大跨悬索桥MTMD抖振控制的参数优化

针对悬索桥抖振控制问题,建立有限元模型,应用神经网络和遗传算法对多重调频质量阻尼器(MTMD)进行双参数优化。以某大跨悬索桥为例,利用神经网络改进的谐波合成模拟方法(RBF-WAWS法)对脉动风速进行模拟,并换算成抖振力作用主梁上,通过时程分析及后处理获取主跨跨中横桥向响应值。将响应值的均方差作为优化目标函数,以MTMD总质量、个数及阻尼比作为优化变量和约束条件,采用神经网络拟合目标函数并应用改进的自适应遗传算法进行寻优。结果表明,优化后的MTMD能有效控制悬索桥在脉动风作用下的抖振响应,减振率达48%。提出的理论与计算方法对悬索桥中MTMD的设置及参数选取具有实际工程意义。

Parameter Optimization of Multiple Tuned Mass Damper Based on Long-span Suspension Bridge Damping Control

Based on the suspension bridge damping control,the finite element model is established while neural network and genetic algorithm is employed to achieve optimization on MTMD(Multiple Tuned Mass Damper)in the thesis.This paper mainly makes a study on a large span suspension bridge through the following three steps.Firstly,the random fluctuating wind is simulated by the superposition of harmonic method improved by the neural network and converted into the buffeting force applying to the beam,through which the lateral displacement of the bridge in mid span is achieved by time-history analysis and post-processing.Then,the root-mean-square of lateral displacement is considered as the optimal objective function and the total weight,the quantity and damping ratio of MTMD is taken as the optimization variables and constraints.Finally,the neural network is used to fit the objective function while the improved adaptive genetic algorithm is applied to obtain the optimal solution in the objective function.It shows that the optimized MTMD can control the buffeting response of the suspension bridge effectively under the action of fluctuating wind and the damping rate reaches 48%.Therefore,the theory and method in the thesis play a guiding role in setting up the suspension bridge MTMD and selecting parameters in actual projects.