不完整模态数据下基于布谷鸟算法的结构损伤识别研究  

Structural damage detection based on the Cuckoo Algorithm under incomplete modal data

作　　者：郑昱 马青云 邢云霞 李萌 Zheng Yu;Ma Qingyun;Xing Yunxia;Li Meng(Sanmenxia Tobacco Monopoly Bureau,Sanmenxia Henan 472400,China)

机构地区：[1]三门峡市烟草专卖局,河南三门峡472400

出　　处：《山西建筑》2025年第1期70-74,共5页Shanxi Architecture

摘　　要：鉴于安装在结构上的少量传感器难以获得完整的模态数据,文章提出一种使用不完整模态数据来定位和量化结构损伤的有效方法。首先,采用一种改进的缩聚系统方法来匹配有限元模型和实际测量中的自由度差异,从而解决模态空间不完整性问题。然后,利用不完整模态数据获得的结构柔度矩阵计算结构的静态位移。最后,利用结构的静态位移建立损伤优化函数,并采用布谷鸟算法进行求解。通过数值模拟和试验验证了所提方法的有效性和鲁棒性。数值和试验结果表明,在测量传感器数量有限的情况下,所提出的损伤识别方法仍具有高效且稳定的性能。In this paper,a novel and effective damage diagnosis algorithm is proposed to localize and quantify structural damage using incomplete modal data,considering the existence of some limitations in the number of attached sensors on structures.Firstly,an Improved Reduction System(IRS)method is adopted to match the degree of freedom differences between the finite element model and the actual measurements,thereby solving the problem of modal space incompleteness.Then,the structural flexibility matrix obtained from the incomplete modal data is used to calculate the static displacement of the structure.Finally,a damage optimization function is established using the static displacement of the structure and solved using the Cuckoo Algorithm.The effectiveness and robustness of the proposed method are verified through numerical simulation and experiments.The numerical and experimental results indicate that the proposed damage identification method still has exhibits efficient and stable performance even with a limited number of measurement sensors.

关 键 词：损伤识别 不完整模态数据 柔度矩阵 布谷鸟算法 

分 类 号：TU317[建筑科学—结构工程]