锻造变形均匀性的支持向量机模型及应用

Support vector machine model for uniformity of forging deformation and application

针对超大尺寸高强度钛合金棒材锻造成形过程中存在变形不均匀的难题,以物理热压缩模拟试验和数值模拟为基础,采用机器学习方法,建立了钛合金棒材锻造变形均匀性的支持向量机模型。结合锻造工艺参数的归一化处理,获得了锻造变形均匀性优化模型;提出了实际锻造温度和应变分布均匀性评价函数和锻造工艺参数的多目标优化模型;采用优化算法,获得了基于实际锻造温度和应变分布均匀性的锻造工艺参数。将上述模型应用于钛合金棒材的锻造过程,以锻造温度、锻造速度和压下量为优化变量,实际锻造温度与应变分布均匀性为优化目标,优化了直径Φ400mm的1300 MPa钛合金棒材7道次锻造工艺参数组合。

Aiming at the problem of non-uniformity in the forging process of high-strength titanium alloy bars with ultra large size,a sup-port vector machine model of forging deformation uniformity of titanium alloy bar was established by using machine learning method based on the physical thermal compression simulation tests and numerical simulation experiments.Combined with the normalization of forging process parameters,the optimization model of forging deformation uniformity was obtained.The evaluation function of the distribution uni-formity for actual forging temperature and strain and the multi-objective optimization model of forging process parameters were presented.The forging process parameters based on the distribution uniformity of actual forging temperature and strain were obtained by using optimi-zation algorithms.The above mentioned models were applied to the forging process of titanium alloy bars.Taking the forging temperature,forging speed and reduction amount as optimization variables,and the distribution uniformity of actual forging temperature and strain as op-timization objectives,the combination of the seven-pass forging process parameters of the 1300 MPa titanium alloy bars with the diameter ofΦ400 mm was optimized.