VLSI Signal Processing for QNDE of Highway Bridge

Abstract

Evaluation of highway bridges using quantitative nondestructive techniques is a great challenge. A research project currently being carried out at the ATLSS center of Lehigh University is to investigate the issue involved in QNDE of large structures with an emphasis on highway bridges. Our approach is to develop a remotely accessible, economically affordable, and highly reliable continuous monitoring system using advanced signal processing techniques and very large scale integration(VLSI) technology. The result of this project will dramatically lower the cost and enhance the capability of monitoring highway bridges. A particular fatigue damage monitoring system is being developed because fatigue damage assessment has been an important issue in bridge inspection and evaluation. The algorithm used for estimating fatigue damages requires rainflow counting, stress histogram generation, and equivalent stress range calculation. Using calculated equivalent stress range and appropriate AASHTO fatigue design curve, the total number of fatigue cycles can be estimated. The remaining fatigue life of the monitored bridge can be obtained by subtracting the number of used fatigue cycles from the total number of fatigue cycles. The entire system consists of sensors and processing modules distributed on a bridge and powered by small batteries, a radio repeater near the bridge powered by a larger battery, and a computer at central facility. The sensors and processor modules will be capable of collecting and processing data on site in real time. Processed data from each individual sensor and processor modules on the bridge will be transmitted to the radio repeater.KeywordsFatigue LifeFatigue DamageStress RangeVery Large Scale IntegrationStress CycleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.