A time domain approach for data interpretation from long‐term static monitoring of historical structures. Issue 5 (1st March 2021)

• Record Type: Journal Article
• Authors: Baraccani, Simonetta; Palermo, Michele; Gasparini, Giada; Trombetti, Tomaso
• Is Part Of: Structural control and health monitoring. Volume 28:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-01
• Subjects: amplitudes -- data analysis -- historical buildings -- reference quantities -- residuals -- structural health monitoring; Structural engineering -- Periodicals; Structural control (Engineering) -- Periodicals; Automatic data collection systems -- Periodicals; Detectors -- Periodicals; 624.17
• DOI: 10.1002/stc.2708
• Languages: English
• ISSNs: 1545-2255

Abstract

Summary: The conservation of historical buildings requires periodic inspections, maintenance, and/or strengthening interventions, resulting in significant costs. The accurate estimate of the structural condition may contribute to optimize the allocation of resources. With the diffusion of innovative technologies of Structural Health Monitoring (SHM), several permanent monitoring systems have been installed in the last decades in historical buildings. This fact has encouraged investigations about methods for the assessment of structural health based on recorded data. The aim of this study is to introduce a time‐domain approach for the analysis and interpretation of large amount of data from long‐term static monitoring of historical masonry structures. It is assumed that the recorded signals can be decomposed into two main components: a periodical one, mainly due to environmental actions, and a non‐periodical component related to potential variations in the state of conservation of the structure. The analysis of the two components is conducted through specific descriptors (here referred to as "reference quantities") by means of statistical evaluations. Such reference quantities could be used as the roots for the establishment of standardized procedures for data analysis and interpretation. The approach has been applied to analyze data from the SHM system of the Two Towers of Bologna (Italy).