Author: Sachin Kambli

Publisher:

Published: 2007

Total Pages: 148

ISBN-13:

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.