Transactions of Materials and Heat Treatment

Title：Establishment on prediction model of surface performance for ultrasonic roll extrusion bearing ring and optimization on process parameters

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ClassificationCode：TG376.1

year,vol(issue):pagenumber：2021,46(3):118-125

Abstract：

In order to improve the surface performance of bearing ring strengthen by ultrasonic roll extrusion technology and realize the optimal control of process parameters, for bearing ring material of 42CrMo steel, the prediction model of radial basis function (RBF) neural network between surface performance and process parameters (rotation speed, feeding speed, amplitude and static pressure) was established by ultrasonic roll extrusion orthogonal test, and the significant influences of process parameters on the surface performance (surface roughness, residual stress and hardness) were analyzed by variance analysis method and Taguchi algorithm. Then, three sets of optimal combinations for process parameters were obtained, and the optimal combinations of process parameters were verified by experiments and prediction models. The results show that compared the optimal parameter combinations with the orthogonal test results, the maximum residual compressive stress and the hardness increase by 0.59% and 0.79% respectively, and the minimum surface roughness decreases by 12.9%.

Funds：

国家自然科学基金资助项目(U1804145);国家重点研究专项（2018YFB2000405）

刘志飞(1996-)，男，硕士研究生 E-mail：769240878@qq.com 通讯作者:王晓强（1972-），男，博士，教授 Email：wang_xq2002@163.com

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