Sequential Importance Sampling Algorithm in Damage Detection of a Cable Stayed Bridge

Abstract

Damage detection of civil infrastructure has gained significant momentum in the last decade due to aging and being more prone to failure of infrastructure. New advances in sensing technology have made it possible to detect damage in giant infrastructure more effectively. As the size of structure increases, the number of installed sensors on the structure increases significantly. This increase in the number of sensors makes it more challenging to collect and interpret the data. Therefore, utilizing the minimum number of sensors at any time of detection while maintaining an effective monitoring system is of great interest. In this paper, we will develop an innovative on/off sensors methodology using the sequential importance sampling technique to choose the sensors to be turned on at any given time while tracking the potential damage. This method will be used on a cable stayed bridge over Mississippi River called Luling Bridge. The finite element (FE) model of the bridge is developed to introduce the damage at different girder locations in the bridge. This model will be used to show the effectiveness of the proposed sequential importance sampling method in providing effective monitoring with minimal number of turned activated sensors at any given time.