Structural Health Monitoring

The goal of this work is to develop and investigate the properties of a new type of multifunctional composite which is based on multi-walled carbon nanotubes (MWCNT). The composite was prepared from a MWCNT "bucky paper" film which was sandwiched between two adhesive layers. Both two point probe and four point probe methods were used to test its mechanical strain sensing properties. The Young' modulus and shear modulus of MWCNT film composite were acquired by the nanoindentation test and direct shear test. A free vibration test was also performed to investigate its structural damping properties. Our research indicated that this new type of carbon nanotube based composite is potentially capable of functioning as a strain sensor and damping device simultaneously for structural vibration control.

The integration of Artificial Intelligence (AI) into Structural Health Monitoring (SHM) systems has emerged as a transformative solution for predictive failure analysis in pressure systems such as pressure vessels, pipelines, and industrial reactors. This study aims to systematically examine the role of AI-powered SHM frameworks in enhancing the reliability, safety, and operational efficiency of these high-risk infrastructures. A total of 63 peer-reviewed journal articles and conference papers published between 2000 and 2023 were reviewed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The selected studies were analyzed in terms of AI techniques applied, types of sensors integrated, fusion architectures, model performance metrics, validation methods, and real-world industrial applications. The review reveals that AI models-especially machine learning and deep learning algorithms-have significantly improved the early detection of faults, classification accuracy, and remaining useful life (RUL) prediction when supported by multi-sensor fusion frameworks. Models such as support vector machines (SVM), convolutional neural networks (CNN), and long short-term memory (LSTM) networks were frequently used and demonstrated strong performance, often achieving accuracy levels exceeding 90% across varied industrial scenarios. Furthermore, many of these systems have been successfully deployed in operational environments, leading to measurable improvements in maintenance scheduling, reduced downtime, and heightened safety. However, the review also identifies critical implementation challenges, including data scarcity, limited model interpretability, system integration constraints, and cybersecurity vulnerabilities. These barriers highlight the need for standardized practices, improved data governance, and interdisciplinary collaboration.

For a Chinook salmon restoration project in the lower Yuba River in California, we designed and deployed a wireless sensor network to monitor river temperatures at micro-habitat scales. The study required that temperatures be measured along a 3 km study reach, across the channel, and into off-channel areas. To capture diel and seasonal fluctuations, sensors were sampled quarter-hourly for the full duration of the six-month juvenile salmon winter residency. This sampling duration required that nodes minimize power-use. We adopted event-based software on MSP430 micro-controllers with 433 MHz radio and minimized the networking dutycycle. To address link failures, we included network storage. As the network lacked real-time clocks, data were timestamped at the destination. This, coupled with the storage, yielded timestamp inaccuracies, which we realigned using a novel algorithm. We collected over six months of temperature data from 35 sensors across seven nodes. Of the packets collected, we identified 21% as being incorrectly timestamped and were able to realign 41% of these incorrectly timestamped packets. We collected temperature data through major floods, and the network uploaded data until the flood destroyed the sensors. The network met an important need in ecological sampling with ultra-low power (multi-year battery life) and low-throughput. CCS Concepts: • General and reference → Empirical studies; • Hardware → Sensor applications and deployments; • Computer systems organization → Sensor networks; • Networks → Network protocol design; Sensor networks;

The use of load and structural performance measurement information is vital for efficient structural integrity management and for the cost of energy production with Offshore Wind Turbines (OWTs). OWTs are dynamically sensitive structures subject to an interaction with a control unit exposed to repeated cyclic wind and wave loads causing deterioration and fatigue. This study focuses on the quantification of the value of structural and environmental information on the integrity management of OWT structures, with the focus on fatigue of welded joints. By utilizing decision analysis, structural reliability methods, measurement data, as well as the cost-benefit models, a Value of Information (VoI) analysis can be performed to quantify the most beneficial measurement strategy. The VoI assessment is demonstrated for the integrity management of a butt welded joint of a monopile support structure for a 3 MW OWT with a hub height of approximately 71m. The conditional value of three-year measured oceanographic information and one-year strain monitoring information is quantified posteriori in conjunction with an inspection and repair planning. This paper provides insights on how much benefits can be achieved through structural and environmental information, with practical relevance on reliability-based maintenance of OWT structures.

Fibre Bragg Grating (FBG) sensors are increasingly being used on a wide range of civil, industrial and aerospace structures. The sensors are created inside optical fibres (usually standard telecommunication fibres); the optical fibres technology allows to install the sensors on structures working in harsh environments, since the materials are almost insensitive to corrosion, the monitoring system can be positioned far away from the sensors without sensible signal losses, and there is no risk of electric discharge. FBG sensors can be used to create strain gages, thermometers or accelerometers, depending on the coating on the grating, on the way the grating is fixed to the structure, and on the presence of an specifically designed interface that can act as a transducer. This paper describes a test of several different FBG sensors to monitor an high pressure pipe that feeds the hydraulic actuators of a 6 degrees-of-freedom shaking table at the ENEA Casaccia research centre. A bare FBG sensor and a copper coated FBG sensor have been glued on the pipe. A third sensor has been mounted on a special interface to amplify the vibrations; this last sensor can be placed on the steel pipe by a magnetic mounting system, that also allows the its removal. All the sensor are placed parallel to the axis of the pipe. The analysis of the data recorded when the shaking table is operated will allow to determine which kind of sensor is best suited for structural monitoring of high pressure pipelines.

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is wel...

Remote and real-time displacement measurements are crucial for a successful bridge health monitoring program. Researchers have attempted to monitor the deformation of bridges using remote sensing techniques such as an accelerometer when a static reference frame is not available. However, errors accumulate throughout the double-integration process, significantly reducing the reliability and accuracy of the displacement measurements. To obtain accurate reference-free bridge displacement measurements, this paper aims to develop a real-time computing algorithm based on hybrid sensor data fusion and implement the algorithm via smart sensing technology. By combining the accelerometer and strain gauge measurements in real time, the proposed algorithm can overcome the limitations of the existing methods (such as integration errors, sensor drifts, and environmental disturbances) and provide real-time pseud-static and dynamic displacement measurements of bridges under loads. A wireless sensor, SmartRock, containing multiple sensing units (i.e., triaxial accelerometer and strain gauges) and a Micro Controlling Unit (MCU) were utilized for remote data acquisition and signal processing. A remote sensing system (with SmartRocks, an antenna, an industrial computer, a Wi-Fi hotspot, etc.) was deployed, and a laboratory truss bridge experiment was conducted to demonstrate the implementation of the algorithm. The results show that the proposed algorithm can estimate a bridge displacement with sufficient accuracy, and the remote system is capable of the real-time monitoring of bridge deformations compared to using only one type of sensor. This research represents a significant advancement in the field of bridge displacement monitoring, offering a reliable and reference-free approach for remote and real-time measurements.

This research studies multi-physics simulation of a frequency doubling antenna sensor for wireless strain measurement. The frequency doubling technology allows easy distinguishing of backscattered passive sensor signal (at the doubled frequency 2ƒ) from environmental reflection (at original reader interrogation frequency ƒ). Upon bonding to a base structure, because strain/deformation causes resonance frequency change of the antenna sensor, the passive wireless antenna sensor can be used to measure strain in the underlying base structure. To accurately model the mechanical and electromagnetic behaviors of the frequency doubling antenna sensor, a multiphysics coupled simulation approach is proposed. For simulating both the matching network performance and the antenna behavior under strain/deformation, two commercial software packages, COMSOL and ADS, are combined to leverage the strength of each package.

An radiofrequency identification (RFID)-based folded patch antenna has been developed as a novel passive wireless sensor to measure surface strain and crack, for the structural health monitoring of metallic structures. Up to 2.5 m of read range is achieved by a proof-of-concept prototype patch antenna sensor with a strain sensitivity around -760 Hz/με, which is equivalent to a normalized strain sensitivity of -0.74 ppm/με. In this paper, we propose to consider the change of the substrate dielectric constant due to strain when modeling the antenna sensor. An enhanced strain sensitivity model is introduced for more accurately estimating the strain sensing performance of the hereby introduced smart skin antenna sensor. Laboratory experiments are carried out to quantify the dielectric constant change under strain. The measurement results are incorporated into a mechanics-electromagnetics coupled simulation model. Accuracy of the multi-physics coupled simulation is improved by integrating dielectric constant change in the model.

In this paper, a new approach using mobile sensor networks is proposed for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper describes the design concept of a flexure-based mechatronic (flexonic) mobile sensing node and its application in structural health monitoring. The flexonic mobile sensing node is capable of maneuvering on structures built with ferromagnetic materials, as well as attaching/detaching an accelerometer onto/from a steel structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments, where two flexonic mobile sensing nodes are adopted for maneuvering on a steel portal frame. Transmissibility function analysis is then conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes of using mobile sensors for future structural health monitoring.

In a modern metropolis, metro rail systems have become a dominant mode for mass transportation. The structural health of a metro tunnel is closely related to public safety. Many vibration-based techniques for detecting and locating structural damage have been developed in the past several decades. However, most damage detection techniques and validation tests are focused on bridge and building structures; very few studies have been reported on tunnel structures. Among these techniques, transmissibility function and cross correlation analysis are two well-known diagnostic approaches. The former operates in frequency domain and the latter in time domain. Both approaches can be applied to detect and locate damage through acceleration data obtained from sensor arrays. Furthermore, the two approaches can directly utilize structural response data without requiring excitation measurement, which offers advantages in field testing on a large structure. In this research, a numerical finite element model of a metro tunnel is built and different types of structural defects are introduced at multiple locations of the tunnel. Transmissibility function and cross correlation analysis are applied to perform structural damage detection and localization, based on simulated structural vibration data. Numerical results demonstrate that the introduced defects can be successfully identified and located. The sensitivity and feasibility of the two approaches have been verified when sufficient distribution of measurement locations is available. Damage detection results of the two different approaches are compared and discussed.

Le for sharing their expertise and providing assistance during my graduate study. I would also like to thank Andy Udell for his help with fabrication of experimental setups. Most importantly, I would like to express my heartfelt gratitude to my parents and my wife. I will always be indebted to you for your love, encouragement and unconditional support.

An radiofrequency identification (RFID)-based folded patch antenna has been developed as a novel passive wireless sensor to measure surface strain and crack, for the structural health monitoring of metallic structures. Up to 2.5 m of read range is achieved by a proof-of-concept prototype patch antenna sensor with a strain sensitivity around -760 Hz/με, which is equivalent to a normalized strain sensitivity of -0.74 ppm/με. In this paper, we propose to consider the change of the substrate dielectric constant due to strain when modeling the antenna sensor. An enhanced strain sensitivity model is introduced for more accurately estimating the strain sensing performance of the hereby introduced smart skin antenna sensor. Laboratory experiments are carried out to quantify the dielectric constant change under strain. The measurement results are incorporated into a mechanics-electromagnetics coupled simulation model. Accuracy of the multi-physics coupled simulation is improved by integrating dielectric constant change in the model.

In a modern metropolis, metro rail systems have become a dominant mode for mass transportation. The structural health of a metro tunnel is closely related to public safety. Many vibration-based techniques for detecting and locating structural damage have been developed in the past several decades. However, most damage detection techniques and validation tests are focused on bridge and building structures; very few studies have been reported on tunnel structures. Among these techniques, transmissibility function and cross correlation analysis are two well-known diagnostic approaches. The former operates in frequency domain and the latter in time domain. Both approaches can be applied to detect and locate damage through acceleration data obtained from sensor arrays. Furthermore, the two approaches can directly utilize structural response data without requiring excitation measurement, which offers advantages in field testing on a large structure. In this research, a numerical finite element model of a metro tunnel is built and different types of structural defects are introduced at multiple locations of the tunnel. Transmissibility function and cross correlation analysis are applied to perform structural damage detection and localization, based on simulated structural vibration data. Numerical results demonstrate that the introduced defects can be successfully identified and located. The sensitivity and feasibility of the two approaches have been verified when sufficient distribution of measurement locations is available. Damage detection results of the two different approaches are compared and discussed.

In this paper, a new approach using mobile sensor networks is proposed for structural health monitoring. Compared with static sensors, mobile sensor networks offer flexible system architectures with adaptive spatial resolutions. The paper describes the design concept of a flexure-based mechatronic (flexonic) mobile sensing node and its application in structural health monitoring. The flexonic mobile sensing node is capable of maneuvering on structures built with ferromagnetic materials, as well as attaching/detaching an accelerometer onto/from a steel structural surface. The performance of the prototype mobile sensor network has been validated through laboratory experiments, where two flexonic mobile sensing nodes are adopted for maneuvering on a steel portal frame. Transmissibility function analysis is then conducted to identify structural damage using data collected by the mobile sensing nodes. This preliminary work is expected to spawn transformative changes of using mobile sensors for future structural health monitoring.

Resumo O Edifício Copan, projetado por Oscar Niemeyer e conhecido por sua grandiosidade e forma sinuosa, foi construído entre 1952 e 1972, um período marcado por avanços significativos nas tecnologias do concreto armado e no controle tecnológico da obra. Devido ao desenvolvimento de recalques de longo prazo, as fundações vêm sendo monitoradas há 68 anos. Como as medições neste caso histórico foram realizadas utilizando métodos não digitais, isso adiciona elementos interessantes à discussão sobre a transição para a era digital na construção, especialmente no que diz respeito às lições aprendidas sobre o desempenho estrutural e à importância de preservar os acervos documentais ao longo da existência da edificação. Palavras-chave: Recalques de longo prazo. Monitoramento estrutural. Edifício Copan.

Structural health monitoring (SHM) refers to the process of
evaluating the condition of structures to detect damage, ensure
safety, and extend service life. It involves the use of various
technologies, such as nondestructive evaluation (NDE) methods,
sensors, data analytics, and advanced imaging techniques, to
monitor, assess, and analyze the performance of structures under
operational or environmental loading. Advances in drone
technology and photogrammetry have revolutionized SHM by
offering detailed, efficient, and non-invasive solutions for assessing
structural conditions. This article explores the application of drone
imagery and photogrammetry in SHM, focusing on their
methodologies, advantages, and applications using real-world
case studies.

A popular method to conduct structural health monitoring is the spatio-temporal study of vibration signatures, where vibration properties are extracted from collected vibration responses. In this article, a novel methodology for extracting and analyzing distributed acceleration data for condition assessment of bridge girders is proposed. Three different techniques are fused, enabling robust damage detection, localization, and quantification. First, stochastic subspace identification is used as an output-only method to extract modal properties of the monitored structure. Second, a reduced-order stiffness matrix is reconstructed from the stochastic subspace identification data using the system equivalent reduction expansion process. Third, a particle swarm optimization algorithm is used to update a finite element model of the bridge girder to match the extracted reduced-order stiffness matrix and modal properties. The proposed approach is first verified through numerically simulated d...

Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures' stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.

The seismic performance of a two storey post-tensioned Laminated Veneer Lumber (LVL) building during the aftershock sequence following the 6.3 M W 22 nd February 2011 Canterbury earthquake is presented. The building is made from a new form of timber construction combining the use of concrete PRESSS technology and wood products using post-tensioning elements with large timber members. Originally a test specimen, the building was demounted and reassembled as the offices of the STIC research consortium on the campus of UoC. Close to the beginning of construction the 7.1 M W 2010 Darfield earthquake occurred in the Canterbury area however construction went ahead as planned with the building being almost complete when the more devastating 2011 February event occurred. Innovative techniques have been used to evaluate the seismic response of the building and this paper presents a general overview of building performance and provides insight into the behaviour of a post-tensioned structure.

The interaction between a semi-infinite underground pipeline and the surrounding soil during longitudinal seismic wave propagation is examined in the article. The wave travels through the soil with its front perpendicular to the pipeline's axis, and the nonlinear laws of interaction (friction) on the surface of their contact, including the Amonton-Coulomb law, are used to solve related wave problems for the pipeline and soil. The method of characteristics and the finite difference method are sequentially used to solve these problems numerically. The implementation of the law of interaction (friction) processes is shown, depending on the parameters of the wave in soil and the mechanical characteristics of soil. It was determined that a wave in soil that involves the pipeline generates a powerful wave in the pipeline. The amplitude of this wave is many times greater than the amplitude of the wave in soil, and it propagates through the pipeline without attenuation. The dependences of the amplitude of this wave on the parameters of the law of friction, waves in soil, and the mechanical characteristics of soil are determined.

Finite element model reduction methods have been widely used to reduce the computational costs of structural analysis and design. Using model reduction methods, global (original) models can be approximated by reduced models with much smaller matrix size. Although various model reduction methods such as dynamic condensation and component mode synthesis (CMS) have been proposed over the last several decades, many challenging issues still must still be addressed to improve the solution accuracy and computational efficiency of reduced models. The work in this thesis focuses on the development of enhanced model reduction, general mode selection, and accurate error estimation methods to overcome the known disadvantages and limitations of existing model reduction methods. In this work, we first develop a new component mode synthesis enhancing the Craig-Bampton (CB) method, the most popular model reduction method. To develop the enhanced CB method, the original transformation matrix in the ...

Carbon fiber-reinforced polymer composite is used in various industries such as aerospace, automobile, and civil engineering. During the manufacturing stage and end-user stage, carbon fiber composite material is subjected to different kinds of damage, such as delamination, de-bonding, and fiber breakages. Those damages may lead to destroying the application with a life-threatening catastrophe. To identify these kinds of damages, several non-destructive testing (NDT) techniques are used, such as visual, ultrasonic, and optical fiber sensing. However, when considering the initiation and propagation of the damage, microlevel and invisible cracks are crucial. This study used plain weave carbon fiber fabric with an appropriate resin-hardener mixture to make carbon fiber-reinforced composite sheets by hand layer-up process. Subsequently, the samples were subjected to drop weight impact tests with 0.6 j, 1.2 j, 3.0 j, 6.0 j, and hammer impact tests respectively. By using an Ectane-2 eddy current inspection equipment, both sides of the carbon fiber samples were scanned before and after the impact damage. The defect's location could be seen on the c-scan plane, while the crack propagation could be seen on the impedance plane of the Ectane-2-magnify software screen. Variations in voltage showed an irregular pattern on the impedance plane because of the damage to the carbon fiber strips that affected the electrical conductivity of the composite. The eddy current inspection method is capable of identifying the damage location and propagation of plain weave carbon fiber-reinforced polymer composites. In the future, fiber weaves such as twill and unidirectional need to be investigated.

ΠΕΡΙΛΗΨΗ_Σε χρονική απόσταση σχεδόν 40 χρόνων από την ολοκλήρωση των επεμβάσεων ενίσχυσης στον φέροντα οργανισμό της Ροτόντας μετά τον σεισμό της 20ης Ιουνίου 1978, δρομολογήθηκε, εγκρίθηκε και υλοποιήθηκε συστηματική σειρά (επαν)ελέγχων, ερευνών τεκμηρίωσης και τοπικών επεμβάσεων σε κρίσιμα σημεία του φέροντα οργανισμού του μνημείου, στο πλαίσιο α) των μελετών ωρίμανσης «Ανάδειξη 8 (οκτώ) μνημείων UNESCO στην πόλη της Θεσσαλονίκης», 2021-23, β) του ερευνητικού «Καινοτόμος απεικόνιση υπεδάφους αρχαιολογικών χώρων και εσωτερικού δομικών στοιχείων μνημείων στις 3 και 4 διαστάσεις» (ΕΚΑΤΥ), 2020-23, και γ) του έργου του Ταμείου Ανάκαμψης και Ανθεκτικότητας «Θεσσαλονίκη: ανάδειξη του μνημειακού συνόλου της Ροτόντας (μνημείο UNESCO). Προστασία κελύφους και διαμόρφωση περιβάλλοντος χώρου», 2022-24. Η ολοκληρωμένη αυτή προσέγγιση παρέχει τα αναγκαία στοιχεία τεκμηρίωσης προς την κατεύθυνση του συνεχούς ελέγχου της συμπεριφοράς του φέροντα οργανισμού και της αποτελεσματικής προστασίας του μνημείου σε βάθος χρόνου (υπό δημοσίευση, ISSN : 1106-5311).
ABSTRACT_Almost 40 years after the accomplishment of strengthening interventions on the structural system of the Rotunda following the earthquake of June 20th 1978, a systematic series of (re)assessments, documentation research, and local interventions at critical points of the bearing structure of the monument were organized, approved, and implemented in the frame of a) the maturation studies “Enhancement of 8 (eight) UNESCO monuments in Thessaloniki City”, 2021-23, b) the research project: “Innovative imaging of the subsurface of archaeological sites and the interior of structural elements of monuments in 3 and 4 Dimensions” (EKATY), 2020-23, and c) the Recovery and Resilience Facility (RRF) project “Thessaloniki: Enhancement of Rotunda’s Monumental Complex (UNESCO Monument). Protection of the Building Shell and Landscaping of the Environmental Archaeological Site”, 2022-24. This integrated approach provides the necessary documentation for the ongoing structural health monitoring and the effective protection of the monument in the course of time (under publication, ISSN : 1106-5311).

Reconstruction of inhomogeneous dielectric objects from microwave scattering by means of quantitative microwave tomography is a nonlinear, ill-posed inverse problem. In this paper, we employ the Huber function as a robust regularization approach for this challenging problem. The resulting reconstructions both in 2D and 3D from sparse data points for piecewise constant objects are encouraging. The reconstructions of more complex permittivity profiles from breast phantom data indicate potential for use in biomedical imaging.

The versatility and easy installation of Distributed Optical Fiber Sensors (DOFS) compared with traditional monitoring systems is an important characteristic to consider when facing the Structural Health Monitoring (SHM) of real world structures. The DOFS used in this study provide continuous (in space) strain data along the optical fiber with high spatial resolution. The main issues and results of two different existing structures monitored with DOFS, are described in this paper. The main SHM results of the rehabilitation of an historical building used as hospital and the enlargement of a prestressed concrete bridge are presented. The results are obtained using a novel DOFS based on an Optical Backscattered Reflectometry (OBR) technique. The application of the optical fiber monitoring system to two different materials (masonry and concrete) provides also important insights on the great possibilities of this technique when monitoring existing structures. In fact, the influence in strain transfer between the DOFS and the bonding surface is one of the principal effects that should be considered in the application of the OBR technique to real structures. Also, and because structural surfaces generally present considerable roughness, the procedure to attach the optical fiber to the two monitored structures is described.

Wet wipe machines are machines for high capacity production at high speeds. Even the short downtimes of the machines in the production area lead to huge losses for manufacturers. However, in these machines; unexpected breakdowns such as belt breakage, bearing damage, sensor motor failures, pneumatic air leaks are frequently encountered. In order to prevent unwanted stoppages, a sensor, actuator and plc based application has been implemented to prevent failure parameters and to detect faultlessly by monitoring the operation parameters. As a result of the studies carried out, our wet wipe machines that we produce have been adapted to the industry 4.0 concept.

As well known, the damping or energy dissipation capacity of bridge columns is very important because it is directly related to the design spectrum and affects the seismic performance of whole bridge systems. For this reason, several investigations evaluating the energy dissipation capacity of segmental columns, which has a small energy dissipation capacity itself, have been conducted by adopting various material types of energy dissipating (ED) bars. This paper investigates the damping capacity of post-tensioned (PT) segmental rocking columns connected with large diameter (36.5 mm) martensitic SMA bars at their base as ED bars. Two aspect ratios for the columns are considered: 7.5 for slender and 5.0 for medium size. Moment-curvature relationships and complementary computational tools are adopted to model the behavior of the columns. A bilinear model for the PT tendon and a modified four-spring model for the martensitic SMA bar are used. From the quasi-static cyclic analysis, the m...

she worked in architectural practices in London, Israel and Sri Lanka, predominantly focussing on healthcare and housing projects, before co-founding and jointly directing the award winning practice -Architects In Residence (A.I.R.) At A.I.R. she set up diverse cross industry teams ranging from ship builders to fashion designers to develop alternative methods of fabrication. In 2007 A.I.R.s prefabricated solid panel timber housing won the Off-site category at the Wood Awards, the first of its kind in the UK. Following the earthquake in Haiti, Kate worked with Development Workshop France, as consultants to Save the Children USA, designing transitional schools that incorporated safer construction methods. In 2010 she moved her practice knowledge into research and education where she is exploring cultural landscapes, rural industries and, through their growth and adaptation, a new rural architectural vernacular. Kirsty McDougall is Senior Tutor in Woven Textiles at the Royal College of Art. She is the co-founder of menswear textile brand Dashing Tweeds and director of Kirsty McDougall Woven Textile Design. Her work has been exhibited internationally in museums, on catwalks and in many books and publications. Kirsty won a Jerwood Prize in 2010 and Dashing Tweeds won a Scottish Fashion Award for Textiles in 2012.Kirsty has extensive experience in teaching and mentoring at a wide range of institutions. Her research interests include exploring the combinations of heritage and technology in wool-based textiles; new materials and intelligent textile development; sustainability in UK based fashion and textile design and manufacture and developing new modes of working for the textile designer/ manufacturer.

This paper provides a general review of the NDT techniques, including what principle these methods work, their advantages, disadvantages, and limitations. NDT techniques are used worldwide in various industries like construction, oil and gas, and aerospace to evaluate the conditions of the structure and materials used in that structure without causing any damage to the structure. The methods covered in this paper are generally used in the construction industry, including tests for surface hardness and strength like rebound hammer, ultrasonic pulse velocity, core test, CAPO test, and some tests for corrosion assessment like halfcell potentiometer and carbonation test. A review of this paper aims to provide a comprehensive overview of the various NDT methods used in the construction industry and their role in ensuring the quality, safety, and reliability of structures and materials.

Structural Health Monitoring (SHM) is a crucial scope of work in civil engineering specifically on monitoring the in-service and ageing coastal bridge deck concrete structure serviceability and limit state status performance. One of the possible natural process that pose detrimental effects to such structure performance monitoring is the steel rebar pitting corrosion problem. Progressive pitting corrosion process on the certain steel rebar area in low quality of concrete cover due to chloride ingression will cause local premature damage the steel rebar which obviously affect the serviceability performance of the structural element, i.e. displacement. However, the available displacement monitoring methods become an issue when it comes to engineering practicality and costs considerations. Therefore, the purpose of this study is to monitor and analyze the vertical displacement of an undamaged and damage reinforced concrete beam using the digital signal processing technology, Digital Im...

Transient impulses caused by local faults are critical informative indicators for rolling element bearing fault diagnosis. The methods for accurately extracting transient impulses while suppressing strong background noise and interference components have received extensive studies. In this paper, a novel fault diagnosis scheme based on optimized wavelet packet denoising (WPD) and modulation signal bispectrum (MSB) is proposed, which takes advantage of the transient impulse enhancement of WPD and the demodulation ability of MSB to diagnose bearing faults more accurately. Firstly, the measured signals are decomposed into a series of time-frequency subspaces using wavelet packet transform. An optimal threshold value is selected based on the proposed threshold criterion by considering unbiased autocorrelation of envelope and Gini index (GI) of the transient impulses. Subsequently, the subspaces are denoised by the WPD with the optimized threshold value, and the master subspaces that containing the fault related transient impulses are selected based on the GI indicator. Finally, the MSB is utilized to further purify the signal and extract the modulation components contained in the transient impulses, and the suboptimal MSB slices are selected based on the characteristic frequency intensity coefficient (CFIC). The MSB detector is then obtained by averaging the suboptimal MSB slices to determine the type of the bearing faults. The proposed WPD-MSB is validated based on the simulation and experimental studies. Compared with the variational mode decomposition and Teager energy operator (VMD-TEO), fast kurtogram (FK) as well as conventional MSB, the proposed WPD-MSB method has superior performance in extracting the fault feature of the incipient defects on different bearing components.

This work presents the effect of the high curvature to thickness ratio on the characteristics of Lamb Waves propagating over the skins of composite structures. It is accessed how the curvature on composite skins affects the group velocity of the symmetrical (S0) and asymmetrical (A0) wave modes. It is also accessed the gradient of curvature effect, when the wave propagates from a flat to a curved part on the skin. The results are intended to be used for the improvement of structural health monitoring of wings and wind turbine blades. This is accomplished through dynamic explicit linear finite element method simulations of plates with flat and curved parts made of Eglass-epoxy bidirectional laminate. As the skin structures are often designed to withstand torsional loads, the fibers are aligned with 45 degrees from the leading edge (curved region) throughout the analysis. Several skins with different curvature to thickness ratios are generated and simulated. Results and trends are presented and can be used to improve the algorithms for damage detection on those structures. It is shown that the group velocity of the incoming waves change considerably with the presence of curvature, for both main modes of vibration.

Fiber reinforced polymers (FRP) have become more popular construction materials in the last decade due to the reduction of material costs. The installation and performance evaluation of the first FRP-wrapped balsa wood bridge in Louisiana is described in this document. A comprehensive instrumentation and loading test scheme is discussed and details are illustrated. The selected bridge structure in this demonstration project will potentially provide a new approach to enhancing the transportation infrastructure in Louisiana. The test bridge is the Pierre Part Bridge located on route LA 70 in Assumption Parish, LADOTD District 61. The instrumentation consisted of regular strain gauges, fiber optic strain and temperature sensors, accelerometers, and acoustic emission sensors. The measured results from each of the gauges are summarized, and comparisons are made between the finite element models of the bridge structure and the field test results. Before placing the instrumentation on the field bridge, extensive laboratory explorations and numerical analysis were conducted and the research results have been documented in this report. Several years after the bridge had been opened to traffic, a delamination in one of the panels was observed. The deck was removed and replaced with a new deck grating. After a visual inspection and discussion with the fabricator, it turned out that a shifting on the top FRP surface in one of the panels occurred while the panel was being infused with epoxy. There is a good reason that less epoxy was infused after the rearranging of the FRP stop surface was carried out, and this could have led to the delamination problem.

Vibration sensing systems play a critical role in ensuring the safety and longevity of modern structures, contributing to the advancement of intelligent and sustainable infrastructure. This research focuses on the design and implementation of a vibration-detecting system utilising accelerometers and velocity transducers for continuous monitoring and structural health assessment. The study emphasizes the importance of structural health monitoring for enhancing safety, reducing maintenance costs, extending the lifespan of vital structures, and increasing resistance to harsh situations. The developed vibration sensing system strategically deploys accelerometers and velocity transducers to convert mechanical vibrations into electrical impulses, enabling real-time monitoring and comprehensive structural health analysis. Integrating this system into smart infrastructure projects enables data-driven decisionmaking, resource-optimised performance, and improved energy efficiency. These sensors improve the monitoring of structural safety evaluations during events such as earthquakes, severe winds, and imbalanced operations of equipment, thereby protecting lives and property. In addition, constant monitoring facilitates the early detection of damages or irregularities, allowing for swift responses and efficient resource allocation for preventive maintenance. This research underscores the pivotal role of vibrationdetecting systems in advancing intelligent and sustainable infrastructure, ultimately leading to safer and more durable buildings and environments. These technologies contribute to the creation of robust and environmentally friendly structures by providing realtime data insights to engineers that will in turn guide the policymakers in ensuring a sustainable future for the built environment.

Obelisks presented an important element in the architecture of ancient Egypt. This research is concerned with the re-erection of an obelisk that belongs to the famous Pharoah Ramses II. It was found broken and was transported to the Grand Egyptian Museum for restoration and display. An observation of Ramses II Cartouche at the bottom side of the obelisk base inspired the authorities to provide an innovative architectural design to display the obelisk elevated. The supporting structure was designed to allow the visitors to walk underneath the obelisk and observe Ramses II's signature. The idea of elevating the obelisk presented several challenges including evaluating the obelisk's current condition, restoration and fixation methodology, structural stability, and uncertainties of material characteristics, amongst others. To control the obelisk deformations under lateral loading, state-of-the-art base isolators were introduced. For the task to be achieved, a multidisciplinary t...

Earthquakes induce dynamic stresses in structures, and past seismic events have demonstrated that existing heritage buildings are highly vulnerable. This vulnerability applies to both reinforced-concrete and masonry buildings, which are concentrated in historic centres throughout Italy. Significant variations in construction account for the inadequacy of existing structures to withstand seismic actions, such as the materials used and the construction details, which can be neglected in building practices. This work focuses on the analysis of heritage buildings through an inventory using the Caratterizzazione TIpologica Strutturale (CARTIS) form developed by the Seismic Engineering University Laboratories Network in conjunction with the Civil Protection Department. On knowing a building framework, structural health monitoring (SHM) systems can be applied on the town compartments (TCs) that are prone to the highest vulnerabilities. A priority criticalities scale can be devised starting from the building inventory by identifying the TCs through the CARTIS-based data. This approach can be used to determine a safety threshold obtained via structural parametrical analysis using commercial software (VEMnl) with different building typologies. The next stage consists of the implementation of appropriate SHM to provide important information regarding the structural integrity of the buildings. The proposed methodology is outlined in this paper with reference to the suggested SHM system.

Structural health monitoring (SHM) is responsible for identifying techniques and for prototyping systems performing a state diagnosis of structures. Its aim is to prevent sudden civil infrastructure failure as a result of several invisible sources of damage. Since structural damage is often caused by ground phenomena involving circumscribed geographical areas, it is useful to extend SHM systems to allow for the exchange of information among nearby buildings and then to increase the timeliness of the alerts. To this end, in this article, an SHM based on the IoT paradigm is proposed (SHM-IoT). SHM-IoT carries out both localised monitoring on a single building, and it uses information collected by several sensors correlated in time, aiming to identify potentially dangerous damage. It also performs a wider monitoring on a group of buildings in order to alert a larger number of people. SHM-IoT also sends a remote notification, which is finalised in order to alert the authorities and rescuers about the status of each monitored building. In this context, synchronisation problems arise because the information collected by each sensor of the SHM-IoT needs to be correlated in time in order to be used for damage evaluation and alert generation. In this paper, the hardware and software architectures of the proposed SHM-IoT are presented together with the synchronisation requirements and the methods of satisfying them. Experiments are undertaken to validate the SHM-IoT in real scenarios.

Structural health monitoring (SHM) is responsible for identifying techniques and for prototyping systems performing a state diagnosis of structures. Its aim is to prevent sudden civil infrastructure failure as a result of several invisible sources of damage. Since structural damage is often caused by ground phenomena involving circumscribed geographical areas, it is useful to extend SHM systems to allow for the exchange of information among nearby buildings and then to increase the timeliness of the alerts. To this end, in this article, an SHM based on the IoT paradigm is proposed (SHM-IoT). SHM-IoT carries out both localised monitoring on a single building, and it uses information collected by several sensors correlated in time, aiming to identify potentially dangerous damage. It also performs a wider monitoring on a group of buildings in order to alert a larger number of people. SHM-IoT also sends a remote notification, which is finalised in order to alert the authorities and resc...

Structural health monitoring (SHM) is responsible for identifying techniques and for prototyping systems performing a state diagnosis of structures. Its aim is to prevent sudden civil infrastructure failure as a result of several invisible sources of damage. Since structural damage is often caused by ground phenomena involving circumscribed geographical areas, it is useful to extend SHM systems to allow for the exchange of information among nearby buildings and then to increase the timeliness of the alerts. To this end, in this article, an SHM based on the IoT paradigm is proposed (SHM-IoT). SHM-IoT carries out both localised monitoring on a single building, and it uses information collected by several sensors correlated in time, aiming to identify potentially dangerous damage. It also performs a wider monitoring on a group of buildings in order to alert a larger number of people. SHM-IoT also sends a remote notification, which is finalised in order to alert the authorities and resc...

Three-stage automatic operational modal analysis using mathematical mode elimination by density-based clustering method
Document Type : Article

Authors

A. Salar Mehrabad 1  A. Shooshtari  2
1 PhD Student, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Iran

2 Associate Professor, Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

10.24200/j30.2024.63122.3258
Abstract

Estimating a structure's modal parameters is essential for various applications, including health monitoring, damage detection, design verification, and model updating. Modal parameters are a structure's natural frequencies, mode shapes, and damping ratios. They can be used to understand the structure's dynamic behavior and to identify any changes that may occur over time. Operational modal analysis (OMA) is a technique that uses the response of a structure to environmental loads to estimate modal parameters. OMA is a non-destructive testing method that can be used on structures in their operating environment. This makes it a valuable tool for health monitoring and damage detection of buildings, bridges, wind turbines, and stadiums. One of the challenges of OMA is that its methods rely on the user's judgment to separate physical modes from spurious modes and to distinguish between real modes of the structure. Spurious modes are not caused by the actual structure but by noise or other environmental factors. Real modes are caused by the structure itself. In recent years, there has been extensive research on automating OMA methods for modal parameter estimation. Most of these studies have attempted to minimize the need for user intervention in modal parameter calculation by using machine learning techniques. Machine learning techniques can be used to identify physical modes automatically and to distinguish between real modes of the structure. This research uses the Stochastic Subspace Identification (SSI) method for OMA. The DBSCAN clustering method is used to separate physical modes from spurious modes. Finally, the hierarchical clustering method is used to distinguish between real modes of the structure. The proposed algorithm was implemented on a 6-degree-of-freedom structure and a real bridge. The results show that the proposed method has a higher power to separate physical modes from spurious modes than previous methods.
Keywords

Automatic operational modal analysis  machine learning  clustering  structural health monitor

Two techniques of data pre-processing for neural networks are considered in this paper: (i) data compression with the application of the principal component analysis method, and (ii) various forms of data scaling. The novelty of this paper is associated with compressed input data scaling by the rotation (by the "stretching") in neural network. This approach can be treated as the new proposition for data preprocessing techniques. The influence of various types of input data pre-processing on the accuracy of neural network results is discussed by using numerical examples for the cases of natural frequency predictions of horizontal vibrations of load-bearing walls. It is concluded that a significant reduction in the neural network prediction errors is possible by conducting the appropriate input data transformation.

Utilizando técnicas de mapeamento cognitivo, este estudo explora as concepções de network para o desenvolvimento da carreira de empresários incubados. Mais precisamente, buscou-se mapear os significados compartilhados pelos empresários incubados com relação às redes informais de apoio à carreira empreendedora, explorando as características e o modelo conceitual que embasa tais redes. Este estudo usa uma abordagem qualitativa de uso recente nos estudos organizacionais que toma como base a representação social. Os dados foram coletados por meio de entrevistas que incentivavam a livre evocação de ideias pelos participantes. Cinquenta e três empresários de sete incubadoras participaram da pesquisa. Os significados compartilhados pelos empresários indicam algumas das funções da mentoria como sendo fundamentais para o desenvolvimento da carreira. Os resultados fortalecem a interpretação de que há a emergência de um modelo de mentoria informal no ambiente das incubadoras, revelado através do discurso dominante sobre o papel da network para o desenvolvimento da carreira. O estudo traz contribuições para as áreas da carreira empreendedora e das redes informais de mentoria, mostrando que as concepções dos empresários sobre redes agregam novas categorias às funções da mentoria no contexto da carreira empreendedora. Cognição Empreendedora, Carreira Empreendedora, Network, Mentoria, Mapas Cognitivos. Using cognitive mapping techniques, this study explores networking concepts for the incubated businessman's career development. More precisely, we attempted to present the meanings shared by incubated businessmen concerning the informal networks that support the entrepreneurial career, exploring the characteristics and underlying conceptual model of these networks. The study employs a qualitative approach, recently used in organizational studies, which is based on social representation. Data were collected through interviews using a free evocation technique. Fifty-three entrepreneurs were studied, in seven incubators in the city of Recife. The participants' shared meanings indicate some of the mentoring functions as being fundamental to career development. The results support the interpretation of an emerging informal mentoring model in the incubators environment revealed by the dominant discourse on the role of networking in career development. The study brings theoretical contributions to the entrepreneurial career and informal mentoring networks areas, by showing that entrepreneurs' concepts of networks combine old and new categories of the mentoring function in the context of the entrepreneurial career.