Structural Interpretation of Data from Static and Dynamic Structural Health Monitoring of Monumental Buildings

Structural Health Monitoring (SHM) has a crucial role in the diagnosis and conservation of historical buildings, which are typically characterized by articulated fabrics, constructed over decades using different materials and construction techniques. All these issues lead to very complex structural behaviour whose reliable assessment cannot disregard from a sound interpretation of data from SHM systems. SHM systems can be classified into (i) static systems, monitoring the long term time evolutions of specific quantities (such as amplitude of cracks, inclination of walls, relative distances, etc.) and (ii) dynamic systems, continuously monitoring the dynamic response (velocities, accelerations) in order to gather information upon overall dynamic properties such as natural frequencies, mode shapes and damping ratios. The recorded raw data need to be processed in order to distinguish eventual evolutionary trends from the seasonal and daily variations related to thermal effects. In the present work, a simple unified approach for data interpretation acquired from both static and dynamic SHM systems installed in historical buildings is presented. The approach is aimed at: (i) introducing reference quantities for interpretation of seasonal and daily variations, (ii) providing order of magnitudes of reference quantities and (iii) identifying eventual evolutionary trends which could be related to the presence of potential structural criticalities. The approach is illustrated referring to the “Two Towers” of Bologna.

[1] P. P. Rossi and C. Rossi, Surveillance and Monitoring of Ancient Structures : Recent Developments ., System, p.1–15, (1998).

[2] H. Sohn, C. R. Farrar, F. Hemez, and J. Czarnecki, A Review of Structural Health Monitoring Literature 1996 – 2001, Third World Conf. Struct. Control, no. December, p.1–7, (2002).

[3] S. Beskhyroun, L. D. Wegner, and B. F. Sparling, New methodology for the application of vibration-based damage detection techniques, Struct. Control Heal. Monit., no. May 2011, p. n/a-n/a, (2011).

DOI: https://doi.org/10.1002/stc.456

[4] A. G. P. Julius S. Benedat, Random Data Analysis and Mesurement Proceedures. (2000).

[5] S. Baraccani, G. Gasparini, M. Palermo, S. Silvestri, and T. Trombetti, A Possible Interpretation of Data acquired from Monitoring Systems, Twelfth Int. Conf. Comput. Struct. Technol., p.1–12, (2014).

DOI: https://doi.org/10.4203/ccp.106.100

[6] J. F. Claerbout, Fundamentals of Geophysical Data Processing: With Application to Petroleum Prospecting. (1976).

[7] B. Barnhart, The Hilbert-Huang Transform: theory, applications, development, Theses Diss., p.101, (2011).

[8] G. D. Claudio Ceccoli, Pierpaolo Diotallevi, Piero Pozzati, L. Sanpaolesi, Indagini inerenti le strutture murarie e fondali e consolidamento delle parti in elevazione della Torre Garisenda., (2001).

[9] M. Palermo, S. Silvestri, G. Gasparini, S. Baraccani, and T. Trombetti, An approach for the mechanical characterisation of the Asinelli Tower (Bologna) in presence of insufficient experimental data, J. Cult. Herit., vol. 16, no. 4, p.536–543, (2015).

DOI: https://doi.org/10.1016/j.culher.2014.05.002

[10] T. Trombetti, M. Palermo, S. Silvestri, and G. Gasparini, the Dynamic Properties of the Asinelli Tower in Bologna, 2014, no. October, p.14–17.