基于改进遗传算法的超高层建筑动力传感器优化布置  

Optimization of Dynamic Sensor Placement in Super High-Rise Buildings Based on Improved Genetic Algorithm

作　　者：李浩 赵东拂 王延璨[1] Li Hao;Zhao Dongfu;Wang Yancan(School of Civil and Transportation Engineering,Beijing University of Civil Engineering and Architecture,Beijing,China;Engineering Structure and New Materials of Beijing University Engineering Research Center,Beijing,China;Beijing Advanced Innovation Center for Future Urban Design,Beijing University of Civil Engineering and Architecture,Beijing,China;Multi-Functional Shaking Tables Laboratory,Beijing University of Civil Engineering and Architecture,Beijing,China;Beijing Energy Conservation&Sustainable Urban and Rural Development Provincial and Ministry Co-construction Innovation Center,Beijing,China)

机构地区：[1]北京建筑大学土木与交通工程学院,北京 [2]工程结构与新材料北京市高等学校工程研究中心,北京 [3]北京未来城市设计高精尖创新中心,北京 [4]北京建筑大学大型多功能振动台阵实验室,北京 [5]北京建筑大学北京节能减排与城乡可持续发展省部共建协同创新中心,北京

出　　处：《科学技术创新》2025年第11期136-139,共4页Scientific and Technological Innovation

基　　金：国家自然科学基金项目(51378045)。

摘　　要：为实时监测超高层建筑结构动力特性,对超高层建筑结构动力传感器优化布置进行了研究。利用简化模型代替精细化模型进行优化计算,提出改进遗传算法进行优化布置。按照层间剪切模型原理对精细化模型进行简化,简化后的模型与精细化模型各阶自振频率大致一致,误差不超过5%;利用改进后的遗传算法以基于模态保证准则(MAC)为目标函数进行传感器优化布置。对改进前后的遗传算法计算结果进行对比,结果表明:改进后的遗传算法解决了遗传算法陷入局部最优的问题,且能够用较少的遗传代数得到测点布置方案,提高了计算效率。In order to facilitate real-time monitoring of the dynamic properties of super high-rise structures,a study is conducted on the optimal placement strategy of dynamic sensors.The simplified model was used in lieu of the detailed finite element model for optimization,and an improved genetic algorithm was introduced for this purpose.Initially,a refined finite element model of the structure was established.Subsequently,the model was simplified according to the interstory shear model,with the natural frequencies of the simplified model aligning closely with those of the detailed model,with a deviation of less than 5%.The improved genetic algorithm,employing the Modal Assurance Criterion(MAC)as the objective function,was used for sensor optimization.A comparison of the pre-and post-improvement results shows that the enhanced algorithm effectively addresses the issue of convergence to local optima and is able to produce an optimal sensor placement with fewer generations,improving computational efficiency in sensor layout planning.

关 键 词：超高层建筑 简化模型 动力传感器优化布置 改进遗传算法 

分 类 号：TU978[建筑科学—建筑技术科学]