• 비파괴검사학회지
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• 제32권6호
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• pp.648-660
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• 2012

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

• Structural Monitoring and Maintenance
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• 제6권3호
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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.

• Smart Structures and Systems
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• 제5권4호
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• pp.397-413
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• 2009

Composite bridges offer many advantages compared to current steel and aluminum bridges. This paper presents the results of a comprehensive on-going research program to develop innovative Diagnostic Prognostic System (DPS) and a structural evaluation of Composite Army Bridge (CAB) system. The DPS is founded on three technologies: optical fiber sensing, remote data transmission, and virtual testing. In developing this system, both laboratory and virtual test were used in different damage scenarios. Health monitoring with DPS entailed comparing live strain data to archived strained data in various bridge locations. For field repairs, a family of composite chords was subjected to simple ramp loads in search of ultimate strength. As such, composite bridge specimens showcased their strengths, heralded the viability of virtual testing, highlighted the efficacy of field repair, and confirmed the merits of health monitoring.

• Smart Structures and Systems
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• 제5권4호
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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.

• 비파괴검사학회지
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• 제22권3호
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• pp.239-245
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• 2002

현재까지 다양한 토목구조물들은 여러 가지 요인에 의한 노후화와 축척된 손상에도 불구하고 별다른 조치 없이 계속해서 사용되고 있었다. 따라서, 이러한 구조물들의 효율적인 유지관리를 유해 계측관리가 중요시되었다. 이에 본 논문에서는 비파괴계측에 의해 사장교의 실시간 계측모니터링시스템을 개발하고자 하며 이를 통해 교량의 안전관리를 하고자 하였다. 계측모니터링시스템은 교량의 유지관리를 도모하고, 교량 관리의 경제적 비용을 줄이게 되며 사장교의 새로운 설계 및 분석방법을 개발하는데 중요한 데이터를 제공할 것이다.

• Smart Structures and Systems
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• 제21권5호
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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.

• Smart Structures and Systems
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• 제18권2호
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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.

• Smart Structures and Systems
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• 제13권5호
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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.

• 한국구조물진단유지관리공학회 논문집
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• 제6권2호
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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.

• Smart Structures and Systems
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• 제28권6호
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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.