摘要
基于BP神经网络的理论和算法,建立了BP神经网络模型;通过拉伸实验测定了不同淬火温度下TC16合金的力学性能,使用建立的BP神经网络模型,对实验数据进行了训练和仿真,研究了TC16钛合金在不同淬火温度下的变形行为。结果表明,使用该BP神经网络模型可以得到很高的计算精度,预测误差在5%,该方法适用于TC16合金的进一步研究。
Based on the theory and algorithm of BP neural network, a BP neural network model was established, the mechanical properties of TC16 alloy were measured by tensile experiments and the experimental data were trained and simulated by the BP neural network model, the deformation behavior of TC16 titanium alloys was studied under different quenching temperature. The results show that the BP neural network model can get high calculation accuracy and its prediction errors are in 5%.This method is suitable for further research of TC16 alloy.
出处
《铸造技术》
CAS
北大核心
2013年第7期830-832,共3页
Foundry Technology
关键词
热处理
淬火
力学性能
TC16合金
heat treatment
quenching
mechanical properties
TC 16 alloy
