Intelligent identification of bridge modal parameters based on sliding-window OPTICS algorithm and DATA-SSI algorithm

被引：0
|
作者：
Chen Y. [1 ]
Zhong Z. [1 ,2 ]
Luo X. [1 ,2 ]
机构：
[1] School of Civil Engineering and Architecture, Zhejiang Industry Polytechnic College, Shaoxing
[2] College of Civil Engineering and Architecture, Zhejiang University, Hangzhou
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2024年 / 43卷 / 07期
关键词：
bridge structure; density clustering algorithm; sliding-window theory; stability diagram; stochastic subspace identification (SSI);
D O I：
10.13465/j.cnki.jvs.2024.07.003
中图分类号：
学科分类号：
摘要：
Here, aiming at shortcomings of existing data-driven stochastic subspace identification (DATA-SSI) algorithm and their being unable to realize intelligent screening of true and false modes in stability diagram, a new intelligent identification algorithm for modal parameters was proposed. Firstly, the sliding window technique was introduced to realize reasonable division of input signals, and avoid occurrence of false modes and mode omissions. Secondly, OPTICS (ordering points to identify clustering structure) density clustering algorithm was introduced to realize intelligent screening of real modes in stability diagram. Finally, the proposed algorithm was applied in modal frequencies and modal shapes identification process of a certain large cable-stayed bridge main girder structure. The results showed that errors among frequency values identified using the proposed improved algorithm and theoretical values (MIDAS finite element results) as well as actual values (on-site dynamic characteristics measurement results) are within 5%; the identified modal shapes have higher similarity to theoretical modal shapes. © 2024 Chinese Vibration Engineering Society. All rights reserved.
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页码：18 / 29
页数：11
相关论文
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