Journal
ENGINEERING STRUCTURES
Volume 156, Issue -, Pages 175-187Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2017.10.045
Keywords
Masonry towers; Structural health monitoring; Stochastic subspace identification method; Environmental variability; Experimental models; Principal component analysis
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Funding
- Region of Tuscany (Project MOSCARDO - ICT technologies for structural monitoring of age-old constructions based on wireless sensor networks and drones)
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This paper aims at assessing the influence of environmental parameters on the modal characteristics of age-old masonry constructions. The results of a long-term ambient vibration monitoring of the San Frediano bell tower in Lucca (Italy) are reported. The tower, dating back to the 11th century, has been fitted along its height with four triaxial seismometric stations, which were left active for about one year. Data from the monitoring system have been processed via the Stochastic Subspace Identification Method in order to identify the tower's modal characteristics and their variations over the year. The dependence of the tower's frequencies on the ambient temperature was first studied and simulated via simple auto-regressive models. Then, some output-only models based on the principal component analysis (PCA) were applied, under the hypotheses of both linear and nonlinear (Kernel PCA) dependence of the natural frequencies on the unknown environmental parameters. The results indicate PCA to be an effective tool for detecting changes in the dynamic characteristics of masonry constructions.
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