

FAN Wenxin;SHI Yongpeng;FENG Zaixin;HE Sheng;WANG Xue;SHI Yaoyao;College of Mechanical and Power Engineering, The North University of China;College of Material Science and Engineering, The North University of China;  
The radial basis function(RBF) neural network model was established by DEFORM-3D and RBF neural network model in the toolbox of MATLAB, the input parameters were friction coefficient, preheating temperature,extrusion speed and mold preheat temperature. The results show that the RBF neural network model has a good performance in predicting the temperature and pressure, which can well reflect the complex relationship between process parameters and the quality of warm-extrusion forming, and improve the design efficiency and reduce the cost of the experiment.
【Fund】: 山西省自然科学基金资助项目(2012011023-2)
【CateGory Index】: TG376
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