Figure 3 - uploaded by Filippo Ubertini
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Geometrical survey of the bell-tower: front view (a); sectional view (b); plan at the base of the belfry (c) and plan at the base of the cusp (d).
Source publication
This article presents the development and the results of 1 year of implementation of a simple vibration-based structural health monitoring system for preventive conservation and condition-based maintenance of an Italian monumental masonry bell-tower. The system is based on the data recorded by a small number of high-sensitivity accelerometers, on r...
Context in source publication
Context 1
... 8 m high and has a cone shape with width varying from 3.5 to 2 m. The shaft has a dodecagonal cross section and reaches the height of about 26 m, including basement. The belfry has an hexagonal cross-section and reaches the height of about 41 m. The cusp completes the tower on the top and has the shape of a pyramid with hexagonal cross-section. Fig. 3 is a solid representation of the structure consisting of an external front view, a sectional view, a three-dimensional view and the plans at the base of the belfry and of the cusp. The solid CAD model has been constructed on the basis of detailed architectural survey data (courtesy of Arch. Francesco Ventura, cf Acknowledgments), ...
Similar publications
The paper describes the strategy adopted to assess the structural condition of the tallest historic tower in Mantua (Italy) after the Italian seismic sequence of May-June 2012 and exemplifies the application of health monitoring using (automated) operational modal analysis. The post-earthquake survey (including extensive visual inspection, historic...
Since destructive tests are not allowed for historical structures, numerical model updating using accelerometers has gained a lot of attraction in the last decade. Furthermore, another application of structural health monitoring is damage detection for near-real-time monitoring of cultural heritage assets of infrastructures such as masonry bridges....
Citations
... Vibration-based monitoring (VBM) [13,14] evaluates structure safety by observing their global response, crucial for damage detection and classification. This methodology uses vibration sensors like accelerometers to record structural vibrations, enabling the identification of anomalies and changes in dynamic behavior. ...
This paper focuses on the acquisition and
analysis of ambient vibrations for structural monitoring
in the Castello Ursino Museum in Catania, Italy. The
main goals are twofold: using the Tromino® measurement
system for structural monitoring and identifying highenergy
zones to place self-sustaining autonomous nodes
for vibration measurement. The study's findings from the
museum's measurement campaign locate the primary
Pinacoteca Room, sited at the second level, as specific area
of interest regarding vibrations, such as induced from
sources like structural dynamics, visitor activity, and
traffic. Moreover, laboratory tests demonstrate the
feasibility of employing autonomous nodes aligned with
Tromino® for vibration measurement, utilizing these
vibrations as a potential energy source for sustaining the
measuring nodes.
... Tracking the variation of frequencies over time, assessing environmental effects, and analyzing changes and anomalies in the dynamic behavior of a building are essential aspects of SHM. Applying SHM to a building can provide helpful information on the vibration sources, the variation of dynamic properties, and the structural ''safety'' state of the structure, making damage detection possible; in fact, changes in the dynamical properties over time can represent structural damage indicators [3][4][5]. ...
... Relevant applications are described in [6][7][8]. Data-driven methods relying on regression and output-only techniques, like the principal component analysis of the frequencies time-histories, are adopted in [5,9,10]. ...
... Several long-term vibration monitoring campaigns on ancient masonry towers [4,5,9,10] have pointed out that the frequencies tend to increase with temperature. The Guinigi Tower does not exhibit such a trend. ...
... Relative rotation of the foundation system Exponent of the Benzeggagh-Kenane fracture energy criterion Visco-plastic regularization applications of vibration-based SHM systems exploiting OMA methods to historical masonry buildings can be found in [21][22][23][24][25][26][27][28][29]. In this context, the removal of environmental effects from the tracked modal features is a task of the utmost importance [30,31]. ...
Operational Modal Analysis (OMA) is a powerful approach to be used in structural performance assessment of historical masonry buildings during their service life. OMA is effective for detecting global damage to masonry buildings, although in some conditions it may exhibit poor sensitivity in detecting local/slight structural damage. Additionally, establishing robust correlations between changes in modal features and the residual load-bearing capacity of monitored buildings is an unresolved task in most of real-world applications. To deepen into these aspects, this paper presents an experimental and numerical program involving two full-scale masonry wall specimens tested under controlled laboratory conditions. Progressive damage was induced in diverse structural settings, and OMA was used to identify the modal features of the wall systems at increasing damage levels. Damage-induced decays in modal features were correlated with performance limit states related to the structures' residual load-bearing capacity, while non-linear Finite Element (FE) models were defined to replicate the tests. The obtained results contribute to filling current research gaps by demonstrating that natural frequencies and mode shapes can be sensitive to local and slight structural damage, also proposing correlations between damage-induced decays in modal features and performance limit states, hence corroborating the use of FE models for replicating damage-induced decays in both vibration frequencies and mode shapes.
... Furthermore, the robustness of these methods is conditioned by operational and environmental effects, whose variations may often mask changes due to damage [19][20][21][22]. To this end, a common strategy, in SHM field, is to develop a model capable of explaining the operational and environmental induced changes to the modal properties, in order to decouple them and the structural damage effects, for instance through regression models, autoregressive models or principal component analysis [23,24,[24][25][26][27][28]. ...
... Tracking the variation of frequencies over time, assessing environmental effects, and analyzing changes and anomalies in the dynamic behavior of a building are essential aspects of SHM. Applying SHM to a building can provide helpful information on the vibration sources, the variation of dynamic properties, and the structural "safety" state of the structure, making damage detection possible; in fact, changes in the dynamical properties over time can represent structural damage indicators [3], [4], [5]. ...
... Relevant applications are described in [6], [7] and [8]. Data-driven methods relying on regression and output-only techniques, like the principal component analysis of the frequencies time-histories, are adopted in [9], [5], [10]. ...
... Several long-term vibration monitoring campaigns on ancient masonry towers ( [4], [9], [5], [10]) have pointed out that the frequencies tend to increase with temperature. The Guinigi Tower does not exhibit such a trend. ...
... Monitoring the variation of frequencies over time, assessing environmental effects and analysing changes and anomalies are essential ingredients of damage detection. This operation can be accomplished via regression and output-only methods [1,10,11,25,26] and machine learning techniques [4,19]. ...
This paper describes the experiments carried out on a mediaeval masonry tower in the historic centre of Lucca and some finite element numerical simulations of the tower's experimental response. The Guinigi Tower, one of the most iconic monuments in Lucca, has been continuously monitored by high-sensitivity seismic stations that recorded the structure's response to the dynamic actions of the surrounding environment. The monitoring campaign results have been analysed to show the effectiveness of dynamic monitoring as a valuable source of information on the structural properties of the tower. The dynamic analyses of the tower and the surrounding palace subjected to some seismic events recorded during the experiments have highlighted the capabilities of experiment-based finite element modelling. The calibration of the finite element model and the numerical analysis have been carried out by resorting to procedures developed at ISTI-CNR and able to consider the nonlinear behaviour of masonry materials.
... In recent decades, structural health monitoring is gathering relevance due to its role in supporting decision making for the maintenance of civil infrastructures and architectural heritage [1][2][3][4]. In addition, recent advances in technology and accessibility of sensors and recording systems fostered the application of dynamic identification, in particular the installation and operation of continuous monitoring systems. ...
Recent developments in sensors and data processing made the structural health monitoring (SHM) sector expanding to big-data field, particularly when continuous long-term strategies are implemented. Nevertheless, main shortcomings are due to the identification and extraction of modal features. In fact, although machine learning methods have been implemented to automate modal identification processes, intense user interaction and time-consuming procedures are still required, limiting the extensive use of these techniques. In order to provide a fully automated procedure capable of identifying and extracting modal properties from covariance driven SSI analyses, an innovative and flexible algorithm for Iterative Hierarchical Clustering Analysis (IHCA) is proposed. To evaluate the stability and robustness of the IHCA method, a Variance-Based Global sensitivity Analysis (VBGA) was performed considering a numerical and experimental case study. The outcomes demonstrated that the IHCA is stable in clustering the physical structural modes and selecting the most representative modal features.
... Widely used statistical models for self-supervised methods include time series analysis models [84], Bayesian-based models [53], and various ML models [54], [85]. Unsupervised methods mainly include multivariate analysis such as principal components analysis (PCA) [70], canonical correlation analysis (CCA) [86], independent component analysis (ICA) [62], and cluster analysis [63]. More details on the statistical models used in data-driven methods are clarified in section 5 of this survey. ...
... Besides, several different MA models can be utilized jointly for more accurate analysis. Ubertini et al. [70] integrate several multivariate analysis methods to detect damage of a historic structure, San Pietro bell-tower in Italy. A multivariate linear regression (MLR) model is adopted to remove the effects of temperature in identified natural frequencies, and PCA is used to remove the effects of other unmeasured environmental factors. ...
Estimating engineering structures’ health conditions and predicting their future behaviors are fundamental problems for a city’s safe and efficient operations. Data-driven solutions estimate the health conditions using statistical models generated from measurement data. They have attracted growing interest recently because advances in information and communication technologies (ICT) have enabled numerous real-world measurement data, and the flourishing big data community has provided enormous state-of-the-art data analytics algorithms. Nevertheless, most existing studies remain in numerical simulation while neglecting their real-world implementation, restricting the extensive development of data-driven methods. In this survey, we provide a structural overview of the past decade’s data-driven structural health monitoring (SHM) systems and algorithms from the perspective of real-world implementation. Specifically, we cover various aspects of the design and implementation of monitoring systems, including sensing technologies, communication technologies, and processing software. In addition, we classify the used data sources and statistical models with fined details. Under the proposed taxonomy, their limitations and advantages are thoroughly discussed. Based on our insights into existing studies, we clarify two major implementation challenges: the digressive performance in the real-world environment and inefficient computing systems for real-time data analytics. Possible solutions are then proposed to mitigate those challenges and promote the implementation of data-driven methods. Finally, we raise our outlook on future trends and suggest promising directions for further investigation.
... This technology uses concepts of passive reconstruction of a system's Green's function (or transfer function) that have been developed in various fields, including seismology, underwater acoustics, and also structural inspections [20][21][22][23][24][25][26]. Examples include ambient vibrations in bridges induced by traffic [27][28][29][30], aerodynamic vibration signatures from aircraft wings and wind-turbine blades [31,32], wind-induced vibrations in high-rise buildings [33], among others. This paper presents the latest performance evaluation of a high-speed rail inspection prototype based on this "passive" approach that was tested at the Transportation Technology Center (TTC) in Pueblo, CO, USA at speeds up to 80 mph. ...
Background
Continuous monitoring is essential for detecting internal defects in rails and prevent derailment related accidents. Existing techniques do not facilitate continuous monitoring because they require specialized test cars and can only operate at speeds of up to 30 mph.
Objective
The objective of this study is to evaluate the performance of a high-speed rail inspection system using a non-contact ultrasonic technique with the potential of operating at train revenue speeds.
Methods
The technique utilizes air-coupled transducers that record the ultrasonic guided waves generated by the rail-wheel contact and does not require a controlled acoustic source of excitation. A modified version of the traditional Welch’s periodogram technique is utilized to extract the Green’s function between two points on the rail. The passively extracted Green’s function is then analysed statistically to detect structural discontinuities (e.g., defects) in the rail.
Results
Results from fields tests performed at the Transportation Technology Centre (TTC) in Pueblo, CO, USA, demonstrate possible test speeds as high as 80 mph. From these field tests, the performance of the system is evaluated using Receiver Operating Characteristic (ROC) curves for a range of different operational parameters including test speed, location of the sensors relative to the locomotive (source), signal-to-noise ratio (SNR) of the raw signals, SNR of the reconstructed transfer function, baseline distribution length in the statistical analysis, wheel-rail interactions, and redundancies introduced from multiple runs over the same track.
Conclusions
This study presents the current stage of development and performance of the passive rail inspection system with full-scale experiments under field conditions. The results indicate the potential of the system to operate at high speeds as well as possible avenues of future improvement to the system.
... Moreover, since the structural input is due to the ambient vibrations (usually modelled as a white noise process [3][4][5]), OMA methods allow to identify the structural system when it is under operative conditions. This kind of methods have been used to identify structural systems [6][7][8], to perform structural health monitoring (SHM) [9][10][11][12][13], to calibrate finite elements models [14] and to detect structural damages [15,16]. OMA methods has been applied on historical buildings [7,17,18], tall buildings [19,20], bridges [21-23], masonry structures [24], dams [25], offshore platforms [26,27] and other structural systems [28][29][30][31]. ...
Operational modal analysis (OMA) methods are nowadays common in civil, mechanical and aerospace engineering to identify and monitor structural systems without any knowledge on the structural excitation provided that the latter is due to ambient vibrations. For this reason, OMA methods are embedded with stochastic concepts and then it is difficult for users that have no-knowledge in signal analysis and stochastic dynamics. In this paper an innovative method useful for structural health monitoring (SHM) is proposed. It is based on the signal filtering and on the Hilbert transform of the correlation function matrix. Specifically, the modal shapes are estimated from the correlation functions matrix of the filtered output process and then the frequencies and the damping ratios are estimated from the analytical signals of the mono-component correlation functions: a complex signals in which the real part represents the correlation function and the imaginary part is its Hilbert transform. This method is very simple to use since requires only few interactions with the users and thus it can be used also from users that are not experts in the aforementioned areas. In order to prove the reliability of the proposed method, numerical simulations and experimental tests are reported also considering comparisons with the most popular OMA methods.
