Fully automated operational modal analysis for Structural Health Monitoring of Heritage Buildings

The thesis is focused on the definition of an integrated fully automated procedure for the modal identification and tracking in the Cultural Heritage. The established framework aimed to investigate the possibility of a designing an automated procedure for the modal parameters extraction and tracking from long-term monitoring system data minimizing the variance in the estimation. The proposed flow chart is a self-adaptive algorithm both to the structural dynamics and to the different sources of the unknown dynamic excitation. Firstly, the aim is building an automated procedure for the modal identification able to manage all the sources of uncertainty that affect the problem in every phase. Then, the proposed procedure is used in a wider method for analysing large dataset of long-term dynamic monitoring data aiming to track the modal quantities over the time minimizing the bias. That point is crucial to increase the accuracy in the estimation of the damage sensitive features in a Structural Health Monitoring (SHM) workflow to enable the detection. The work of thesis deepened that aspects investigating the historic masonry towers by means of numerical models and real data. Lastly, some numerical simulations are performed to investigate the possibility of an integration with global and local dynamic measurements. Despite the application of the method on a specific class the whole framework is conceived to be adapted to different classes of buildings and measuring devices through a data driven process.