锻压技术

基于遗传算法的冷锻压力机广义肘杆机构的多目标优化

英文标题：Multi-objective optimization on generalized knuckle mechanism in cold forging press based on Genetic Algorithm

作者：潘庆元李江国金魏李亚军

单位：北京机电研究所

分类号：TH122

出版年,卷(期):页码：2013,38(3):79-84

摘要：

建立了冷锻压力机广义肘杆机构的向量化运动模型，并以此为基础确定了由曲柄存在条件、极位传动角条件、摆杆限位条件、滑块侧向力不换向条件、下连杆最大偏角条件、下死点直线传力条件、工艺性条件和行程限定等组成的约束方程组。提出了“产品经济性”、最大扭矩、工作区速度和最大加速度等指标相结合的优化适应度函数，使用遗传算法计算得到了杆系参数的工程最优解。与原参数相比，最优解的综合性能提升了2.94%。

A vectorial motion model of generalized knuckle mechanism in a cold forging press was established, on the base of which, the constraint equations set containing crank existence conditions, transmission angle spacing conditions, pendulum limit conditions, slide lateral force non-commutation condition, nether-link maximum declination condition, bottom dead point(BDP) beeline force transmission condition, process conditions and the stroke limit were derived. A fitness function combining the “product economy (PE)”, the maximum torque, the work region velocity and the maximum acceleration was put forward, and the Genetic Algorithm(GA) was used to select the engineering optimal solution of the link system parameters. Compared with the original parameters, the combination property of the optimum solution has risen by 2.94%.

基金项目：

国家科技重大专项“高档数控机床与基础制造装备”资助项目(2009ZX04004071 )

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