Structural health monitoring: a tool for managing risks in sub-standard conditions

In the last decade the number of structural health monitoring (SHM) systems designed and implemented on historic structures increased exponentially. Monitoring perfectly meets principles and guidelines of the recently issued Italian and European seismic codes as it is considered a strategic activity in the knowledge process of historic buildings, in order to understand their structural behavior and have a deeper insight on their health conditions. Thanks to SHM it is possible to intervene on buildings with more confidence (and only when necessary), but also to prevent the execution of intrusive strengthening interventions, in full compliance with the minimum intervention principle, so important in the restoration field. The object of monitoring is to identify, locate and classify type and severity of damages induced by external actions or degradation phenomena and to assess their effects on the structural performance. In this way it is possible to take appropriate measures to reduce the danger of collapse and, when necessary, perform strengthening interventions to improve the structural and seismic capacity. Motivated by the above reasons, the paper provide a contribution to the application of integrated methodologies and techniques, based on SHM, for the assessment and protection of cultural heritage (CH) buildings and existing structures. Selected case studies, equipped with distributed sensors and acquisition systems, allowed the definition and successive validation of SHM as a knowledge-based assessment tool, implemented to: (1) avoid the execution of unnecessary interventions and assess structural vulnerabilities; (2) evaluate intervention needs, following an incremental approach during their execution; (3) control the damage states of buildings in a post- seismic scenario. Monitoring data, automatically processed through dedicated software for static monitoring and automated algorithms for modal parameters extraction, are then used for the assessment of the health conditions and the identification of active damaging processes based on numerical simulations and robust statistical models.