The influence of environmental parameters on the dynamic behaviour of the San Frediano bell tower in Lucca. (1st February 2018)

• Record Type: Journal Article
• Authors: Mario Azzara, Riccardo; De Roeck, Guido; Girardi, Maria; Padovani, Cristina; Pellegrini, Daniele; Reynders, Edwin
• Is Part Of: Engineering structures. Volume 156(2018)
• Page Start: 175
• Page End: 187
• Publication Date: 2018-02-01
• Subjects: Masonry towers -- Structural health monitoring -- Stochastic subspace identification method -- Environmental variability -- Experimental models -- Principal component analysis; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2017.10.045
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Long-term ambient vibration monitoring of the San Frediano bell tower in Lucca and data analysis. Assessment of the dependence of the tower's dynamic characteristics on temperature. Output-only linear and nonlinear environmental models for damage detection. Abstract: 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.