Uncertainty quantification in structural health monitoring: Applications on cultural heritage buildings. (January 2016) - Lorenzoni, Filippo; Casarin, Filippo; Caldon, Mauro; Islami, Kleidi; Modena, Claudio
Abstract: In the last decades the need for an effective seismic protection and vulnerability reduction of cultural heritage buildings and sites determined a growing interest in structural health monitoring (SHM) as a knowledge-based assessment tool to quantify and reduce uncertainties regarding their structural performance. Monitoring can be successfully implemented in some cases as an alternative to interventions or to control the medium- and long-term effectiveness of already applied strengthening solutions. The research group at the University of Padua, in collaboration with public administrations, has recently installed several SHM systems on heritage structures. The paper reports the application of monitoring strategies implemented to avoid (or at least minimize) the execution of strengthening interventions/repairs and control the response as long as a clear worsening or damaging process is detected. Two emblematic case studies are presented and discussed: the Roman Amphitheatre (Arena) of Verona and the Conegliano Cathedral. Both are excellent examples of on-going monitoring activities, performed through static and dynamic approaches in combination with automated procedures to extract meaningful structural features from collected data. In parallel to the application of innovative monitoring techniques, statistical models and data processing algorithms have been developed and applied in order to reduce uncertainties and exploit monitoring results for an effective assessment and protection of historical constructions. Processing software for SHM was implemented to perform the continuous real time treatment of static data and the identification of modal parameters based on the structural response to ambient vibrations. Statistical models were also developed to filter out the environmental effects and thermal cycles from the extracted features. Highlights: Application of structural health monitoring to cultural heritage buildings. System identification algorithms are implemented to reduce uncertainties. Regression analysis is applied to filter environmental effects and identify damages. Automated algorithms are implemented to extract meaningful features from SHM data.