基于计算机视觉的静态实测有限元模型更新方法的实验研究

Lanxin Luo, Ye Xia, Ao Wang, Limin Sun
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引用次数: 0

摘要

准确的有限元模型在结构健康监测中起着重要的作用。在传统的静态有限元模型更新(FEMU)过程中,需要中断交通的加载试验来获取静态数据,这很不方便。本文提出了一种基于计算机视觉技术和WIM系统的静态FEMU方法,避免了上述缺陷。首先,利用计算机视觉确定载荷位置,白车身系统确定载荷值,进行交通荷载作用下的静态响应仿真;其次,利用信号处理技术从监测数据中提取实测静态数据。第三,利用粒子群算法进行FEMU分析。最后,在具有SHM系统的桥梁模型上进行了实验,结果验证了该方法的方便性和准确性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer Vision-based Finite Element Model Updating Method Using Measured Static Data: An Experimental Study
Accurate FE models play an important role in structure health monitoring (SHM). In the traditional static finite element model updating (FEMU) process, loading tests interrupting the traffic are required for obtaining static data, which is inconvenient. This paper proposes a novel static FEMU method based on computer vision technology and WIM system, avoiding the mentioned defects. Firstly, the static response simulation under traffic load is carried out with the computer vision determining the load location and the BIW system deciding the load value. Secondly, signal processing technology extracts the measured static data from the monitoring data. Thirdly, the PSO method is utilized to perform the FEMU. An experiment is designed on a bridge model with an SHM system, and results verify the convenience and accuracy of the proposed method
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