首页|基于ACBO-GM联合方法的高维变量结构模型修正

基于ACBO-GM联合方法的高维变量结构模型修正

扫码查看
原文链接
  • 万方数据
  • 维普
工程结构模型修正常面临变量维度高、非线性程度强等现实问题，其模型修正的精度和效率受到严重影响，为改善这一不足，提出基于改进物体碰撞算法(Advanced Colliding Bodies Optimization，ACBO)和高斯白噪声扰动(Gaussian-white-noise Mutation，GM)的联合修正方法。在联合方法中，ACBO实现从传统的"一对一"到"优对多"的碰撞模式的转变，GM则用于保证碰撞过程中种群的多样性，可有效提升结构模型修正效率。基于一系列测试函数，对比分析标准物体碰撞算法(Colliding Bodies Optimization，CBO)和联合优化方法的优化性能;给出基于ACBO-GM联合方法的修正流程，并将其应用于钢框架修正算例和悬臂梁修正实例，对比研究基于联合修正方法与基于遗传算法(Genetic Algorithm，GA)的修正精度和效率。研究表明，ACBO-GM联合优化方法在精度和效率方面都明显优于传统的CBO方法，该优化方法的可行性得到验证;基于ACBO-GM联合方法在钢框架和悬臂梁两个工程结构修正案例中的应用，其修正精度均与基于GA方法的精度一致，但修正效率显著优于基于GA的修正方法。
Research on Model Updating of Engineering Structures with High Dimensional Variables Based on ACBO-GM Combined Methodology
Model updating of engineering structures is usually facing the practical problems of high dimensional variables and strong nonlinearity,which seriously affects the accuracy and efficiency of model updating.In order to solve the problems,a combined method of advanced colliding bodies optimization(ACBO)and Gaussian-white-noise mutation(GM)is proposed.In this method,the ACBO is used to realize the transition from the traditional″one to one″ pattern to″optimal to many″ collision pattern,and the GM is used to ensure the diversity of population during the collision process.Hence,the efficiency of structural model updating is improved greatly.Based on a series of test functions,the optimization performances of the standard colliding bodies optimization(CBO)algorithm and the combined approach are analyzed and compared.The updating process based on ACBO-GM combined method is introduced,and the proposed method is applied to a steel frame and a cantilever beam.The updating performances such as accuracy and efficiency of the combined method and the genetic algorithm(GA)are compared.The results show that the ACBO-GM combined method is superior to the traditional CBO method in both accuracy and efficiency,which verifies the feasibility of the proposed method.Furthermore,the applications of ACBO-GM combined method to aforementioned two engineering structures indicate that the accuracy of this method is essentially the same as that of GA,but the efficiency is much higher than that of GA.

vibration and waveadvanced colliding bodies optimizationGaussian-white-noise mutationmodel updatingcombined optimization methodgenetic algorithm

夏志远、王友、唐柏鉴、周广东、史慧媛

展开 >

苏州科技大学 土木工程学院,江苏 苏州 215011

河海大学 土木与交通学院,南京 210098

振动与波 改进物体碰撞算法 高斯白噪声扰动 模型修正 联合优化方法 遗传算法

国家自然科学基金资助项目国家自然科学基金资助项目江苏省自然科学基金资助项目江苏省科协青年科技人才托举工程资助项目苏州市建设系统科研资助项目(2021)

5220818852108236BK202009862021-077

2024

10.3969/j.issn.1006-1355.2024.04.002

噪声与振动控制
中国声学学会

噪声与振动控制

CSTPCD北大核心
影响因子：0.622
ISSN：1006-1355
年,卷(期)：2024.44(4)