蠕变时效成形工艺参数多目标优化

Multi-objective Optimization of Processing Parameters for Creep Aging Forming via Particle Swarm Algorithm

提出了一种综合运用试验设计、响应曲面法及多目标优化的工艺参数优化方法,以成形效率和时效后材料的屈服强度为试验指标,以时效温度、时效时间和应力为试验变量,按Box-Behnken试验设计方案进行试验;利用试验结果构造试验指标和试验变量间的响应曲面并对其分析;结合响应曲面建立多目标优化模型;运用基于动态目标加权的具有量子行为的粒子群算法得到Pareto最优解集;提出一种最小归一化距离选解法,从非劣解集中选出最优解,得到综合最优工艺解187.9℃、6.42 h、250 MPa。按优化前后的工艺参数进行单曲率蠕变时效成形试验,相比优化前,成形效率由14.0%提高到19.4%,屈服强度由442.354 MPa提高到451.786 MPa,两个目标同时得到了优化,验证了工艺参数优化方法的有效性。

An optimization method for processing parameters is presented, which is a comprehensive applying for experimental design, response surface method and multi-objective optimization. Taking the forming efficiency and the yield strength as the optimization indexes, aging temperature, aging time and stress as the optimization variables, the experiments are conducted according to Box-Behnken design principle. Then the response surface models are constructed based on the experimental results, and the multi-objective optimization model is further established. The Dynamic weighted aggregation based on the quantum-behaved particle swarm optimization algorithm is introduced to provide the designer with a set of Pareto optimal solutions, a minimum normalized distance method has been presented to select the optimal solution and the corresponding processing parameters （ 187.9 ℃, 6.42 h, 250 MPa） are the comprehensive optimal parameters. Tension of creep aging have been carried out with the parameters pre-and post-optimization, the results show that the forming efficiency increase from 14.0% to 19.4% and the yield strength increase from 442.354 MPa to 451.786 MPa, which prove the present processing parameter optimization method for creep aging forming is effective.