基于滑窗OPTICS算法和DATA-SSI算法的桥梁模态参数智能化识别

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摘要针对现有基于数据驱动的随机子空间算法（Data-driven Stochastic Subspace Identification-DATA SSI）存在的不足，无法实现稳定图中真假模态的智能化筛选，提出了一种新的模态参数智能化识别算法。首先通过引入滑窗技术来实现对输入信号的合理划分，以避免虚假模态和模态遗漏现象的出现；其次通过引入OPTICS密度聚类算法（Ordering Points To Identify the Clustering Structure）实现稳定图中真实模态的智能化筛选，最后将所提算法运用于某实际大型斜拉桥主梁结构的频率和模态振型识别过程中。结果表明，所提改进算法识别的频率值结果与理论值（MIDAS有限元结果）以及实际值（现场动力特性实测结果）间的误差均在5%以内，且识别的模态振型图与理论模态振型图具有很高的相似性。

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	陈永高1
	钟振宇1
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	罗晓峰1
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关键词 ：桥梁结构, 随机子空间算法, 滑窗原理, 密度聚类算法, 稳定图

Abstract：In order to better identify the modal parameters of existing bridge structures. Moreover, in view of the shortcomings of the existing Data-driven Stochastic Subspace Identification(DATA SSI algorithm), which is unable to achieve automatic screening of true and false modes in the stability diagram. A new intelligent identification algorithm of modal parameters is proposed. Firstly, the sliding window technology is adopted to achieved the division of input signals, so as to avoid the false modes and modal omission as much as possible. Secondly, the Ordering Points To Identify the Clustering Structure (OPTICS) algorithm is used to fulfill the intelligent screening of the real modes in the stability diagram. Finally, the proposed algorithm is applied to a real large cable-stayed bridge for identifying the frequency and mode shapes of the main beam. The results show that the errors among the frequency value which is identified by the improved algorithm, the theoretical value (It means MIDAS finite element results) and the actual value (field dynamic characteristic measurement result) are within 5% separately, and the identified mode shape diagram has a high similarity with the theoretical mode shape diagram.

Key words： Bridge structure Stochastic Subspace Identification Sliding-window theory Density-based spatial clustering algorithm Stability diagram

收稿日期: 2023-05-25 出版日期: 2024-04-15

引用本文:

陈永高1，钟振宇1,2，罗晓峰1,2. 基于滑窗OPTICS算法和DATA-SSI算法的桥梁模态参数智能化识别[J]. 振动与冲击, 2024, 43(7): 18-29.
CHEN Yonggao1, ZHONG Zhenyu1,2, LUO Xiaofeng1,2. Intelligent identification of bridge modal parameters based on sliding-window OPTICS algorithm and DATA-SSI algorithm. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(7): 18-29.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2024/V43/I7/18

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