An Automated Algorithm for Experimental OMA: Application on a Warren Truss Railway Bridge with a Permanent Monitoring System

In the attempt to move towards time-efficient and cost-effective condition-based monitoring of transport infrastructures, Structural Health Monitoring (SHM) has gained a key role, and driven researchers and infrastructure managers attention. SHM consists of the extraction of quantitative information regarding bridge health status, from the measurement of its response. Since able to reflect changes of the mechanical properties of the structure under analysis, modal parameters are commonly used to track the evolution of its condition. Operational Modal Analysis (OMA) represents a well-established procedure through which it is possible to monitor the evolution of bridge modal properties. This paper focuses on the application of an automated algorithm for experimental OMA exploiting data collected from a permanent monitoring system mounted on a Warren truss railway bridge. This kind of structure became extremely popular after World War II. The bridge under analysis was recently instrumented with a set of different sensing devices, including thermistors and velocimeters, with the final aim of continuously monitoring its condition. In particular, the results in terms of modal parameters identification are presented in this work: the focus is put on natural frequencies and associated mode shapes extraction, analysing then their trends during the first months of acquisition.