提出了一种基于光学扫描和计算模型的结构健康监测方法

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
W. Flores-Fuentes, I. Y. Alba-Corpus, O. Sergiyenko, J. Rodríguez-Quiñonez
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引用次数: 0

摘要

本文提出了一种将动态三角扫描和车辆图像识别载荷估计相结合的桥梁位移连续监测方法。车辆-桥梁相互作用是一个非平稳动态过程参数,与理解桥梁的静态失稳行为具有高度相关性。当测量桥梁的结构空间坐标时,了解特定时间内桥梁上的荷载,可以将桥梁位移与车辆-桥梁相互作用的影响联系起来。为了验证观测到的桥梁位移是由于其运行性质还是由于其存在结构损伤,必须对这种相关性进行评估。所提出的方法是连续结构健康监测方法,基于在实验室环境中评估的三种方法的组合:(1)用于位移测量的三维光学扫描系统,(2)用于车辆-桥梁相互作用评估的载荷测量系统,以及(3)两个测量系统的数据相关性;在真实环境中的桥梁中实现,以收集它们的历史行为。总的来说,对于每种方法,都介绍了测量系统的原理、遵循的实验室实验方法和获得的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A structural health monitoring method proposal based on optical scanning and computational models
This article proposes a method for continuous bridge displacement monitoring combining the dynamic triangulation scanning and load estimation by vehicle image recognition. The vehicle–bridge interaction is a non-stationary dynamic process parameter of high relevance to understanding the static instability behavior of bridges. The knowledge of the load on a bridge in the specific time when its structural spatial coordinates are measured allows correlating the bridge displacement with the effect of vehicle–bridge interaction. The evaluation of such correlation is mandatory in order to verify if the observed bridge displacement is due to the nature of its operation or due to it is presenting structural damage. The proposed method is continuous structural health monitoring method, based on the combination of three approaches evaluated at laboratory environment: (1) a three-dimensional optical scanning system for displacement measurement, (2) a load measurement system for vehicle–bridge interaction assessment, and (3) a two-measurement systems data correlation; to be implemented in bridges at a real environment to collect their historical behavior. Overall, for each approach, the measurement systems’ principles, the laboratory experimental methodology followed, and results obtained are presented.
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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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