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采用DEFORM-3D软件对新开发的大型全纤维曲轴TR镦锻过程进行数值仿真,得到该曲轴单拐的成形载荷。针对该型号曲轴单拐的成形载荷过大,导致设备过载的现象,利用正交实验法讨论了对锻件成形载荷有重大影响的三个关键工艺参数:模具与锻件的摩擦因子μ、弯曲速度v和锻件的始锻温度T,得到了其对锻件成形载荷的影响规律。利用BP神经网络建立锻件最大成形载荷的计算模型,该模型比原来的有限元计算时间更短,提高了优化过程的效率。利用BP神经网络构建了主要影响因素对锻件最大成形载荷的响应面,并得到使成形载荷最优的设计参数范围。研究发现,μ和T的取值区间分别在0.2～0.4和1180～1200℃时,既能保证锻件顺利成形,又能降低成形载荷、保护设备。
The upsetting process of newly developed large-scale full-fiber crankshafts was numerically simulated by DEFORM-3D software to obtain the single-crank forming load of the crankshaft. According to the single crankshaft forming load of the model crankshaft is too large, leading to the phenomenon of equipment overload, the use of orthogonal experimental method discussed the forging forming load has a significant impact on the three key process parameters: die and forging friction factor μ, bending velocity v And forging forging temperature T, get its forging forming load law. The calculation model of maximum forming load of forging is established by BP neural network, which is shorter than the original finite element calculation and improves the efficiency of the optimization process. The response surface of the main influencing factors to the maximum forming load of the forging was constructed by using BP neural network, and the range of the design parameters to optimize the forming load was obtained. The results show that the values of μ and T range from 0.2 to 0.4 and from 1180 to 1200 ℃ respectively, which can not only ensure forging smooth forming but also reduce the forming load and protect the equipment.