Experimental Vibration Analysis for Civil Engineering Structures

When approaching the evaluation of an existing structure, the proper definition of its numerical model can be a difficult task. When designing new structures geometry, restrain conditions and all specific details are chosen by the designer, while in the assessment of an existing structure all these parameters are characterized by uncertainties. Therefore, visual inspections, on-site tests, and geometric surveys are of primary importance for the characterization of the actual structural behaviour and to reduce uncertainties to obtain reliable structural models. In this regard, a technique to assess the representativity of the numerical model is the Operational Modal Analysis (OMA). This technique was applied to characterize the dynamic behaviour and obtain a representative model of a bridge subjected to progressive damage due to external sources that have altered the constraint conditions, so its structural response to external actions. The area where the bridge is located is subjected to the landslide of a mountainside which causes differential movements in the foundations. Ambient vibration tests were performed to characterize the dynamic response of the structure in operational conditions and carry out OMA analysis through up-to-date methods, such as SSI covariance. The results from surveys and OMA highlighted modifications in the supports of the bridge with respect to the initial design. These outcomes were implemented into the numerical model of the bridge to closely match the experimentally obtained modal properties, therefore achieving an updated model which is suited to properly replicate the actual structural performance of the bridge.

The dynamic characteristics of a structure reflect its global structural behaviour. It is common practice to perform structural damage detection based on changes in the modal parameters between a reference state and the current (possibly damaged) state, using ambient vibration tests. However, the environmental and operational conditions also affect the structural dynamic characteristics, therefore the exclusion of these effects is necessary in order to correctly identify the damage.This paper presents a case study of a 40-years-old bridge located on the reservoir of Aguieira Dam. This bridge was severe damaged due to internal swelling reactions in concrete which affected particularly the piers and foundations and was disabled in 2015.Between 2011 and 2021, eight ambient vibration tests and 20 geodetic survey campaigns were carried out. A statistical analysis procedure was used to remove environmental and operational effects on the identified structural dynamic characteristics to assess the progression of the bridge damage. Finally, a joint analysis of the results obtained by both methods is established.The study demonstrates that, using statistical analysis tools, it is possible to detect the changes in the dynamic characteristics, caused by the structural damage. The results obtained from the ambient vibration tests were also confirmed by geodetic survey.

The continuous application of Operational Modal Analysis (OMA) to time-series recorded on civil engineering structures, and the subsequent tracking of modal properties, allow the characterization of the evolution of their dynamic behaviour, which is particularly important on wind turbines, since their structural performance is highly dependent on it.However, it is impractical to manually analyse long periods of data, being essential to automatize OMA and to link results obtained in different datasets, which can be achieved through the comparison between a reliable set of references and the estimated modal properties. Nevertheless, the establishment of such a set of references is usually accomplished through a manual analysis, which is time-consuming and may produce a biased result. Furthermore, due to the impact of the operating conditions on the modal properties, several sets of references should be defined, making this process even more longstanding and prone to subjectivity.Therefore, the present work validates a clustering-based approach to automatically obtain a group of reference properties to be used in the tracking of the modal properties of an onshore wind turbine, resorting to data from a continuous monitoring program in Portugal.

The advent of IoT will create a digital twin of real infrastructure on Cyber Physics System. However, installing and controlling a large number of sensors is a cost-labor. Against, there is a method of estimating bridge vibration by installing sensors on vehicle instead of installing sensors on the bridge. This method has highly mobility and agility, and it can collect big data before perfect installation of sensors on bridges. However, the accuracy of the obtained bridge features decreases, it should be analyze by data driven method with big data. While Deep Neural Network is a great solution for big data analysis, it has poor explainability. This study focuses on screening techniques by signal processing. SSMA (Spatial Singular Mode Angle), which is one of the bridge screening indexes based on mechanics, was calculated from the data of repeatedly traveling over more than 100 various bridges. The scatter plot of bridge length and SSMA has a large tendency as shown in previous studies. This trend can be used for detection of outlier which may equal change of bridge length, and this detection method can be improved by variance suppression filter in previous study or may provide the explainability based on mechanics for the result of deep learning method.

Modal parameters are key factors in vibrational serviceability assessments of long-span cable-supported bridges. The recent development of automated operational modal analysis (OMA) has enabled modal tracking according to environmental and operational conditions (EOCs). However, in contrast to the successful implementations for natural frequencies, there are still challenges in the investigation of damping ratio due to (1) inherent errors in damping estimates and (2) epistemic uncertainties on the effects of EOCs. In this regard, this study proposes the framework to establish a reliable probabilistic regression model for the damping ratio of an actual cable-stayed bridge by incorporating various machine learning (ML) algorithms. First, a conventional automated OMA algorithm is improved by employing a displacement reconstruction algorithm and the optimized unsupervised clustering method. These approaches can reduce the model-order dependencies in OMA-based damping estimates with minimum user intervention. The proposed framework is then employed to estimate the long-term damping ratio from 2.5 years of structural health monitoring data. The monthly fluctuation and amplitude dependency of long-term damping characteristics are discussed. Subsequently, the deep Gaussian Process (DGP) model is applied to damping estimates for developing a probabilistic regression model. A statistic-based and knowledge-based data cleansing strategies are proposed to enhance the model’s regression performance. A comparative study with different regression models validates the robustness of DGPs. Finally, the predictability of the trained model is validated using the actual monitoring datasets.

In the attempt to move towards time-efficient and cost-effective condition-based monitoring of transport infrastructures, Structural Health Monitoring (SHM) has gained a key role, and driven researchers and infrastructure managers attention. SHM consists of the extraction of quantitative information regarding bridge health status, from the measurement of its response. Since able to reflect changes of the mechanical properties of the structure under analysis, modal parameters are commonly used to track the evolution of its condition. Operational Modal Analysis (OMA) represents a well-established procedure through which it is possible to monitor the evolution of bridge modal properties. This paper focuses on the application of an automated algorithm for experimental OMA exploiting data collected from a permanent monitoring system mounted on a Warren truss railway bridge. This kind of structure became extremely popular after World War II. The bridge under analysis was recently instrumented with a set of different sensing devices, including thermistors and velocimeters, with the final aim of continuously monitoring its condition. In particular, the results in terms of modal parameters identification are presented in this work: the focus is put on natural frequencies and associated mode shapes extraction, analysing then their trends during the first months of acquisition.

Automated operational modal analysis of civil engineering structures and suspension bridges based on vibrational monitoring data can be performed at a reliable enough level to consider its outputs as correct interpretations of the modal dynamics in the measurement data. This work proposes a new robust and automatic algorithm for tracking the evolution of these detected modal properties over time. The algorithm requires only a few inputs that are easy to define and does not require prior knowledge of the target bridge. It can deal with imperfect modal detection data and distinguish between closely spaced modes. The algorithms functionality is illustrated using two numerical examples and one experimental example from the Hardanger Bridge monitoring project.

Transmissibility-based operational modal analysis (TOMA) can be used to determine the modal parameters under different excitations, where no assumptions about the nature of the excitations are required. Classical OMA methods are based on the assumption that the excitation is white noise. However, this cannot always be satisfied. Ground vibrations caused by rail, road traffic or construction site operations represent various excitations for the building. These excitations can also contain harmonic components. By using TOMA, the restriction to white noise can be abandoned. Furthermore, the application of TOMA from ground excitation has not been properly addressed yet.This study is performed using experimental data from a 2-story timber structure resting on a concrete slab under laboratory conditions. Ground excitation is applied using a vibration test system on the slab. The identification focuses on the first floor, where frequency, damping, and mode shapes are identified. Several aspects are examined, such as the influence of the number of sensors as well as the level and type of excitation. Moreover, TOMA is compared to the poly-reference least squares frequency domain estimator (p-LSCF) method. The results show the potential of TOMA for the monitoring of buildings even when only subjected to small ground excitation or with few numbers of sensors.

Bayesian structural model is expected to be of great use in structural health monitoring updating because it can account for the uncertainty in measurement data. However, when considering correlations between model parameters, which are generally ignored, the joint posterior probability density function (PDF) takes a complex form and cannot be expressed as a simple function. In this case, it is necessary to include many samples in the tail space of the PDF to estimate the lower confidence bound. The Markov chain Monte Carlo (MCMC) method, which is often used in Bayesian structural model updating, generates samples near the expected value, making it difficult to estimate the tail space. To address this issue, the present study applied the Replica Exchange Monte Carlo method, which complements the samples in the tail space of the joint posterior PDF. The proposed method was applied to the maximum acceleration data of a high-speed railway bridge in Japan, and the characteristics of the tail samples in the parameter space were analyzed. In addition, a train speed-maximum acceleration relationship was calculated, and the dynamic behavior of the structural model with the complemented tail sample was compared with that of the conventional MCMC samples.

There exists several methods to indirectly estimate prestressing forces in post-tensioning external tendons based on monitoring another relevant parameter. In this study, non-destructive vibration-based monitoring is employed to estimate their effective tension forces. A continuous monitoring of the tensioning process of a tendon installations on a 12-span concrete bridge for a high-speed railway is carried out using high sensitivity accelerometers distributed along the tendon. An operational modal analysis is then conducted for the signals at each stage of the tensioning process and the modal properties are extracted. Then, the effective tension force is estimated through a model updating of an analytical model of the tendon for each stage. The taut string model including bending effects is considered together with several boundary conditions: simply supported at both ends, clamped-simply supported and semi-rigid supports by including rotational stiffness of the connections. Thus, the tension force is estimated by minimizing a cost function defined in terms of the experimental and theoretical modal properties in terms of the natural frequencies and mode shapes. Finally, the estimated tension forces using different boundary conditions are compared with the measured ones given by the hydraulic unit during the tensioning process. A comparison between estimated and measured tendon forces including instantaneous losses along the tendon is carried out. That is, a discussion on friction losses (curvature friction and wobble coefficients) and the effect of the anchor set for the installed unbounded tendons is performed.

The structural health assessment of buildings during their life is a very actual and important topic to monitor effects of ageing and, more importantly, to exclude risks for users after exceptional events. This evaluation, periodically carried out, provides important information about the structural health condition and may be crucial to evaluate the need of interventions after exceptional events, or simply to schedule the building maintenance. In this framework, a monitoring system should be installed not only on strategic constructions and infrastructures, but also on residential buildings.The paper discusses about the dynamic structural health monitoring of a considerably number of residential buildings located in Central Italy (Marche Region).The framework adopted to design the structural health monitoring systems and to post-process the acquired data, as well as the adopted instruments, are described, starting from the preliminary dynamic identification of the building to the monitoring system design and installation. The architecture for data acquisition, transfer and storage are also discussed. Moreover, some results of the monitoring are presented, and their relevance in the context of structural assessment after exceptional events (e.g., earthquakes) is addressed.

The exploration of the wind energy available offshore is of vital importance to overcome the energy dependence on fossil fuels and, depending on the deepness of different locations, this task may only be feasible if based on floating solutions. Although the application of Operational Modal Analysis (OMA) techniques to time-series obtained from onshore wind turbines faces a significant number of difficulties, as many of its assumptions are more severely violated than in conventional civil engineering structures, it has already been shown that these can still provide an efficient and reliable way to characterise and track the dynamic properties of these structures. Floating offshore wind turbines (FOWT) face not only the same challenges related to the dynamic wind loading as the onshore cases, but also the effects of the induced platform motions from both this action and wave loading. Although OMA applications for FOWT are yet to be properly developed and tested, some numerical preliminary tests, mostly focused on the platform motions, have indicated that they may still be used to extract and characterise the complex dynamics of these structures. In this work, we apply the conventional Covariance driven Stochastic subspace identifications (SSI-COV) algorithm to the experimental data obtained from a fully operational FOWT and show that it can still be used for these structures. We also present different methodologies and modifications to the conventional data pre-processement and study their impact on the results.

A rapid and economical vibration-based non-destructive testing equipment has been developed to detect anomalies in external post-tensioning tendons used in post-tensioned bridges. This method provides a complementary non-destructive testing (NDT) technique to traditional inspection methods and other NDT techniques such as ultrasonic wave-based testing. The non-destructive tendon tester (NDTT) has been developed for testing the external tendons of a 12-span railway continuous concrete bridge. Thus, the NDTT has been designed, developed and applied to 25 tendons with a total of 216 tendon segments. The experimental tests for each tendon segment are carried out employing the operational modal analysis technique using several vertical and lateral accelerometers. From these, several structural performance indicators (PIs) based on the modal properties are extracted: fundamental frequency, the ratios between higher frequencies and the fundamental one, the symmetry/antisymmetry of mode shapes through the Modal Assurance Criterion between symmetric test point measurements, damping of the fundamental mode and an estimation of the tension force. The latter is estimated through an in-line updating process of an analytical model (taut-string theory including bending stiffness) of the tendon segment. Once segment PIs are derived, the NDTT system analyses all the segment results of each tendon (9, 6 or 3 segments, depending on the tendon location), and an anomaly detection procedure searches for unexpected values based on significant deviation on the expected values depending on the segment location in the tendon.

Selected results collected in the continuous dynamic monitoring of a 3-span overpass using MEMS accelerometers are reported in the paper. The investigated structure is a steel-concrete composite bridge characterized by a rather complex geometry. The overpass has a total length of 108 m and spans of 30 m + 48 m + 30 m.Several bending and torsion modes are identified during the continuous monitoring, with the temperature significantly affecting all natural frequencies. Moreover, a clear effect of changing environment is detected for torsion modes as well, whereas no remarkable changes of bending mode shapes are detected.

The contribution is devoted to a prestressed concrete road bridge structure in Pforzheim, Germany, which has been in operation since 1953. A key feature of this frame bridge is the design of the side spans consisting of frame legs constructed as seperated tension and compression members. The bridge deck has been retrofitted by the means of an additional layer of reinforced concrete in 2006. Due to the limited accessibility of certain prestressed concrete members, a reliable assessment based on periodic visual inspections is not ensured. Therefore, periodic in-depth full scale vibrational analyses were performed according to DIN 1076 (1999) which is the mandatory code for periodic bridge inspections in Germany. A follow-up assessment in 2020 is compared with a baseline investigation from 2003, having been conducted by the same organisations in a similar manner.

Since mid-2022, a consortium of 3 partners, SISGEO, LEMTA and SNCF Réseau, is carrying out the AUDACE project, as part of the “Smart Bridges” project in France. Our objective is to provide bridge managers with real-time information regarding the occurrence of a collision of a railway bridge deck. This type of incident, likely to cause damages that can impact the stability of the structure, represents more than 50% of incidents recorded on the SNCF Réseau (SNCFR) bridges. SNCFR selected several bridges regularly experiencing this type of incident for SISGEO to install a set of relevant sensors. Among them, the AD-SIGNUM solution provides a continuous and global SHM of the bridge. AD-SIGNUM is based on several key technologies. First, geophones are used to measure vibrations of structures giving access to low amplitude signals in either quiet or noisy environment. Then, a particular effort is paid on the processing of asynchronous signals in order to make deployment and maintenance of autonomous sensors easy, flexible, and efficient. Finally, rather than gathering an endless amount of data, we focus on a qualitative perspective. This in-depth approach aims to measure the own vibration of the structure, and its evolution over time, apart from punctual non-typical disruptions. The LEMTA will compare different “Machine Learning” algorithms with supervised, unsupervised and reinforcement learning approaches to select the best performing approach to identify the critical parameters to detect anomalies and signs of impact damage to finally draw conclusions for the bridges manager to take the right decisions.

This paper describes a monitoring/inspection technique for the estimation of longitudinal stress in continuous welded rails (CWR) to infer the rail neutral temperature (RNT), i.e. the temperature at which the net longitudinal force in the rail is zero. The technique is based on the use of vibration measurements and machine learning (ML). A finite element analysis is conducted to model the relationship between the boundary conditions and the longitudinal stress of any given CWR to the vibration characteristics of the rail. The results of the numerical analysis are used to train a ML algorithm that is then tested using field data obtained by an array of accelerometers polled on the track of interest. In the study presented in this article, the proposed technique was tested in the field. A commercial FEM software was used to model the rail track as a short rail segment repeated indefinitely and under varying boundary conditions and stress. Three ML models were developed using hyperparameter search optimization techniques and k-fold cross validation to infer the stress or the RNT the frequencies of vibration extracted from the time waveforms obtained from two accelerometers temporarily attached to the rail. The results of the experiments demonstrated that the success of the technique is dependent on the accuracy of the model and the ability to properly label the modes of the detected frequencies. The ML was also able to learn from the experimental data only and successfully predicted the neutral temperature of the tested rail section.

The rupture of the contact wire (CW) of a railway overhead contact line (OCL or catenary) of a high-speed line is expected to be a rare event, however, its occurrence can have catastrophic consequences due to the failure of the pantograph against the catenary, possibly enlarging the extension of the damage portion on the catenary. The prevention of such events through proper catenary monitoring is gaining high interest, with several proposal of direct catenary monitoring of the catenary. The purpose of this work is to find the signature of variables measurable at the end of an OCL section, so that it is possible to reveal the presence of a failure in the contact wire, and to stop the traffic before a train runs under the broken catenary. The paper investigates, by means of numerical simulation, the dynamical behavior of the catenary, when a failure in the contact wire of the OCL occurs. The dynamical response of the OCL is simulated through nonlinear dynamical analysis, to define existing pattern of the variables that can be measured at line’s extremities, where the tensioning devices of the conductors are located. Several scenarios of failure locations are investigated, so that the measured force signature, to get a more general view of the pattern of the alert signals to be recognized.

Due to train load and aging, the dynamic properties of railway tracks degrade over time and deviate over space, which should be monitored to facilitate track maintenance decisions. A train-borne laser Doppler vibrometer (LDV) can directly measure track vibrations in response to the moving train load, which can be potentially applied to large-scale rail infrastructure monitoring. This paper characterizes track structures as a distributed system by estimating transfer functions between the wheel-rail force and the response of each sleeper measured by a train-borne LDV. A challenge with this technique is that a train-borne LDV measures only a fragment of the response for each sleeper while the train load is moving. To investigate the feasibility of this technique and the influence of key factors, we perform numerical simulations using a vehicle-track model and analyze the estimation performance through comparison with simulated impact hammer tests. We find that the transfer function estimated under a moving excitation is close to but noisier than that estimated under an impact load. Partial measurement affects the estimation performance significantly, and a wider sleeper provides a better estimate and a higher frequency resolution. Train speed is a crucial factor for a train-borne LDV system. As the vehicle speed increases, the estimation performance gets better at high frequencies but worse at low frequencies.

The monitoring of the railway infrastructure is nowadays of the utmost importance to guarantee the reliability of this kind of transportation and the safety of people involved. To this end, diagnostic trains are regularly employed to perform monitoring activities. However, while along high-speed railway lines their runs are usually scheduled once every two/four weeks, the diagnostic runs are much less frequent along main lines. Therefore, techniques able to detect anomalies on the line through measurements taken on-board in-service vehicles have been proposed in recent years. In this work, a wireless system developed to simultaneously monitor the vehicle dynamics and identify possible issues on specific track sections is presented. The detection of track defects is made possible by analysing acceleration RMS computed in specific frequency bands, considering several travels along the same track section recorded during a long-term experimental campaign. The proposed method would allow carrying out continuous monitoring campaigns, providing freight wagon with a cheap and easy to install measuring setup. In the end, the designed system could support the maintenance strategy along conventional lines, where the runs of the diagnostic vehicles are scheduled at long time periods one apart the other.

The increase of rail traffic in the last decades requires a continuous improvement of railway lines monitoring techniques, to provide higher levels of infrastructure safety and to properly manage effective maintenance plans. In this respect, the possibility to rely on in-service vehicles equipped with a simpler set of sensors (e.g., accelerometers) could increase data availability and support the maintenance strategy, that normally relies on special purpose diagnostic trains to periodically inspect the railway line. In this paper, data coming from vertical accelerometers installed on bogies of a commercial vehicle have been considered to monitor the track longitudinal level, that is the most important track geometry parameter that drives maintenance operations along high-speed lines. The proposed strategy relies on a multiple linear regression model that allows estimating the track longitudinal level, considering as input different predictors computed from the available acceleration data. The adoption of the pre-built regression model and the vehicle dynamic data allows to estimate the track geometry parameter along different sections of the line. These results can represent a useful tool to develop a methodology for track condition-based maintenance based on acceleration data from commercial vehicles.

The construction of buildings with cross-laminated timber (CLT) panels has grown steadily in recent years, mainly because of the environmental advantages of wood over other building materials. However, there are still doubts about the dynamic behavior of CLT buildings in countries with high seismicity and how their dynamic properties vary with temperature and relative humidity changes. The present work shows the modal properties’ monitoring of a 5-story CLT building prototype. The prototype building is located in Chile and has dimensions of 4.04 m, 6.44 m, and 14.5 m for width, length, and height, respectively. The CLT panels are made of radiata pine wood, and the joints between panels were executed with self-drilling screws and metal hardware (hold-down and angle-bracket). The CLT building was instrumented with ten uniaxial accelerometers (model PCB393B12) distributed on different floors and directions to measure the lateral dynamic response to environmental vibrations. The five main frequencies, damping ratios, and modal shapes were estimated through the operational modal analysis methods EFDD and SSI. Preliminary results suggest that, on average, the lateral and torsional frequencies measured in the CLT building were between 3.13 Hz and 13.88 Hz. These experimental results will allow a process of calibration and updating of finite element models of this type of buildings for their subsequent incorporation into Chilean structural design regulations.

Natural frequencies are the most widely used modal characteristics in vibration-based monitoring. However, they can be highly influenced by temperature and this influence can completely mask the effect of damage. Displacement mode shapes are less sensitive to temperature, but obtaining them in a dense grid, a requirement for damage localization, is cumbersome due to the large number of sensors needed. Strain mode shapes on the other hand can be nearly insensitive to temperature, while obtaining them in a dense grid is possible when fiber-Bragg gratings (FBG) are used. This work presents an overview of the continuous modal strain-based monitoring of three steel railway bridges of different structural typologies. All bridges were instrumented with FBGs and their strain mode shapes were automatically obtained on an hourly basis from ambient and operational dynamic strains. The influence of temperature on the strain mode shapes is investigated and their low sensitivity to temperature is confirmed for all bridges. The damage detection and localization capabilities of the strain mode shapes are also demonstrated numerically and experimentally.

Offshore wind turbines supported by monopiles have demonstrated their suitability to meet sustainable energy goals. However, there remains uncertainty about how long these foundations can stay operating within serviceable deflection limits after many years at sea. In particular, storm events can impose extremely large moments about the mudline due to intense wind and wave load profiles, having irreversible effects on the soil and shifting the system’s natural frequencies. During these large oscillations, soil nonlinearity causes energy dissipation due to material damping, which must be accounted for to design against resonance. In this paper, a dynamic Winkler-type model captures nonlinear soil-structure interaction by reappropriating monotonic soil reaction curves using Masing’s rules to form discretised hysteretic stress paths. Under simple sinusoidal loading, the model displays super-harmonics in the frequency spectrum that could lead to resonance. The analysis suggests that the super-harmonic frequencies are functions of the excitation frequency for simplified loading conditions, and could be used to estimate more complex hysteretic soil-structure behaviour with structural health monitoring techniques.

This paper presents the results of a large scale laboratory test that employed two Rayleigh-based distributed fiber optic sensing technologies to monitor dynamic strain profiles in a wind turbine that was subjected to dynamic strains representative of a typical offshore wind turbine environment. The two technologies used were Optical Frequency Domain Reflectometry (OFDR) and Phase-based Time Domain Reflectometry ( $$\varPhi $$ Φ -OTDR). $$\varPhi $$ Φ -OTDR technology is used in Distributed Acoustic Sensing (DAS), and can capture measurements over large distances (several kilometers). Representative dynamic strain profiles were determined prior to testing using a prototype floating offshore wind turbine simulated in the computational software, OpenFAST. Fiber optic cables were installed onto a wind turbine tower in different orientations to capture global tower deformations and local dynamic strain at the tower’s connections. First, a quasi-static bend test was conducted to calibrate the sensing techniques. Second, the wind turbine tower was mounted on the 6-DOF shake table at the Pacific Earthquake Engineering Research (PEER) Center and was subjected to multidirectional (translational and rotational) shaking to induce dynamic strain profiles similar to offshore conditions. Different configurations of loose bolts at the turbine flange connections were also tested to evaluate the proposed sensing approach. The results show good agreement between $$\varPhi $$ Φ -OTDR and OFDR measurements and show that the technologies captured both local and global structural phenomena; the effect of loose bolts on strain response was readily identified. In addition, numerous lessons on effective installation techniques were identified and summarized. $$\varPhi $$ Φ -OTDR’s ability to accurately capture dynamic strain over large distances makes it a promising candidate for structural health monitoring of large civil systems, though mitigating vibration noise is essential to measure small strains accurately.

A one-year seismological campaign took place in the site of the Saint-Guérin dam in 2015, and continuous vibration data of the dam under ambient noises were registered by 3 sensors installed on the dam crest. This contribution analyzes the ambient vibration data during 3 days with the dam’s reservoir at its maximum level, aiming to show two benefits of collecting such data for arch dams: (1) estimation of modal frequencies and (2) calibration of a numerical model. First, spectral analyses are performed on the vibration data by using the Enhanced Frequency Domain Decomposition method, leading to 10 natural frequencies of the dam obtained within a range of [0, 11] Hz. Particularly, two vibration scenarios of the dam with different spectral contents are identified, and they are found to be related with the opening of the intake gate of the dam. The importance of collecting and analyzing ambient vibration data under different external excitations (if applicable) is thus highlighted, as it can avoid missing some modes of interest. Secondly, a 3D numerical model of the dam is created with a compressible reservoir modelled by fluid elements. By simply tunning the model’s stiffness parameters, a reasonable predictive model is obtained given that it is able to accurately provide the dam’s frequencies up to the 10th mode. This model then provides a good representation of the dam under normal reservoir level and can be used for further safety evaluation of the dam.

A dam-foundation seismic interaction model, to be used in the frame of the FEM (Finite Element Method) codes for the study of dam-foundation-reservoir systems, was recently implemented and tested by RSE (a company with the mission of performing research into the field of electrical energy, with special focus on national strategic projects). The model was developed to overcome the main deficiencies (above all the excessive conservativeness of the results) of traditional and simplified methods. The model can ideally reproduce the same behaviour of the actual semi-unbounded foundation, representing the seismic wave propagation in a computation domain delimited by artificial boundaries. The model is adopted, in comparison with the traditional massless approach, to simulate the seismic response of Monticello Dam subjected to a low intensity earthquake occurred in 2015 not far from the dam site. The case study of Monticello Dam (Napa County, California, USA) allows to compare the simulated behaviour of the dam with the seismic records, available both at the foundation and at the dam crest. The results of the study enable to assess the reliability of the seismic wave propagation model for its use in real cases and to highlight the advantages of using the model as an alternative to traditional analysis approaches.

The 170 m-high Cahora Bassa dam, in operation since 1974, Mozambique, is one of the most important dams in Africa. Aiming to control its dynamic behavior over time, the dam was instrumented with a continuous vibrations monitoring system in 2010, consisting of force-balance accelerometers and data acquisition units, and of customized software for data management and analysis. This paper is dedicated to the experience acquired over the past 12 years for the case of Cahora Bassa dam, with emphasis on the instrumentation challenges faced on site and the adopted solutions, as well as on the developed software. The latest results on the dynamic behavior monitoring of the dam are presented, namely (a) the analysis of the evolution of the natural frequencies over time and of the corresponding mode shapes, and (b) a study on the measured seismic response. The comparison is made with numerical results, obtained using a calibrated finite element model of the Cahora Bassa dam-reservoir-foundation system.

This paper focuses on vibration-based analysis for model calibration and structural condition assessment of large concrete dams. The case study is the 170 m-high Cahora Bassa arch dam, Mozambique. In operation for almost 50 years, the dam presents deterioration signs due to concrete swelling, and in 2010 it was instrumented with a continuous dynamic monitoring system. In this work, the vibrations measured under ambient/operational conditions for more than a decade are analyzed in order to estimate the modal parameters of the dam, which are then used to calibrate and validate a new finite element model of the Cahora Bassa dam-reservoir-foundation system. After that, finite element analyses are performed to simulate the dynamic behavior of the dam for future years, considering a scenario of progressive damage due to concrete swelling. The presented results show that the dynamic performance of Cahora Bassa dam in normal operating conditions is not being affected by the existing concrete swelling phenomenon, and that vibration-based analysis can provide valuable data for detecting structural changes in concrete dams due to progressive deterioration.

Cabril dam is a 132 m-high double curvature arch dam in Portugal. In operation for almost 70 years, the dam presents some signs of deterioration, including horizontal cracks along the upper part of the structure, which occurred during the first filling of the reservoir, and concrete swelling caused by alkali-aggregate reactions, detected in the 1980s. The dam was instrumented with a pioneering continuous vibrations monitoring system in 2008, designed to monitor the dynamic behavior under ambient/operational conditions and during seismic events, aiming to provide useful data for structural safety control. In recent years, the software component of the monitoring system was complemented with new programs for automatic data management, automatic detection of seismic vibrations, automatic modal identification, and comparison with finite element modeling results. This paper presents the latest addition to this software, a new automatic analysis program developed for structural health monitoring of Cabril dam. This program applies a methodology to detect structural modification based on the analysis of natural frequencies over time (global stiffness changes can be correlated with frequency values), and it also deals with automatic email sending, containing updated results for supporting dam performance assessment and informed management.

This paper presents the use of ambient vibration measurement to better understand the behavior of dams. This type of measurement is under development and is not currently used by EDF for monitoring purposes but only to adjust finite-element analyses of concrete dams.The paper describes not only the practical use of the recording devices and the processing of the signal but also some feedbacks from measurements on 20 concrete dams. A simple instrumentation process is proposed to support the calibration of numerical models, especially in seismic evaluation and the use of the data for the calibration of finite-element model (gravity and arch dams) is presented and discussed. Obviously, this single measurement does not make it possible to highlight the effect of the reservoir level and ambient temperature on the frequency response of dam.Consequently, a focus is proposed on a long-term vibration recording on an arch dam: effect of season and water level are discussed, and numerical models are developed to explain some complex evolutions of frequencies.

KMIDam is a technology platform from Kinemetrics Inc. Designed to manage portfolios of dams with real-time information before, during and post-event. Leveraging a combination of smart sensing, modeling, digital twins, and real-time processing tools, KMIDam provides immediate feedback during events, and tracks changes of structures that may lead to problems over time. In this paper, we will provide an overview of the KMIDam platform through the lens of real-world case studies, including multi-dam and extreme condition implementations. We will also discuss how KMIDam enables improved operation and safety by enabling operators to assess the condition of each structure, understand the immediate impact of events, and track changes that happen to structures over time.

This paper investigates the impact of the sample size on a surrogate model in the context of parameter inverse analysis for high arch dams. A deep learning-based surrogate model is developed and integrated with Jaya optimization algorithm to enhance the computational efficiency and accuracy of the inverse analysis. The input variables for the training set of the surrogate model are generated by Latin Hypercube Sampling (LHS). The output variables are obtained based on a high-precision finite element model calculation. By comparing the model accuracy and computation time across different sample sizes (ranges from 20 to 200 times the number of input variables), the optimal sample size is identified. The study was conducted for the case study of an actual high arch dam in China for which measured data are available. The results indicate that a sample size of 100 times the number of input variables achieves a favorable balance between accuracy and computation time.

To release the effect of complicated boundary condition on determining accurate cable force, an innovative approach based on mode shape was proposed recently by the authors. With multiple synchronized measurements to identify mode shape values, it has been verified numerically and then experimentally that excellent accuracy in tension estimation can be achieved with precise fitting of the sinusoidal component of each chosen mode shape. This study aims to further explore the applicability of the proposed method in determining the tension of linked suspenders for certain arch bridges. Numerical analysis and mock-up test are performed for this study. It is clear to observe with finite element method that the mode shapes in each segment of the linked suspenders still mostly follow a sinusoidal function with a variation only observable near the boundary or linkage due to the influence of the hyperbolic components, which is essential to make the proposed method applicable. The numerical analysis results also show that accurate tension can be obtained. Then, the mock-up test with linked strands in laboratory is further conducted to verify the applicability of the approach in practice. The experimental results demonstrate that the error of computed tension is pretty small. It is particularly noteworthy that the measurements together with careful mode selection and appropriate choice in covering range of measurement are all critical to hold such a superb accuracy.

To develop a fully automated monitoring system of cable tension based on real-time vibration signals, this research first employs an efficient stochastic subspace identification method with tailored parameter selection to continuously identify the three frequencies of adjacent modes for the cables of Mao-Luo-Hsi Bridge. Most importantly, an automated algorithm is delicately established to robustly sieve out the stable modal frequencies of the cable by using the deep learning technique of convolutional neural network. The tension is finally computed with one available cable frequency according to the priority order predetermined by the statistics of identification rate. Overall, the current study achieves an automated cable tension monitoring system by completing several imperative works in the analysis of long-term cable vibration signals, the selection of suitable parameters, and the verification of proposed procedures. Furthermore, the real-time cable tension monitoring results of Mao-Luo-Hsi Bridge for two years is presented to solidly attest the robustness and performance of the developed tension monitoring system in real applications.

Cost-cutting in maintenance and inspection budgets are causing a mismatch between the current state of resourcing allocated to bridge preventive management and the real budget that would be needed to ensure safe and functioning transport routes in the long run. SHM is rarely implemented and, very often, only a sufficient spatial density of the sensor network is guaranteed. Issues related to both network topology and optimal sensor placement (OSP) are therefore pivotal to maximise the quality of SHM information that can be retrieved from a limited quantity of sensors while reducing overall SHM costs to the minimum. The present work investigates this optimisation problem by analysing different heuristic algorithms for OSP and assessing the effectiveness and reliability of the candidate sensor configurations derived therefrom in extracting accurate dynamic features and identifying damage occurrence in infrastructure systems. A real multi-span bridge subjected to progressive damage scenarios is used as a benchmark case study and a data-driven modal-based multi-objective approach is exploited to measure the utility of each configuration, allowing to determine the best possible sensor deployment.

This paper describes the use of the evolutionary game theory model to improve the finite-element model updating of civil engineering structures. For real-world applications, the finite element model updating problem is usually formulated via the maximum likelihood method. This method may transform the updating problem into two sub-problems: a bi-objective optimization and a decision-making sub-problem. In the bi-objective sub-problem, the main physical parameters of the structure are modified in order to minimize the relative differences among the experimental and numerical modal properties of the structure (natural frequencies and mode shapes). As a result of this sub-problem, a set of possible optimum solutions, the so-called Pareto front, is obtained. Subsequently, a decision-making problem is tackled, selecting the best solution among the elements of Pareto front. In order to reduce the simulation time without compromising the accuracy of the solution, an evolutionary game-theory algorithm has been considered herein to solve the updating problem. For this purpose, the finite element model updating of a real cable stayed Viana do Castelo footbridge has been performed. Finally, to assess the performance of this updating method, the obtained results have been compared with those obtained via implementation of a conventional method.

The use of simplified modal analysis methods for the modal analysis of bridge decks contributes to the intelligent modelling process for the analysis of the dynamic behaviour of bridges opening the way to easily feed a Digital Twin (DT) accelerating the demands of the Decision Support System (DSS) in real time. This work presents a novel method that allows the modal analysis of bridge decks by applying a formulation that reduces the structural problem to a reduced number of degrees of freedom associated with the structural response mechanism mobilised in the bridge deck vibration. A parametric study is proposed to analyse the dynamic structural response of a total of 20 bridge decks of different lengths and number of spans. The proposed method is experimentally tested by a dynamic loading test of a full-scale railway bridge deck. As a result of the analysis, the proposed method reflects an adequate convergence with the experimental dynamic structural response.

In recent years, the degradation over time of bridges put the focus on the structural health monitoring of such infrastructures. The continuous vibration monitoring of these structures presents two main advantages. The first one is the prediction of the degraded condition by means of suitable algorithms and the second one is related to the possibility of receiving real time alarms if some thresholds are exceeded. Nevertheless, the use of traditional wired monitoring systems is still limited by high cost related to both the instrumentation and the system installation on the structure. Moreover, the wires maintenance and the time required for data processing represent two significant constraints. In this paper, a feasible solution to these problems is presented. An innovative monitoring system, based on a network of wireless sensors managed by a gateway, has been designed. The wireless sensor nodes have been developed by adopting low-power and low-cost electronic components. Such sensors can acquire vibration data and perform pre-processing operations on board. Moreover, these devices can operate for a long time through the adoption of energy harvesting techniques for the battery recharge. The developed system has been installed for a long-term field test on a railway bridge, in parallel to traditional wired accelerometers. Many significant data have been collected and analysed to assess the performance of the system. The validation of this approach will allow to install these devices in an easy and cheap way on many infrastructures, with the goal to get synthetic structural health indicators in real time.

The paper presents a case study analysis on time-domain dynamic response of the highway bridge to live loads. The considered steel-concrete bridge structure has specific dynamic characteristics and defects in the form of superfluous permanent deformations of spans. Consequently, the bridge superstructure exhibits excessive, low-damped vibrations induced by cargo traffic.The goal of this paper is to model and analyze the impact of permanent deflections of the bridge spans on the structure performance in operational conditions. The analysis is based on results of experimental tests of bridge dynamic response to live loads as well as results of numerical simulations of the mutual interaction of vehicles and the bridge structure by means of FEM dynamic time-history analysis. Obtained results of the experimental vibration tests and theoretical analyses served as an input for the bridge current performance assessment in term of its safety, serviceability and condition related to durability.Proposed diagnostic procedure can be useful also in assessment of influence of permanent deflections on interactions between vehicles and other types of bridge structures.

Bridges play a primary role in the road and railway networks, and their inoperability due to damage or collapses following natural disasters or due to ageing, have impacts from both the social and the economic perspectives. For these reasons, an accurate control of their health conditions is of paramount importance, especially for bridges located on strategic roadways.This paper deals with the design and the installation of the structural health monitoring system of the newly built “Filomena Delli Castelli” cable-stayed bridge over the Saline river, in Central Italy. The bridge has a steel-concrete composite deck about 190 m long, with a peculiar plan shape given by the presence of a pedestrian and cycling path with curvilinear layout in the downstream side of the deck. The monitoring system is described, discussing about the adopted instrumentations and their location for both static and dynamic measurements. Moreover, the preliminary tests and studies that supported the design of the monitoring system, are also presented. Then, issues relevant to data acquisition, transfer and storage are addressed. Preliminary data from the monitoring system are also shown, and considerations about their usefulness in a structural health monitoring process are provided.

The Ashton Bridge contains 48 inclined fully locked coil hanger cables that are connected to its arch ribs and tie beams by steel fork sockets. Ambient Vibration Testing was used to estimate the cable forces after construction and compare them to predicted forces. Local finite element models of each cable were created. The fork socket drawings supplied by the manufacturer were used to model the sockets in order to simulate the stiffness properties. A 3rd order theory nonlinear analysis was performed on the local models followed by form finding. Thereafter the natural frequencies were computed using the Lanczos method. The frequencies in the local models were iterated until they matched the ones from the site measurements. When the two frequencies matched, the tension in the cable was evaluated. Due to the large variations in the forces of cables 1 and 24 on both arches compared to other cable groups in the bridge, they were considered as measurement errors. However the primary method for engineer’s approval relied on lift-off tests that ensured that the design force was achieved in the cables. The total variation between the forces estimated from the measured data and the forces predicted by the bridge’s finite element model was –3.18%. This was deemed as acceptable.

The Brivio bridge is a reinforced concrete tied-arch bridge composed of three spans of 44 m that crosses the Adda River in the Province of Lecco (northern Italy). The structure was completed in 1917, and – despite its age – it is still a crucial node for the vehicular traffic of the Lombardy regional network. Within a research program promoted by the Lombardy Region, a dynamic monitoring system was installed in the bridge. The paper presents the preliminary activities carried out before the monitoring period and selected results of the first two years of continuous monitoring. Special emphasis is given to the Structural Health Monitoring methodology implemented for the detection of anomaly occurrence using natural frequencies and mode shapes. A fully automated modal estimation and tracking software was developed and led to the identification of seven vibration modes for each span. As expected, temperature variations significantly affect natural frequencies, whereas no remarkable changes in mode shapes have been detected so far.

Structural health monitoring (SHM) schemes are prevailing for the maintenance of civil engineering constructions. Of specific interest to this paper are accelerometers and weigh-in-motion sensors due to their extensive implementation in highway infrastructures. Both sensing technologies are often expensive and require external power sources, which complicates their use in distributed monitoring systems. As an improved alternative, this work presents an exploratory study of the potential use of piezoelectric bimorph cantilever beams as vibration sensors and energy harvesters. The benefits of such sensors are several: they don’t need an external power supply; they are easily adaptable to various geometries and frequencies; they have no limitation on the time resolution; and they are cheaper than commercial accelerometers of comparable capabilities. The vibration sensing properties of the proposed type of sensors are evaluated through experiments conducted on small scaled vibrating systems and real-scale beams. Their applicability to power up an innovative weigh-in-motion sensor based on smart pavement technologies is also evaluated. Overall, the study demonstrates that long-term and self-sustained vibration monitoring by piezoelectric bimorph cantilever beams is feasible for different types of civil engineering constructions.

In recent years, existing transport infrastructures have experienced significant safety criticalities implying expensive repairs, significant business downtime and occasionally demolition with a relevant economic and social impact. Vibration Based Monitoring (VBM) represents a strategic tool for real time assessment of potential damages suffered by civil/strategic structures and infrastructures due to aging and/or after a critical event. As a part of VBM, experimental dynamic identification methods allow to characterize modal properties of existing structures both in stationary and non-stationary conditions. The process used to calibrate the numerical model (digital twin) minimizing the errors between considered parameters of real and numerical structure can be considered an inverse engineering application.This paper focuses on the dynamic calibration of a Finite Element (FE) model related to the “Ponte della Musica – Armando Trovajoli” bridge locate in Rome (Italy), built by means design documentation and visual inspection.The model calibration has been performed in terms of eigenfrequencies and equivalent viscous damping factor evaluated by means of accelerometric recordings. Several numerical FEM models were built using different boundary conditions. Uncertainties derived from external constrains and executive details have been accounted by varying stiffness and other mechanical parameters within several parametric analyses with the aim to fit experimental dynamic properties with simulated ones. The present study has been performed within the Task WP6 “Monitoring and Satellite Data” of the DPC-Reluis 2022–2024 agreement, with the aim to further analyse the influence of temperature on the vertical displacement of monitored bridge and compare them with satellite data information.

The condition assessment of bridge structures is carried out worldwide mainly by means of manual inspections, occasionally by recalculations and, if necessary, by specific monitoring campaigns. However, such periodic inspections may lead to delayed damage detection, which can result in safety losses and consequential damages but also to increased rehabilitation costs. In view of increasing digitalization, the research project “Bridge Asset Management (BrAssMan)”, funded by the Federal German mFUND scheme, aims at supplementing the current maintenance management of road bridges with reliable data-based analyses. To be able to establish a comprehensive and intelligent asset management for a large number of bridges, data-based condition statements are to be derived, based on numerical models, standardized monitoring systems and comparative parameters (key performance indicators). For this purpose, the large stock of German road bridges was analyzed and subdivided into clusters in cooperation with partners from the road authorities, with regard to structural type, materials, and age in order to ensure comparability and transferability of the monitoring concepts. For a large number of steel bridge structures typical examples of structural solutions are orthotropic steel decks as well as hangers and cables. Within the scope of the research project, five bridges – each with these characteristics – are being equipped with standardized monitoring systems. Based on calibrated numerical models and generated measurement data, a homogenized database for optimized condition control will be made available. The data will improve the safety, availability and reliability of bridge structures allowing for reduction of economic losses as well as of environmental impact due to traffic-disturbances.

Every structure needs to be monitored throughout its useful life, to ensure an adequate level of safety and due to external events - both natural and not – that can disturb its state of equilibrium. Moving from these demands, in recent years, Move Solutions has implemented a structural monitoring system, static and dynamic, consisting of a variety of completely wireless sensors, operating with LoRaWAN technology, together with a special Cloud platform developed with the aim of facilitating the analysis and visualization of data by the operators in charge of the activities. The system is based on excellent sensor synchronization (500 μs) through which a dataset conforming to OMA (Operational Modal Analysis) is obtained. From the accelerometric data, it is possible to extrapolate the daily frequencies and modal shapes using the FDD (Frequency Domain Decomposition) technique. For long-term monitoring, it is necessary to identify only structure modes of vibration among all those calculated by FDD; this is made possible by a multi-level clustering algorithm, designed by Move Solutions, that can differentiate useful vibrational modes from the “spurious” ones, which will be discarded. The following step is defined as Tracking, where the aim is to monitor the variations of the previously identified vibrational modes over time. The use of a wireless and fully automated monitoring system on the Cloud can give a big boost in simplifying the management of all infrastructures, cutting costs and digitizing processes.

In accordance with the latest national standard, the dynamic characterization of bridges and viaducts has become mandatory: a necessary action for newly constructed works in terms of dynamic testing and strongly recommended in the case of verification of existing structures. Based on the experience acquired for over fifteen years, we want to classify the construction types according to the actions to which they are subjected in relation to the possibility of carrying out an efficient operational analysis. In other words, to describe the optimal solutions according to the constructive characteristics; that is, if the excitation of the wind alone is better, or if it is preferable to have it combined with road or rail traffic that occurs nearby and how much it is preferable to stay on a motorway overpass, rather than on a road alongside, but not in continuity, with another in which traffic has not been interrupted. The work aims to evaluate the type of transducers most suitable for performing OMA on this type of structure. Having established that accelerometers, although less resolute than velocimeters, allow better phase stability, we will evaluate which of them that are the best in terms of performance-cost, especially in terms of spectral noise compared to the magnitude to be measured. The potential and limitations of wireless solutions are also analyzed and compared with traditional wired ones.

To evaluate the maintenance of the structural conditions of a viaduct or bridge, the temporal control of frequency variability is usually adopted. Considering that the frequency is very influenced by the temperature, small variations are not easily intercepted, and significant variations are instead often forerunners of irreversible damage. Another solution consists in the direct control of kinematic quantities. One particularly suitable in this regard is the velocity, as the kinetic energy is related to the elastic deformation energy. The detection of the vibration velocities alone, however, is not very indicative, as the variability can occur due to a simple increase in vibrations. The ideal would be to classify typical traffic conditions and use them as a basic element for comparing similar and recurring situations. Dynamic weighing makes it possible to catalogue a multitude of traffic models, to be taken as reference models, to make effective velocity control. A sort of dimensionless and universalization of the measure. If then the dynamic weighing is done from the intrados, together with the measurement of the accelerations and the determination of the velocities, there is also evidence of the deformations in various points that can add useful information about the health of the artifact, in a context of elaboration of a large amount of data (big data).

We present an experimental study of the effects of geometric nonlinearities on vibrations of rotating machines support structures. The initial stiffness of a structure, computed in its unloaded state, is affected by the applied forces, the so-called geometric stiffness. Here we study these effects via experimental methods designed to evaluate previous mathematical models. Our model is a metal beam under compression supporting a DC motor. The presence of large axial compressive force will reduce the beam stiffness and natural frequencies leading to unexpected, potentially dangerous resonance states. Experimental imperfections led to observation of interesting phenomena not predicted in our previous theoretical and numerical studies. We also observe, as expected, occurrence of the so called Sommerfeld Effect, when underpowered excitation sources get their rotation regime stuck at resonances.

Given the current availability of increasingly advanced sensors and processing capabilities, structural health monitoring (SHM) is the most suitable approach to the maintenance of operating structures. The recent trends in literature indicate that unsupervised data-driven damage detection algorithms may allow a transition from human inspections to continuous and automatic monitoring. However, there are still few examples that prove their effectiveness in real scenarios, i.e., in presence of uncontrolled environmental and operational conditions. This paper tries to bridge this gap, by presenting an application where vibration-based unsupervised damage detection is used to spot the existence of an ongoing corrosion process on operating tie-rods. These structural elements are metallic slender beams subject to axial load, used to balance lateral forces of arches and vaults, in both modern and ancient civil structures. Like all slender structures, they undergo significant vibration levels which make the use of modal identification algorithms particularly effective. In a recent study, the authors demonstrated how modal parameters can be used to define a multivariate damage feature which allows a separation between the environmental effects and damage. This paper investigates the potential of using a Gaussian mixture model for detecting damage in tie-rods through unsupervised data clustering. The potential of the proposed approach is demonstrated considering real data, acquired under uncontrolled environmental and operational conditions, and in presence of real damage.

Buildings could be under wind and earthquake induced excitation during their lifetime. The common practice is to install effective damping systems to reduce the excess vibrations. These systems normally include a sufficient number of dampers installed at several locations depending on the nature of excitation. However, it is not always feasible to install dampers of high mass ratio due to space or building floor plan limitations. In this paper, a novel combination of tuned mass damper (TMD) and tuned liquid damper (TLD) is proposed for reducing the seismic response of mass irregular buildings. This combination may reduce the number of TMDs required for effective vibration control. The use of TLDs can improve the level of vibration control and allow us to use lightweight TMDs. In this study, a TLD -building coupled interaction numerical model is established and the liquid inside the conventional rectangular TLD is discretized by four node-isoparametric finite elements. In addition, the TMD is attached to the different floors of the buildings to determine the vibration capabilities of the hybrid dampers under real earthquake excitations. The numerical study demonstrates a notable reduction in the vibration amplitude of the building related to the proper selection of damper parameters.

The application of modular construction in tall slender structures is a relatively novel concept. Modular buildings with heights exceeding 130m have been successfully constructed by combining reinforced concrete cores with steel-framed volumetric modules. Slender structures typically have an increased susceptibility to wind-induced acceleration responses which may give rise to occupant discomfort, and modular structures are no exception. The lightweight nature of modular buildings implies that they are more likely to exhibit large horizontal accelerations than other more traditional forms of construction. As modular construction techniques are employed in ever taller, more slender buildings, design analysis requires better understanding and information about the dynamic behaviour of modular structures. The damping ratio of a structure is one of the key parameters in predicting its acceleration response. Typically, empirical damping ratio values obtained from previous full-scale testing are used when analysing the acceleration response of a structure and its compliance with habitability requirements. However, no suitable previous full scale monitoring campaigns have been carried out on tall modular buildings. This paper presents data obtained from a full-scale vibration monitoring campaign on the world’s tallest modular building. The ambient acceleration response of the 135 m tall modular structure was recorded over a three-month period. These data are processed using modal analysis techniques to estimate the fundamental natural frequency and damping ratio of the structure. The results obtained using Bayesian and random decrement-based techniques are compared and their dependence on the stage of construction is evaluated. The measurements were obtained when the building was in both partially- and fully constructed conditions, allowing the relative stiffness and damping contributions of the core and modules to be investigated. The results of this research provide greater insight into the dynamic behaviour of modular buildings increasing confidence in design analysis results and enabling modular construction to be pushed to new heights.

In this work, the complex mode shapes of closely spaced modes of a slender lattice tower structure identified with stochastic subspace identification (SSI) are investigated.The SSI delivers its results in the form of complex eigenvalues and eigenvectors. For a proportionally damped structure, the mode shape components of a single mode shape lie almost on a line in the complex plane, referred to as the mean phase. For closely spaced modes it is known, that the mode shape components are not necessarily on a line in the complex plane. The mean phase deviation as an identification quality criterion for the identification of mode shapes has less significance in connection with close modes, so that a different examination of these mode shapes is necessary.This study is performed using experimental data of a lattice tower under environmental variability. For the mode shapes of the closely spaced modes of the structure, two dominant phases are observed in the complex plane corresponding to the two measurement directions. The influence of the environmental conditions and different structural states of the structure on the corresponding mode shapes is investigated. A new approach in dealing with complex mode shapes of closely spaced modes was developed and allows a better interpretation of the identification results and can be useful in assessing the state of the structure.

Wind turbines are usually designed for a lifetime of 20 years in Europe. A typical design of a wind turbine shows only little consideration for differences in location (flat areas, complex terrain), wind fields (rotating wind, upwind), or accessibility of the structure (off-shore, on-shore). Moreover, most wind turbines are typically equipped with only a few sensors that are used to control the turbine and record electrical and meteorological data. This makes it difficult to set up an efficient maintenance strategy to optimize maintenance intervals, the replacements of malfunctioning parts, the durability of the components, the cost of electricity, and to determine the remaining useful life.The authors are members of a group from the Technical University of Munich who have had the opportunity to work on several projects dealing with the improvement of monitoring systems and using a combination of wireless, wired, and other sensing techniques. It was the objective to obtain critical data at carefully selected points of the tower of a hybrid wind turbine out of pre-stressed concrete and steel. Automatic data recording, evaluation, and transmission techniques have been implemented to update material models in the frame of a digital twin of the turbine, identify icing on blades, optimize maintenance and operational parameters, and increase the overall sustainability of the turbine. The paper summarizes some of the findings from more than seven years of research.

Particle impact damper (PID) is an emerging passive damping technology with significant advantages over other passive damping systems. It is not commonly used in practice because of its low damping rate compared to the common viscous damper. Owing to various nonlinear phenomena present in the impact damping process, the analytical methods for design optimization of PID are rarely found. It is observed that the particle impact damper has two phases of damping when it is applied to a single-degree-of-freedom (SDOF) vibration system. In the first damping phase of the PID, there is significant damping with many strong head-on collisions in the PID. On the other hand, the second damping phase begins when the vibration amplitude of the primary system is reduced to a certain level and negligible damping of the PID is observed in this phase of long duration with only a few ineffective impacts in the PID. To improve the overall damping rate of the PID, it is proposed to combine the PID with a small external friction damper (FD) to reduce the duration of the ineffective damping phase of the PID in the free vibration of the primary system. A numerical model is established for the proposed hybrid damper and it is validated by experiments. The numerical model can simulate the response of the primary system with the proposed hybrid damper over a wide range of design parameters and an optimal design combination can be determined. It is shown by both numerical and experimental results that the proposed hybrid damper can improve the damping performance significantly and provides robust damping in free vibrations of SDOF systems.

Timber floors can be susceptible to human-induced vibration due to the low density of timber compared to other construction materials. Human-induced vibration is a complex problem due to many involved parameters. As in many dynamic systems, the response depends on the dynamic parameters and the excitation source. Therefore, more advanced assessment methods must consider suitable human-floor interaction models. The most straightforward classification is based on the dynamic response. The increasing use of timber in commercial and office buildings requires more complex analysis than in residential dwelling. Therefore, the timber research community has proposed specific procedures for low-frequency floors. The dynamic response of timber floors improves under a combination between timber and other materials with complementary properties. Timber composite floors are generally made of wood products coupled with concrete, steel, glass or other wood products through a continuous or discontinuous connection. This paper reviews the most recent findings and research trends on vibration issues related to timber floors.

Ambient vibrations of a six-story lightweight timber frame building were measured under different environmental conditions in order to obtain the modal parameters of the structure. Changes in temperature and relative humidity in timber can influence its response in terms of modal parameters. Namely, a moisture content change in the timber can affect stiffness, strength, and shape of the elements as well as the properties of the connections. Monthly measurements have been performed on a six-story lightweight timber frame building in Varberg, Sweden, built in 2021. The in-situ tests were performed using five battery-driven data acquisition units with 14 uni-axial accelerometers. Additionally, the building is permanently monitored using temperature and humidity sensors, starting ever since its construction phase. The ambient vibration data have been analyzed using two different only-output methods. The results obtained under different temperature and humidity conditions were compared in order to assess the effect of the environmental conditions in the building. This information can be used to ensure the building meets safety and performance requirements, as well as to identify potential issues that may need to be addressed during building design.

The identification of modal parameters under ambient excitation is a crucial step in structural health monitoring for civil engineering structures. This paper proposes an automatic modal analysis method based on Covariance-driven Stochastic Subspace Identification (SSI-Cov), which consists of two stages: parameter-optimized SSI and adaptive cluster analysis. The first stage investigates the optimization of two key parameters in the SSI method, namely the block rows of the Toeplitz matrix and the model order. In the second stage, a multi-step clustering approach is proposed that performs Max-min clustering based on hierarchical clustering. This framework achieves accurate identification without relying heavily on the setting of the hierarchical clustering cut-off threshold, as only one initial mode is required during the hierarchical clustering. Field tests on a timber structure benchmark is presented to demonstrate the effectiveness of this operational workflow in automatically identifying closely spaced modes.

Cross-laminated timber (CLT) floors are typically composed of prefabricated CLT panels assembled on a construction site. The actual connections are commonly disregarded at design stage. CLT floors are modelled either as a monolithic slab or more frequently as a collection of CLT panels with no connections. This paper presents a numerical study designed to demonstrate the effect of two common inter-panel connections, i.e. single surface spline and half-lapped joint, on vibration modes of various CLT floor configurations. The inter-panel connections are modelled as an equivalent 2D elastic strip between the CLT panels. This uncomplicated yet robust approximation of reality can be used readily in design practice, regardless finite element (FE) software used to determine modal properties of a floor. The corresponding monolithic floors and those without inter-panel connections are studied for comparison. The results showed that the common practice of modelling CLT floors either as monolithic slabs or as a set of independent panels should come to an end.

The earthquake of L’Aquila on the 6th April 2009 was the fifth stronger earthquake recorded in Italy. To support citizens, around 3300 timber house modules have been built in the region of L’Aquila. These single- or two-story buildings are characterized by total surface from 40 to 70 square meters, realized by employing two of most common wood-based earthquake-resistant structural systems, namely the light-frame or the cross-laminated timber (CLT) system respectively. After 13 years, these structures require maintenance interventions to preserve their original functionality, as also emphasized by recent accidental partial collapses and by individual diagnostic investigations. Among others, this paper reports some major experimental evidences which have been collected from in-field monitoring investigations on timber load-bearing components. Most importantly, the attention is focused on the proposal assessment of a rapid but reliable operational protocol and monitoring strategy which could be applied for diagnostic purposes, based on vibration frequency analysis and its modification over time, to possibly monitor “rapidly” and timely retrofit such a wide number of timber modular houses.

Structural Health Monitoring (SHM) is increasingly important in protecting and maintaining architectural heritage. Its main goal is to distinguish ordinary fluctuations in a building’s response from other, possibly anomalous, behaviour. SHM starts setting sensors to measure accelerations or velocities and other environmental parameters over time at fixed points of the structure. The time series processing makes it possible to perform modal tracking and damage/anomaly detection while correlating dynamical and environmental parameters. In practice, these activities are conducted separately, using different numerical codes. Thus, the idea is to take the first step to distance from such practice, leveraging the MOSCARDO system, which encompasses a Wireless Sensor Network (WSN) and a platform designed according to a cloud architecture that provides services for storing and processing data from the WSN. We employ a code based on the Stochastic Subspace Identification (SSI) technique to improve the system’s capabilities, and we exploit the SSI’s theoretical features to get an efficient implementation that will be integrated into the cloud-based platform. This pipeline is here presented considering data collected from a monitoring campaign on the “Matilde donjon” in Livorno (Italy) and reporting preliminary numerical results on the identification of the modal parameters.

The dynamic identification of a reinforced concrete bell tower was investigated in this paper by analysing the case study of the tower of San Giovanni Battista church in Firenzuola (Florence, Italy). The bell tower and the church were built between 1959 and 1966 based on the project of two Italian architects, Carlo Scarpa and Edoardo Detti. Since its construction, the bell tower has shown some concerns arising from the dynamic interaction between the bells’ swinging and the tower. Currently, this phenomenon and the progression of the degradation of the reinforced concrete are leading to the necessity of conservative restoration works. The paper focused on these aspects by illustrating the results of a one-day of experimental campaign. Indeed, the integration of Structural Health Monitoring (SHM) techniques for historical structures always raises great interest in the scientific community but only a few scientific papers deal with the structural response of towers under bell-induced loads. With this aim, the signal acquisition was conducted both under ambient vibrations (wind and traffic) and under vibrations induced by the swinging of one of the five bells currently located on the tower. The results of these tests were analysed with the aim to identify natural frequencies and modal shapes.

The dynamic behaviour of an almost 200 m tall telecommunication tower has been monitored for about eight years. It consists of three structural sections: a reinforced concrete shaft that carries a tubular steel section and a hollow glass fibre reinforced plastic cylinder at the top. Beside the structural response at different levels, also the temperatures at different locations of the steel section as well as wind speeds and directions have been measured. Based on the acquired data, the modal parameters of the structure have been continuously identified by means of an automated procedure. From the identified results, several conclusions concerning relations between environmental conditions and the dynamic behaviour of the system could be drawn.These relations do not only concern seasonal changes of the natural frequencies due to varying temperatures. Also system changes, such as icing of the structure, can be identified from modal parameters. Additionally, very interesting non-linear dependencies of natural frequencies and modal damping ratios on the vibration amplitudes have been observed. It is very likely, that these system nonlinearities are caused by the bahaviour of the tuned mass damper installed at the tower’s top. Further analyses are carried out for the sake of an enhanced interpretation of the findings from the monitoring data.

Building with timber is one of the ways to limit our carbon footprint, using a lighter material reduces the need for deep foundations and storing carbon in the structure itself is a solution for reducing the atmospheric part of it. Oppositely to the more classical materials of the building industry, steel and concrete, there is very limited knowledge about the behavior of tall slender timber structures under weather solicitations and the vibration of high-rise buildings made of wood is a main question limiting their development.The experimental European funded research program DynaTTB focused on the measurement, on site, on existing timber towers, of the structural damping with regard of the excitation by buffeting wind and the resulting comfort feeling of occupants. In France an experimental campaign on two tall composite towers, with a concrete core and timber walls and floors was achieved in 2021 before and after completion of both buildings. Assumptions made by the designers have been compared with real values measured on site giving way to design guidelines addressed to structural designers’ offices. Extracting the relevant information from the recorded data is not straightforward, as described in this paper, because timber structures are more sensitive than other ones to the contribution of inner walls, façade and foundation to stiffness and damping.

The actual dynamic behavior of the masonry civic Clock tower in a little village, heavily damaged by the recent 2016 seismic sequence of central Italy, is thoroughly investigated by means of a detailed numerical model built and calibrated using the experimental modal properties obtained through Ambient Vibration Tests. The goal is to update the uncertain parameters of the Finite Element Model (elastic moduli, mass densities, constraints, and boundary conditions) to minimize the discrepancy between experimental and numerical dynamic features. Due to the high nonlinear dependency of the objective function of this optimization problem on the afore-mentioned parameters, and the likely possibility to get trapped in local minima, a fully automated Finite Element Model Updating procedure based on genetic algorithms and global optimization is used, leading to the successful estimation of the uncertain parameters of the tower. The results allowed to create a reference digital replica of the current structural condition of the tower and to set the performance standards that will help to optimize the control of the structural integrity over time.

Masonry bell towers are significant expressions of past construction techniques and distinctive landmarks in historical centers of towns of the Inner Areas of the Apennines. Their preservation in earthquake prone regions represents a significant technical challenge, which can take advantage of advanced tools for structural assessment and monitoring under operational conditions as well as extreme loads. In this perspective, vibration-based Structural Health Monitoring (SHM) represents an attractive solution thanks to its minimal invasiveness and the ability to detect damage onset from the analysis of the global response of the structure without any prior information about the damage itself.The present paper illustrates preliminary results of modal-based SHM of the Civitacampomarano belfry. The tower is located close to a landslide and in an earthquake prone region, so timely assessment of possible damage plays a critical role for its conservation and maintenance. The architecture of the SHM system and the technological solutions adopted for continuous monitoring of the vibration response of the tower under operational conditions are described, focusing the attention on the effect of environmental variables and earthquake input on the modal parameters of the structure.

The presented work proposes a Structural Health Monitoring procedure based on the structural dynamic characterization aimed to a progressive removing of the temporary provisional structures installed in a Romanic church for a safety purpose. The procedure is illustrated in its application to a real case (the complex of the San Giorgio in Ruballa Church, sited in the province of Florence) and it wants to provide a general method for a fast structural integrity assessment of sensitive structures which require non-invasive investigations, as historical buildings. The activity consists in the installation of a proper dynamic monitoring system (accelerometers) for the controlled removal of the temporary shoring system. The first step of the procedure involved the global dynamic characterization of the structure through vibrations measurements recorded in its reinforced state (with temporary shoring system). The following step includes the repetition of the measurements as the removal operations progresses, in order to evaluate the effect of the single temporary shoring system removal. The check between the modal parameters before and after the dismantling phase is carried out both in terms of comparing the frequency of the identified modes and by comparing the modal shapes, using the Modal Assurance Criterion (MAC). The measurements are performed using anthropic and environmental elements as excitation source and the modal parameters extraction is carried out using Operational Modal Analysis techniques. The methodology turned out to be useful to keep under control the Church structural safety during the removal operations, revealing that the dismantling operations didn’t affect the structural conditions of the manufact.

Model calibration plays a decisive role in the assessment of structural damage using techniques developed by model-based approaches. In this study, an artificial neural network (ANN) based procedure is presented to construct the baseline model of the 24.25 m high minaret of Hacılar mosque (Turkiye). Since the swaying behaviors of slender minarets are comparable to those of a beam-like system, a three-dimensional (3D) system formed by brick elements is transferred into a simplified system composed of only beam elements regardless of its peculiar geometries as well as the complicated connections between the booting part and surroundings. The simplified model is calibrated by targeting the modal information generated on the 3D building using a 4-uniaxial accelerometer network capturing only the lowest modes. The physical simplified model is promptly calibrated by adjusting not only stiffness but also mass and Poisson’s ratio parameters simultaneously. As a result, the modal information of the calibrated model gets closer to the counterparts obtained from the 3D system, especially in the fundamental mode.

Among the most popular techniques for repairing and retrofitting masonry structures are those based on carbon fiber reinforced polymers (CFRP), textile reinforced mortar (TRM) and mortar reinforced with electro-welded wire mesh (WWM). These techniques have demonstrated to perform well in laboratory experiments and in real seismic events. However, up to date, there is no experimental field technique able to assess the effectiveness of this intervention in a non-destructive manner. In this study, four full scale unreinforced masonry walls were constructed in laboratory and retrofitted using CFRP, TRM and WWM methods. The walls were tested under a quasi-static cyclic load pattern and their modal properties were identified at different levels of load and damage by applying low intensity impact.The results reveal variations in the modal frequencies of all the walls. However, these variations were only significant when the reinforcements distributed on the entire face of the panel. When damage was affecting the support conditions, it can be only identified when it was originally generated and not its progression.

The eighth (and last) axiom of Structural Health Monitoring (SHM) states that damage increases the complexity of a system. After its introduction, several methods to measure complexity have been explored in the scientific literature. Among these, entropy measures demonstrate to be very straightforward to apply, with a relatively simple concept behind them. Thus, based on this feature, researchers proposed damage identification methodology in several branches of research, such as mechanical engineering, civil engineering, etc. In this work, the authors present an analytical study on the dependency of spectral entropy measures from the modal characteristics of a structural system, showing that an analytical relation exists for what concerns a Single Degree of Freedom (SDoF) system. A comparison between spectral entropy of different physical quantities (displacements, velocity, accelerations, etc.) is discussed for their use in SHM. Finally, different contributions of variation in entropy (i.e., due to external sources and structural properties) are analysed to better understand the causes of these perturbations. The work is of particular interest for cultural heritage structures since many of these are characterised by the presence of protruding elements, most of the time assimilable to SDoF systems (e.g., lanterns, belfries, pinnacles, etc.), when their dynamic is analysed relatively to their base movement.

In the case of degraded building material and developing cracks, steel tie-rods allow for a fast, relatively simple, and very effective strengthening intervention, especially for high rise masonry structures such as medieval bell towers. However, their design has a high impact on the external aesthetic of the structure; thus, they are generally not considered as an acceptable definitive solution. Here, several designs are proposed for the replacement of such a pre-existing reinforcement system with less invasive options. These candidates are then compared considering multiple factors such as the conservation of the architectural design, the uncertainties in terms of geometric and mechanical properties, the nonlinear behaviour of the damaged masonry walls, and the required level of structural safety. The placement of these alternative strengthening interventions along the tower height is also optimised according to the specific crack pattern – reflected in a subdivision of the calibrated Finite Element Model in of macroelements – and the most probable collapse mechanism. Their viability is finally assessed and ranked.

A research team of experts from the University of California, Berkeley (USA), Urgench State University (Uzbekistan), Miyamoto International Silk Road (Uzbekistan) and Sigma Innovative Tech (Uzbekistan) has been working on studying and monitoring heritage monuments in Khiva, (Uzbekistan) since 2018. Among its recent efforts, the Islam Khodja minaret and the adjacent madrasah were laser scanned in the summer of 2022. This minaret is the tallest minaret in the ensemble of heritage monuments surrounded by the fortified walls of the inner city of Khiva, Itchan Kala. For this part of the project, the laser scans were conducted from eight positions to ensure the geometry of the monument is obtained with a high accuracy and that the coverage is sufficient to create a detailed finite element model. In 2021, the minaret’s resonant frequencies were measured via ambient vibration study. Sensitive accelerometers were installed at several elevations of the minaret. The response of the structure to the ambient noise was recorded and analyzed. This paper summarizes the results of the laser scanning and the ambient vibration studies. In the next phase of the project, the collected point cloud will be used for the finite element modelling of the minaret and surrounding structures. The results of the ambient vibration study will be used to calibrate the numerical model to ensure a close correlation between the performance of the model and that of the real structure.

Structural Health Monitoring (SHM) is a field of increasing interest and worthy of new approaches and innovative applications. Italian territory is rich of architectural and cultural heritage that needs to be managed, monitored and conserved. This work presents a possible framework for the monitoring of such heritage that is suitable for large scale analyses and permits a fast and quick assessment, useful to the stakeholders responsible for its management. The proposed algorithms are based on an appealing technique, that gained popularity during the last years in the field of SHM, represented by the advanced multi-temporal differential synthetic aperture radar interferometry. Although the exploitation of these technique for the SHM of architectural and cultural heritage is still an open issue, different applications available in literature show promising potentialities. The algorithms and procedures proposed in this work are applied to a case study area located in the historic centre of Rome (Italy) to show the potentialities of the method. To this aim, COSMO-SkyMed ascending and descending datasets are processed applying the small baseline method obtaining deformation time series and mean velocity maps of the permanent scatterers located in the investigated area, for both geometry acquisitions. The information from these datasets are then elaborated and integrated with information from other data sources in order to provide a first estimation of potentially critical elements within the analyzed stock at urban level.

Structural Health Monitoring (SHM) is a promising approach for assisting the condition-based structural maintenance of heritage buildings, via the continuous analysis of diagnostic data collected by a network of sensors. Within this context, vibration-based SHM is receiving increasing attention but the practical applications on heritage structures are still not frequent and generally based on the use of a limited number of sensors.The paper is mainly aimed at presenting selected results from the dynamic monitoring of the Milan Cathedral. It should be noticed that the dynamic response of the structure is continuously collected in a reasonably well distributed measurement grid (27 channels of data), so that mode shapes-based methods could be conveniently used for anomaly detection and localization.After a concise historic background on the historic monument and a description of the dynamic monitoring system installed in the Milan Cathedral, the paper focuses on the dynamic characteristics of the monument and on the monitoring of environmental parameters. Subsequently, the results collected in the first years of dynamic monitoring are presented and discussed, with special attention being given to the influence of environmental parameters on the variations observed in the modal behavior of the building. Furthermore, as the response to seismic events was recorded during the monitoring, comments are given on the seismic behavior of the cathedral.

A key issue in the field of SHM is the identification of a set of key performance indicators (KPI) able to fully describe a structure behaviour and its health status. Among all available KPIs, modal parameters are often chosen as monitoring indicators, since their variation, if correctly interpreted, can help recognise the presence of damage or the beginning of an incipient degradation process. However, structural variations might not be due solely to damages and attention should be paid to properly classify them. This paper aims at discussing the influence of thermal effects on the dynamics of concrete bridges, as environmental temperature changes tend to induce structural variations that might be somehow misclassified as damages over a short observation period. A considerable dataset of vibration data collected from one-year monitoring of several highway bridges (with different static schemes, cross-sections, span lengths, etc.) is analysed to support this discussion. Data are part of a large industrial SHM framework dedicated to the monitoring of bridges through MEMS-based distributed measurement nodes. All the analysed structures show a modification in their natural frequencies due to a variation of environmental temperature. The vibration modes affected by temperature variations are both flexural and lateral modes, depending on the bridge structural characteristics.By discussing how temperature can influence the dynamic behaviour of bridges, the paper also aims at identifying those mechanisms governing frequency variations related to changes in the environmental conditions and finding possible similarities between structures behaving in the same way. Great attention is also given on how to deal with modal parameters modifications, when the monitored structure is part of a more complex Early Warning System (EWS) and, in general, when reliable thresholds must be set on the Key Performance Indicators chosen to detect the birth and growth of damage.

Ageing of existing infrastructure, man-made intervention and increasing effects of climate change are prognosed to intensify the pressure on Critical Infrastructure, including natural environment, thus requiring more effective and accurate monitoring campaigns aimed to provide a continuous real-time alerting in case of potential failures. To date, monitoring activities still rely on the deployment of several contact sensors, each providing a single point measurement and requiring access to the asset to be monitored with impacts on safety, in case of endangered structures or unstable slopes, and on operations as for example traffic block on a bridge for instrument installation purposes. Ground-based Interferometric Radars (GB-InRa) provide remote sensing capability allowing to monitor wide areas or structures in their entirety and without the need to place any contact sensors; thanks to its intrinsic characteristics, Radar Interferometry can be a fundamental asset to guarantee a 24/7 accurate monitoring of critical infrastructures, having continuous information on failure precursors and timely alerts as soon as there are exceedances of the user-defined thresholds.Regarding dynamic monitoring, GB-InRa is able to detect even the smallest vibrations of the structure, providing real-time information on natural frequencies (without any low-frequency cut-off), Structural Health Monitoring and Operational Modal Analysis. This article is aimed to provide an overview of the InRa systems currently available within IDS GeoRadar portfolio and the variety of application where they can be deployed, with a specific focus on railway monitoring and relevant benefits granted by this remote sensing capability with sub-millimetric accuracy for advanced SHM projects.

The School of Engineering Main Building of the University of Naples “Federico II” has been for years the core of an experimental research in the area of the structural monitoring aimed at the seismic risk mitigation and management. It is a relevant scientific and technical problem still of current interest, especially because it is a building characterized by a relevant architectural value located nearby the Campi Flegrei, a large and active volcanic area. It is also located nearby the Diego Armando Maradona Stadium, the home stadium of the S.S.C. Napoli football team. During one of the key events of the Serie A season, a monitoring system was installed aimed at analyzing the vibration response of the building under the excitation of about hundred thousand people inside and outside the Maradona Stadium. Data have been processed according to different approaches to put in evidence the amount and variety of information that can be obtained from a vibration-based structural and seismic monitoring system. The results show that the response amplitude is influenced by the operational loading caused by the supporters of the local football team when approaching the stadium and during the match. Such a loading shows characters common to an input ground motion but with a significant influence of the random excitation due to the surrounding environment. In fact, the input due to the supporters jumping in the stadium is characterized by a dominant frequency component and some directionality, but with a significant random response superimposed to it. The vibrations at the ground of the building as well as those measured at the upper floors have been therefore processed to characterize the input as well as structural response in these unique operational conditions.