Tzuyang Yu Portrait

Dr. Tzuyang Yu
Associate Chair for Doctoral Studies, Professor, Civil and Environmental Engineering
University of Massachusetts Lowell

Xingwei Wang Portrait

Dr. Xingwei Wang
Professor, Electrical & Computer Engineering
University of Massachusetts Lowell

Zhu Mao Portrait

Dr. Zhu Mao Assistant Professor, Mechanical Engineering University of Massachusetts Lowell

Development of a System-Level Distributed Sensing Technique for Long-Term Monitoring of Concrete and Composite Bridges

The project is to develop a system-level distributed sensing technique for the long-term monitoring of bridges (e.g., concrete and composite bridges), using fiber optic, video motion, and electromagnetic sensors. Design of a cost-efficient, easy-to-install distributed fiber optic sensing system for monitoring maximum strain/displacement, shift of neutral axis, and creep deformation of bridges is key to understanding the in-situ durability performance of our transportation infrastructure. This project aims to deliver 1) cost-efficient, easy-to-install design and implementation of fiber optic sensors for various bridge components (e.g., girders and piers), 2) integrated interpretation of distributed strains, structural modal frequencies, and radar images for structural health of a bridge system (local and global), and 3) field implementation (new Grist Mill Bridge, Hampden, ME) and development of a database for a composite bridge.

In this presentation, we will show our laboratory development and field instrumentation of the proposed system-level distributed sensing technique. Our focus is on the establishment of baseline measurements on the Grist Mill Bridge, using fiber optic, video motion, and electromagnetic sensors. Conventional strain gauges were also installed on the bridge to allow us perform comparative study on distributed static strain data (fiber optic sensors vs. strain gauges) and dynamic response (video camera sensor vs. strain gauges) of the bridge upon vehicle live loading. From our research result, we have found the correlations among fiber optic, video camera, and strain gauge sensors.