• Title/Summary/Keyword: structural health monitoring of bridge

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Wireless structural health monitoring of stay cables under two consecutive typhoons

  • Kim, Jeong-Tae;Huynh, Thanh-Canh;Lee, So-Young
    • Structural Monitoring and Maintenance
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    • v.1 no.1
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    • pp.47-67
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    • 2014
  • This study has been motivated to examine the performance of a wireless sensor system under the typhoons as well as to analyze the effect of the typhoons on the bridge's vibration responses and the variation of cable forces. During the long-term field experiment on a real cable-stayed bridge in years 2011-2012, the bridge had experienced two consecutive typhoons, Bolaven and Tembin, and the wireless sensor system had recorded data of wind speeds and vibration responses from a few survived sensor nodes. In this paper, the wireless structural health monitoring of stay cables under the two consecutive typhoons is presented. Firstly, the wireless monitoring system for cable-stayed bridge is described. Multi-scale vibration sensor nodes are utilized to measure both acceleration and PZT dynamic strain from stay cables. Also, cable forces are estimated by a tension force monitoring software based on vibration properties. Secondly, the cable-stayed bridge with the wireless monitoring system is described and its wireless monitoring capacities for deck and cables are evaluated. Finally, the structural health monitoring of stay cables under the attack of the two typhoons is described. Wind-induced deck vibration, cable vibration and cable force variation are examined based on the field measurements in the cable-stayed bridge under the two consecutive typhoons.

Performance evaluation of in-service open web girder steel railway bridge through full scale experimental investigations

  • Sundaram, B. Arun;Kesavan, K.;Parivallal, S.
    • Structural Monitoring and Maintenance
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    • v.6 no.3
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    • pp.255-268
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    • 2019
  • Civil infrastructures, such as bridges and tunnels are most important assets and their failure during service will have significant economic and social impact in any country. Behavior of a bridge can be evaluated only through actual monitoring/measurements of bridge members under the loads of interest. Theoretical analysis alone is not a good predictor of the ability of a bridge. In some cases, theoretical analyses can give less effect than actual since theoretical analyses do not consider the actual condition of the bridge, support conditions, level of corrosion and damage in members and connections etc. Hence actual measurements of bridge response should be considered in making decisions on structural integrity, especially in cases of high value bridges (large spans and major crossings). This paper describes in detail the experimental investigations carried out on an open web type steel railway bridge. Strain gages and displacement transducers were installed at critical locations and responses were measured during passage of locomotives. Stresses were evaluated and extrapolated to maximum design loading. The responses measured from the bridge were within the permissible limits. The methodology adopted shall be used for assessing the structural integrity of the bridge for the design loads.

Condition assessment of reinforced concrete bridges using structural health monitoring techniques - A case study

  • Mehrani, E.;Ayoub, A.;Ayoub, A.
    • Smart Structures and Systems
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    • v.5 no.4
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    • pp.381-395
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    • 2009
  • The paper presents a case study in which the structural condition assessment of the East Bay bridge in Gibsonton, Florida is evaluated with the help of remote health monitoring techniques. The bridge is a four-span, continuous, deck-type reinforced concrete structure supported on prestressed pile bents, and is instrumented with smart Fiber Optic Sensors. The sensors used for remote health monitoring are the newly emerged Fabry-Perot (FP), and are both surface-mounted and embedded in the deck. The sensing system can be accessed remotely through fast Digital Subscriber Lines (DSL), which permits the evaluation of the bridge behavior under live traffic loads. The bridge was open to traffic since March 2005, and the collected structural data have been continuously analyzed since. The data revealed an increase in strain readings, which suggests a progression in damage. Recent visual observations also indicated the presence of longitudinal cracks along the bridge length. After the formation of these cracks, the sensors readings were analyzed and used to extrapolate the values of the maximum stresses at the crack location. The data obtained were also compared to initial design values of the bridge under factored gravity and live loads. The study showed that the proposed structural health monitoring technique proved to provide an efficient mean for condition assessment of bridge structures providing it is implemented and analyzed with care.

Structural health monitoring system for Sutong Cable-stayed Bridge

  • Wang, Hao;Tao, Tianyou;Li, Aiqun;Zhang, Yufeng
    • Smart Structures and Systems
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    • v.18 no.2
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    • pp.317-334
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    • 2016
  • Structural Health Monitoring System (SHMS) works as an efficient platform for monitoring the health status and performance deterioration of engineering structures during long-term service periods. The objective of its installation is to provide reasonable suggestions for structural maintenance and management, and therefore ensure the structural safety based on the information extracted from the real-time measured data. In this paper, the SHMS implemented on a world-famous kilometer-level cable-stayed bridge, named as Sutong Cable-stayed Bridge (SCB), is introduced in detail. The composition and core functions of the SHMS on SCB are elaborately presented. The system consists of four main subsystems including sensory subsystem, data acquisition and transmission subsystem, data management and control subsystem and structural health evaluation subsystem. All of the four parts are decomposed to separately describe their own constitutions and connected to illustrate the systematic functions. Accordingly, the main techniques and strategies adopted in the SHMS establishment are presented and some extension researches based on structural health monitoring are discussed. The introduction of the SHMS on SCB is expected to provide references for the establishment of SHMSs on long-span bridges with similar features as well as the implementation of potential researches based on structural health monitoring.

Structural health monitoring of the Jiangyin Bridge: system upgrade and data analysis

  • Zhou, H.F.;Ni, Y.Q.;Ko, J.M.
    • 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.

Optimal Sensor Allocation of Cable-Stayed Bridge for Health Monitoring (사장교의 상시감시를 위한 최적 센서 구성)

  • Heo, Gwang-Hee;Choi, Mhan-Young
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.6 no.2
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    • pp.145-155
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    • 2002
  • It is essential for health monitoring of a cable-stayed bridge to provide more accurate and enough information from the sensors. In experimental modal testing, the chosen measurement locations and the number of measurements have a major influence on the quality of the results. The choice is often difficult for complex structures like a cable-stayed bridge. It is extremely important a cable-stayed bridge to minimize the number of sensing operations required to monitor the structural system. In order to obtain the desired accuracy for the structural test, several issues must take into consideration. Two important issues are the number and location of response sensors. There are usually several alternative locations where different sensors can be located. On the other hand, the number of sensors might be limited due to economic constraints. Therefore, techniques such as methodologies, algorithms etc., which address the issue of limited instrumentation and its effects on resolution and accuracy in health monitoring systems are paramount to a damage diagnosis approach. This paper discusses an optimum sensor placement criterion suitable to the identification of structural damage for continuous health monitoring. A Kinetic Energy optimization technique and an Effective Independence Method are analyzed and numerical and theoretical issues are addressed for a cable-stayed bridge. Its application to a cable-stayed bridge is discussed to optimize the sensor placement for identification and control purposes.

Structural health monitoring of a high-speed railway bridge: five years review and lessons learned

  • Ding, Youliang;Ren, Pu;Zhao, Hanwei;Miao, Changqing
    • Smart Structures and Systems
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    • v.21 no.5
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    • pp.695-703
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    • 2018
  • Based on monitoring data collected from the Nanjing Dashengguan Bridge over the last five years, this paper systematically investigates the effects of temperature field and train loadings on the structural responses of this long-span high-speed railway bridge, and establishes the early warning thresholds for various structural responses. Then, some lessons drawn from the structural health monitoring system of this bridge are summarized. The main context includes: (1) Polynomial regression models are established for monitoring temperature effects on modal frequencies of the main girder and hangers, longitudinal displacements of the bearings, and static strains of the truss members; (2) The correlation between structural vibration accelerations and train speeds is investigated, focusing on the resonance characteristics of the bridge at the specific train speeds; (3) With regard to various static and dynamic responses of the bridge, early warning thresholds are established by using mean control chart analysis and probabilistic analysis; (4) Two lessons are drawn from the experiences in the bridge operation, which involves the lacks of the health monitoring for telescopic devices on the beam-end and bolt fractures in key members of the main truss.

An image-based deep learning network technique for structural health monitoring

  • Lee, Dong-Han;Koh, Bong-Hwan
    • 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.

Entropy-based optimal sensor networks for structural health monitoring of a cable-stayed bridge

  • Azarbayejani, M.;El-Osery, A.I.;Taha, M.M. Reda
    • 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.

Structural health monitoring and resilient assessment by novel intelligent models

  • C.C. Hung;T. Nguyen;C.Y. Hsieh
    • Structural Monitoring and Maintenance
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    • v.10 no.4
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    • pp.339-360
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    • 2023
  • In this paper, to assess the performance of a multi-span simply supported RC bridge, the dynamic characteristics of the bridge were measured and determined by structural health monitoring and resilient assessment via operational modal analysis as well as FE modeling. Supporting finite element (FE) models were created and analyzed according to the design drawings. This study used 2D plane monitoring of locations of hole in the infill wall and used 3D health monitoring and resilient assessment. From the results of 3Dsymmetric frame, if the frame is unsymmetrical, the used model can lead to the reduction in the internal forces. The recommendations from this study is from some discrepancies observed between 2D and 3D models, if possible 3D model should be used in analyzing the real frames.