Vibrations of existing structures induced by wind, traffic, and human activities are often ambient in nature. These vibrations typically have low amplitudes, making it challenging to capture their motion with a camera. This paper presents a framework for measuring the displacement of structural ambient vibrations without physical contact using a low-cost camera. The micro-amplitude vibrations of the structure are captured by the camera and then amplified using the Phase-Based Video Motion Magnification (PVMM). The centroid of structural target segments in each image frame is tracked using the proposed Shape-Box Tracking (SBT). Unwanted background objects are removed using the proposed Line-Based Color Selection (LCS). Vibration characteristics are determined using frequency-based analysis and Random Decrement Technique (RDT). Two experiments based on the proposed framework were conducted to demonstrate its effectiveness. The first involved free-decay vibration testing with large amplitudes, while the second focused on ambient vibration with small amplitudes, emphasizing motion magnification. The success of this method paves the way for applying low-cost cameras in the operational measurement of existing structures

Piezoelectric materials possess the unique ability to convert mechanical stress into electrical voltage and vice versa, making them highly suitable for various smart engineering applications. One of their most promising uses is in the field of vibration energy harvesting, where ambient mechanical vibrations can be transformed into usable electrical energy. For instance, when integrated into roads, pavements, or structural components, piezoelectric sensors and actuators can harvest energy from dynamic loads such as moving vehicles or pedestrians. In renewable energy systems, particularly wind turbines, blade vibrations can lead to structural fatigue and efficiency loss. The integration of piezoelectric elements for active vibration control can significantly reduce unwanted oscillations and enhance operational stability and energy output. Simultaneously, functionally graded materials (FGMs) — advanced composites with spatially varying properties — are increasingly being used in the design of wind turbine blades and other mechanical components due to their ability to optimize strength and reduce stress concentrations. This research focuses on the active vibration control of tapered FGM beams with porous structures using embedded piezoelectric actuators. The modeling approach combines Euler-Bernoulli beam theory with the finite element method (FEM), and the governing equations are derived through Hamilton’s principle to accurately capture the dynamic behavior of the system.

Piezoelectric vibration energy harvesters (PVEHs) have demonstrated their potential for sustainable energy generation from diverse ambient vibrations for low-power devices and systems. However, great challenges remain concerning harvesting more energy from low-frequency input sources and broadband random excitations. In this paper, a novel PVEH featuring a lead zirconate titanate (PZT) hollowed trapezoidal cantilever beam is proposed, simulated, optimized and fabricated to effectively broaden its output bandwidth at low frequency ranges. Under 1 g acceleration, the traditional solid PVEH showed a resonant frequency of 47.80 Hz and a maximum output power density of 14.22 mW/cm3, while the proposed PVEH showed two resonant frequencies of 21.30 Hz and 50.40 Hz. Compared to the traditional solid PVEH, the first-order resonant frequency was reduced by 55.44% and the corresponding maximum output power density was 3.3 times higher in the proposed PVEH. Furthermore, a parallel synchronized switch harvesting inductor quadruple voltage rectifier (P-SSHI-QVR) circuit is designed to extract energy from the proposed PVEH. For the proposed PVEH incorporating the P-SSHI-QVR circuit, the maximum stored voltage was 20.49 V at a first-order resonant frequency of 21.30 Hz and 5.68 V at a second-order resonant frequency of 50.40 Hz, with corresponding maximum stored powers of 36.89 μW and 2.97 μW, respectively. This study verified the feasibility of the optimized design through simulation and experimental comparison.

The dynamic characterization of historical buildings located in a complex geological and seismological context is essential to assess seismic vulnerability and to guide conservation strategies. This study presents a non-invasive, ambient vibration-based, investigation of the Norman Castle of Aci Castello (Sicily, Italy), applying Horizontal to Vertical Spectral Ratio (HVSR), Horizontal to Horizontal Spectral Ratio (HHSR), and Random Decrement Method (RDM) to evaluate the structure’s dynamic behavior and potential Soil–Structure Interaction (SSI) effects. The fundamental site frequency, estimated within a broad plateau in the range 2.05–2.70 Hz, does not overlap with the structural frequencies of the castle, which range approximately from 6.30 Hz to 9.00 Hz in the N–S structural direction and from 3.50 Hz to 8.50 Hz in the E–W direction, indicating absence of global SSI resonance. However, the structure exhibits a complex multimodal response, with direction-dependent behavior evident both in spectral peaks and in damping ratios, ranging from 2.10–7.73% along N–S and 0.90–5.84% along E–W. These behaviors can be interpreted as possibly linked to structural complexity and the interaction with the fractured volcanic substrate, characterized by shallow cavities, as well as to the material degradation of the masonry. In particular, the localized presence of subsurface voids may induce a perturbation of the low-frequency ambient vibration wavefield (e.g., microseisms), producing a localized increase in spectral amplitude observed at Level I. The analysis indicates the absence of global SSI resonance due to the lack of overlap between site and structural fundamental frequencies, while significant local SSI effects, mainly related to cavity-induced wavefield perturbation, are observed and may represent a potential vulnerability factor. These findings highlight the relevance of vibration-based diagnostics for heritage vulnerability assessment and conservation strategies.

Abstract The advancement of information and energy technologies has spurred an increased demand for low-power and compact electronic devices with across various fields. Developing energy harvesting technologies to capture ambient and sustainable energy offers a promising solution to complement or replace conventional batteries. The piezoelectric technique provides a solution for energy harvesting from different energy sources, and high-frequency operation in piezoelectric energy harvesting offers several advantages. These include increased power output, as more charge is generated per unit of time, which increases the current. Additionally, better alignment with the natural resonance of piezoelectric elements enhances energy conversion efficiency. Piezoelectric energy harvesters have gained significant attention in recent years due to their ability to convert ambient mechanical vibrations into electrical energy, which opens up new possibilities for environmental monitoring, asset tracking, portable technologies and powering remote “Internet of Things (IoT)” nodes and sensors. Mechanical vibrational energy, which is provided by continuous or discontinuous motion, is an infinite source of energy that may be found anywhere. The purpose of this article is to highlight developments in three independent but closely connected multidisciplinary domains, starting with the piezoelectric materials and related manufacturing technologies related to the structure and specific application; the paper presents the state of the art of materials that possess the piezoelectric property, from classic inorganics such as PZT to lead-free materials, including biodegradable and biocompatible materials. These inherent properties of flexible piezoelectric harvesters make it possible to eliminate conventional batteries for lifetime extension of implantable and wearable IoTs. This paper describes the progress of piezoelectric perovskite material-based flexible energy harvesters for self-powered IoT devices for biomedical/wearable electronics over the last decade. Keywords: Piezoelectricity, energy harvesters, device architectures, nanostructures, piezoelectric materials synthesis, flexible electronics.

Vortex-induced vibrations (VIVs) pose a significant serviceability and fatigue concern for long-span cable-stayed bridges, which are characterized by low natural frequencies and limited structural damping. Tuned mass dampers (TMDs) are widely used to mitigate VIVs, but evaluating their effectiveness requires accurate estimation of modal damping ratios. Operational modal analysis (OMA) using ambient vibration data has become a practical tool for in-service damping estimation, though its accuracy is often compromised by low signal-to-noise ratios, algorithmic sensitivity, and environmental variability. In this regard, this study presents field validation of OMA-based damping estimation using long-term structural health monitoring (SHM) data from a cable-stayed bridge equipped with a multiple TMD (MTMD) system. Ambient vibration measurements collected before and after the MTMD installation were analyzed using a displacement-reconstruction approach. Additionally, a field excitation test utilizing one TMD unit was conducted to obtain a reference damping ratio. The results demonstrate that OMA, when combined with displacement reconstruction, yields reliable damping estimates that closely align with the reference value. The findings further reveal the amplitude-dependent activation of the MTMD system, with effective damping achieved only under sufficient wind-induced excitation. These insights offer practical implications for evaluating damping and verifying the performance of passive control devices under operational bridge conditions. These findings highlight the applicability of OMA for in-service evaluation of passive vibration-control devices and provide practical implications for assessing bridge serviceability and MTMD performance under operational conditions.

This study presents a methodology for determining the optimal placement of sensors along the height of buildings to minimize uncertainty in reconstructing structural response at non-instrumented floors. Recent advancements in sensing technology have expanded the application of sensor data in earthquake and structural engineering, including model validation, post-event damage assessment, and structural health monitoring. However, to lower the costs of sensor installation and maintenance—particularly at the regional scale—it is essential to strategically place sensors to maximize the value of the collected data. Because the optimal sensor configuration depends on the specific objectives of an instrumentation project, there is no universal solution to the sensor placement problem. In this study, we focus on identifying sensor locations that allow for accurate interpolation of structural responses at non-instrumented floors with minimal prediction uncertainty. This objective supports the primary goal of the California Strong Motion Instrumentation Program (CSMIP), which is to collect structural response data with the highest possible accuracy and the lowest uncertainty. The proposed method is limited to stationary excitations (e.g., ambient vibrations or distant earthquakes) and to buildings with uniform mass and stiffness distributions along their height. Under these assumptions, a Gaussian Process Regression (GPR) model is used to quantify response prediction uncertainty and minimize the total uncertainty across the building height by placing sensors at the most informative locations. The GPR model is based on a simple shear-flexural beam representation, which effectively approximates the building using very few parameters—parameters that can be estimated from limited building information. The proposed method is verified and validated using both simulated and real data. Finally, a table is proposed that can be used by strong motion networks to facilitate more quantitative decision-making regarding sensor placement. While assumptions used in this study may seem restrictive, they strike a practical balance between accuracy and simplicity for large-scale applications such as CSMIP. The extension of this work to non-stationary excitations and general building types by training the GPR model on recorded seismic data rather than random vibration theory is under development.

Seismic failure assessment of a 19th-Century masonry minaret with and without iron clamp and dowel Retrofit: Experimental Testing, ambient vibration validation and numerical modeling

Damping identification using topological signal processing of ambient vibration measurements

During the service life of bearings in ship systems, they operate under discrete constant operating conditions involving load levels, rotational speeds, and ambient vibrations. Traditional research mostly relies on idealized laboratory conditions of single constant load and constant speed, leading to significant discrepancies between the derived performance degradation patterns and actual on-site scenarios of marine bearings. In view of this, this study integrates the maximum entropy method (MEM) and Poisson counting principle (PCP) to analyze the variation law of the bearing performance degradation parameter—degradation probability—with changes in load ratio and rotational speed. Temperature gradients and impact vibrations are excluded to align with the actual experimental scope. The research results show that (1) the degradation probability of the optimal vibration performance state of the test bearings exhibits an overall nonlinear increasing trend during operation. (2) For the same time series, the degradation probability increases with the rise in load ratio and enters the non-zero phase earlier (indicating earlier degradation initiation). (3) Except for the 3rd–6th time series at 6000 r/min, the degradation probability within the same time series decreases with increasing rotational speed under discrete constant speed conditions.

Scour, defined as water-induced erosion of soil around bridge piers, poses a significant threat to the stability and safety of bridges. Investigation of scour effects around the bridge piers is essential to ensure the long-term performance of bridges. This study examines the effects of local scour on the structural integrity of highway bridges by integrating on-site measurements, 3D computational fluid dynamics (CFD) simulations, and nonlinear finite element (FE) analysis. A highway bridge located over the Senoz Stream in Çayeli, Rize (Türkiye), which suffered significant pier damage due to time-induced local scour, is considered. Since site investigation on the damaged bridge was not feasible, a nearby structurally identical bridge was selected for ambient vibration testing and numerical simulations. The local scour depth around bridge piers was estimated for different scenarios using validated 3D CFD simulations based on a synthetic flow input derived from different return periods calculated using the Gumbel distribution. The scour depth was then incorporated into a nonlinear FE model using a Concrete Damage Plasticity (CDP) approach to simulate failure mechanisms. The numerically obtained damage patterns were found to closely match the actual collapse observed in the damaged bridge. The novelty of this study lies in the integrated use of field-based modal testing, advanced CFD scour modelling, and nonlinear damage assessment to realistically simulate scour-induced bridge failure. The results emphasise the importance of coupling hydraulic and structural analyses to improve bridge safety assessments under complex environmental hazards.

The proliferation of wireless sensor networks in industrial Internet of Things (IIoT) applications demands sustainable power solutions that eliminate battery replacement requirements while maintaining operational reliability in varying vibration environments. This paper presents a frequency-tunable magnetoelectric (ME) energy harvester that addresses the fundamental challenge of frequency mismatch between ambient industrial vibrations and harvester resonance through position-dependent magnetic force manipulation. The proposed system employs a Terfenol-D/PMNT/Terfenol-D sandwich transducer mounted on a cantilever beam within an adjustable magnetic circuit, enabling continuous frequency tuning through air gap modification for different magnetic field configurations. A comprehensive theoretical framework incorporating position-dependent magnetic forces was developed to predict the system behavior. Additionally, Multi-walled carbon nanotube (MWCNT)-enhanced epoxy bonding layers with 2 wt.% concentration were analyzed and demonstrated six-fold power improvement over conventional epoxy. The experimental validation shows frequency tuning from 40 Hz to 65 Hz through air gap adjustment of only 1 mm, corresponds to a 62.5% tuning range. Further experimental investigation proves a ten-fold power output improvement up to 2 mW by employing a four-magnet circuit design compared to the two-magnet configuration through specific adjustment of the air gap width.

Robust piglet nursing behavior monitoring through multi-modal fusion of computer vision and ambient floor vibration

The expansion of Indonesia’s national electricity transmission network has become a strategic priority for PT PLN to meet the increasing energy demands. One of the key projects is the construction of the 500 kV Bangil Substation, which necessitates a reliable and stable foundation design, strongly influenced by the geotechnical characteristics of the subsurface. This study aims to assess site-specific seismic vulnerability using the microtremor method combined with borehole data as a validation tool. Microtremor measurements provide insights into the site’s dynamic response through natural ambient vibrations, while borehole logs supply stratigraphic and mechanical information for cross-validation. The integration of both datasets enables a comprehensive evaluation of subsurface conditions, which is critical for earthquake-resilient foundation planning. The analysis focuses on key parameters including natural frequency (0.94–3.89 Hz), H/V amplitude (2.1–4.40), seismic vulnerability index (1.10–12.90 s 2 /cm), and average shear wave velocity (Vs 30 ) ranging (274 - 396 m/s). The results indicate that the majority of the study area falls into stable site classifications (SC and SD), suggesting favorable ground conditions for the substation infrastructure.

PremiseThe structural and dynamic properties of columnar cacti are key inputs for stability analyses; however, no previous studies have been able to resolve these properties from full‐scale tests in situ.MethodsI present an approach using non‐destructive ambient vibration data to measure the resonance properties (modal frequencies and mode shapes) of single‐stem saguaro cacti and resolve key biomechanical properties. I tested the approach on 11 spears in the Tucson, Arizona region, United States.ResultsSaguaro fundamental frequencies ranged between 0.55 and 3.7 Hz with damping ratios of 1.5–2.1%. Additional higher‐order modes were identified below 10 Hz. Fundamental frequencies scaled linearly with the ratio of stem diameter to height‐squared, but deviated from analytical theory due to an observed increase in Young's modulus for taller plants. Calculated ratios between second‐ and first‐order bending frequencies also deviated from beam theory, indicating that stiffness decreases vertically for a given stem, especially for taller spears. These deviations both likely arise from the morphology of internal wooden ribs, which provide the main flexural rigidity. Numerical modeling at one site confirmed the cantilever approximation and height‐dependent stiffness, revealing an empirically derived Young's modulus that decreased exponentially from 107 Pa at the top of the stem to 108 Pa at its base. Twelve days of monitoring at another site showed that frequencies drift with diurnal cycles, suggesting softening of the outer tissue as temperatures warm during the day.ConclusionsThis non‐destructive approach for structural assessment provides valuable data for biomechanical characterization and stability and ecological analyses.

Abstract Piezoelectric energy harvesting is a promising approach for powering nano- to microwatt-scale electronic devices using ambient vibrations. While most conventional energy harvester designs consider uni-directional excitation, real-world environments often involve multi-directional excitations. In this work, the dynamic and electrical response of a piezoelectric energy harvester (PEH) beam is investigated under bidirectional excitation. Experimental setup is developed such that transverse excitation to the energy harvester is provided by an electrodynamic shaker and axial excitation applied through a smart miniature shaker. A coupler is incorporated into the assembly to transmit axial motion from a miniature shaker to the energy harvester, which introduces an additional resonance mode that modifies the system’s response. The coupler is therefore included in the simulation models. The findings demonstrate that when bidirectional excitation is precisely tuned, can alter system dynamics and significantly improve the energy harvesting potential. It is observed that the voltage improvement compared to unidirectional excitation is 181.15% at the axial /transverse frequency ratio (A/T ratio)= 1.0 and 365.17% at the A/T ratio = 2.0. This work underscores the need to consider both structural interactions and multi-axis vibration inputs when designing and optimizing PEH systems for real-world applications.

Bridges and viaducts are critical infrastructure assets, yet their maintenance remains a challenge due to aging, increased traffic loads, and insufficient documentation. While Structural Health Monitoring (SHM) and Building Information Modelling (BIM) have independently advanced viaduct management, their integration is still underexplored. This study proposes a novel framework integrating SHM, BIM, and Artificial Neural Networks (ANNs) for comprehensive viaduct management. Field tests, including ambient vibration analysis, were conducted to capture the Rio Claro Viaduct’s dynamic behaviour. This information was used for the calibration of a finite element model. Simulated damage scenarios were created to train ANNs that use modal curvature damage indices for damage detection and severity assessment. The integration of these components into an enriched BIM model centralizes data for efficient visualization and decision-making. The framework demonstrated high accuracy, with ANNs achieving an average precision of 85% in damage classification and an R² of 0.96 in severity prediction. Validation using a decade-separated dataset confirmed the framework’s robustness, showing negligible structural deterioration over time. It is intended to provide an intuitive user interface so that asset managers can make data-driven decisions, overcoming the limitations of traditional visual inspections. This research attempts to bridge the gap between BIM and SHM applications by offering a replicable, efficient solution for infrastructure management.

Abstract This paper discusses the seismic performance of existing schools based on the analysis of a reinforced concrete school building located in Tijuana, Mexico. The building has an illustrative configuration and geometry of schools in the region. Ambient vibration tests and complementary studies were conducted to evaluate the actual behavior of the building, including concrete rebar scanning, carbonation detection, core sampling, and soil mechanical properties. The material characteristics and dynamic properties allowed the calibration of a detailed 3D model in OpenSees. Nonlinear static and dynamic analyses were conducted using the analytical model to obtain the response under 77 different ground motions. The reported damage was related to the actual capacities of schools based on a field inspection after the September 19, 2017 earthquake in Mexico. Vulnerability curves were then used to determine the probability of damage in structural and non-structural components and, therefore, the overall performance under the imposed scenarios.

This study quantifies shear and flexural stiffnesses and their changes over time to support structural health monitoring of in-service bridge superstructures across four girder types: reinforced concrete (RC) beams, prestressed concrete (PSC) girders, steel girders, and ultra-high-performance concrete (UHPC) sections, using field ambient vibration testing. A total of 20 bridges across Georgia and Iowa are assessed, involving over 100 hours of on-site data collection and traffic control strategies. Results show that field-measured natural frequencies differ from theoretical predictions by average of 30–35% for RC, and 20–25% for PSC, 15–25% for steel and 2% for UHPC, reflecting the complexity of in situ structural dynamics and challenges in estimating material properties. Site-placed RC beams showed stiffness reduction due to deterioration, whereas prefabricated PSC girders maintained consistent stiffness with predictable variations. UHPC sections exhibited the highest stiffness, reflecting superior performance. Steel girders matched theoretical values, but a span-level test revealed that deck damage can reduce frequencies undetected by localized measurements. Importantly, vibration-based measurements revealed reductions in structural stiffness that were not apparent through conventional visual inspection, particularly in RC beams. The research significance of this work lies in establishing a portfolio-based framework that enables cross-comparison of stiffness behavior across multiple girder types, providing a scalable and field-validated approach for system-level bridge health monitoring and serving as a quantitative metric to support bridge inspections and decision-making.

The bridge crossing the Gesso River is a multi-span masonry arch bridge built in the 19th century in Cuneo, Piedmont, Italy. Due to extended local degradation and damage, the bridge recently underwent a significant strengthening intervention. Ambient vibration tests (AVTs) were performed both before and after the strengthening to assess the effectiveness of the repairs. The paper presents the results of the dynamic investigations, identifying the modal characteristics of the masonry bridge through different techniques. The pre-intervention analysis revealed clear anomalies, including a sort of "frequency splitting" phenomenon and irregularities in the mode shapes, that were localized in the regions of maximum masonry decay. After the strengthening works, the identified modal parameters showed an increase of natural frequencies, along with the resolution of previously identified mode shape irregularities, indicating a clear improvement of the bridge structural condition. As a final remark, the presented results highlight the value of operational modal analysis (OMA) as a non-destructive tool for validating the effectiveness of rehabilitation measures.