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Abstract：
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In order to realize the prediction of axial straightness error of the connecting rod bushing during the power spinning and improve the performance of connecting rod bushing, RBF neural network model was established based on the MATLAB platform among the thinning ratio, feeding ratio, the first pressure ratio and axis straightness error. Then, it is trained by the simulation data, and straightness error of the inside and outside axis was predicted. Next, comparing the prediction value with simulation value, the prediction error percentage of RBF neural network was obtained, and the prediction performance of the RBF neural network model in the actual production was verified by comparing with the measured values. Furthermore, the prediction error percentage was compared with that of the BP neural network built under the same conditions, and RBF neural network can predict the axial straightness error of the connecting rod bushing during power spinning. Thus, compared with BP neural network, RBF neural network can obtain higher convergence rate, better learning rate, more stable training process and higher prediction accuracy.
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Funds：
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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）；中北大学第十届研究生科技基金项目(20131018)
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AuthorIntro：
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作者简介：吉梦雯 (1995-)，女，硕士研究生
E-mail：1720205497@qq.com
通讯作者：樊文欣(1964-)，男，博士，教授
E-mail：fanwx@nuc.edu.cn
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Reference：
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