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Investigation on the Processing-Properties of Hot Deformed TA15 Titanium Alloy via Support Vector Regression

机译:基于支持向量回归的热变形TA15钛合金加工性能研究

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According to an experimental dataset on the tensile strength and elongation of TA15 titanium alloy under different hot deformation process parameters including temperature, strain, strain rate and cooling condition, support vector regression (SVR) combined with particle swarm optimization (PSO) for its parameter optimization, is proposed to establish a model for prediction of the tensile strength and elongation of hot deformed TA15 titanium alloy. For tensile strength, the mean absolute percentage error (MAPE) achieved by SVR is 0.65% and 0.68% for the training and test set, respectively. At the same time, the MAPE for elongation achieved by SVR is 1.51% and 3.36% for the training and test set, respectively. The MAPEs for both tensile strength and elongation achieved by SVR are much smaller than those of BPNN by using identical training and test samples. Accordingly, the established SVR model was adopted to illustrate the relationships among tensile strength, elongation, and the process parameters. From the 3D surface of tensile strength vs. temperature and strain rate, it is found that to reach a higher tensile strength, a strain rate lower than 0.01s~(-1) is required, and a lower strain will be helpful for achieving the maximum elongation. These suggest that SVR as a novel approach has a theoretical significance and potential practical value in fabrication of TA15 titanium alloy with desired properties.
机译:根据TA15钛合金在不同热变形过程参数(包括温度,应变,应变速率和冷却条件)下的拉伸强度和伸长率的实验数据集,结合粒子群优化(PSO)和支持向量回归(SVR)进行参数优化提出建立模型以预测热变形TA15钛合金的拉伸强度和伸长率。对于拉伸强度,对于训练集和测试集,SVR实现的平均绝对百分比误差(MAPE)分别为0.65%和0.68%。同时,对于训练集和测试集,通过SVR实现的MAPE伸长率分别为1.51%和3.36%。通过使用相同的训练和测试样品,通过SVR获得的MAPE的抗张强度和伸长率均远小于BPNN。因此,采用建立的SVR模型来说明拉伸强度,伸长率和工艺参数之间的关系。从抗拉强度与温度和应变率的3D表面可以看出,要达到较高的抗拉强度,需要的应变率应低于0.01s〜(-1),而较低的应变将有助于获得较高的抗拉强度。最大伸长率。这些表明,SVR作为一种新颖的方法,在具有所需性能的TA15钛合金的制造中具有理论意义和潜在的实用价值。

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