Abstract

Bridge collapse in recent years due to lack of maintenance has been increasing. One of the examples is The Morandi Bridge collapse in Genoa, that killed 41 people in 2018 with serious economic consequences [2]. In addition, common means and methods used for bridge health monitoring do not have the possibility to predict the evolution of the structural state. For this reason, a semi-empirical method based on a twin model and data register in specific points is exposed herein. It achieves to implement a predictive diagnosis of the bridge. This was applied to Pirihueico Bridge and allows to characterize the response of the structure under operational conditions in real time. This bridge is located at P.K. 114.29 of Route 203, in the commune of Panguipulli in the province of Valdivia (Los Lagos Region, Chile). The environment is characterized by being a forest and tourist area with low population density and an expected low traffic flow, both heavy and light