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深入分析了各变形工艺参数对TB8合金固溶处理显微组织的影响规律,建立了固溶组织再结晶体积分数、平均晶粒尺寸与变形工艺参数间的神经网络预测模型。结果表明,冷却和热处理制度相同的条件下,变形温度、变形程度和应变速率等变形工艺参数对TB8钛合金形变且固溶处理后的显微组织有重要的影响,若想获得晶粒较为细小且均匀的组织,需要在合适的应变速率下适当提高变形程度和降低变形温度;人工神经网络的预测结果与实测结果的高度拟合,表明人工神经网络模型可以较为精确地预测TB8合金的显微组织随变形工艺参数的变化而变化的情况。以上研究工作为TB8合金热加工工艺的制定提供了更为科学的理论依据。
The effect of deformation parameters on the microstructure of solution treatment of TB8 alloy was deeply analyzed. The neural network prediction model of volume fraction of recrystallization solution, average grain size and deformation parameters was established. The results show that under the same conditions of cooling and heat treatment, deformation parameters such as deformation temperature, degree of deformation and strain rate have an important effect on the microstructure of TB8 titanium alloy after solution treatment. If the grain size is small And uniform structure, the deformation degree and the deformation temperature need to be appropriately increased at appropriate strain rate. The artificial neural network model can accurately predict the microstructure of TB8 alloy Changes in the organization with changes in the deformation process parameters. The above research work provides a more scientific theoretical basis for the development of TB8 alloy thermal processing technology.