This article presents the development and the results of 1 year of implementation of a simple vibration-based structural health monitoring system for preventive conservation and condition-based maintenance of an Italian monumental masonry bell-tower. The system is based on the data recorded by a small number of high-sensitivity accelerometers, on remote automated frequency tracking and on a multivariate statistical analysis criterion for damage detection, combining data regression, principal component analysis, and novelty analysis. The analysis of monitoring data highlights the main characteristics of the response of the tower to wind, swinging bells, and low-return period earthquakes. Despite the low levels of vibration in operational conditions, the system is seen able to track the time evolution of five natural frequencies of the structure and successfully use such information for detecting anomalous deviations from normal conditions. More in general, the presented results show a promise toward a more widespread use of low-cost vibration-based monitoring systems for cultural heritage preservation.

Synthetic Aperture Radar Interferometry (InSAR) using satellite data is revealing a promising tool for monitoring long-term deformation phenomena in critical infrastructural systems. Nevertheless, its use in structural engineering is still quite limited and a general understanding of its potential is still missing, especially when dealing with bridge structures for which specific methods of data processing and displacement assessment with error quantification need to be developed, accounting for the type of deformation phenomena and for the orientation of the bridge. In order to partly fill this research gap, this paper proposes a post-processing methodology to derive two-dimensional displacement configurations of multi-span bridges with properly defined error bounds, using both ascending and descending Synthetic Aperture Radar acquisitions. In order to obtain an engineering meaningful estimate of the uncertainties affecting the reconstructed bridge deformations, both random and systematic errors are quantified, accounting for the orientation of the bridge with respect to the Line-Of-Sights of the satellites, the hypothesized deformation plane and the accuracy of InSAR measurements. The proposed procedure has been applied to the illustrative case study of the Albiano-Magra Bridge in Italy, collapsed on 8 April 2020. The results, referred to the monitoring period 2015–2020, demonstrate the effectiveness of the proposed method in supporting engineering assessments. In particular, an initially temperature-induced stationary deformation phenomenon has been observed, with all spans moving upwards or downwards during summer and winter. Afterwards, displacements of increasing amplitude for two side spans have been observed during the three years preceding the failure, providing information on the possible cause of collapse.

This work investigates the use of an advanced long-term vibration-based structural health monitoring tool to automatically detect earthquake-induced damages in heritage structures. Damage produced in a monumental bell-tower at increasing values of the Peak Ground Acceleration (PGA) of the seismic input is predicted by incremental nonlinear dynamic analysis, using a Finite Element model calibrated on the basis of experimentally identified natural modes. Then, predicted damage effects are artificially introduced in the monitoring data to check for their detectability. The results demonstrate that a very small damage, associated to a low intensity and low return period earthquake, is clearly detected by the monitoring system.