基于粒子群算法的虚拟质量优化布置研究  

Research on Virtual Mass Optimization layout Based on Particle Swarm Optimization

作　　者：周润芳 ZHOU Run-fang(Shanxi Agricultural University,College of Urban and Rural Construction,Jinzhong 030600 China)

机构地区：[1]山西农业大学城乡建设学院,山西晋中030600

出　　处：《自动化技术与应用》2025年第2期48-51,共4页Techniques of Automation and Applications

基　　金：山西农业大学青年科技创新基金(2020QC21)。

摘　　要：在结构上附加虚拟质量的损伤识别方法可以避免附加真实质量的局限,并增加测试模态数据量。损伤识别的精度与虚拟质量的布置方案有很大关系,因此提出连续粒子群算法对虚拟质量的位置进行优化,并通过简支梁结构的数值模拟验证该方法的有效性。结果表明,应用粒子群算法进行虚拟质量的优化,具有操作简单、搜索效率高的优点,得到的优化方案能够准确识别结构的损伤。The damage identification method of adding virtual mass to the structure can avoid the limitation of adding real mass and increase the amount of test modes.The accuracy of damage identification is closely related to the layout of virtual mass.Therefore,this pa-per proposes a continuous Particle Swarm Optimization algorithm to optimize the location of virtual mass,and verifies the effec-tiveness of this method through the numerical simulation of simply supported beam structure.The results show that the applica-tion of particle swarm optimization to optimize the virtual mass is easy to use and highly efficient,and the obtained optimization scheme can accurately identify the structural damage.

关 键 词：损伤识别 粒子群算法 灵敏度矩阵 

分 类 号：TP391.98[自动化与计算机技术—计算机应用技术]