【摘要】 采用人工神经网络（ANN）的方法，研究挤压比、挤压比压、挤压温度和挤压速率对喷射成形TiC_p/ZA35复合材料力学性能的影响，建立了TiC_p/ZA35复合材料热挤压的人工神经网络模型。模型的输入参数为挤压比、挤压比压、挤压温度和挤压速率，输出参数为复合材料的抗拉强度。该模型可以仿真TiC_p/ZA35复合材料在不同热挤压工艺参数下的力学性能，也可以优化热挤压工艺参数，模型结果与实验结果误差小于1.8%，拟合率为0.986。推荐热挤压工艺优化参数为：挤压比22，挤压比压415 MPa，挤压温度315℃，挤压速率8 mm·s^-1，此工艺条件下复合材料的抗拉强度为486.7 MPa。热挤压间接对复合材料进行了时效处理，材料晶内析出晶须状和颗粒状的MnAl6强化相。弥散强化和位错强化作用使热挤压喷射沉积TiCp/ZA35复合材料较未挤压复合材料抗拉强度提高38.3%。更多还原

【Abstract】 The effects of heat extrusion processing of spray forming TiC_p/ZA35 composites on extrusion ratio, extrusion specific pressure, extrusion temperature and extrusion rate had been studied by artificial neural network（ANN）. The artificial neural network model was created for heat extrusion processing. The input parameters of the ANN model were extrusion ratio, extrusion specific pressure, extrusion temperature and extrusion rate. The output of the ANN model was ultimate tensile strength. The model can be used for the prediction of properties of spray forming TiC_p/ZA35 composites as functions of processing parameters. It can also be used for the optimization of the processing parameters. The ANN results are in good agreement with experimental phenomena, the biggest relative error and coincidence rate is less than 1.8% and 0.986. The optimized heat extrusion ratio, extrusion specific pressure, extrusion temperature and extrusion rate are 22415 MPa, 315 ℃ and 8 mm·s^-1 respectively, and the tensile strength of spray forming TiC_p/ZA35 composites is 486.7 MPa. The reinforcement phase MnAl6 whisker or particle is precipitated in the grains due to the indirect aging treatment of composites by hot extrusion. Dispersion strengthen and dislocation strengthen contribute a combination factor to increase the room temperature mechanical properties of the hot extruded TiC_p/ZA35 composites, which is 38.3% higher than that of TiC_p/ZA35 composites without heat extrusion.更多还原