Statistical Analysis of Modal Properties of a Cable-Stayed Bridge through Long-Term Wireless Structural Health Monitoring

Abstract

A dense deployment of sensors is often beneficial for obtaining a more complete understanding of the dynamic behavior of complex structures, such as long-span bridges. Wireless smart sensor networks are advantageous in this regard because they are less expensive and easier to deploy than traditional wired sensor networks. A dense array of wireless smart sensor networks with 113 smart sensors was installed on a cable-stayed bridge in South Korea to record ambient acceleration. The deployment features the world’s largest wireless smart sensor network for civil structural monitoring. In total, 10 GB of data were collected from the deck sensor nodes during a 1-year period of deployment. The natural excitation technique, in conjunction with the eigensystem realization algorithm, was used to perform system identification. A comprehensive statistical analysis of modal properties, such as natural frequencies, modal damping, and mode shapes of the bridge, was performed. The relationship between temperature and natural frequency was also examined. The statistical analysis of system identification results demonstrates that using data obtained by a wireless smart sensor network provides a high resolution and confidence in identified modal properties.