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.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



