Transactions of Materials and Heat Treatment

Title：Prediction of extrusion force in backward extruding connecting rod  bushing process by RBF neural network

Authors： Fan Wenxin1 Li Zhiwei1 Li Fenggang1 Guo Peijian1 Zhang Houzu1 Liu Tao2 Hao Xiaohua1

Unit： 1.College of Mechanical Engineering North University of China Taiyuan 030051 China 2.Taiyuan Military Representative Office of Armored Military Representative Bureau Taiyuan 030006 China

KeyWords： connecting rod bushing RBF neural network backward extrusion extrusion force QSn70.2 tin bronze

ClassificationCode：TG391

year,vol(issue):pagenumber：2019,44(5):180-184

Abstract：

By using the singlefactor test method,the extrusion test of tin bronze connecting rod bushing was simulated by the simulation software Simufact, then the extrusion temperature, die radius and extrusion ratio were selected as the test factors, and the extrusion force was selected as the evaluation index. [JP3]Based on software MATLAB, the RBF neural network model of the relationship between extrusion factors and extrusion force was established，and the nonlinear relationships between extrusion temperature, die radius, extrusion ratio and extrusion force were obtained. The RBF neural network model was trained by the experiment data, and then the extrusion force was predicted by the trained RBF neural network model. In the end, the predicted extrusion force value was compared with the simulated extrusion force value. The results show that the neural network model can predict the extrusion force in the process of backward extruding connecting rod bushing with high precision.

Funds：

山西省自然科学基金资助项目(2012011023-2)；山西省高校高新技术产业化项目(20120021)

作者简介：樊文欣（1964-），男，博士，教授 Email：fanwx@nuc.edu.cn

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