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将TC6钛合金经过不同热暴露工艺处理后,测得其富氧α层的厚度。利用BP人工神经网络建立富氧α层的厚度与热暴露工艺(热暴露温度、保温时间)之间的关系网络模型。结果表明:所建的模型可以很好的预报不同热暴露工艺下富氧α层厚度,而且还可以通过富氧α层厚度得到最优的热暴露工艺。建立了富氧α层厚度为50μm热暴露工艺临界图以便指导生产实践。
TC6 titanium alloy after different heat exposure process, measured the thickness of its oxygen-rich α layer. The BP artificial neural network was used to establish a network model of the relationship between the thickness of oxygen-enriched α layer and the thermal exposure process (thermal exposure temperature and holding time). The results show that the proposed model can predict the thickness of oxygen-enriched α-layer under different heat-exposure processes and obtain the optimal thermal exposure through the thickness of oxygen-enriched α-layer. Oxygen-rich α-layer thickness of 50μm thermal exposure process critical map in order to guide the production practice.