考虑环境因素的桥梁动力学特性识别方法

doi:10.3969/j.issn.1674-0696.2024.11.03

重庆交通大学学报（自然科学版） ›› 2024, Vol. 43 ›› Issue (11): 18-26.DOI: 10.3969/j.issn.1674-0696.2024.11.03

• 交通基础设施工程 • 上一篇

考虑环境因素的桥梁动力学特性识别方法

李阿坦1，朱逸尘2，张立奎1，熊文2，赵先民1

(1. 安徽交控道路养护有限公司安徽合肥 236000； 2. 东南大学交通学院江苏南京 211189)

收稿日期:2024-03-01 修回日期:2024-09-24 发布日期:2024-11-27
作者简介:李阿坦(1975—)，男，安徽巢湖人，高级工程师，主要从事路桥工程方面的研究。E-mail:343889340@qq.com 通信作者：朱逸尘(1992—)，男，江苏苏州人，副研究员，博士，主要从事结构健康监测方面的研究。E-mail:zhuyichen@seu.edu.cn
基金资助:
国家自然科学基金青年科学基金项目（52208150）；江苏省基础研究计划项目青年基金项目（BK20220853）；安徽省交通控股集团有限公司科技项目（JKKJ-2021-02）

Identification Method of Bridge Dynamic Characteristics Considering Environmental Factors

LI Atan1, ZHU Yichen2, ZHANG Likui1, XIONG Wen2, ZHAO Xianmin1

(1. Anhui Transportation Holding Group Road Maintenance Co., Ltd., Hefei 236000, Anhui, China; 2. School of Transportation, Southeast University, Nanjing 211189, Jiangsu, China)

Received:2024-03-01 Revised:2024-09-24 Published:2024-11-27

摘要/Abstract

摘要： 在长期结构健康监测（SHM）中，运营模态分析（OMA）技术通常用于识别结构的动力学特性（桥梁固有频率和阻尼比）。然而，传统的OMA方法没有考虑环境变化的影响，这会影响结构参数识别的准确性。数据驱动模型虽然能够评估和预测环境变化趋势，但无法反映结构参数的物理意义。针对上述问题，笔者提出了一种考虑环境因素的桥梁动力学特性识别方法，可将运营模态分析与数据驱动模型相结合，在考虑环境变化的同时识别动力学参数，采用了贝叶斯概率框架，允许将数据中的不确定性和相关性纳入模型并通过模拟数据验证了该方法的合理性，还将其应用于一座大跨度悬索桥的吊索监测数据。结果表明：该方法可以在不同温度条件下提供较为一致的模态参数估计，同时所识别出的温度相关参数均在所预测的0.95置信区间内，并与预先发现的温度影响趋势一致，该方法能够在考虑环境因素的同时有效识别桥梁动力学特性。

关键词: 桥梁工程；动力学特性识别；运营模态分析；结构健康监测；高斯过程；贝叶斯概率框架

Abstract: In long-term structural health monitoring (SHM), operational modal analysis (OMA) techniques are commonly used to identify the dynamic characteristics of structures, i.e., the bridge natural frequency and damping ratio. However, traditional operational modal analysis methods do not consider the effects of environmental changes, which can affect the accuracy of structural parameter identification. Data-driven models are capable of assessing and predicting environmental trends, but they can’t reflect the physical meaning of structural parameters. To address these issues, a method for identifying the dynamic characteristics of bridges considering environmental factors was proposed, which combined operational modal analysis with data-driven models to identify dynamic parameters while considering environmental changes. Bayesian probabilistic framework was employed and the uncertainty and correlation in the data were incorporated into the proposed model. The rationality of the proposed method was validated through a simulated data example and applied it to the suspension cable monitoring data of a large-span suspension bridge. The results show that the proposed method can provide more consistent modal parameter estimation under different temperature conditions, while the identified temperature-related parameters are all within the predicted 0.95 confidence interval and are consistent with the pre-discovered trends of temperature effects. It is illustrated that the proposed method can effectively identify the dynamic characteristics of bridges while considering environmental factors.

Key words: bridge engineering; identification of dynamic properties; operational modal analysis; structural health monitoring; Gaussian processes; Bayesian probabilistic frameworks

中图分类号:

U447

李阿坦1，朱逸尘2，张立奎1，熊文2，赵先民1. 考虑环境因素的桥梁动力学特性识别方法[J]. 重庆交通大学学报（自然科学版）, 2024, 43(11): 18-26.

LI Atan1, ZHU Yichen2, ZHANG Likui1, XIONG Wen2, ZHAO Xianmin1. Identification Method of Bridge Dynamic Characteristics Considering Environmental Factors[J]. Journal of Chongqing Jiaotong University(Natural Science), 2024, 43(11): 18-26.

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考虑环境因素的桥梁动力学特性识别方法

Identification Method of Bridge Dynamic Characteristics Considering Environmental Factors

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