PSI - Issue 84

Gianluca Centofanti et al. / Procedia Structural Integrity 84 (2026) 1339–1346

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review under responsibility of the scientific committee of the Conference Keywords: OMA; SHM; Bridge monitoring; Multi-span bridge.

1. Intruduction Italy is characterised by one of the most extensive and complex infrastructure networks in Europe, comprising approximately 2’179 tunnels with a total length of 1’759 km and 21’072 bridges and viaducts extending over 2’829km, considering only the main national and motorway routes [https://www.ansfisa.gov.it/opere-d-arte]. This extensive infrastructure network was largely constructed in the post-war period during the economic boom between the 1950s and 1970s, and a significant proportion of these assets may no longer comply with current safety requirements (Calvi G.M. et al., 2019). Following the collapse of the Polcevera Viaduct in August 2018, the need for a more structured and systematic approach to the surveillance of civil infrastructure assets became evident. Such an approach should encompass the full asset management process, ranging from inventory and classification to safety assessment and instrumental monitoring, with the aim of gaining improved insight into the residual service life of structures (Santarsiero G. et al.,2021). Within this context, the implementation of Continuous Structural Health Monitoring (CSHM) technologies is particularly valuable, as it provides real-time data on the structural condition of infrastructure assets, thereby supporting informed maintenance and preservation strategies. Among the most adopted techniques are those based on ambient vibration analysis, namely Operational Modal Analysis (OMA). One of the main advantages of OMA-based approaches is that they are non-destructive and non-invasive, as they do not require artificial excitation sources; for this reason, they are well suited for real-time monitoring under operational conditions (Andreose F. et al., 2024; Comanducci G. et al. 2015). OMA techniques exploit ambient excitations such as traffic loads, wind actions and low amplitude microtremors, which may also originate from anthropogenic activities. These vibrations are recorded by sensors installed on the structure and subsequently processed to extract the modal characteristics of the system, including natural frequencies, mode shapes and damping ratios. These modal parameters exhibit a high sensitivity to variations in structural stiffness and energy dissipation mechanisms and are therefore widely employed as damage-sensitive indicators for the assessment of structural integrity. To address these emerging requirements in infrastructure safety, ANAS S.p.A., the primary Italian road infrastructure operator managing more than 32’000 km of roads nationwide, launched in 2022 a pioneering initiative known as the SHM Programme, with a total investment of €275 million. The programme aims to implement structural monitoring systems on 1,000 infrastructure assets across the Italian territory by 2026 [https://www.stradeanas.it/it/monitoraggio-ponti-territorio]. For the processing of monitoring data, ANAS S.p.A. has adopted a dedicated software platform (P3P) equipped with automated analysis algorithms operating continuously. This platform was developed by a research group involving the University of Perugia, Politecnico di Milano and the University of Padua, within the research activities of the FABRE Consortium, a national research consortium focused on the assessment and monitoring of bridges, viaducts and other civil engineering structures ( García-Macías E. et al., 2022). The collaboration between ANAS S.p.A. and the FABRE Consortium has also been extended to the configuration and initialisation activities of the analyses performed by the platform. These activities include the subdivision of measurement data acquired from the monitored structures into groups suitable for subsequent interpretation, the selection and calibration of parameters associated with the OMA algorithms, and the definition of training periods for learning the baseline structural behaviour (Tomassini E, et al., 2025). At present, the ANAS SHM P3P platform comprises 249 edge units connected to continuously operating monitoring projects. Among the monitored assets, the majority are prestressed reinforced concrete (PSC) structures (87.3%), while the remaining portion consists of reinforced concrete (RC) (5.5%), steel (4.1%) and composite steel–concrete structures (3.2%), with a nearly uniform distribution among these categories (see Figure 1). Within the subset of PSC viaducts, more than 75% are characterised by a simply supported beam static scheme, while approximately 10% consist of simply supported beams with a continuous deck slab. RC viaducts exhibit a more