State of the Art Review on Bridges Structural Health Monitoring (Model Testing)

Heiza, Khaled; Khalil, Ayman; Nawawy, Omar El

doi:10.21608/iccae.2016.43759

Cited by 4 publications

(2 citation statements)

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“…Numerous valuable studies have been conducted to investigate the reasons and how SHM systems are used to monitor bridges, which have stated the reasons (Figure 1) [21][22][23][24][25]. In addition to receiving and collecting information from bridges, SHM is also capable of evaluating, analyzing, and predicting obtained data in order to determine appropriate actions for raising and enhancing the capacity and life-span of bridges.…”

Section: Structural Health Monitoring (Shm) System For Bridgementioning

confidence: 99%

Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art

et al. 2022

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In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are making big changes to the way traditional structural health monitoring (SHM) is done. Also, the capacity, flexibility, and robustness of artificial intelligence (AI) techniques for solving complex real-world problems have led to an increasing interest in applying these methods to SHM systems of infrastructures in recent years. Therefore, an analytical evaluation of recent advancements in SHM for infrastructures appears to be important. The bridge is one of the significant transportation infrastructures where existing environmental and destructive variables can have a negative impact on the structure's life and health. The SHM system for bridges in different stages of their life cycle, such as construction, development, management, and maintenance, is seen as a complementary part of intelligent transportation systems (ITS). The main goal of this study is to look at how AI can be used to improve the current state of the art in data-driven SHM systems for bridges, including conceptual frameworks, advantages, and challenges, as well as existing approaches. This article presents an overview of the role of AI in data-driven SHM systems for bridges in the future. Finally, some potential research possibilities in AI-assisted SHM are also emphasized and detailed.

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Section: Structural Health Monitoring (Shm) System For Bridgementioning

confidence: 99%

Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art

et al. 2022

View full text Add to dashboard Cite

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“…In order to properly identify problems at a higher level in a hierarchical system, it is generally required to have some understanding of the lower levels. Each subsequent level's success may be affected by the prior levels' results in comparison to the one being completed [52][53][54]. Damage has been categorized in various novel ways by researchers [52,53] Level V (Damage prediction): After completing the previous four levels, this level assesses the bridge's remaining usable life or its viability status, depending on the situation.…”

Section: Defining and Identifying The Damagementioning

confidence: 99%

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

et al. 2022

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The challenges of urban administration are growing, as the population, automobiles, and cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A key feature of the “smart cities” of today is that they use cutting-edge technology in their infrastructure and services. With strategic planning, the smart city utilizes its resources in the most efficient manner. With reduced expenses and enhanced infrastructure, smart cities provide their residents with more and better services. One of these important urban services that can be very helpful in managing cities is structural health monitoring (SHM). By combining leading new technologies like the Internet of Things (IoT) with structural health monitoring, important urban infrastructure can last longer and work better. A thorough examination of recent advances in SHM for infrastructure is thus warranted. Bridges are one of the most important parts of a city’s infrastructure, and their building, development, and proper maintenance are some of the most important aspects of managing a city. The main goal of this study is to look at how artificial intelligence (AI) and some technologies, like drone technology and 3D printers, could be used to improve the current state of the art in SHM systems for bridges, including conceptual frameworks, benefits and problems, and existing methods. An outline of the role AI and other technologies will play in SHM systems of bridges in the future was provided in this study. Some novel technology-aided research opportunities are also highlighted, explained, and discussed.

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FBG sensors for seismic control and detection in extradosed bridges

Saad

2021

International Journal on Smart Sensing and Intelligent Systems

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Robust fiber Bragg grating (FBG) sensors network to civil engineering structures is presented as real-time monitoring deviation against seismic effects. The network is based on FBG sensors. The base element is a special type of chirped FBG that is validated. The developed network is applied in one of the two towers of concrete and extradosed type of Rades-La Goulette Bridge in Tunisia that in aggressive environment, to enhance the installed conventional structural health monitoring system (SHMS). Precisely, tilt influences of seismic parameters are calculated. Test procedure and obtained results are discussed.

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State of the Art Review on Bridges Structural Health Monitoring (Model Testing)

Cited by 4 publications

References 0 publications

Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art

Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art

The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges

FBG sensors for seismic control and detection in extradosed bridges

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