PSI - Issue 84

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ScienceDirect

Procedia Structural Integrity 84 (2026) 1339–1346

© 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference Abstract The increasing safety requirements for transport infrastructure assets are fostering the adoption of Continuous Structural Health Monitoring (CSHM) platforms capable of reliably detecting deviations from baseline structural behaviour. In Italy, ANAS S.p.A. was among the first asset manager to implement such advanced systems, developing the ANAS SHM P3P software in collaboration with the Consorzio FABRE. The adopted monitoring strategies fall within the framework of Structural Health Monitoring (SHM), which offers the key advantages of being non-destructive and fully compatible with the uninterrupted operation of the infrastructure during data acquisition. At present, the most widely adopted approaches are based on Operational Modal Analysis (OMA) using ambient vibrations. When coupled with automated identification algorithms and advanced statistical modelling, these techniques enable the formulation of control charts and damage-sensitive indicators for the early detection of structural anomalies. A critical aspect in the implementation of SHM systems concerns the definition of sensor layouts, and particularly the subdivision of the monitoring network into sensor subgroups. An appropriate grouping strategy can significantly enhance the interpretability of the identified dynamic features, improve the sensitivity to localised structural changes, and reduce the computational burden associated with on-site edge processing units. Drawing on the experience gained through the long-term collaboration between ANAS S.p.A. and the Consorzio FABRE, this paper presents a set of case studies involving infrastructure assets characterised by different structural typologies and dynamic behaviours. The proposed examples discuss practical criteria for sensor subgrouping and demonstrate how these choices can optimise the interpretation of monitoring results with respect to the dynamic response of the monitored structures. III Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications Lessons learnt from Continuous SHM in the Anas SHM P3P platform: Key-role of sensor sub-groups management Gianluca Centofanti a, *, Giuseppe Chellini a , Lorenzo Lepori b , Stefano Anastasia b , Paolo Mannella b , Walter Salvatore a a Department of Civil and Industrial Engineering, University of Pisa. Largo L. Lazzarino, 1 – 56122 Pisa, Italy b ANAS S.p.A,- 00185 Roma, Italy

* Corresponding author. E-mail address: gianlucacentofanti@consorziofabre.it

2452-3216 © 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference 10.1016/j.prostr.2026.06.171