Effects of stochastic traffic flow on modal parameter identification of beam type bridges

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Oct.2023, Vol.46 No.10: 1380-1387

DOI: 10.3969/j.issn.1003-5060.2023.10.013

Authors

HE Wenyu $ ^{1,2} $, GU Linqing $ ^{1} $, REN Weixin $ ^{3} $, LI Miao $ ^{4} $

(1. School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, China; 2. Anhui Engineering Laboratory for Infrastructural Safety Inspection and Monitoring, Hefei 230009, China; 3. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, China; 4. College of Civil Engineering, Hunan City University, Yiyang 413000, China)

Abstract and Keywords

Abstract: In the existing bridge modal parameter identification, the stochastic traffic flow is regarded as a part of the ambient excitation, and the influence of additional mass of vehicles is ignored. The damage induced changes in modal parameters will be masked by the changes induced by stochastic traffic flow, thus affecting the accuracy of subsequent damage detection. In this paper, the cellular automaton model is used to simulate the specific position of stochastic traffic flow on the bridge. The traffic flow information is loaded into finite element model to calculate the dynamic response of the bridge. Then, taking simply supported beams and continuous beams as examples, the stochastic subspace identification method is used to identify the modal parameters, and the differences in the vehicle-bridge system, bridge with local damage, and the undamaged bridge are compared. The influences of stochastic traffic flow, parked vehicle and single moving vehicle on the identification results of frequencies and mode shapes are investigated. The results indicate that both local damage and stochastic traffic flow will reduce the identified frequencies and change the mode shapes, so it is essential to consider the influence of stochastic traffic flow and eliminate its effects in modal parameter identification under ambient excitation.

Keywords: stochastic traffic flow; cellular automaton model; parameter identification; stochastic subspace identification

作者信息

贺文宇 $ ^{1,2} $，谷林清 $ ^{1} $，任伟新 $ ^{3} $，李苗 $ ^{4} $

（1. 合肥工业大学土木与水利工程学院，安徽合肥 230009；2. 安徽省基础设施安全检测与监测工程实验室，安徽合肥 230009；3. 深圳大学土木与交通工程学院，广东深圳 518061；4. 湖南城市学院土木工程学院，湖南益阳 413000）

摘要和关键词

摘要: 现有的桥梁模态参数识别中,将随机车流视为一部分环境激励,忽略了车辆附加质量的影响,桥梁由于损伤导致的模态参数变化会被随机车流所引起的变化掩盖,从而影响后续损伤识别的正确性。文章利用元胞自动机模型模拟作用在桥梁上的随机车流的具体位置,将车流信息加入有限元模型,计算桥梁的动力响应;以简支梁和连续梁为例,应用随机子空间法识别模态参数,并比较车-桥系统、局部损伤桥梁和无损桥梁的模态参数差异;对比分析采用随机车流、单个移动车辆和静置车辆3种方式模拟车流时对频率与振型识别结果的影响。结果表明,桥梁局部损伤和随机车流均会导致识别的频率减小和振型改变,环境激励下的模态参数识别中必须考虑随机车流的作用并剔除其影响。

关键词: 随机车流；元胞自动机模型；参数识别；随机子空间法

Funding

国家自然科学基金资助项目（51878234；52378298）；安徽省杰出青年基金资助项目（2208085J20）；湖南省自然科学基金资助项目（2021JJ50145）；湖南省教育厅科学研究优秀青年资助项目（19B106）和深圳市科技创新委员会孔雀团队资助项目（KQTD20180412181337494）

合肥工业大学学报(自然科学版)

Navigation