ABSTRACT
Maintenance of railway bridges is one of the major challenging activities in the railway sector, due to the number, the variety and the advanced age of structures. Structural health monitoring (SHM) can be of great help to assess the state of bridges and to program their maintenance. Despite major achievements have been reached in recent years, there is still the need both to standardize monitoring and design methodologies for a large-scale application of these systems to railway works and to collect and manage a large amount of data. For these reasons, RFI is carrying on a research activity to define typological systems to standardize and optimize the SHM to be applied on a large scale of bridges belonging to the national network. With these systems it will be possible to deepen and estimate, on the basis of objective information, the current state of structures, aiming at establishing the need of a maintenance work or a structural adjustment. Accordingly, together with human inspection, the monitoring will make it possible to build a reliable list of intervention priorities. Regarding the data transmission system and management, the experimental activity aims to define both the most reliable and cost-effective data transmission architectures. Eventually, the aim is to integrate on-field systems with the RFI IoT central platform capable of managing Big Data also by resorting to Artificial Intelligence algorithms.
