• Smart Structures and Systems
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• v.5 no.4
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• pp.369-379
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• 2009

The sudden collapse of Interstate 35 Bridge in Minneapolis gave a wake-up call to US municipalities to re-evaluate aging bridges. In this situation, structural health monitoring (SHM) technology can provide the essential help needed for monitoring and maintaining the nation's infrastructure. Monitoring long span bridges such as cable-stayed bridges effectively requires the use of a large number of sensors. In this article, we introduce a probabilistic approach to identify optimal locations of sensors to enhance damage detection. Probability distribution functions are established using an artificial neural network trained using a priori knowledge of damage locations. The optimal number of sensors is identified using multi-objective optimization that simultaneously considers information entropy and sensor cost-objective functions. Luling Bridge, a cable-stayed bridge over the Mississippi River, is selected as a case study to demonstrate the efficiency of the proposed approach.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.505-524
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• 2010

Wireless structural monitoring systems consist of networks of wireless sensors installed to record the loading environment and corresponding response of large-scale civil structures. Wireless monitoring systems are desirable because they eliminate the need for costly and labor intensive installation of coaxial wiring in a structure. However, another advantageous characteristic of wireless sensors is their installation modularity. For example, wireless sensors can be easily and rapidly removed and reinstalled in new locations on a structure if the need arises. In this study, the reconfiguration of a rapid-to-deploy wireless structural monitoring system is proposed for monitoring short- and medium-span highway bridges. Narada wireless sensor nodes using power amplified radios are adopted to achieve long communication ranges. A network of twenty Narada wireless sensors is installed on the Yeondae Bridge (Korea) to measure the global response of the bridge to controlled truck loadings. To attain acceleration measurements in a large number of locations on the bridge, the wireless monitoring system is installed three times, with each installation concentrating sensors in one localized area of the bridge. Analysis of measurement data after installation of the three monitoring system configurations leads to reliable estimation of the bridge modal properties, including mode shapes.

• Wind and Structures
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• v.20 no.2
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• pp.293-314
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• 2015

In this paper, wireless monitoring of typhoon-induced variation of dynamic characteristics of a cable-stayed bridge is presented. Firstly, cable-stayed bridge with the wireless monitoring system is described. Wireless vibration sensor nodes are utilized to measure accelerations from bridge deck and stay cables. Also, modal analysis methods are selected to extract dynamic characteristics. Secondly, dynamic responses of the cable-stayed bridge under the attack of two typhoons are analyzed by estimating relationships between wind velocity and dynamic characteristics. Wind-induced variations of deck and cable vibration responses are examined based on the field measurements under the two consecutive typhoons, Bolaven and Tembin. Finally, time-varying analyses are performed to investigate non-stationary random properties of the dynamic responses under the typhoons.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.421-431
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• 2006

Nowadays, the importance of safety monitoring for facilities is increasing. Therefore, the introduction of ubiquitous technology to replace the existing manually-operated methods is required. In this study, a web-based GIS system that provides monitoring information of bridges in real-time for the application of a bridge management system through the use of ubiquitous technology is constructed. Particular attention is given to the effective interconnection of bridge monitoring information and bridge management system and, through a ubiquitous environment, how to connect this with the UFID and the GIS-based bridge management system (BMS) operated by the Ministry of Construction and Transportation. In addition, data expression methods are also suggested that state the detailed locations and attributes of structures in bridge management by using GIS.

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.305-321
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• 2022

Bridge structural health monitoring with the aim of continuously assessing structural safety and reliability represents a topic of major importance for worldwide infrastructure managers. In the last two decades, due to their potential economic and operational advantages, drive-by approaches experienced growing consideration from researcher and engineers. This work addresses two technical topics regarding indirect frequency estimation methods: bridge and vehicle dynamics overlapping, and bridge expansion joints impact. The experimental campaign was conducted on a mixed multi-span bridge located in Lombardy using a Ford Galaxy instrumented with a mesh of wireless accelerometers. The onboard time series were acquired for a number of 10 passages over the bridge,performed at a travelling speed of 30 km/h, with no limitations imposed to traffic. Exploiting an ad-hoc sensors positioning, pitch vehicle motion was compensated, allowing to estimate the first two bridge bending frequencies from PSD functions; moreover, the herein adopted approach proved to be insensitive to joints disturbance. Conclusively, a sensitivity study has been conducted to trace the relationship between estimation accuracy and number of trips considered in the analysis. Promising results were found, pointing out a clear positive correlation especially for the first bending frequency.

• Smart Structures and Systems
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• v.11 no.6
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• pp.637-662
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• 2013

The Jiangyin Bridge is a suspension bridge with a main span of 1385 m over the Yangtze River in Jiangsu Province, China. Being the first bridge with a main span exceeding 1 km in Chinese mainland, it had been instrumented with a structural health monitoring (SHM) system when completed in 1999. After operation for several years, it was found with malfunction in sensors and data acquisition units, and insufficient sensors to provide necessary information for structural health evaluation. This study reports the SHM system upgrade project on the Jiangyin Bridge. Although implementations of SHM system have been reported worldwide, few studies are available on the upgrade of SHM system so far. Recognizing this, the upgrade of original SHM system for the bridge is first discussed in detail. Especially, lessons learned from the original SHM system are applied to the design of upgraded SHM system right away. Then, performance assessment of the bridge, including: (i) characterization of temperature profiles and effects; (ii) recognition of wind characteristics and effects; and (iii) identification of modal properties, is carried out by making use of the long-term monitoring data obtained from the upgraded SHM system. Emphasis is placed on the verification of design assumptions and prediction of bridge behavior or extreme responses. The results may provide the baseline for structural health evaluation.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.9-18
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• 2006

This paper presents schematically the monitoring system installed in Yongjong Bridge, a self-anchored suspension bridge located in the expressway linking Seoul and Incheon International Airport. Automatic measurement of instrumented civil engineering structures is now widely applied for behavior monitoring during construction in field as well as long-term monitoring for lifetime assessment of bridge structures. A representative example of results that can be acquired through structural health monitoring system is presented by means of data measured during a few years after the opening of the bridge. In order to effectively measure the tension force for hangers that have relatively short length or high tension force, a static tension measurement device has been explored. Newly equipped railway system on the existing bridge results in change of dead load, consequently dynamic characteristics have also been changed. This result can be detected by the monitoring system during and after railway construction.

• Smart Structures and Systems
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• v.13 no.5
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• pp.775-796
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• 2014

This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.

• KCI Concrete Journal
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• v.11 no.3
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• pp.109-114
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• 1999

Recently the interest in the safety assessment of civil infrastructures has increased. As bridge structures become large-scale, it is necessary to monitor and maintain the safety of large bridges, which requires smart systems that can make long-term monitoring a reality . Civil engineers have applied monitoring systems to several bridges, such as the New Haeng-Ju Bridge and Riverside Urban Highway Bridge, but these applications have some problems with the sensors for long-term measurement, setup techniques for the bridge monitoring system and the assessment of measured data. In the present study, an optical fiber sensor smart system was tested and confirmed in laboratory tests on the concrete members. By Attaching optical fiber sensors to the structural parts of the Sung-San Bridge, the bridge load test was measured. These smart concrete structure systems can be applied to bridges and the load capacity of the bridge can assessed.