Digital Image Correlation for Assessment of Bridges’ Technical State and Remaining Resource

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Structural Control & Health Monitoring Pub Date : 2024-09-04 DOI:10.1155/2024/1763285
Nadiia Kopiika, Yaroslav Blikharskyy
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Abstract

Bridges enable communications and transportation of goods nationally and internationally, underpinning economic and social activities, and thus they are pylons of our prosperity and mobility. Bridges worldwide are constantly subjected to physical wear, ageing, deterioration, hazards, environmental influences, and increased loading. Loss of performance and functionality of bridge structures would have a crucial impact on overall infrastructural resilience and would cause significant negative economic and social consequences. Monitoring their behaviour for different loading conditions relies on accurate estimations of the stress-strain state of various critical components and remaining capacities. These activities are of high importance for better planning and lifespan prolongation, that is, the extension of their service life and prevention of unforeseen collapses, in line with sustainability principles of well-informed maintenance. In many cases, access to the structure is limited or even impossible, which causes the need for the deployment of remote and contactless methods. One such innovative technique, which has recently attracted attention in scientific and practical applications, is the digital image correlation (DIC). DIC is a contactless approach applicable for obtaining the full field of strains and deformations of full-scale real structures. Although the DIC approach has been widely used in world engineering practice for monitoring bridges and has proved to be a reliable and accurate method, there is a lack of systematic integral review on previous practical applications, revealing limitations and perspectives. This is the main motivation and novelty of this study, which will describe selected case studies in which DIC was used on real full-scale bridge structures and propose improvements for the method.

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用于评估桥梁技术状态和剩余资源的数字图像相关性
桥梁为国内外的通信和货物运输提供了便利,是经济和社会活动的基础,因此也是我们繁荣和流动性的支柱。世界各地的桥梁不断受到物理磨损、老化、损坏、危险、环境影响和荷载增加的影响。桥梁结构性能和功能的丧失将对整个基础设施的恢复能力产生至关重要的影响,并将对经济和社会产生重大负面影响。对桥梁结构在不同荷载条件下的行为进行监测,有赖于对各种关键部件的应力应变状态和剩余承载能力进行精确估算。这些活动对于更好地规划和延长使用寿命(即延长使用寿命和防止意外坍塌)具有重要意义,符合明智维护的可持续性原则。在许多情况下,进入建筑结构的途径有限,甚至不可能,因此需要采用远程和非接触式方法。最近在科学和实际应用中备受关注的一项创新技术就是数字图像相关技术(DIC)。DIC 是一种非接触式方法,适用于获取全尺寸真实结构的全场应变和变形。尽管 DIC 方法已被广泛应用于世界桥梁监测工程实践中,并被证明是一种可靠而准确的方法,但目前还缺乏对以往实际应用的系统性整体回顾,以揭示其局限性和前景。这正是本研究的主要动机和新颖之处,它将描述在实际全尺寸桥梁结构中使用 DIC 的选定案例研究,并提出改进该方法的建议。
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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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