摘要
为了准确和快速确定最佳摩擦焊接工艺参数,提出了一种最小二乘支持向量机与鱼群算法相结合的摩擦焊接工艺参数优化方法。以摩擦时间、摩擦压力和顶锻压力3个主要摩擦焊接工艺参数为优化对象,焊接接头抗拉强度为优化目标,通过最小二乘支持向量机拟合优化对象与优化目标之间的复杂函数关系。首先进行焊接试验,以试验数据为样本对模型进行训练,然后用鱼群算法对模型进行优化,获得最佳摩擦焊接工艺参数。结果表明,该方法具有建模容易、求解快捷等优点,优化得到的工艺参数与正交回归优化的工艺参数相比,使焊接接头的抗拉强度提高了2.1%。
In order to determine friction welding technological parameters correctly and quickly, an optimization model for friction welding technological parameters based on least square support vector machine (LSSVM) and artificial fish-swarm algorithm (AFSA) was presented. With three friction welding technological parameters such as fiction pressure, upset pressure and fiction temperature as optimization parameters, welding joint tensile strength as optimization object, the nonlinear mapping relation between optimization parameters and optimization object was fitted by LSSVM. Firstly, experiments were taken to get data samples, and LSSVM model was established through data samples above. Then, the model was optimized by AFSA to get welding technological parameters. The results show that the construction model is easy, the optimization solution is quick, and the parameters optimized by this method make welding joint tensile strength increase by 2.1 % comparing with that parameters optimized by orthogonal regression method.
出处
《焊接学报》
EI
CAS
CSCD
北大核心
2008年第12期104-108,共5页
Transactions of The China Welding Institution
关键词
摩擦焊接
工艺参数
优化
最小二乘支持向量机
人工鱼群算法
friction welding
technological parameter
optimization
least square support vector machine
artificial fish-swarm algorithm
