A Particle Swarm Optimization Algorithm with Sigmoid Increasing Inertia Weight for Structural Damage Identification

被引：4
|
作者：
Chen, Zhen [1 ,2 ]
Wang, Yaru [1 ]
Chan, Tommy H. T. [2 ]
Li, Xiaoke [1 ]
Zhao, Shunbo [1 ,3 ]
机构：
[1] North China Univ Water Resources & Elect Power, Sch Civil Engn & Commun, Zhengzhou 450045, Peoples R China
[2] Queensland Univ Technol QUT, Sch Civil & Environm Engn, Brisbane, Qld 4000, Australia
[3] North China Univ Water Resources & Elect Power, Collaborat Innovat Ctr Efficient Utilizat Water R, Zhengzhou 450046, Peoples R China
来源：
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 07期
基金：
中国国家自然科学基金;
关键词：
structural damage identification; particle swarm optimization; inertia weight; identification accuracy; ADAPTATION;
D O I：
10.3390/app12073429
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
In this study, a particle swarm optimization with a sigmoid increasing inertia weight (SIPSO) algorithm is proposed for structural damage identification based on the optimization of structural vibration response constraints. In view of the existing problems for particle swarm optimization algorithms used for structural damage identification, such as low accuracy of damage identification and easy misjudgment of damage location, the sigmoid increasing inertia weight is introduced to improve the global and local search ability of the algorithm. Simulation results show that the parameters of the sigmoid increasing inertia weight have a significant effect on the performance of the SIPSO algorithm for structural damage identification. Compared with similar improved particle swarm optimization algorithms, the SIPSO algorithm has some advantages of fast convergence speed, high identification accuracy, and strong robustness ability in structural damage identification.
引用
收藏
页数：20
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