Structural health monitoring of a cable-stayed bridge using acceleration data via wireless smart sensor network

This paper presents the data analysis results of structural health monitoring (SHM) carried out on a cable-stayed bridge in Korea (the 2 ^nd Jindo Bridge) using a dense array of scalable wireless smart sensors. As a prior work, a finite element (FE) model is constructed based on an in-depth study of the detailed drawings, and the acceleration data from the existing wired monitoring system is analyzed to be used as a reference data of wireless sensors' performance. A total of 70 wireless smart sensor nodes have been deployed underneath of the deck, on the pylons, and on the cables to capture the vibration of the bridge excited by traffic and environmental loadings. Data analysis is carried out for modal properties of deck/pylon and tension forces of cables. Modal properties of the bridge are identified using the stochastic subspace identification methods based on the measured 3-axis acceleration, and the results are compared with those obtained from the existing wired monitoring system and FE analysis. Tension forces of 10 parallel wire strand cables among 60 stay cables are also estimated from the ambient acceleration data, and compared with those of the initial design and obtained during two previous regular inspections. The results of the data analyses demonstrate that the present dense wireless smart sensor networks perform very effectively for SHM of the cable-stayed bridge, giving direct access to the physical status of the bridge.