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Abstract：
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In order to optimize the forging process and improve the comprehensive performance of mechanical oil pump shaft, based on the 5×25×1 three-level topological structure, the neural network optimization model for forging process of mechanical oil pump shaft was designed and constructed by taking the heating temperature of billet, initial forging temperature, final forging temperature, mold preheating temperature and forging deformation amount as five input parameters, wear performance as output parameter, and tansig function as transfer function, and the training, prediction and validation of the neural network model were carried out. The results show that the average relative training error of the model is 3.2%, the relative prediction error is lower than 5%, and the model has high prediction accuracy and strong prediction ability. Compared with the present production line, the wear volume of the high speed steel SKH-51 mechanical oil pump shaft forged by model optimization is reduced by 51.9%, and the wear performance is obviously improved.
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Funds：
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广西高校科研项目（KY2016YB686）
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AuthorIntro：
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莫洪武（1980-），男，硕士，副教授
E-mail：nzymhw@163.com
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Reference：
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