This study presents the long-term static monitoring data acquired from the Dome of Santa Maria del Fiore in Florence. The monitoring system, operating since the late 1980s, includes displacement transducers and temperature sensors strategically placed along radial, meridian, and parallel directions of the dome, recording time series of over 54,000 samples, as well as force-balance accelerometers measuring the structural response at four levels in three directions. The data was pre-processed accounting for various anomalies, including missing data, spikes, and shifts and then analysed from a statistical point of view considering the whole time series. The work highlights key challenges in handling anomalies and assessing data quality, and discusses the integration of multi-modal data, supporting the need for automated pre-processing frameworks and future incorporation of dynamic measurements into the structural assessments of the dome.

SHM for Historic Masonry: Long-Term Data from the Dome of Santa Maria del Fiore / Marafini, F.; Zini, G.; Barontini, A.; Mendes, N.; Betti, M.; Bartoli, G.. - ELETTRONICO. - 753 LNCE:(2025), pp. 485-500. ( 8th International Conference on Mechanics of Masonry Structures Strengthened with Composite Materials, MuRiCo8 2025 Bologna June 25th-27th 2025) [10.1007/978-3-032-05032-8_37].

SHM for Historic Masonry: Long-Term Data from the Dome of Santa Maria del Fiore

Marafini, F.;Zini, G.;Betti, M.;Bartoli, G.
2025

Abstract

This study presents the long-term static monitoring data acquired from the Dome of Santa Maria del Fiore in Florence. The monitoring system, operating since the late 1980s, includes displacement transducers and temperature sensors strategically placed along radial, meridian, and parallel directions of the dome, recording time series of over 54,000 samples, as well as force-balance accelerometers measuring the structural response at four levels in three directions. The data was pre-processed accounting for various anomalies, including missing data, spikes, and shifts and then analysed from a statistical point of view considering the whole time series. The work highlights key challenges in handling anomalies and assessing data quality, and discusses the integration of multi-modal data, supporting the need for automated pre-processing frameworks and future incorporation of dynamic measurements into the structural assessments of the dome.
2025
Lecture Notes in Civil Engineering
8th International Conference on Mechanics of Masonry Structures Strengthened with Composite Materials, MuRiCo8 2025
Bologna
June 25th-27th 2025
Goal 13: Climate action
Marafini, F.; Zini, G.; Barontini, A.; Mendes, N.; Betti, M.; Bartoli, G.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1440692
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