System Identification of Highway Bridges Using Long-term Vibration Monitoring Data


Book Description

The need for maintenance and protection of critical highway infrastructure links has led in recent years to significant developments in the area of bridge structural health monitoring. Taking advantage of the instrumentation of three highway bridges located in Southern California, this dissertation focuses on the application of system identification (SI) techniques to a database consisting of more than 2,000 data sets collected over a period of nine years. The data sets consist of ambient and traffic induced vibration records, earthquake records, and controlled vehicles test data. During the controlled vehicle tests acceleration transducers were mounted on the vehicle chassis to study the potential for bridge identification using instrumented vehicles. It is demonstrated long-term monitoring needs to be conducted in a permanent or periodic basis in combination with the application of SI techniques for the purpose of identifying changes in structural response characteristics and material properties due to aging factors and earthquake intensity. The ambient and traffic-induced vibration data were analyzed using the frequency domain decomposition technique for identification of modal parameters, i.e. natural frequencies and mode shapes. For a five-year period, a reduction of the first natural frequency is found to be approximately 2% for a 3-span straight bridge, 5% for a 3-span highly curved bridge and 3% for a four-span slightly curved bridge. Using seismic acceleration records, the bridge modal parameters are identified using time domain SI techniques. It is found the identified first frequency of one of the bridges decreases up to 20% during an earthquake of moderate intensity (PGA> 0.37g) with epicenter close (




System Identification of Highway Bridges Using Vibration Data


Book Description

This study takes advantage of the instrumentation of three highway bridges located in Southern California. It shows the application of system identification (SI) techniques using more than 2,000 acceleration response data sets collected over a period of nine years. The data consist of ambient and traffic induced vibration records, earthquake records, and controlled vehicles test data. Transducers were mounted on the test vehicle chassis to study the potential for bridge identification using instrumented vehicles. For a five-year period, a reduction of the first natural frequency is found to be approximately 2% for a 3-span straight bridge, 5% for a 3-span highly curved bridge and 3% for a four-span slightly curved bridge. Also, the identified first frequency of one of the bridges decreases up to 20% during an earthquake of moderate intensity (PGA=0.37g) with epicenter close (20km) to the bridge site. State-space models generated from measurements successfully replicate the bridge response. Then, the Young's modulus and boundary stiffness are identified by means of Finite Element (FE) model updating. Finally, fragility curves show bridge seismic vulnerability increases with time.




Health Assessment Of Engineered Structures: Bridges, Buildings And Other Infrastructures


Book Description

Health Assessment of Engineered Structures has become one of the most active research areas and has attracted multi-disciplinary interest. Since available financial recourses are very limited, extending the lifespan of existing bridges, buildings and other infrastructures has become a major challenge to the engineering profession world-wide. Some of its related areas are only in their development phase. As the study of structural health assessment matures, more new areas are being identified to complement the concept.This book covers some of the most recent developments (theoretical and experimental) and application potentials in structural health assessment. It is designed to present currently available information in an organised form to interested parties who are not experts in the subject.Each chapter is authored by the most active scholar(s) in the area. After discussing the general concept, various currently available methods of structural health assessment (such as the use of smart sensors) are presented. Health Assessment discusses the following: sensor types, platforms and data conditioning for practical applications; wireless collection of sensor data, sensor power needs and on-site energy harvesting; and long term monitoring of structures. Uncertainty in collected data is also extensively addressed. A chapter discussing future directions in structural health assessment is also included.




Bridge Maintenance, Safety, Management, Resilience and Sustainability


Book Description

Bridge Maintenance, Safety, Management, Resilience and Sustainability contains the lectures and papers presented at The Sixth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2012), held in Stresa, Lake Maggiore, Italy, 8-12 July, 2012. This volume consists of a book of extended abstracts (800 pp) Extensive collection of revised expert papers on recent advances in bridge maintenance, safety, management and life-cycle performance, representing a major contribution to the knowledge base of all areas of the field.




Computation of Vehicular-induced Vibrations and Long-term Instrumentation Reliability for Structural Health Monitoring of Highway Bridges


Book Description

Real-time monitoring of fracture critical steel bridges can potentially enhance inspection practices by tracking the behavior of the bridge. Significant advances have occurred in recent years on the development of robust hardware for field monitoring applications. These systems can monitor, process, and store data from a variety of sensors (e.g. strain gages, crack propagation gages etc.) to track the behavior of the bridge. The research outlined in this dissertation is part of a large study focused on the development of a wireless system for use in long-term monitoring of bridges. The wireless monitoring system had a target maintenance-free life of ten years, and independent from the power grid. Thus, the feasibility to harvest energy for the monitoring system is an important step in the development of the system. In addition, the reliability of the sensors in the bridge is very important upon the success of the system. The focus of this dissertation is on two primary aspects of the wireless monitoring system. First, the feasibility to harvest energy from vehicular-induced vibrations is evaluated through analytical models of highway bridges under truck loads. Acceleration results from simple line-element models and detailed finite element models of five steel bridges in Texas and Oregon are compared with actual field data from the same bridges. Second, the dissertation also highlights studies on the identification of strain gages and installation procedures that result in long lives. In addition, the effect of temperature fluctuations and other environmental factors on the sensor drift and noise is also considered. In long-term monitoring applications, slight sensor drift and noise can build up over time to produce misleading results. This dissertation presents the results of transient dynamic analyses of bridges under moving truck loading and laboratory tests on gage durability that were conducted as part of a research project sponsored by the National Institute of Standards and Technology (NIST).




Structural Health Monitoring of Long-Span Suspension Bridges


Book Description

Long span suspension bridges cost billions. In recent decades, structural health monitoring systems have been developed to measure the loading environment and responses of these bridges in order to assess serviceability and safety while tracking the symptoms of operational incidents and potential damage. This helps ensure the bridge functions properly during a long service life and guards against catastrophic failure under extreme events. Although these systems have achieved some success, this cutting-edge technology involves many complex topics that present challenges to students, researchers, and engineers alike. Systematically introducing the fundamentals and outlining the advanced technologies for achieving effective long-term monitoring, Structural Health Monitoring of Long-Span Suspension Bridges covers: The design of structural health monitoring systems Finite element modelling and system identification Highway loading monitoring and effects Railway loading monitoring and effects Temperature monitoring and thermal behaviour Wind monitoring and effects Seismic monitoring and effects SHMS-based rating method for long span bridge inspection and maintenance Structural damage detection and test-bed establishment These are applied in a rigorous case study, using more than ten years' worth of data, to the Tsing Ma suspension bridge in Hong Kong to examine their effectiveness in the operational performance of a real bridge. The Tsing Ma bridge is the world's longest suspension bridge to carry both a highway and railway, and is located in one of the world’s most active typhoon regions. Bridging the gap between theory and practice, this is an ideal reference book for students, researchers, and engineering practitioners.




Short and Long-term Structural Health Monitoring of Highway Bridges


Book Description

Structural Health Monitoring (SHM) is a promising tool for condition assessment of bridge structures. SHM of bridges can be performed for different purposes in long or short-term. A few aspects of short- and long-term monitoring of highway bridges are addressed in this research. Without quantifying environmental effects, applying vibration-based damage detection techniques may result in false damage identification. As part of a long-term monitoring project, the effect of temperature on vibrational characteristics of two continuously monitored bridges are studied. Natural frequencies of the structures are identified from ambient vibration data using the Natural Excitation Technique (NExT) along with the Eigen System Realization (ERA) algorithm. Variability of identified natural frequencies is investigated based on statistical properties of identified frequencies. Different statistical models are tested and the most accurate model is selected to remove the effect of temperature from the identified frequencies. After removing temperature effects, different damage cases are simulated on calibrated finite-element models. Comparing the effect of simulated damages on natural frequencies showed what levels of damage could be detected with this method. Evaluating traffic loads can be helpful to different areas including bridge design and assessment, pavement design and maintenance, fatigue analysis, economic studies and enforcement of legal weight limits. In this study, feasibility of using a single-span bridge as a weigh-in-motion tool to quantify the gross vehicle weights (GVW) of trucks is studied. As part of a short-term monitoring project, this bridge was subjected to four sets of high speed, live-load tests. Measured strain data are used to implement bridge weigh-in-motion (B-WIM) algorithms and calculate the corresponding velocities and GVWs. A comparison is made between calculated and static weights, and furthermore, between supposed speeds and estimated speeds of the trucks. Vibration-based techniques that use finite-element (FE) model updating for SHM of bridges are common for infrastructure applications. This study presents the application of both static and dynamic-based FE model updating of a full scale bridge. Both dynamic and live-load testing were conducted on this bridge and vibration, strain, and deflections were measured at different locations. A FE model is calibrated using different error functions. This model could capture both global and local response of the structure and the performance of the updated model is validated with part of the collected measurements that were not included in the calibration process.




Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures


Book Description

In the past, when elements in structures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools.




Feasibility of Vibration-based Long-term Bridge Monitoring Using the I-35W St. Anthony Falls Bridge


Book Description

Vibration based structural health monitoring has become more common in recent years as the required data acquisition and analysis systems become more affordable to deploy. It has been proposed that by monitoring changes in the dynamic signature of a structure, primarily the natural frequency, one can detect damage. This approach to damage detection is made difficult by the fact that environmental factors, such as temperature, have been shown to cause variation in the dynamic signature in a structure, effectively masking those changes due to damage. For future vibration based structural health monitoring systems to be effective, the relationship between environmental factors and natural frequency must be understood such that variation in the dynamic signature due to environmental noise can be removed. A monitoring system on the I-35W St. Anthony Falls Bridge, which crosses the Mississippi River in Minneapolis, MN, has been collecting vibration and temperature data since the structures opening in 2008. This provides a uniquely large data set, in a climate that sees extreme variation in temperature, to test the relationship between the dynamic signature of a concrete structure and temperature. A system identification routine utilizing NExT-ERA/DC is proposed to effectively analyze this large data set, and the relationship between structural temperature and natural frequency is investigated.