基于GA-NLP的剪刀式折叠桥梁展桥机构多目标优化设计

针对新型剪刀式折叠桥梁展桥机构的优化设计问题，首先建立了展桥机构的运动学和静力学模型，然后以展桥机构关键铰点位置和岸桥节与竖直方向所成夹角为优化设计变量，以展桥机构的空间位置为主要约束条件，以展桥油缸、连杆、关键铰点受力峰值最小为优化目标，通过正规化和加权处理构造了展桥机构多目标优化分析模型，并采用遗传算法（genetic algorithm, GA）和非线性规划(nonlinear programming, NLP)混合算法对该优化分析模型进行求解。最后，利用ADAMS（automatic dynamic analysis of mechanical systems，机械系统动力学自动分析）软件验证了展桥机构多目标优化分析模型的正确性。结果表明，优化后展桥油缸承载的拉力与推力峰值分别减小了57.9%和25.3%，连杆承载的拉力与压力峰值分别减小了26.1%和55.2%，展桥机构2个关键铰点受力峰值分别减小了23.5%和26.8%。研究结果可为展桥机构的改进设计提供理论依据。

Multi-objective optimization design of deployable mechanism of scissor folding bridge based on GA-NLP

Aiming at the optimization design of deployable mechanism of a new type of scissor folding bridge,the kinematics and statics models of the deployable mechanism were established at first.Then,the key hinge position of the deployable mechanism and the angle between the side bridge section and the vertical direction were selected as the variables for optimization design.The spatial position of the deployable mechanism was selected as the main constraint condition.Meanwhile,the optimization target was defined as minimizing the peak force of deployable bridge cylinder,linkage and the key hinge points.After the multi-optimization targets were normalized and weighted,the multi-objective optimization analysis model of the deployable mechanism was constructed.The genetic algorithm and nonlinear programming(GA-NLP)hybrid approach was used to solve the multi-objective optimization model.The correctness of the multi-objective optimization model of the deployable mechanism was verified by ADAMS software.The research results showed that the peak pulling force and pushing force of deployment mechanism cylinder decreased by 57.9%and 25.3%respectively.The peak pulling force and pressure of linkage decreased by 26.1%and 55.2%respectively,and the peak force of two key hinge points of deployable mechanism decreased by 23.5%and 26.8%respectively.The research results can provide a theoretical basis for the optimization design of the deployable mechanism.