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为了得到高速压铸过程中的最优工艺参数,用试验数据得到的各工艺参数范围作为神经网络的训练样本,建立压铸工艺参数(浇注温度、模具温度、高速充填速度)与凝固时间、二次枝晶臂间距、抗拉强度的非线性映射关系,并运用遗传算法对函数关系式中的压铸工艺参数寻优,从而获得最优的一组压铸工艺参数。在该工艺参数下,零件的成形质量最佳,凝固时间少,二次枝晶臂间距小,抗拉强度高。
In order to obtain the optimal process parameters during high-speed die-casting, the process parameters of the die-casting process parameters (pouring temperature, mold temperature, high-speed filling speed) and setting time were established by using the range of the process parameters obtained from the test data as training samples. Crystal arm spacing, tensile strength of the non-linear mapping, and the use of genetic algorithms to optimize the die casting process parameters in order to obtain the best set of die-casting process parameters. Under the process parameters, the forming quality of the parts is the best, the setting time is small, the spacing of the secondary dendrite arm is small, and the tensile strength is high.