Structural Health Monitoring for In-Service Highway Bridges Using Smart Sensors

With the rapid development of electrical circuits, Microelectromechanical system (MEMS) and network technology, wireless smart sensor networks (WSSN) have shown significant potential for replacing existing wired Structural health monitoring (SHM) systems due to their cost effectiveness and versatility. A few structural systems have been monitored using WSSN measuring acceleration, temperature, wind speed, humidity; however, a multi-scale sensing device which has the capability to measure the displacement has not been yet developed. In this research, a new high accuracy displacement sensing system has been developed combining a high resolution analog displacement sensor and MEMS-based wireless microprocessor platform. The developed multi-scale sensing system is evaluated in a laboratory bridge structure to check its performance. Finally, the developed hybrid multi-scale displacement sensing system was deployed on in-service highway bridge for expansion joint displacement measurement. The second part of the thesis presents the use of a damage detection algorithm applied to a lab scale truss structure and then to a in service highway bridge. To date, many damage detection strategies have been developed and implemented on lab-scale or simple bridge structures however, damage detection research has rarely been conducted taking full scale in-service structures into account with ambient vibration. Among the different approaches modal flexibility method is one of the sensitive tools for damage detection which has been widely used over the last two decades. This thesis presents a damage detection based on the stochastic damage locating vector (SDLV) method for an in-service highway bridge using ambient vibration data from long-term SHM