ArticlePublisher preview available
To read the full-text of this research, you can request a copy directly from the authors.

Abstract and Figures

Historical buildings demand constant surveying because anthropogenic (e.g., use, pollution or traffic vibration) and natural or environmental hazards (e.g., environmental changes or earthquakes) can endanger their existence and safety. Particularly, in the Andean region of South America, earthen historical constructions require special attention and investigation due to the high seismic hazard of the area next to the Pacific coast. Structural Health Monitoring (SHM) can provide useful, real-time information on the condition of these buildings. In SHM, the implementation of automatic tools for feature extraction of modal parameters is a crucial step. This paper proposes a methodology for the automatic identification of the structural modal parameters. An innovative and multi-stage approach for the automatic dynamic monitoring is presented. This approach uses the Data-Driven Stochastic Subspace Identification method complemented by hierarchical clustering for automatic detection of the modal parameters, as well as an adaptive modal tracking procedure for providing a clear visualization of long-term monitoring results. The proposed methodology is first validated in data acquired in an emblematic sixteenth century historical building: the monastery of Jeronimos in Portugal. After proving its efficiency, the algorithm is used to process almost 5000 events containing data acquired in the church of Andahuaylillas, a sixteenth century adobe building located in Cusco, Peru. The results in these cases demonstrate that accurate estimation of predominant modal parameters is possible in those complex structures even if relatively few sensors are installed.
This content is subject to copyright. Terms and conditions apply.
ORIGINAL PAPER
Automated long-term dynamic monitoring using hierarchical
clustering and adaptive modal tracking: validation and applications
Giacomo Zonno
1
Rafael Aguilar
1
Rube
´n Boroschek
2
Paulo B. Lourenço
3
Received: 12 July 2018 / Accepted: 5 September 2018 / Published online: 19 September 2018
ÓSpringer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract
Historical buildings demand constant surveying because anthropogenic (e.g., use, pollution or traffic vibration) and natural
or environmental hazards (e.g., environmental changes or earthquakes) can endanger their existence and safety. Particu-
larly, in the Andean region of South America, earthen historical constructions require special attention and investigation
due to the high seismic hazard of the area next to the Pacific coast. Structural Health Monitoring (SHM) can provide useful,
real-time information on the condition of these buildings. In SHM, the implementation of automatic tools for feature
extraction of modal parameters is a crucial step. This paper proposes a methodology for the automatic identification of the
structural modal parameters. An innovative and multi-stage approach for the automatic dynamic monitoring is presented.
This approach uses the Data-Driven Stochastic Subspace Identification method complemented by hierarchical clustering
for automatic detection of the modal parameters, as well as an adaptive modal tracking procedure for providing a clear
visualization of long-term monitoring results. The proposed methodology is first validated in data acquired in an
emblematic sixteenth century historical building: the monastery of Jeronimos in Portugal. After proving its efficiency, the
algorithm is used to process almost 5000 events containing data acquired in the church of Andahuaylillas, a sixteenth
century adobe building located in Cusco, Peru. The results in these cases demonstrate that accurate estimation of pre-
dominant modal parameters is possible in those complex structures even if relatively few sensors are installed.
Keywords Historical buildings Andean adobe structures Long-term monitoring Automatic identification
Adaptive modal tracking
1 Introduction
Structural Health Monitoring (SHM) is an area that has
increasingly become of interest to improve the knowledge
of existing structural systems and their seismic perfor-
mance [13]. In the case of cultural heritage buildings, an
increment in the use of SHM has been triggered due to the
high complexity of this type of constructions and the dif-
ficulty to quantify long-term variables such as aging of
materials and effects of environmental conditions. There
are several examples of applications of SHM within the
context of conservation of historical constructions such as
studies in churches [46], towers [7,8], buildings and
bridges [911]. In Latin America and, particularly in Peru,
there is a significant presence of historical earthen con-
structions [12], which evidence high vulnerability due to
issues in the material itself such as its low tensile strength
and brittle behavior [13,14]. These constructions require
special attention and investigation with modern tools which
are capable of overcoming local needs and on-site negative
circumstances (i.e., absence of electricity or internet con-
nection, unfavorable climatic conditions, limited techno-
logical resources, etc.).
Within the available monitoring tools, vibration-based
SHM is considered a suitable and efficient approach since
&Rafael Aguilar
raguilar@pucp.pe
1
Department of Engineering, Pontificia Universidad Cato
´lica
del Peru
´-PUCP, Av. Universitaria 1801, San Miguel,
Lima 32, Peru
2
Department of Civil Engineering, University of Chile, Av.
Blanco Encalada 2002, Santiago, Regio
´n Metropolitana,
Chile
3
Department of Civil Engineering, University of Minho,
ISISE, Campus de Azure
´m, 4800-058 Guimara
˜es, Portugal
123
Journal of Civil Structural Health Monitoring (2018) 8:791–808
https://doi.org/10.1007/s13349-018-0306-3(0123456789().,-volV)(0123456789().,-volV)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... A continuación, se realiza la descripción de las tres metodologías que se usaron para el proceso de detección de daño: 1) modelos predictivos Auto Regresivos de variable eXógena (ARX, por sus siglas en inglés), 2) modelos de Análisis de componentes principales (PCA, por sus siglas en inglés) y 3) modelos de redes neuronales convolucionales (CNN, por sus siglas en inglés). Los dos primeros métodos utilizan los datos procesados de las aceleraciones mediante una rutina de identificación modal automática basada en un enfoque de agrupación jerárquica (Zonno, Aguilar, Boroschek, et al., 2018). Estos se validan utilizando los datos del estudio de identificación de daño en el puente Z24 en Suiza, que fue instrumentado con acelerómetros y dañado progresivamente, para comparar los resultados obtenidos y comprobar la efectividad de los modelos desarrollados. ...
... Se empieza a partir la solución en tiempos discretos de un modelo determinístico-estocástico y de espacio estacionario. Esta ecuación es simplificada en el caso de la solución para un método de solo salida, como se muestra en el cuadro 2, considerando a la señal de entrada como ruido blanco Gaussiano (Zonno, Aguilar, Boroschek, et al., 2018). El objetivo principal del método es la identificación de las matrices A y C, que contienen información sobre las frecuencias, amortiguamientos y formas modales de la estructura analizada (Chácara, 2013). ...
... Este valor debe ser estimado en un rango determinado, mediante procesos iterativos que permitan establecer el valor óptimo, ya que la selección de un valor muy alto permite la obtención de un mayor número de modos, pero puede ocasionar la identificación de modos numéricos falsos (Aguilar, 2010). Para cada orden seleccionado, se construye la matriz de observabilidad extendida, como se muestra en el cuadro 7, permitiendo la estimación de las matrices A y C (Zonno, Aguilar, Boroschek, et al., 2018). Figura 2.7: Esquema del algoritmo del método SSI-Data (Adaptado de Luís F. Ramos et al., 2013; Los resultados del método SSI-data suelen presentarse en un diagrama de estabilización. ...
Thesis
Full-text available
Structural health monitoring (SHM) is becoming increasingly important in the field of structural engineering, since it allows a continuous assessment of the structural performance of a construction. This is possible through the identification of damage in real time when sensitive parameters, such as dynamic properties, are monitored, since they are intimately related to the physical properties of the structure. This knowledge allows for a faster and more effective decision making in terms of maintenance and intervention of existing buildings, helping to preserve them. In addition, it is vitally important in the case of the preservation of historical buildings as it is a non-destructive and non-invasive method that provides essential knowledge for their assessment. Since Peru has a large number of adobe buildings, which represent its cultural and historical heritage and are of great economic importance for the tourism they generate, they need modern and innovative techniques for their maintenance and preservation. The present investigation develops a set of methodologies capable of detecting and locating damage in earthen structures through the dynamic monitoring of environmental vibrations. This is done by instrumenting the constructions using high sensitivity accelerometers that allow to continuously extract the dynamic properties from vibrations without the need of controlled sources of excitation. First, the methodologies will be validated using the emblematic study case of the Z24 bridge, where results of the damage identification are available. Then, they will be applied in a simple structure consisting of an inverted steel pendulum, tested and progressively damaged to check their effectiveness and make the necessary adjustments. Next, an adobe wall will be tested in the same way, checking the applicability of the methodologies and the problems that arise when implemented in a traditional adobe structure. Finally, the churches of San Pedro Apóstol de Andahuaylillas and San Juan Bautista de Huaro, of great cultural importance for the country, will be studied. They have been instrumented with accelerometers and have a long-term monitoring system. The change of its dynamic properties and the occurrence of a seismic movement near the churches during the monitoring time will be studied. The conservation of adobe buildings currently presents a challenge for structural engineering due to the lack of building codes at the time they were built, the little knowledge of the construction processes, the high variability of their mechanical properties, and the effect of natural and environmental phenomena. It is also important to note that the environmental variations of temperature and humidity significantly affect the dynamic response in adobe structures, being an important problem the separation of variations caused by these and those caused by damage. The development of methodologies to overcome these problems will result in tools that contribute to the timely identification of damage in historic buildings, allowing early maintenance and helping to preserve them.
... The implemented monitoring systems are summarized in Fig. 2, and consist: (i) local acquisition and storage of the raw data (dynamic and environmental data), (ii) transmission of the raw data by a 4g data plan to the central monitoring station, (iii) reception and storage of data, (iv) processing of raw data, and (v) publishing the results in a web platform using a cloud engine. For the processing of the dynamic raw data (stage iv of the monitoring system), an automatic processing tool was developed and tested in [14]. In particular, the developed tool is able to identify automatically the frequencies, mode shapes and damping values of the structure through four main steps: (a) digital signal pre-processing of the dynamic data; (b) application of the SSI-Data method to obtain the stabilization diagram; (c) filtering of the stabilization diagram with the application of hard and soft validation criteria; (c) automatic detection of the modal parameters using hierarchical clustering approach and automatic thresholds; and (d) the Bell tower application of an adaptive modal tracking for a final cleaning of the dynamic results (see more details in [14]). ...
... For the processing of the dynamic raw data (stage iv of the monitoring system), an automatic processing tool was developed and tested in [14]. In particular, the developed tool is able to identify automatically the frequencies, mode shapes and damping values of the structure through four main steps: (a) digital signal pre-processing of the dynamic data; (b) application of the SSI-Data method to obtain the stabilization diagram; (c) filtering of the stabilization diagram with the application of hard and soft validation criteria; (c) automatic detection of the modal parameters using hierarchical clustering approach and automatic thresholds; and (d) the Bell tower application of an adaptive modal tracking for a final cleaning of the dynamic results (see more details in [14]). Within this context, the implemented dynamic monitoring system consists of a Kinemetrics Obsidian 8x [15], a data acquisition unit with a capacity of 8-channels and 24 bits of resolution ( Fig. 3f) and four uniaxial force balance accelerometers Episensor ES-U2 [16] with a bandwidth range from DC to 200 Hz, a dynamic range of 155 dB+, a sensitivity of 10 V/g, and an operating temperature range from −20 °C to 70 °C (Fig. 3c). ...
... Such action requires providing continuous or quasi-continuous (continuous for some time) measurements. It is useful here to utilise and integrate different surveying technologies, i.e., metrological or physical monitoring [14,16,20,28]. ...
... All inclinometers are subject to accuracy validation and calibration. Detailed procedures for such approaches are presented in ref. [3,17,28]. ...
Article
Full-text available
Safe exploitation of a building requires constant monitoring of both the object itself as well as its surrounding through the monitoring system. These tasks find particular applications when operating large construction projects, especially in urbanised areas. Besides the warning function and undertaking reactions, the monitoring system allows for recording changes in object geometries to assess their stability. To conduct monitoring, various sensors and instruments that work within the applied measuring systems can be used. As an example, one can mention precise inclinometers (‘electronic bubbles’) allowing for accurate determination of inclination angles. The paper discusses the precision and functional aspect of the original inclinometer developed and improved by the authors. The working principle of the device is based on optical fibres, light projection and its detection on a CCD camera objective. The presented issue is a low-cost solution offering high measurement accuracy, which may be used in structural monitoring of objects located in the impact zone of a deep excavation or other nearby ongoing investments.
... The reliability of automated OMA is dependent on how well the spurious poles are eliminated so that the stabilized poles are grouped into physical modes without user intervention. This study used a soft-validation procedure to secure stable poles with repeated modal identifications by increasing the model order (the eigenvalue number in the model) [41,42]. The spurious poles were eliminated by comparing the Euclidian distances of the same poles between the kth and (k + 1)th model orders: ...
Article
Full-text available
Accurate damping estimation is critical to the serviceability assessment of large and flexible civil infrastructure. However, the frequency of sensor faults found in the long-term monitored data of large-scale structures is a potential cause of errors in the damping estimates. A machine-learning-based fault-data management approach is proposed whereby erroneous data are identified and removed automatically. A support Vector Machine (SVM) is used to automatically detect and recover/isolate multiple types of sensor faults from measured accelerations. The labeled training samples are artificially augmented using digital simulation of a random process. An envelope function is introduced to reflect the time-varying trends of signals. A new feature, the Maximum Correlation Factor, is proposed to measure similarities between the simultaneously measured signals in order to classify faulty and normal data. The performance of the trained SVM classifier was validated via long-term data from the wireless sensor network of a cable-stayed bridge in South Korea. The modal damping ratios were then estimated from the faulty and recovered data. The improved performance of the damping estimation via spike removal and fault isolation was evaluated in terms of the correlation function and stabilization diagram in the output-only modal analysis. The recovered data provided a more robust and consistent damping estimate, and demonstrated the efficacy of the proposed fault-data management strategy that uses a new SVM feature.
... N4SID needs fewer parameters for tuning), the N4SID method is being considered for the SWS. Also, the use of Bayesian and clustering analysis techniques, described in Boroschek and Bilbao (2019) and Zonno et al. (2018), are also being explored for future implementation in the proposed SWS. ...
Article
Full-text available
The seismic response of an instrumented 22-story rehabilitated building is presented. The building analyzed is as part of a complex (called CCUT) with three low-rise structures and a common basement founded on soft soil that was built in 1964. Since it was under construction until date, the building tower has experienced differential settlements and tilting. To mitigate such problems, the building has been subjected to several rehabilitations over the years. During the 1985 and 2017 high-intensity earthquakes in Mexico City, the tower suffered some damage. The aim of this article is to discuss the structural health monitoring system implemented for the tower and to describe the structure’s performance since the last rehabilitation in 2009. A monitoring methodology designed and implemented as a structural warning system based on five structural health indicators, two on seismic severity and three on structural performance, to automatically process seismic records, is presented. The results of the seismic response of the CCUT tower between 2011 and 2018 indicate that the structure had suffered moderate damage. Analysis of data, corroborated by building inspection, confirmed that the structure exhibited good performance during the 19 September 2017 Puebla-Morelos earthquake. The importance of the information obtained from the structural warning system is highlighted as a promissory tool for establishing a robust decision framework for occupants’ safety.
... A new feature was proposed for this purpose. Then, automatic modal damping estimation was performed based on SSI-COV (Magalhaes et al. 2009;Reynders et al. 2012;Zonno et al. 2018). A more stable automated damping ratio estimation method is examined using the stabilization diagram and hierarchical clustering. ...
... Recently, a lot of research effort has been focused on extracting the modal responses via on-line modal analysis methods [6][7][8][9][10][11]. Commonly, to assist in identifying modes, it is possible to try and locate the peaks of a frequency response function. ...
Chapter
Historical structure is an integral component of the world's cultural identities. However, despite its cultural significance, it is the most prone type of building due to environmental factors such as aging of the materials, the effect of temperature, soil condition, and natural disasters such as earthquakes and typhoons. Therefore, the preservation of historical structure is one of the growing interests in recent years, and in monitoring the historical structure's state correctly, different methods and tools introduced. One of the methods in determining the health of the historical structure implemented a decade ago is Structural Health Monitoring (SHM). Generally, there are two types of SHM, long-term monitoring or Static SHM, which measures slow varying factors, and Dynamic SHM which determines the dynamic properties of the structure. However, with the continuous advancement of the SHM, the uncertainty and inaccuracy of the model and results are still the most significant gap in the application of SHM. This paper aims to review some of the applications of SHM in the preservation and monitoring of historical structure to provide knowledge about the topic and determine gaps and challenges based on the existing literature and studies.
Article
For existing structures, the development of seismic vulnerability studies requires the availability of information related to geometry, boundary conditions, material properties, and accumulated damage. In the case of historical constructions, modern conservation criteria recommend carrying out a comprehensive structural assessment that involves the use of concurrent experimental diagnosis complemented with numerical and analytical approaches for structural analysis. This paper presents a proposal for a comprehensive integration of these perspectives by the application of several tools for the seismic performance analysis of an iconic Andean historical adobe building: the 'San Pedro Apostol Church' located in Andahuaylillas, Southern Peru. In this church, several non-destructive techniques for geometrical and damage assessment were combined with structural exploration tools, nonlinear numerical modeling, and simplified analytical tools for performing predictive seismic analysis. The results indicate the feasibility of the integration of these techniques for studying existing earthen buildings and their capacity to properly predict observed damage in past earthquakes (i.e. failures of bell towers, façade walls, tympani, and triumphal arches). In particular, the analyses allowed the identification of high seismic vulnerability of the studied church in occasional earthquakes (earthquakes with a return period of 72 years) due to the activation of collapse mechanisms consisting of rocking of the façade walls and out-of-plane overturning of the lateral walls.
Article
The development of a fully automated system identifier without the need for human intervention, is a key step for real-time vibration-based Structural Health Monitoring (SHM). In this paper a novel approach based on the Dirichlet Process Gaussian Mixture Model (DP-GMM) is developed in order to analyze the stabilization diagram. The aim is to separate the true physical modes from the mathematically spurious modes in a fully automated manner, whilst eliminating the need for any manually specified parameters or thresholds. The parametric Covariance Driven Stochastic Subspace Identification (SSI-Cov) is adopted to estimate the modal parameters, and consequently establish the initial stabilization diagram. From there, the use of a two-stage algorithm involving a DP-GMM is proposed to non-parametrically perform an automated cleaning of the stabilization diagram. The contributions of the paper are five-fold: (1) A probabilistic approach based on a DP-GMM is proposed to analyze the stabilization diagram. To the best knowledge of the authors, this study presents one of the first attempts of DP-GMM for full automation of Operational Modal Analysis (OMA). The method is validated using the field test data from a large-scale operating cable-stayed bridge, which has two closely-spaced modes around 3Hz. Not only are these two complicated scenarios consistently identified, but the performance of the method with respect to the problem of missing modes is compared against a reference method based on the conventional multi-stage clustering technique used in OMA, wherein superior performance of the proposed method is demonstrated. (2) The method does not require specification of any threshold or parameter at any stage of the algorithm for cleaning the stabilization diagram, making the approach a potential for robust and fully automated modal identification. (3) Compared to many conventional multi-stage clustering techniques, the proposed approach is computationally efficient as intelligent updates are made to the model using multiple linear algebra properties. (4) New feature vectors are developed which are justified using a combination of mathematical rigor, visual understanding, and engineering intuition. (5) Due to the probabilistic nature of the method, the identification results are accompanied with uncertainty bounds. Several mathematical proofs are presented to explain the observed behavior of the uncertainty bounds.
Article
Full-text available
The paper presents structural health monitoring (SHM) activities performed on some representative cultural heritage (CH) buildings in the city of l’Aquila after the strong earthquake (Mw = 6.3) that struck the Abruzzo region (central Italy) on April 6, 2009. The severity and the extent of damages caused by the earthquake to historical buildings and monument were never reached before in the recent Italian earthquake history. Emergency activities started immediately after the earthquake to protect CH structures, including damage survey and design/implementation of temporary safety measures. Some historic buildings were soon equipped with monitoring systems in order to assess the level of damage and verify the effectiveness of the executed provisional interventions. The paper focuses in particular on two case studies, i.e. the Spanish Fortress and the Civic Tower. The results of preliminary investigations are reported, including damage survey and operational modal analysis for modal parameter identification using ambient vibration tests. 3-year static and dynamic monitoring features, automatically extracted from raw data acquired by continuous monitoring systems, were then processed using a data-driven approach based on regression analysis to filter out the environmental effects. Following this approach data are decomposed into their reversible and irreversible components, the latter being associated with active damaging processes and the residual structural performance of the two buildings assessed.
Article
Full-text available
Adobe constructions account for a significant portion of the built heritage, associated with early building techniques, material accessibility and low-cost. Nonetheless, adobe buildings, due to their low mechanical properties and overturning resistance, are subject to early structural damage, such as cracking, separation of structural elements and, possibly, collapse in areas of high seismic hazard. The lack of maintenance and absence of adequate retrofitting techniques usually intensifies the loss of historic fabric. The current paper, aims at the structural assessment and seismic safety, in current conditions, of the Church of Kuño Tambo, a religious adobe structure of the 17th century, in Cusco region, in Peru. The inspection and diagnosis involved sonic testing and damage mapping, while ambient vibration tests revealed the modal response of the structure. The assessment of seismic vulnerability, together with the necessity of retrofitting measures were verified through nonlinear static and pushover parametric analyses, complemented with a macro-block limit analysis and a performance based assessment, under local seismic criteria. A more realistic response from dynamically induced ground motions was performed, by a nonlinear time history analysis, according to the Eurocode 8 framework. Through an integrated approach, in situ inspection, testing, numerical and analytical modelling are associated under the scope of reproducing the existing structural damage, the sequence of inelastic behavior and verification of the necessity of retrofitting measures.
Article
Full-text available
A recent survey of the historic complex of “Santa Maria del Carrobiolo” in Monza (Italy) highlighted that two sides of the bell-tower are directly supported by the load-bearing walls of the apse and South aisle of the neighbouring church. After the discovery of the weak structural arrangement of the building, a network of 10 displacement transducers, integrated by five temperature sensors, was installed in the tower to check the opening variation of the main cracks. Subsequently, ambient vibration tests were performed and closely spaced modes with similar mode shapes were clearly identified: since the dynamic characteristics of the tower are quite different from those obtained in past experimental studies of similar structures and conceivably related to the construction sequence, a simple dynamic monitoring system was installed in the tower to complete the health monitoring aimed at the preservation of the historic structure. The paper—after a brief description of the tower and a summary of selected evidences provided by on-site survey, historic research and static monitoring—focuses on the dynamic characteristics identified in the preliminary ambient vibration tests and the main results of 1-year dynamic monitoring. In order to assess the effects of changing temperature on the natural frequencies of the investigated tower, especially in view of the removal of those effects needed for an effective performance assessment, simple correlation studies between modal frequencies and temperature are presented and discussed.
Article
Full-text available
Earth has been a traditional building material to construct structures in many different continents. In particular, adobe buildings are widely diffused in South America, and in Peru where form part of the cultural identity of the nation. Nowadays, the knowledge of existing adobe buildings is far from a complete understanding of the constructive system and a structural health monitoring (SHM) can quantify and reduce uncertainties regarding their structural performance without causing damage to the buildings. In this process, the implementation of automatic tools for feature extraction of modal parameters is desirable. In particular, the automation is important because, during a long-term monitoring, a huge amount of data is recorded and the direct check of the data of the user is not possible. The present work is focused on the development of an automated procedure for managing the results obtained from the parametric identification method, in particular from the Data-Driven Stochastic Subspace Identification method, which requires an automatic interpretation of stabilization diagrams. The work presents a fully automated modal identification methodology based on the following steps: (i) digital signal pre-processing of the recorded data; (ii) modal parameter identification using models with varying dimensions; (iii) automatic analysis of the stabilization diagram with the application of soft and hard validation criteria and the use of hierarchical clustering approach to eliminate the spurious modes; and (iv) automatic choice of the most representative values of the estimated parameters of each clustered mode: natural frequency, damping and mode shape. The developed algorithm was firstly tested with an inverted steel pendulum to check the accuracy and sensitivity, and subsequently, an earthen wall built in PUCP Structure Laboratory was analysed to determine its dynamic behaviour. The developed algorithm shows high percentages of detected frequencies and high sensitivity to the environmental and structural changes.
Article
Full-text available
The response of the San Pietro monumental bell-tower located in Perugia, Italy, to the 2016 Central Italy seismic sequence is investigated, taking advantage of the availability of field data recorded by a vibration-based SHM system installed in December 2014 to detect earthquake-induced damages. The tower is located about 85 km in the NW direction from the epicenter of the first major shock of the sequence, the Accumoli Mw6.0 earthquake of August 24th, resulting in a small local PGA of about 30 cm/s², whereby near-field PGA was measured as 915.97 cm/s² (E–W component) and 445.59 cm/s² (N–S component). Similar PGA values also characterized the two other major shocks of the sequence (Ussita Mw5.9 and Norcia Mw6.5 earthquakes of October 26th and 30th, respectively). Despite the relatively low intensity of such earthquakes in Perugia, the analysis of long-term monitoring data clearly highlights that small permanent changes in the structural behavior of the bell-tower have occurred after the earthquakes, with decreases in all identified natural frequencies. Such natural frequency decays are fully consistent with what predicted by non-linear finite element simulations and, in particular, with the development of microcracks at the base of the columns of the belfry. Microcracks in these regions, and in the rest of tower, are however hardly distinguishable from pre-existing ones and from the physiological cracking of a masonry structure, what validates the effectiveness of the SHM system in detecting earthquake-induced damage at a stage where this is not yet detectable by visual inspections.
Article
Full-text available
The Cathedral of Ica, Peru, is one of the four prototype buildings involved in the ongoing Seismic Retrofitting Project, initiative of the Getty Conservation Institute. The complex historical building, which was heavily damaged by earthquakes in 2007 and 2009, can be divided into two substructures: an external masonry envelope and an internal timber frame built by a construction method known as quincha technique. This study makes use of the information available in literature and the results obtained from experimental campaigns performed by Pontificia Universidad Católica del Perú and University of Minho. Nonlinear behaviour of masonry is simulated in the numerical models by considering specified compressive and tensile softening behaviour, while isotropic homogeneous and linear behaviour is adopted for modelling timber with appropriate assumptions on the connections. A single representative bay was initially studied by performing linear elastic analysis and verifying the compliance with the various criteria specified by the applicable normative to discuss the actual failure of Ica Cathedral. Afterwards, the structural behaviour of the two substructures composing the Cathedral is evaluated independently. Finally, the interaction of these two substructures is investigated by performing structural analysis on the entire structure of Ica Cathedral. Several structural analysis techniques, including eigenvalue, nonlinear static and dynamic analyses, are performed in order to: (1) evaluate the dominant mode shapes of the structure; (2) validate the numerical models by reproducing the structural damage observed in situ; (3) estimate the structural performance; and (4) identify the main failure mechanisms.
Conference Paper
Full-text available
A new method is described for assessing the consistency of structural modal parameters identified with the Eigensystem Realization Algorithm. Identification results show varying consistency in practice due to many sources including high modal density, nonlinearity, and inadequate excitation. Consistency is considered to be a reliable indicator of accuracy. The new method is the culmination of many years of experience in developing a practical implementation of the Eigensystem Realization Algorithm. The effectiveness of the method is illustrated using data from NASA Langley's Controls-Structures-Interaction Evolutionary Model.
Article
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.
Article
The paper presents a damage assessment strategy suitable to historic masonry towers. The methodology is exemplified using the data collected in the continuous dynamic monitoring of the San Vittore bell-tower (Arcisate, Northern Italy). The proposed damage assessment procedure aims not only at detecting the occurrence of structural anomalies, but also at localising the damage in the investigated structure. After a brief description of the tower and past diagnostic survey (including ambient vibration tests and Finite Element modelling), the results of the continuous dynamic monitoring are highlighted and the effect of temperature on automatically identified resonant frequencies is discussed. Subsequently, regression models based on Principal Component Analysis are applied in order to filter out the fluctuations caused by the environmental effects on the identified resonant frequencies. The damage detection and damage localisation issues are then addressed by using novelty analysis tools. The effectiveness of the proposed strategy is demonstrated through the detection and localisation of realistic damage scenarios simulated with the baseline Finite Element model. Specifically, the damage localisation has been tackled by using the “cleaned” modal properties within a continuous Finite Element model updating scheme.
Article
The interest for robust automatic modal parameter extraction techniques has increased significantly over the last years, together with the rising demand for continuous health monitoring of critical infrastructure like bridges, buildings and wind turbine blades. In this study a novel, multi-stage clustering approach for Automated Operational Modal Analysis (AOMA) is introduced. In contrast to existing approaches, the procedure works without any user-provided thresholds, is applicable within large system order ranges, can be used with very small sensor numbers and does not place any limitations on the damping ratio or the complexity of the system under investigation. The approach works with any parametric system identification algorithm that uses the system order n as sole parameter. Here a data-driven Stochastic Subspace Identification (SSI) method is used. Measurements from a wind tunnel investigation with a composite cantilever equipped with Fiber Bragg Grating Sensors (FBGSs) and piezoelectric sensors are used to assess the performance of the algorithm with a highly damped structure and low signal to noise ratio conditions. The proposed method was able to identify all physical system modes in the investigated frequency range from over 1000 individual datasets using FBGSs under challenging signal to noise ratio conditions and under better signal conditions but from only two sensors.