Abstract

Discussed in this talk is the development and deployment of a dense hybrid wireless sensing system for performance monitoring and condition assessment of highway bridges. The wireless sensor system developed allows for real-time, high-rate wireless data collection from an array of different sensors, including vibration monitoring and strain measurements, and affords dense sensor deployments for distributed monitoring to provide insight into both static and dynamic response of an entire system. Results from several recent field deployments are presented and discussed. A test of an end-of-service bridge span with prescribed, progressive damage is highlighted to illustrate on how output-only system identification was applied to the baseline time history response to develop a state-space model of the bridge dynamics used for forward prediction in the form of a Kalman filter. Statistical evaluation of the prediction error in the model demonstrated that the variance can be used to localize and generally quantify the degree of damage in the system. A brief presentation of other projects and future directions in civil infrastructure monitoring using advanced sensor networks concludes the talk.