混合遗传算法在注射机增力机构优化设计中的应用

Application of Hybrid Genetic Algorithms in Optimal Design of Force Increasing Mechanism of Injection Machines

对注射机五铰链斜排双曲肘增力机构进行了运动和力学特性分析,使用混合遗传算法对该增力机构进行了优化设计,该优化设计属于多目标函数优化问题,即以机构总长较小、机构行程较大和力的放大倍数较大为目标函数建立了优化数学模型。对合模力为1000kN的增力机构进行了实例计算,结果表明:与传统设计方法相比,机构总长减小5.26%,行程比增加6.19%,力的放大倍数增加16.05%;与简单遗传算法相比,机构总长减小1.7%,行程比增加2.49%,力的放大倍数增加1.11%。

Dynamic and mechanic analysis were carried out on a five hinged, incline arranged, and double elbowed force increasing mechanism on an injector. An optional mathematics model was formulated to perform an optimal design of the force increasing mechanism using hybrid genetic algorithms. The optimal design was aimed to decrease the total length of mechanism, increase the stroke ratio and increase the amplification of the force. A force increasing mechanism for 1 000 kN clamping was employed as a prototype. Compared with the traditional methods, the optimized total length of the mechanism decreased by 5.26 %, the stroke ratio increased by 6.19 % and the amplification of the force increased by 16.05 %, Compared with regular genetic algorithms, the total length of the mechanism decreased by 1.7 %, the stroke ratio increased by 2.49 % and the amplification of the force increased by 1.11%.