基于自适应改进行为人工鱼群算法的电磁系统优化设计

Optimization Design of Electromagnetic System Based on Adaptive Improved Behavior of Artificial Fish Swarm Algorithm

采用自适应改进行为人工鱼群算法,对电磁系统进行静态优化设计来减少材料的使用和降低生产成本。该算法利用人工鱼群算法的收敛快速性和较好的求取全局极值的能力,求解最优解的领域,然后利用该算法特有的自适应能力和优秀的人工鱼行为,获得最优解,大大提高求解速度和精度。建立了交流接触器电磁系统的静态优化设计的数学模型,求解静态约束条件,编制静态优化计算程序。最后,以CJ20-25型号交流接触器为例进行了优化设计。优化结果表明:在保证产品质量的前提下,优化后的产品有效地节省了材料,达到了降低产品成本的目的。

An adaptive improved behavior of artificial fish swarm algorithm was applied to the electromagnetic system of static optimization design to reduce the material and the cost of product. This algorithm uses rapid convergence and global optimization ability of the artificial fish swarm algorithm to solve the optimal solution domain. Then it uses the unique strong adaptive ability and excellent artificial fish behavior of this algorithm which greatly improves the calculation speed and precision to obtain the optimal solution. The article introduced the AC contactor electromagnetic system static optimization design matbematical model, solved the static constraint condition and developed the static optimization calculation program. Finally, the optimization design was carried out, taking C J20 - 25 AC eontactor as example. The results of the static optimization show that the improved static optimization electromagnetic system of the AC eontactor saves material effectively and reduces the cost of product on the premise of ensuring product quality.