Structural Health Monitoring

Due to the substantial need to continuously ensure safe excavations and sustainable operation of deep engineering structures, structural health monitoring based on remote sensing techniques has become a prominent research topic in this field. Indeed, throughout their lifetime, deep tunnels are usually exposed to many complex situations which inevitably affect their structural health. Therefore, appropriate and effective monitoring systems are required to provide real-time information that can be used as a true basis for efficient and timely decision-making. Since sensors are at the heart of any monitoring system, their selection and conception for deep rock tunnels necessitates special attention. This work identifies and describes relevant structural health problems of deep rock tunnels and the applicability of sensors employed in monitoring systems, based on in-depth searches performed on pertinent research. The outcomes and challenges of monitoring are discussed as well. Results show that over time, deep rock tunnels suffer several typical structural diseases namely degradation of the excavation damaged areas, corrosion of rock bolts and cable bolts, cracks, fractures and strains in secondary lining, groundwater leaks in secondary lining, convergence deformation and damage provoked by the triggering of fires. Various types of remote sensors are deployed to monitor such diseases. For deep rock tunnels, it is suggested to adopt comprehensive monitoring systems with adaptive and robust sensors for their reliable and long-lasting performance.

In the Global scenario of communication, Internet of Things provides the better way to interact with. Healthcare system using IoT is the combination of advance conceptual form of multidisciplinary engineering and medical field which benefit the innovations towards health-care systems. At present scenario, IoT is often incorporated with remote health monitoring solutions, for those who require regular attention such as aged patients and patient with severe conditions. Heavy traffic conditions have always become a burden to ambulance services which results sometimes fatal to critical condition patients. By considering the situation smart ambulance is a solution for the remote observation of patient's body parameters. Here, two innovative ideas have been proposed where an IoT based vehicle takes automatic control actions during emergency inside the ambulance which would be a life savior of patients during hospitalization and incorporation of medical drones to supply the lifesaving drugs inside the ambulance tracking from the nearest location at the shortest period of time. After incorporation with several cases the system comes out with the efficiency of 95%. With this proposed system society will get benefitted specially during the ongoing covid19 pandemic situation by maintaining social distancing.

There is a continuous quest in the research community for superior and more accurate methodology for fault diagnosis and condition monitoring of diverse composite structure. This is because, these structures suffer from various nonlinear mode of failures while in service those are recognised as delamination, voids, matrix crack etc. Early detection of failures is what the most research mainly aims at. In this regard, the implementation of Artificial Intelligence (AI) techniques has been proved to be a versatile method for damage assessment. The collective inevitable use of composite materials in various high-performance engineering industries requires preliminary testing (detection, location, and quantification) for damage to these materials in order to improve their integrity and order. The present paper aims to bring out a concise review on various methodologies employed for damage/fault detection in composite materials with a special emphasis on supervised and unsupervised machin...

Thermography is a widespread technique employed to inspect different equipment through the analysis of measured temperatures. In this case, this method was used to calculate four figures of merit, which evaluate the level of wear in the refractory walls of a dedicated ferronickel electric smelting furnace. Thermograms were taken from 22-year-old refractory walls and new ones in stable state operation. Images were pre- and post-processed by means of self-developed algorithms, where filtering techniques were applied for noise reduction. Results showed higher values and dispersions for the old refractory wall and similarity in the distribution of results for both cases. The study indicates that thermography is a good non-destructive inspection method for following the evolution of wear behavior in refractories submitted to high rates of heat and erosion.

Bragg gratings (FBGs) arranged in series. This arrangement allows a single terminated fiber or fiber loop to monitor several locations in an industrial plant, process line, or engineered structure. The most common way of providing discrimination between the different FBGs is to use FBGs with slightly different wavelengths. Several schemes have been proposed to separate these signals in the wavelength domain, using a tunable laser, an optical spectrum analyzer, or multiple filters. One technique combines a single broadband source with a programmable spectral processor (PSP) that acts as a programmable filter. The flexibility of the PSP allows this approach to be optimized for tracking both AC (" alternating current, " or rapidly oscillating about zero) and DC (" direct current, " or steady) signals. It can also be used to set up a carrier/sideband form of signal demodulation. Moreover, the ability to create customized, nonlinear filter slopes allows a linear signa...

The church of the monastery of Sant Cugat close to Barcelona is a medieval construction characterized by a complex structural behaviour stemming from the interaction among various structural elements built over different periods. Despite having survived for several centuries, such structures are often affected by slow irreversible deterioration mechanisms that can jeopardise their stability in the future. In order to identify such mechanisms at an early stage, and to better understand the cause of visible pathologies, a static structural health monitoring (SHM) system was installed in the church since 2017. Although this monitoring strategy, aimed at the continuous measurement of key slow-varying parameters, has been used successfully in the past to facilitate the diagnosis of this structural typology, the interpretation of data collected by such systems remains a challenging task. One of the main reasons for this is the fact that many monitored damage and deformation features are s...

This article presents a literature review of published methods for damage identification and prediction in mechanical structures. It discusses ways which can identify and predict structural damage from dynamic response parameters such as natural frequencies, mode shapes, and vibration amplitudes. There are many structural applications in which dynamic loads are coupled with thermal loads. Hence, a review on those methods, which have discussed structural damage under coupled loads, is also presented. Structural health monitoring with other techniques such as elastic wave propagation, wavelet transform, modal parameter, and artificial intelligence are also discussed. The published research is critically analyzed and the role of dynamic response parameters in structural health monitoring is discussed. The conclusion highlights the research gaps and future research direction.

The paper presents sharing several of experiences and practices on smart robotic application for overhead
transmission line maintenance and inspection. The robotic puller passes over barriers below the power line, such as the road
with traffic, power distribution lines, river, or vegetation making tasks achieved conveniently, safely, and rapidly without impact
on nearby communities.The target of the research is to create a mobile robot prototype for inspection of overhead power lines.
The inspection robot shall crawl along the ground wire and transpose autonomously across installed equipment on the ground
wire, such as vibration dampers, suspension clamps, compression dead ends, etc.

The present study assessed the Bailey Bridge’s condition and investigated its adaptation as a permanent structure, targeted the Acrow Bailey Bridge in Japan. Field diagnostic loading experiments were performed under various loading conditions, such as dynamic and static loading tests. The onsite data were obtained using a transducer, friction strain gauge, target measurements for the image processing approach, and accelerometer. From the field measurements, the deflection and stresses of the bridge were found to operate within the linear elastic region. The bridge was then accurately modeled based on the in situ geometric configuration of the bridge, and Finite Element Analysis was performed. The model’s accuracy was validated with the onsite data under the linear elastic domain. The model was deployed to check for resistance of critical members. A nonlinear analysis based on the linear and nonlinear buckling method was performed to determine the subject bridge’s Serviceability Limi...

This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classificati...

Structural Monitoring, now known under the acronym SHM (Structural Health Monitoring) has a history of over 150 years, but the current operating manner in a very broad recording frequency spectrum, evolving from the static to the dynamic mode, going through quasi-static or quasi-dynamic monitoring, of only 40-45 years. This paper concerns the monitoring under quasi-static continuous regime of a bridge with exceptional design features: the Incheon Grand Bridge Seoul, South Korea. The bridge, respectively its structural elements made of steel and reinforced concrete, are monitored to ascertain the effect of temperature variations on them. Two of the structural elements observed are of reinforced concrete, Bridge Gap from South line, respectively Gap Bridge from North line. In the monitoring process, pairs of data are formed, the cause, i.e. the air temperature, considered the X variable, and the effect – the movement of the sensors mounted on structural elements, which in this paper w...

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2015Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2015Fiber takviyeli polimer matrisli kompozit malzemeler havacılık, otomotiv, denizcilik gibi pek çok alanda önemli ölçüde kullanılmaktadır. Gelişen teknolojiye bağlı olarak hafif, dayanıklı ve güvenilir malzemeler için olan talep her geçen gün artmaktadır. Bu talepleri karşılayabilmek ve yenilikçi uygulamalar gerçekleştirebilmek için gelişmiş ve nano takviyeli kompozit malzemeler üzerinde ciddi çalışmalar yapılmaktadır. Kompozit malzemeler yüksek mekanik özellikleri ve hafifliği, kimyasal ve çevre koşullarına gösterdiği direnç gibi üstün özelliklerine rağmen katmanlı yapıları nedeni ile hasar oluşumu ve hasarın ilerlemesi konusunda büyük sorunlar göstermektedir. Kompozit malzemelerde çatlak ilerlemesinin takip edilmesi oldukça zordur, ayrıca ara katmanlarda oluşan hasarlar gözle muayene gibi basit yöntemlerle tespit ...

Damage detection in structural health monitoring of metallic or composite structures depends on several factors, including the sensor technology and the type of defect that is under the spotlight. Commercial devices generally used to obtain these data neither allow for their installation on board nor permit their scalability when several structures or sensors need to be monitored. This paper introduces self-developed equipment designed to create ultrasonic guided waves and a methodology for the detection of progressive damage, such as corrosion damage in aircraft structures, i.e., algorithms for monitoring such damage. To create slowly changing conditions, aluminum- and carbon-reinforced polymer plates were placed together with seawater to speed up the corrosion process. The setup was completed by an array of 10 piezoelectric transducers driven and sensed by a structural health monitoring ultrasonic system, which generated 100 waveforms per test. The hardware was able to pre-process...

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in...

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in...

Aim: In view of the 4th Millennium Development Goal set by the UN, this study aimed at analyzing the epidemiology of mortality of children under age 1 and under age 5 in Argentina between 1990 and 2011, and describing measles vaccination coverage in oneyear-old children between 1990 and 2009. Methods: Epidemiological indicators were measured using national data from secondary sources: Infant mortality rate and mortality rate in children under 5; and percentage of coverage in measles vaccination in Argentina. Results: Results show a 54.2% decrease in infant mortality rate, and 54.5% in mortality of children under 5. The most common causes of death during the first five years of life are usually associated to perinatal problems and congenital anomalies. In relation to measles vaccination coverage, there is a positive evolution of this indicator, reaching 100% coverage in 2009. Conclusions: Infant mortality represents an undeniable indicator of avoidable and unnecessary deaths that can...

Résumé : La surveillance de l’intégrité des structures (Structural Health Monitoring - SHM) est une nouvelle technologie, et comme toute nouvelle avancée technologique, elle n’a pas encore réalisé son plein potentiel. Le SHM s’appuie sur des avancées dans plusieurs disciplines, dont l’évaluation non-desctructive, les matériaux intelligents, et les capteurs et actionneurs intégrés. Une des disciplines qui permet son déploiement est la simulation numérique. Le SHM englobe une variété de techniques basées sur la génération d’ondes vibratoires et d’ondes ultrasonores guidées. L’utilisation d’ondes guidées offre en particulier une vaste gamme d’avantages. Le défi majeur associé à la pleine utilisation de la simulation numérique dans la conception d’un système SHM basé sur l’utilisation d’ondes guidées réside dans les ressources de calcul requises pour une simulation précise. La principale raison pour ces exigences est la dispersion induite par la discrétisation numérique, tel qu’indiqué ...

Non-destructive testing (NDT) techniques are usually used for the characterisation of defects arising in polymer composites during manufacturing or in-service use. However, each of these NDT techniques cannot always allow a full diagnosis of the material’s or component’s structural health. Thus, several techniques have to be combined in order to improve the diagnosis of the damaged state of composite structures and their evolution during the part’s life span. This opinion paper proposes a critical overview of the use and applicability of these NDT techniques for the detection and characterisation of damage to structural composite materials in view of in-service performance assessment and residual durability prognosis. It also addresses some current trends of structural health monitoring (SHM) of these materials, such as sensor–actuator embedding and NDT data fusion, and draws future perspectives on how composite SHM could evolve in the digital era, taking advantage of artificial intelligence, Internet of Things and big data to implement digital twins.

The final objective of the study herein reported is the preliminary evaluation of the capability of an original, real-time SHM system applied to a full-scale wing-box section as a significant aircraft component, during an experimental campaign carried out at the Piaggio Lab in Villanova D’Albenga, Italy. In previous works, the authors have shown that such a system could be applied to composite beams, to reveal damage along the bonding line between a longitudinal stiffening element and the cap. Utilizing a suitable scaling process, such work has then been exported to more complex components, in order to confirm the outcomes that were already achieved, and, possibly, expanding the considerations that should drive the project towards an actual implementation of the proposed architecture. Relevant topics dealt with in this publication concern the application of the structural health monitoring system to different temperature ranges, by taking advantage of a climatic room operating at th...

This paper demonstrates the feasibility of simultaneously identifying both the location and severity of structural damage in a beam by using two independent moving load experiments. First, a simple but sufficiently accurate single degree of freedom model is presented to simulate the structure efficiently over a wide range of relevant inputs. We then introduce a damage sensitive feature (DSF) based on the integral of the velocity time history of the beam at its midspan when the load moves over the beam. A critical velocity, a function only of the beam’s first natural frequency and length, is obtained for the proposed DSF, upon which the damage can be located more accurately. The only required data for the damage detection is the midspan velocity-time history of the cracked beam subjected to a moving load, and the midspan static deflection of the intact beam subjected to a load of the same magnitude. In the last section of this paper, the capability of the proposed DSF is examined in ...

This paper presents a novel method for identifying bridge damage using a vehicle equipped with instruments, specifically by using the vehicle's acceleration history to calculate changes in the "Bridge Displacement Profile", which is proven to be sensitive to structural damage. This method, known as "Drive-by Bridge Inspection", has seen a shift in focus from instrumenting the bridge itself to instrumenting a passing vehicle. The research includes simulations of three different bridges, modeled as 1D and 2D Finite Element (FE) beam and plate elements respectively. The interaction between the vehicle and the bridge is simulated in MATLAB, with the vehicle represented as a simple quarter car model traversing a rough profile. The method is also numerically tested for localized damage in the bridge plate model. The paper concludes with a study on the sensitivity to signal noise, corrupted vehicle properties, initial conditions, and the vehicle's transverse position.

Automated Visual Inspection (AVI) has seen revolutionary improvements in defect identification, accuracy, and process effectiveness after integrating Deep Learning technologies. Deep learning has shown outstanding capability in identifying complex patterns, abnormalities, and deviations inside images, enabling real-time and precise diagnosis of flaws. Through comprehensive exploration of state-of-the-art research and case studies, this abstract underscore the significance of deep learning-based AVI in improving product quality, reducing production costs, and minimizing human errors. The fusion of Automated Visual Inspection with Deep Learning not only transforms the landscape of industrial quality control but also opens avenues for further innovation and development in this domain.

Peridynamic based elastodynamic computation tool named Peri-elastodynamics is proposed herein to simulate the three-dimensional (3D) Lamb wave modes in materials for the first time. Peri-elastodynamics is a nonlocal meshless approach which is a scale-independent generalized technique to visualize the acoustic and ultrasonic waves in plate-like structure, micro-electro-mechanical systems (MEMS) and nanodevices for their respective characterization. In this article, the characteristics of the fundamental Lamb wave modes are simulated in a sample plate-like structure. Lamb wave modes are generated using a surface mounted piezoelectric (PZT) transducer which is actuated from the top surface. The proposed generalized Peri-elastodynamics method is not only capable of simulating two dimensional (2D) in plane wave under plane strain condition formulated previously but also capable of accurately simulating the out of plane Symmetric and Antisymmetric Lamb wave modes in plate like structures ...

The aim of this project is to design and create a digital signal detector that can detect incoming and outgoing signals from cell phones. This convenient, pocket-size mobile signal detector can detect the presence of an activated mobile phone from a distance of one and a half meters, and could be used to avoid the use of mobile phones in examination halls, sensitive spaces, and other places. It can also be used to track illegal video sharing and the use of a cell phone for surveillance. Even if the phone is in silent mode, the circuit will detect incoming and outgoing calls, text messages, and video transmission. When the device senses an active cell phone's Radio Frequency (RF) transmission signal, it sounds a beep warning and the Light Emitting Diode (LED) blinks. The alarm will continue to sound until the signal is lost. The circuit is built on a general-purpose PCB that is as thin as possible and housed in a small box.

This paper presents a wave propagation modelling analysis of strong motion records for actual buildings in comparison with an analysis of simple building models. In previous studies on earthquake response of buildings, vibration approaches were used more often than wave propagation approaches; thus, wave propagation through a building has not been investigated enough. We use the normalized input output minimization (NIOM) method, which can model wave propagation in multiple linear systems by considering the statistical correlation among the strong motions at different observation locations. Output wave models simplified by this method show two clear peaks that correspond to incident and reflected waves propagating through the building in the vertical direction. The obtained wave propagation properties, such as wave travel time and wave amplitude ratio, at each story of the building are found to reflect the structural properties like rigidity and damping ratio at that story. Further,...

Nowadays, a doubtful feeling is emerging among society regarding durability of civil structures. Modern techniques such as repairing of structural elements, prestressing, external post-tensioning, and developing kernel components for seismic devices like actuators, dampers, and isolators are accepted but still they are quite uneconomical. In order to make structures safer and stable we have come up with a material named Shape Memory Alloy. Shape memory alloys are special materials with great potential in various civil engineering applications. There are many alloys, among which Ni-Ti alloy have ability to undergo large deformations up to 6 to 8 percent, and return to its undeformed shape (from austenite to martensite) through thermo mechanical properties which includes super elasticity and shape memory effect. Until today, shape memory alloy have found very limited applications in civil engineering probably due to their cost and to limited knowledge of the material in the civil engi...

Prestressed concrete bridges are susceptible to deterioration over time which might significantly affect their capacity and overall performance. In previous decades, infrastructure owners have found that continuous monitoring of these assets is a valuable tool for their management as it facilitates the decision-making process regarding the intervention strategies required. However, as data acquisition and measurement technologies have advanced tremendously in recent years, the amount of information that can be retrieved daily is not easy to manage and analyse. This study presents an evaluation of the effectiveness between different machine learning methods regarding prediction and interpretation of structural responses as well as the feasibility of mapping an independent
variable, aspects such as metric performance, learning curves and residual
plots was analysed. A comparison was made on the machine learning algorithms performing regression analysis where each model scored over 98% in the R-square metric. This study utilised data collected from a prestressed concrete bridge located in Autio, northern Sweden, that has been continuously monitored for more than three years.