Detection and Location of the Degraded Bearings Based on Monitoring the Longitudinal Expansion Performance of the Main Girder of the Dashengguan Yangtze Bridge

Temperature field data from the steel truss arch girder and longitudinal displacement data from six groups of rubber bearings were collected by the structural health monitoring system for the Dashengguan Yangtze Bridge. By using long-term monitoring data, two correlations are investigated: the linear correlation between the longitudinal displacement and the temperature field (including uniform temperature and temperature gradient); and the linear correlation of the longitudinal displacements in different locations. A multivariate linear regression equation is used to model the first correlation, and a Lagrange polynomial interpolation is used to model the second correlation. The final mathematical models, representing the healthy state of the bearings, can be applied to simulate the longitudinal displacements of the main girder. Furthermore, the change regularity of longitudinal displacements for the degraded rubber bearings is revealed taking advantage of a hysteretic model and presumed envelope curves of frictions caused by bearing degradation. A method of detection and location for the degraded bearings is proposed in four detailed steps, and the numerical results demonstrate that this method is effective. (C) 2015 American Society of Civil Engineers.