Investigation on the Processing-Properties of Hot Deformed TA15 Titanium Alloy via Support Vector Regression
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.
TA15 titanium alloy tensile strength elongation support vector machines regression analysis prediction
J.F. Pei C.Z. Cai X.J. Zhu G.L. Wang
Department of Applied Physics, Chongqing University, Chongqing 400044, China
国际会议
11th IUMRS International Conference in Asia(第十一届国际材联亚洲材料大会 IUMRS-ICA 2010)
青岛
英文
134-143
2010-09-25（万方平台首次上网日期，不代表论文的发表时间）