Download Free Continuous And Automated Real Time Bridge Health Monitor Dissemination Of Structural Rating Factors Via The Www Book in PDF and EPUB Free Download. You can read online Continuous And Automated Real Time Bridge Health Monitor Dissemination Of Structural Rating Factors Via The Www and write the review.

Instrumented bridge health monitoring has gained a significant amount of interest in the past few years. The reason being, that instrumented bridge health monitoring provides objective, quantitative information, in lieu of the subjective information provided by visual bridge inspection. This process of collecting data, which may be in the form of real time or archived data, may help civil engineers and bridge designers to improve bridge design, construction, maintenance mechanisms and practice. This thesis reports on one such data collection and monitoring system, which has been implemented at the site of HAM-126-0881L, a typical steel stringer highway overpass bridge located along the Ronald Reagan Cross County Highway in Cincinnati, OH. The instrumentation at this site consists of two components: (1) a weigh-in-motion scale, a digital camera, and a suite of 116 high speed gages together with associated digital data acquisition for monitoring traffic and bridge traffic responses; and (2) a suite of 238 low speed gages together with associated digital data acquisition for monitoring ambient/environmental bridge responses. Both systems are interfaced to PCs at the site running a custom LabView-based software package, which autonomously handles all data post-processing and Graphical User Interface (GUI) functions. The entire monitoring system is connected to the Internet via a high speed ADSL connection. The main focus of the traffic monitor is to capture and synchronize the data obtained for each vehicle from the camera, WIM, and high-speed sensors. In addition to archival of raw data, the monitor automatically rates the bridge as per AASHTO specifications based on the known axle spacing, weights, and strain responses measured for each vehicle. All of this data is presented to users via a user-friendly website where recent vehicles responses and ratings as well as statistical information can be accessed. Some of the targets that were achieved by the author over the previous system were that the monitoring and data acquisition mode of highway vehicles had to be triggered manually in the previous system. After a truck was captured and processed, the monitor would stop and had to be re-started manually. In the current scenario, the monitoring and acquisition process has been automated thus eliminating user input. The entire process of capturing a truck, process all its associated data and post it on the UCII website for online viewing is restricted to less than 4 minutes. This also maximized the number of observations that could be caught in a day. Sensor data acquisition, which was very resource intensive, has been separated from WIM and image acquisition, by creating a master-slave network. The hardware and software on each PC was specifically designed, keeping resource issues in mind. This handles resources in a much better way and makes the system stable. Precise timing parameters were worked-out which makes the hand-off regarding data and flags easier to handle. With real-time data being captured, it was observed that the rating calculations needed re-work. This was resolved leading to error-free rating factor calculations. Also quite a bit of the LabView code was designed for a One-time operation. This was re-designed for the real-time continuous monitoring operation. The UCII web-site was constructed, with a link to the real-time monitor. The GUI was designed to incorporate and categorize the results received from the real-time continuous monitor, not only making it aesthetically appealing but also make result interpretation very intuitive. Statistics were generated regarding results and posted online on the web-site for extended periods of time such as a week or even a month. Capturing of a huge amount of data in a very short time led to enabling of data archiving on the local PC and also on the FTP server, which was synchronized with the entire operation. Thus, an automated and continuous, dedicated-real time monitoring system, combined with an intelligent architectural interface design, data communication protocols and web access go a long way in helping civil engineers establish a deeper understanding of bridge performance.
The safety and serviceability of bridges is of paramount concern for bridge owners and for the traveling public. As our bridge infrastructure continues to age, there is a growing need for new methods and technologies that can enable transportation agencies to better evaluate their bridges to ensure their structural safety and to optimize their maintenance and inspection procedures. Following the collapse of the I-35 Bridge in Minnesota in 2007, the Federal Highway Administration (FHWA) began requiring a bridge load rating for all bridges in the United States. According to the American Society of Civil Engineers, one out of every nine bridges in the United States is classified as structurally deficient and is in urgent need of repair. The required maintenance of these and other bridges is very expensive. In fact, the FHWA estimates that it would cost nine billion dollars per year more than what is currently being spent on bridge maintenance to repair and maintain our deficient bridges. Structural Health Monitoring (SHM) is a technique that has been evolving and has been used in recent years to measure the loading environment and response of bridges in order to assess serviceability and safety. There are several examples around the world that have demonstrated the benefits of SHM using both short- and long-term monitoring. However, transportation agencies still lack the ability to directly implement SHM data into their maintenance and decision making processes. More specifically, transportation agencies are generally not capable of implementing the existing complex methods for using short- or long-term SHM data for bridge evaluation. ☐ The primary objective of this study was to develop new methods for utilizing SHM data that are analogous to more traditional methods and can be easily implemented by transportation agencies to better evaluate their bridges to achieve optimal maintenance and effective decision making. In developing the new methods, two approaches were taken. ☐ The first approach, referred to as the Continuous Rating Factor-Structural Health Monitoring method, uses SHM data to compute continuous rating factors. This approach applies SHM data directly into the Load Resistance Factor Rating (LRFR) equations to produce continuous rating factors for specific bridge components. To do this, the continuously recorded SHM data is converted into structural forces and/or stresses and incorporated directly into conventional rating equations to calculate continuously rating factors over time. More specifically, this new approach converts the measured strain and temperature data to live loads, thermal loads, prestressing losses, i.e. to yield accurate site-specific rating factors for various critical bridge components. ☐ The second approach, referred to as the Reliability Analysis-Structural Health Monitoring method, uses a reliability analysis framework combined with SHM data. In this approach loads and resistances were expressed as Probability Distribution Functions (PDF), where loads and resistances are treated as random variables. The concept of estimating the probability of failure or probability of exceedance is utilized and expressed as a reliability index for a specific bridge component. The reliability analysis was conducted first using design loads and then using long-term SHM data. The analyses were performed using Monte Carlo simulation and Rackwitz-Fiessler method and considered a variety of limit states. In the first type of analysis (using design information), the resistance model, dead load model, and live load model used in the reliability analysis were based solely on design information. In this analysis, the same statistical parameters used to develop the load effects and resistances in the AASHTO LRFD calibration were applied. In the second type of analysis (using SHM data), the load effects consisted of dead, live, and thermal loads. A live load statistical model was created based on data from Weigh-In-Motion (WIM) stations close to the location of the IRIB and a 3-D finite element model. The thermal load statistical model was created based on data from Delaware Environmental Observing System (DEOS) and correlation analysis between measured SHM strain and temperature data from the IRIB. In both cases, reliability indices for the west edge girder were computed along the bridge for various limit states. ☐ In order to demonstrate the two methods, the Indian River Inlet Bridge (IRIB), a prestressed concrete cable-stayed bridge located in Sussex County Delaware, was used as a study case. The research showed that the two methods can serve as possible evaluation approaches for bridges that have SHM systems. Both methods are successful in taking huge amounts of SHM data and translating them into simple and well understood evaluation parameters (ratings and reliability indices). ☐ The primary findings from results given by the continuous rating factor method were (1) SHM data can be used to directly compute bridge load ratings, (2) the developed technique provides results that can be easily understood and utilized by transportation agencies, and (3) the ratings show that thermal effects can have a significant effect on load ratings for long-span bridges. The primary findings from results given by the reliability method based on SHM data were (1) the method can be used to determine whether or not the monitored bridge meets the design code standards in terms of reliability by allowing a comparison of the target reliability indices to indices computed based on SHM data, (2) the developed reliability-based methodology using SHM data can be applied to other bridges, (3) the developed method shows promise for enabling SHM data to be directly incorporated into the maintenance, inspection, and decision making processes, and (4) the work suggests how reliability analysis results can be integrated with bridge field inspection results.
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.
This book presents extensive information on structural health monitoring for suspension bridges. During the past two decades, there have been significant advances in the sensing technologies employed in long-span bridge health monitoring. However, interpretation of the massive monitoring data is still lagging behind. This book establishes a series of measurement interpretation frameworks that focus on bridge site environmental conditions, and global and local responses of suspension bridges. Using the proposed frameworks, it subsequently offers new insights into the structural behaviors of long-span suspension bridges. As a valuable resource for researchers, scientists and engineers in the field of bridge structural health monitoring, it provides essential information, methods, and practical algorithms that can facilitate in-service bridge performance assessments.
Health Monitoring of Bridges prepares the bridge engineering community for the exciting new technological developments happening in the industry, offering the benefit of much research carried out in the aerospace and other industrial sectors and discussing the latest methodologies available for the management of bridge stock. Health Monitoring of Bridges: Includes chapters on the hardware used in health monitoring, methodologies, applications of these methodologies (materials, methods, systems and functions), decision support systems, damage detection systems and the rating of bridges and methods of risk assessment. Covers both passive and active monitoring approaches. Offers directly applicable methods and as well as prolific examples, applications and references. Is authored by a world leader in the development of health monitoring systems. Includes free software that can be downloaded from http://www.samco.org/ and provides the raw data of benchmark projects and the key results achieved. This book provides a comprehensive guide to all aspects of the structural health monitoring of bridges for engineers involved in all stages from concept design to maintenance. It will also appeal to researchers and academics within the civil engineering and structural health monitoring communities.
The book presents recent advances regarding the inspection and monitoring of engineering structures; including bridges, buildings, aircraft and space structures, nuclear reactors and defense platforms. Among the techniques covered are UAV photogrammetry, strain monitoring, infrared detection, acoustic emission testing, residual stress measurements, fiber optical sensing, thermographic inspection, vibration analysis, piezoelectric sensing and ultrasonic testing. Keywords: Bridges, Buildings, Aircraft Structures, Space Structures, Nuclear Reactors, Defense Platforms, UAV Photogrammetry, Strain Monitoring, Infrared Detection, Acoustic Emission Testing, Residual Stress Measurements, Fiber Optical Sensing, Thermographic Inspection, Vibration Analysis, Piezoelectric Sensing, Ultrasonic Testing, Impact Damage, Anaerobic Reactor Performance, Geomembranes, Ossointegrated Implants, Fatigue Crack Growth, Accelerometer, Nonlinear Cable Bracing, Timber Utility Poles, Steel Pipes, Loosened Bolts on Pipes, IMU-based Motion Capture, CFRP Composites, Maglev Guideway Girder, Cable-Pylon Anchorage, Deep Learning Techniques.
With 28% of the approximately 25,000 bridges in Iowa being classified as structurally deficient, functionally obsolete, or both, the State of Iowa follows the national trend of an aging infrastructure in dire need of repair or replacement with a relatively limited funding base to do so. Therefore, there is a need to develop new materials with properties which may lead to longer life-spans and reduced life-cycle costs. In addition, new methods to determine the condition of structures are needed to effectively monitor the structures and identify when the useful life of the structure has expired. High Performance Steel (HPS) has emerged as a new material with enhanced weldability, weathering capabilities, and fracture toughness compared to conventional structural steels. In 2004 the Iowa Department of Transportation (Iowa DOT) opened Iowa's first HPS girder bridge, the East 12th Street Bridge over 1-235 in Des Moines, IA. The objective of the project was to evaluate HPS as a viable option for use in bridges in Iowa through a Structural Health Monitoring (SHM) system. The scope of the project included construction documentation of the E. 12th St. Bridge and concurrently developing a remote, continuous SHM system utilizing Fiber Optic sensing technology to evaluate the structural performance of the bridge. The SHM system included bridge evaluation parameters, similar to design parameters used by bridge engineers, for evaluating the structure. Through the successful completion of this project, a baseline of bridge performance was established which can be used for continued long-term monitoring of the structure. The structural performance of the HPS bridge exceeded design parameters and is performing well. Although some problems were encountered with the SHM system, the system is currently functioning well and recommendations to improve the system have been made.
This book conducts effective research on data-driven Structural Health Monitoring (SHM), and accordingly presents many novel feature extraction methods by time series analysis and signal processing, to extract reliable damage sensitive features from vibration responses. In this regard, some limitations of time series modeling are dealt with. For decision-making, innovative distance-based novelty detection techniques are presented to detect, locate, and quantify different damage scenarios. The performance of the presented methods is demonstrated via laboratory and full-scale structures along with several comparative studies. The main target audience of the book includes scholars, graduate students working on SHM via statistical pattern recognition in terms of feature extraction and classification for damage diagnosis under environmental and operational variations; it would also be beneficial for practicing engineers whose work involves these topics.