Stay Force Estimation in Cable-Stayed Bridges Using Stochastic Subspace Identification Methods

Abstract

In this paper, a vibration-based approach for estimating the cable tension forces in cable-stayed bridges is detailed and applied to the ambient response of the Veterans’ Glass City Skyway Bridge. First, the frequency stabilization diagrams were derived using the covariance-driven stochastic subspace identification (SSI-COV) method. Second, natural frequencies of each stay cable were identified by applying the hierarchical clustering algorithm to the frequency stabilization diagrams. Finally, the identified natural frequencies along with measurable physical and geometrical characteristics of the stay cables were used as input to a cable model that includes geometric nonlinearity and flexural stiffness to obtain the stay-cable tensions. Following the proposed methodology, the combination of the SSI-COV method and hierarchical clustering algorithm can be used as a complementary tool alongside the Fourier transform-based analysis of the cable responses to make a distinction between physical and spurious modes of the stay cables.