Dissertations / Theses on the topic 'Structural Health Monitoring'
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Webb, Graham Thomas. "Structural health monitoring of bridges." Thesis, University of Cambridge, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708027.
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Grisso, Benjamin Luke. "Advancing Autonomous Structural Health Monitoring." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/29960.
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The focus of this dissertation is aimed at advancing autonomous structural health monitoring. All the research is based on developing the impedance method for monitoring structural health. The impedance technique utilizes piezoelectric patches to interrogate structures of interested with high frequency excitations. These patches are bonded directly to the structure, so information about the health of the structure can be seen in the electrical impedance of the piezoelectric patch. However, traditional impedance techniques require the use of a bulky and expensive impedance analyzer. Research presented here describes efforts to miniaturize the hardware necessary for damage detection. A prototype impedance-based structural health monitoring system, incorporating wireless based communications, is fabricated and validated with experimental testing. The first steps towards a completely autonomous structural health monitoring sensor are also presented. Power harvesting from ambient energy allows a prototype to be operable from a rechargeable power source.
Aerospace vehicles are equipped with thermal protection systems to isolate internal components from harsh reentry conditions. While the thermal protection systems are critical to the safety of the vehicle, finding damage in these structures presents a unique challenge. Impedance techniques will be used to detect the standard damage mechanism for one type of thermal protection system. The sensitivity of the impedance method at elevated temperatures is also investigated.
Sensors are often affixed to structures as a means of identifying structural defects. However, these sensors are susceptible to damage themselves. Sensor diagnostics is a field of study directed at identifying faulty sensors. The influence of temperature on these techniques is largely unstudied. In this dissertation, a model is generated to identify damaged sensors at any temperature. A sensor diagnostics method is also adapted for use in developed hardware. The prototype used is completely digital, so standard sensor diagnostics techniques are inapplicable. A new method is developed to work with the digital hardware.Ph. D.
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Ward, Jacob Thomas Elliott. "Guided wave structural health monitoring." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.682233.
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Routine airframe Non-Destructive Testing (NDT) procedures are costly and prone to human error. Guided wave structural health monitoring (GWSHM) shows great promise to in future assist these carefully regulated aerospace NDT practices. Using automatic GWSHM to both detect and localise damage can better focus the human NDT effort and ultimately lead to safer operation of airframes. The thesis presents structural health monitoring techniques for airframes using measurements of guided waves. Work is presented on both metal plates and carbon fibre reinforced plastic panels. An active GWSHM method is considered in its capability to detect and localise damage by measurements of scattered Lamb waves from artificially placed damage. The contribution to knowledge on active GWSHM has been towards effective and practical strategies for placing a low number of transducers into arrays suitable for global coverage. Much early active GWSHM studies often adopted a uniformly sparse distribution of transducer elements, perhaps in an attempt to gain the best possible global coverage. In this thesis, active GWSHM performance has been evaluated for arrays of different geometry and has shown that a uniformly sparse distribution of transducer elements may not be the most effective strategy when using a minimal number of sensors. Simulated and artificial damage, placed with different orientations over a large area, has been used to test candidate array layouts. It finds the layout optimal for damage detection is not necessarily the layout optimal for damage localisation. The zeroth order anti-symmetric Lamb wave mode has been used at low frequency-thickness. The mode, referred to as the flexural mode when propagating with low frequency-thickness, is favoured for its short wave length and long range. At low frequency-thickness this mode is quickly outrun by its symmetric counterpart, causing coherent noise in the signals recorded. Baseline subtraction is used to suppress the coherent noise before imaging. Benign structural features, that would usually hinder damage-localisation from an image, are actually found to assist damage localisation for some array layouts when using the reference baseline signal subtraction technique. A passive GWSHM method is considered in its capability to localise impacts. Impact events on carbon fibre panels are localised using a low frequency passive array. The technique is suggested for evaluating damage from tyre-burst or propeller debris impacts to airframe surfaces. It is particularly relevant to new airframe designs that have significant usage of composite materials on their outer surface. Historically the aerospace sector has readily adopted time of arrival estimation methods similar to those found on a standard oscilloscope. As an example, acoustic emission monitoring, in recent decades has routinely used threshold-crossing as a means of time of arrival measurement. An alternative is presented requiring the whole time series to be post-processed. It extracts an alternative arrival time from propagating waves resulting from the impact, which can be used in time-difference of arrival algorithms. This method is shown to be more reliable and accurate for impact localisation than historical techniques.
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Dawood, Tariq Ali. "Structural health monitoring of GFRP sandwich beam structures." Thesis, University of Southampton, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438529.
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Ullah, Israr. "Vibration-based structural health monitoring of composite structures." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/vibrationbased-structural-health-monitoring-of-composite-structures(f21abb03-5b46-4640-9447-0552d5e0c7d6).html.
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Composite materials are in use in several applications, for example, aircraft structural components, because of their light weight and high strength. However the delamination which is one of the serious defects often develops and propagates due to vibration during the service of the structure. The presence of this defect warrants the design life of the structure and the safety. Hence the presence of such defect has to be detected in time to plan the remedial action well in advance. There are a number of methods in the literature for damage detection. They are either 'baseline free/reference free method' or using the data from the healthy structure for damage detection. However very limited vibration-based methods are available in the literature for delamination detection in composite structures. Many of these methods are just simulated studies without experimental validation. Grossly 2 kinds of the approaches have been suggested in the literature, one related to low frequency methods and other high frequency methods. In low frequency approaches, the change in the modal parameters, curvatures, etc. is compared with the healthy structure as the reference, however in the high frequency approaches, excitation of structures at higher modes of the order of few kHz or more needed with distributed sensors to map the deflection for identification of delamination. Use of high frequency methods imposes the limitations on the use of the conventional electromagnetic shaker and vibration sensors, whereas the low frequency methods may not be feasible for practical purpose because it often requires data from the healthy state which may not be available for old structures. Hence the objective of this research is to develop a novel reference-free method which can just use the vibration responses at a few lower modes using a conventional shaker and vibration sensors (accelerometers/laser vibrometers). It is believed that the delaminated layers will interact nonlinearly when excited externally. Hence this mechanism has been utilised in the numerical simulations and the experiments on the healthy and delaminated composite plates. Two methods have been developed here - first method can quickly identify the presence of the delamination when excited at just few lower modes and other method identify the location once the presence of the delamination is confirmed. In the first approach an averaged normalised RMS has been suggested and experimentally validated for this purpose. Latter the vibration data have then been analysed further to identify the location of delamination and its size. Initially, the measured acceleration responses from the composite plates have been differentiated twice to amplify the nonlinear interaction clearly in case of delaminated plate and then kurtosis was calculated at each measured location to identify the delamination location. The method has further been simplified by just using the harmonics in the measured responses to identify the location. The thesis presents the process of the development of the novel methods, details of analysis, observations and results.
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Singh, Gurjashan. "Health Monitoring of Round Objects using Multiple Structural Health Monitoring Techniques." FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/330.
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Structural Health Monitoring (SHM) techniques are widely used in a number of Non – destructive Evaluation (NDE) applications. There is a need to develop effective techniques for SHM, so that the safety and integrity of the structures can be improved. Two most widely used SHM methods for plates and rods use either the spectrum of the impedances or monitor the propagation of lamb waves. Piezoelectric wafer – active sensors (PWAS) were used for excitation and sensing. In this study, surface response to excitation (SuRE) and Lamb wave propagation was monitored to estimate the integrity of the round objects including the pipes, tubes and cutting tools. SuRE obtained the frequency response by applying sweep sine wave to surface. The envelope of the received signal was used to detect the arrival of lamb waves to the sensor. Both approaches detect the structural defects of the pipes and tubes and the wear of the cutting tool.
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Lannamann, Daniel L. "Structural health monitoring : numerical damage predictor for composite structures." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA390997.
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Nayyerloo, Mostafa. "Real-time Structural Health Monitoring of Nonlinear Hysteretic Structures." Thesis, University of Canterbury. Department of Mechanical Engineering, 2011. http://hdl.handle.net/10092/6581.
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The great social and economic impact of earthquakes has made necessary the development of novel structural health monitoring (SHM) solutions for increasing the level of structural safety and assessment. SHM is the process of comparing the current state of a structure’s condition relative to a healthy baseline state to detect the existence, location, and degree of likely damage during or after a damaging input, such as an earthquake. Many SHM algorithms have been proposed in the literature. However, a large majority of these algorithms cannot be implemented in real time. Therefore, their results would not be available during or immediately after a major event for urgent post-event response and decision making. Further, these off-line techniques are not capable of providing the input information required for structural control systems for damage mitigation. The small number of real-time SHM (RT-SHM) methods proposed in the past, resolve these issues. However, these approaches have significant computational complexity and typically do not manage nonlinear cases directly associated with relevant damage metrics. Finally, many available SHM methods require full structural response measurement, including velocities and displacements, which are typically difficult to measure. All these issues make implementation of many existing SHM algorithms very difficult if not impossible.
This thesis proposes simpler, more suitable algorithms utilising a nonlinear Bouc-Wen hysteretic baseline model for RT-SHM of a large class of nonlinear hysteretic structures. The RT-SHM algorithms are devised so that they can accommodate different levels of the availability of design data or measured structural responses, and therefore, are applicable to both existing and new structures. The second focus of the thesis is on developing a high-speed, high-resolution, seismic structural displacement measurement sensor to enable these methods and many other SHM approaches by using line-scan cameras as a low-cost and powerful means of measuring structural displacements at high sampling rates and high resolution. Overall, the results presented are thus significant steps towards developing smart, damage-free structures and providing more reliable information for post-event decision making.
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Kirikera, Goutham Raghavendra. "A Structural Neural System for Health Monitoring of Structures." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1155149869.
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Islami, Kleidi. "System identification and structural health monitoring of bridge structures." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3423079.
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This research study addresses two issues for the identification of structural characteristics of civil infrastructure systems. The first one is related to the problem of dynamic system identification, by means of experimental and operational modal analysis, applied to a large variety of bridge structures. Based on time and frequency domain techniques and mainly with output-only acceleration, velocity or strain data, modal parameters have been estimated for suspension bridges, masonry arch bridges, concrete arch and continuous bridges, reticular and box girder steel bridges. After giving an in-depth overview of standard and advanced stochastic methods, differences of the existing approaches in their performances are highlighted during system identification on the different kinds of civil infrastructures. The evaluation of their performance is accompanied by easy and hard determinable cases, which gave good results only after performing advanced clustering analysis. Eventually, real-time vibration-based structural health monitoring algorithms are presented during their performance in structural damage detection by statistical models.
The second issue is the noise-free estimation of high order displacements taking place on suspension bridges. Once provided a comprehensive treatment of displacement and acceleration data fusion for dynamic systems by defining the Kalman filter algorithm, the combination of these two kinds of measurements is achieved, improving the deformations observed. Thus, an exhaustive analysis of smoothed displacement data on a suspension bridge is presented. The successful tests were subsequently used to define the non-collocated sensor monitoring problem with the application on simplified modelsQuesto lavoro di ricerca mira a due obiettivi per l'identificazione delle caratteristiche strutturali dei sistemi infrastrutturali civili. Il primo è legato al problema della identificazione del sistema dinamico, mediante analisi modale sperimentale e operativa, applicata ad una grande varietà di strutture da ponte. Basandosi su tecniche nel dominio del tempo e delle frequenze e, soprattutto, su dati di output di accelerazione, velocità o strain, i parametri modali sono stati stimati per ponti sospesi, ponti ad arco in muratura, ponti a travi in calcestruzzo e ad arco, ponti reticolari e ponti in acciaio a cassone. Dopo aver dato una panoramica approfondita dei metodi stocastici standard ed avanzati, sono state evidenziate le differenze degli approcci esistenti nelle loro performance per l'identificazione del sistema sui diversi tipi di infrastrutture civili. La valutazione della loro performance viene accompagnata da casi facilmente e difficilmente determinabili, che hanno dato buoni risultati solo dopo l'esecuzione di analisi avanzate di Clustering. Inoltre, sono stati sviluppati algoritmi di identificazione dinamica automatica in tempo reale basandosi sulle vibrazioni strutturali dei ponti monitorati, a sua volta utilizzati nel rilevamento dei danni strutturali tramite modelli statistici. Il secondo problema studiato riguarda la stima di spostamenti di ordine superiore che si svolgono sui ponti sospesi, eliminando il rumore di misura e di processo. Una volta fornito un trattamento completo della fusione dei dati di spostamento e accelerazione per i sistemi dinamici tramite il filtro di Kalman, la combinazione di questi due tipi di misurazioni ha mostrato un miglioramento nelle deformazioni osservate. Pertanto, è stata presentata un'analisi esauriente di un ponte sospeso e dei sui dati dinamici e di spostamento filtrati. I test positivi sono stati successivamente utilizzati per definire il problema dei sensori non collocati alla stessa locazione ed applicazione su modelli semplificati
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Brigman, Nicholas (Nicholas Allen). "Structural health monitoring in commercial aviation." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/73846.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-90).
The number of aging commercial aircraft in service is steadily increasing as airlines continue to extend the life of their aircraft. Aging aircraft are more susceptible to fatigue and corrosion and require more frequent and intensive inspections and maintenance, which is a financial drain on operators. One way to improve the economics and safety of commercial aircraft is through implementation of a structural health monitoring (SHM) system. An ideal SHM would be able to give be capable of indicating damage type, location, severity, and estimate the remaining life of the structure while the structure is in use. This paper is an overview of how SHM can be applied in commercial aviation including discussion of requirements, implementation, challenges, and introducing several possible SHM systems. The SHM systems introduced in this paper are: vibration based monitoring, fiber optic sensors, and high frequency wave propagation techniques including acoustic emission, ultrasonic, Lamb waves, piezoelectric and MEMS actuator/sensors. The limitations and challenges inhibiting introduction of SHM to industry and recommendations for the future are also discussed.
by Nicholas Brigman.
M.Eng.
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Mani, Girindra N. "Structural Health Monitoring of Rotordynamic Systems." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1144522032.
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Ashwin, Belle. "WIRELESS INTELLIGENT STRUCTURAL HEALTH MONITORING SYSTEM." VCU Scholars Compass, 2008. http://scholarscompass.vcu.edu/etd/1626.
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Metal structures are susceptible to various types of damages, including corrosion, stress damage, pillowing deformation, cracks etc. These kinds of damages in the metal structures occur mainly due to operational conditions and exposure to the environment. Our research involves a portable integrated wireless sensor system with video camera and ultrasound capabilities which is being developed to investigate corrosion damage on real structures in real time. This system uses images of the metal surfaces, which are captured from an integrated wireless sensor and then quantified and analyzed using computational intelligence. The quantification of the obtained images is done with specialized component analysis software which enhances and performs wavelet transforms on the received images. Through this quantized analysis of the images we can detect and isolate regions of degradation on the metal surface. We believe that the final developed system will allow us to detect damage in metallic structures in its early stages, thereby ensuring proper safety and maintenance of its structural health. This system will further be targeted towards medical applications with capabilities of remote health monitoring. The initial target areas being bone structure and cancer detection and analysis. Applying such a wireless data capture system in these areas will reveal a broad spectrum of the usage of such an application system.
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Bogomolov, Denis <1992>. "Structural health monitoring of storage tanks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10215/1/Bogomolov%20-%20PhD%20thesis.pdf.
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In this thesis, Ph.D candidate presents a compact sensor node (SN) designed for long-term and real-time acoustic emission (AE) monitoring of above ground storage tanks (ASTs). Each SN exploits up to three inexpensive low-frequency sensors based on piezoelectric diaphragms for effective leakage detection, and it is capable by means of built-in Digital Signal Processing functionalities to process the acquired time waveforms extracting the AE features usually required by testing protocols. Alternatively, capability to plug three high frequency AE sensors to a SN for corrosion simulated phenomena detection is envisaged and demonstrated.
Another innovative aspect that the Ph.D candidate presents in this work is an alternative mathematical model of corrosion location on the bottom of the AST. This approach implies considering the three-dimensional localization model versus the two-dimensional commonly used according to the literature. This approach is aimed at significant optimization in the number of sensors in relation to the standard approach for solving localization problems as well as to allow filtering the false AE events related to the condensate droplets from AST ceiling. The technological implementation of this concept required the solution of a number of technical problems, such as the precise time of arrival (ToA) signal estimation, vertical localization of the AE source and multilaration solution that were discussed in detail in this work.
To validate the developed prototype, several experimental campaigns were organized that included the simulation of target phenomena both in laboratory conditions and on a real water storage tank. The presented test results demonstrate the successful application of the developed AE system both for simulated leaks and for corrosion processes on the tank bottom. Mathematical and technological algorithms for localization and characterization of AE signals implemented during the development of the prototype are also confirmed by the test results.
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Ding, Wenxiang. "Structural health monitoring of piezoelectric ultrasonic transducers." Electronic Thesis or Diss., Bourges, INSA Centre Val de Loire, 2021. http://www.theses.fr/2021ISAB0008.
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Les transducteurs à ultrasons ont été largement utilisés dans le diagnostic médical, la thérapie, l'évaluation non destructive, le nettoyage, le sonar et d'autres applications. Le bon fonctionnement du transducteur lui-même est un facteur clé de la fiabilité globale du système. Cependant, en raison d'une mauvaise utilisation par l’opérateur ou d'une dégradation des matériaux, des défauts peuvent survenir tels que des ruptures dans le câblage, des fissures dans les matériaux passifs, l’endommagement des matériaux actifs, une délamination entre les couches constitutives du dispositif ... Ce travail de thèse porte sur une analyse détaillée de l'influence de délaminations sur les performances du transducteur, visant à déterminer des procédures pour faciliter le suivi du comportement du transducteur pendant sa durée de vie et la détection des dégradations avant qu'elles n'affectent significativement les performances du système dans son ensemble.Dans le cadre de ce travail, un modèle analytique bidimensionnel original pour l’étude des vibrations couplées dans les résonateurs piézoélectriques est proposé. Des solutions générales pour toutes les grandeurs physiques dans les systèmes de coordonnées cartésiennes et cylindriques sont déduites des équations tensorielles de la piézoélectricité. Elles sont exprimées sous forme de séries de fonctions trigonométriques ou de Bessel. L'impédance électrique, la forme du mode et le spectre de fréquences des céramiques piézoélectriques sont calculés par la méthode analytique proposée ainsi que par la méthode des éléments finis. La comparaison des résultats de ces deux méthodes montre un excellent accord.Une étude systématique de l'influence de différents types de délaminations sur les performances des transducteurs ultrasonores monoéléments et multi-éléments est présentée. Des modèles par éléments finis sont développés pour montrer l'impact des différents types de délaminations ainsi que d'autres facteurs sur l'admittance électromécanique (EMA) de transducteurs composés soit d'un disque soit de parallélépipèdes de céramiques piézoélectriques, d'un milieu arrière et d'une lame adaptatrice. Des études expérimentales sont mises en place pour valider les modèles et des indicateurs quantitatifs sont proposés. Des éléments sont réalisés en impression 3D (milieu arrière, lame adaptatrice) et montés sur des échantillons de céramiques piézoélectriques pour obtenir un transducteur modèle intact et des transducteurs modèles avec délaminations. La comparaison entre les résultats numériques et expérimentaux montre un bon accord et permet d’affirmer que des modifications de l'EMA peuvent révéler l'apparition et l'étendue d'une délamination entre les éléments constitutifs d’une sonde échographiqueUltrasonic transducers have been widely used in medical diagnostic, therapy, non-destructive evaluation, cleaning, underwater sonar, and other applications. The proper functioning of the transducer itself is a key factor in the reliability of the entire system. However, due to the misuse of operators or material degradation, defects may occur, such as breakages in cables, cracks, damaged or weakened crystals, and delamination between layers. This contribution focuses on a detail analysis of the influence of bonding delamination on the performance of the transducer, aiming to determine procedures to facilitate the monitoring of the behavior of the transducer during its lifetime and the detection of degradations before they significantly affect the performance of the system.In the frame of this work, an original two-dimensional analytical model for coupled vibrations of finite piezoelectric resonators is proposed. General solutions for all the physical quantities in Cartesian and cylindrical coordinate systems are deduced from the governing equations. They are expressed as a series of trigonometric or Bessel functions. Electrical impedance, mode shape, and frequency spectrum of piezoceramics are calculated by the proposed analytical method as well as by the finite element method. Comparison of the results of these two methods shows an excellent agreement.A systematic investigation of the influence of different kinds of bonding delamination on the performance of single-element and linear array ultrasonic transducers is presented. Finite element models are developed to show the impact of bonding delamination as well as other factors on the electromechanical admittance (EMA) of ultrasonic transducers, which are composed of a piezoceramic disk or parallelepiped, a backing, and a matching layer. Experimental studies are set up to validate the models and quantitative indicators are proposed. 3D printed backings and matching layers are mounted on piezoceramic elements to obtain an intact model transducer and delaminated ones. Comparison between numerical and experimental results show a good agreement, which allows to affirm that changes in EMA can reveal the occurrence and extent of a delamination in an ultrasound probe
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Singh-Levett, Ishan. "Real-time integral based structural health monitoring." Thesis, University of Canterbury. Mechanical Engineering, 2006. http://hdl.handle.net/10092/1171.
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Structural Health Monitoring (SHM) is a means of identifying damage from the structural response to environmental loads. Real-time SHM offers rapid assessment of structural safety by owners and civil defense authorities enabling more optimal response to major events. This research presents an real-time, convex, integral-based SHM methods for seismic events that use only acceleration measurements and infrequently measured displacements, and a non-linear baseline model including hysteretic dynamics and permanent deformation. The method thus identifies time-varying pre-yield and post-yield stiffness, elastic and plastic components of displacement and final residual displacement. For a linear baseline model it identifies only timevarying stiffness. Thus, the algorithm identifies all key measures of structural damage affecting the immediate safety or use of the structure, and the long-term cost of repair and retrofit. The algorithm is tested with simulated and measured El Centro earthquake response data from a four storey non-linear steel frame structure and simulated data from a two storey non-linear hybrid rocking structure. The steel frame and rocking structures exhibit contrasting dynamic response and are thus used to highlight the impact of baseline model selection in SHM. In simulation, the algorithm identifies stiffness to within 3.5% with 90% confidence, and permanent displacement to within 7.5% with 90% confidence. Using measured data for the frame structure, the algorithm identifies final residual deformation to within 1.5% and identifies realistic stiffness values in comparison to values predicted from pushover analysis. For the rocking structure, the algorithm accurately identifies the different regimes of motion and linear stiffness comparable to estimates from previous research. Overall, the method is seen to be accurate, effective and realtime capable, with the non-linear baseline model more accurately identifying damage in both of the disparate structures examined.
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Ciampa, Francesco. "Structural health monitoring systems for impacted isotropic and anisotropic structures." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558884.
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This thesis investigates the development of ultrasonic Structural Health Monitoring (SHM) systems, based on guided waves propagation, for the localization of low-velocity impacts and the detection of damage mechanisms in isotropic and anisotropic structures. For the identi- cation of the impact point, two main passive techniques were developed, an algorithm-based and an imaging-based method. The former approach is based on the dierences of the stress waves measured by a network of piezoelectric transducers surface bonded on plate-like structures. In particular, four piezoelectric sensors were used to measure the antisymmetrical A0 Lamb mode in isotropic materials, whilst six acoustic emission sensors were employed to record the wave packets in composite laminates. A joint time-frequency analysis based on the magnitude of the Continuous Wavelet Transform was used to determine the time of arrivals of the wave packets. Then, a combination of unconstrained optimization technique associated to a local Newton's iterative method was employed to solve a system of non linear equations, in order to assess the impact location coordinates and the wave group speeds. The main advantages of the proposed algorithms are that they do not require an a-priori estimation of the group velocity and the mechanical properties of the isotropic and anisotropic structures. Moreover, these algorithms proved to be very robust since they were able to converge from almost any guess point and required little computational time. In addition, this research provided a comparison between the theoretical and experimental results, showing that the impact source location and the wave velocity were predicted with reasonable accuracy. The passive imaging-based method was developed to detect in realtime the impact source in reverberant complex composite structures using only one passive sensor. This technique is based on the re- ciprocal time reversal approach, applied to a number of waveforms stored in a database containing the impulse responses of the structure. The proposed method allows achieving the optimal focalization of the acoustic emission source (impact event) as it overcomes the limitations of other ultrasonic impact localization techniques. Compared to a simple time reversal process, the robustness of this approach is experimentally demonstrated on a stiened composite plate. This thesis also extended active ultrasonic guided wave methods to the specic case of dissipative structures showing non-classical nonlinear behaviour. Indeed, an imaging method of the nonlinear signature due to impact damage in a reverberant complex anisotropic medium was developed. A novel technique called phase symmetry analysis, together with frequency modulated excitation signals, was used to characterize the third order nonlinearity of the structure by exploiting its invariant properties with the phase angle of the input waveforms. Then, a \virtual" reciprocal time reversal imaging process was employed to focus the elastic waves on the defect, by taking advantage of multiple linear scattering. Finally, the main characteristics of this technique were experimentally validated.
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Fekrmandi, Hadi. "Development of New Structural Health Monitoring Techniques." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=2923&context=etd.
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During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations.
A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time.
Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.
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Bartoli, Ivan. "Structural health monitoring by ultrasonic guided waves." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3283893.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed December 3, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 311-325).
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Azhari, Faezeh. "Cement-based sensors for structural health monitoring." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/7324.
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The purpose of structural health monitoring is to continuously and accurately assess the performance of structures using a sensory system.
Recently introduced, cement-based sensors are piezoresistive and therefore can be used to sense stress/strain, simply by monitoring their electrical resistivity. These sensors, also known as smart (self-monitoring) structural materials can be used as a part or total component of structures and provide both structural capability and response to applied stress and damage.
In this study cement-based sensors are developed using two types of carbon fibres, as well as both single-walled and multi-walled carbon nano-tubes. A wide range of experiments were conducted to pinpoint the most efficient fibre content, frequency, electrode type and resistivity measurement technique. The influence of different parameters such as curing, temperature, moisture and chloride were also investigated.
The resistivity of the specimens increased with curing time, but became almost constant after a certain amount of time. The resistivity values decreased with increasing temperature and increased with the decrease in temperature at a rate of about 22-35 ohm-cm/°C. It was further found that moisture and chloride have a considerable influence on the electrical resistivity of these sensors.
Next, the response of the developed cement-based sensors to compressive, tensile and flexural loading was explored. The resistivity values from the sensors were compared with load and displacement values as well as strain data acquired from conventional strain gauges.
The results indicate that electrical resistivity of the sensors increases reversibly upon tension and decreases reversibly under compression provided that substantial cracking does not occur and the sensor remains in the elastic range. Once a dense field of micro-cracking followed by macro-cracking occurs, these sensors respond distinctly, possibly even prior to the appearance of visible cracks, providing an early prediction of any upcoming failure.
The resistivity measurements under both compressive and tensile stress demonstrated an excellent correlation with strain. The developed sensors offer gauge factors well above those of electrical strain gauges.
It is concluded, therefore, that cement-based sensors can be the future alternative for conventional sensors in the structural health monitoring of concrete structures.
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Movva, Gopichand. "Optimal Sensor Placement for Structural Health Monitoring." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc700010/.
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In large-scale civil structures, a limited number of sensors are placed to monitor the health of civil structures to reduce maintenance, communication and energy costs. In this thesis, the problem of optimal sensor location placement to infer the health of civil structures is explored. First, a comparative study of approaches from the fields of control engineering and civil engineering is conducted . The widely used civil engineering approaches such as effective independence (EI) and modal assurance criterion (MAC) have limitations because of the negligence of modes and damping parameters. On the other hand, control engineering approaches consider the entire system dynamics using impulse response-type sensor measurement data. Such inference can be formulated as an estimation problem, with the dynamics formulated as a second-order differential equation. The comparative study suggests that damping dynamics play significant impact to the selection of best sensor location---the civil engineering approaches that neglect the damping dynamics lead to very different sensor locations from those of the control engineering approaches. In the second part of the thesis, an initial attempt to directly connect the topological graph of the structure (that defines the damping and stiffness matrices) and the second-order dynamics is conducted.
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Storozhev, Dmitry Leonidovich. "Smart Rotating Machines for Structural Health Monitoring." Cleveland State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1262724991.
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Kolli, Phaneendra K. "Wireless Sensor Network for Structural Health Monitoring." Youngstown State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1274304285.
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Valiante, Rossella. "Innovative techniques for Structural Health Monitoring: a." Doctoral thesis, Universita degli studi di Salerno, 2011. http://hdl.handle.net/10556/213.
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2009 - 2010The here considered SHM procedure concerns innovative techniques for a structural monitoring of aeronautical components, all of them based upon the use of a Scanning Laser Doppler Vibrometer. The vibrometer is used to detect the dynamic response of the component under test, in wave propagation regime. The signal so recorded consists of space and time maps of vibration velocity offplane. The purpose of the study lies in the analysis of such maps, using filtering techniques that separate reflected waves from the incident ones, so that they can enable to identify defects. The innovative application of a novel technique (introduced by Ruzzene) for the first time to stringerized composite specimens, allowed the generation of baseline information directly from the measured dataset. The effectiveness of these methods has been demonstrated through their application to detection of a delamination in a composite stiffened plate and detection of defect/wrinkling in a T-shaped skin to stringer component. The most significant technological innovations achieved through these theses are: • The option key to excite the surface of a complex structure (in this case, the skins of a composite stingerized panel) and to derive the velocity profile on surfaces orthogonal to the excited one (in our case the web of the stringer) has been checked. This is crucial, as it would allow to install the piezo elements on the stringers, to excite them and to read velocities of points over the entire surface of the skin, without disassembly. Up to now, only cases of standard solicitation have been analyzed in literature, or cases where the velocities were acquired on the same surfaces excited. Today, therefore, there is no published study on the analysis conducted in such a manner. • The damage index was also applied to stiffened and greatly complex geometries. Up to now, in literature only analysis applied to simple flat panels can be found. • The FEM simulation was carried out on stiffened panels. In literature there are only simulations carried out on simple structural elements like flat panels without any stiffener. [edited by author]
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García, Cava David. "Data-based vibration structural health monitoring methodology for composite laminated structures." Thesis, University of Strathclyde, 2016. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=26903.
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Composite materials are steadily replacing traditional materials in a wide range of industry sectors thanks to their remarkable properties. Damage in composite materials exhibits complex failure modes which are difficult to identify by conventional techniques. Composite materials demonstrate complex nonlinear vibration behaviour where conventional vibration-based structural health monitoring (VSHM) methods might not give adequate information for damage identification. This thesis investigates the capabilities of singular spectrum analysis (SSA) as a technique for developing a completely data-based VSHM methodology. The methodology decomposes the vibration responses in a certain number of principal components having in consideration all rotational patterns at any frequency including the nonlinear oscillations. This thesis develops two approaches to use SSA in the time and frequency domain. The methodology has been validated using a numerical system and an experiment with delaminated beams. The results demonstrate the methodology capability for assessing damages at different locations and with different sizes. The progression of damage can also be tracked. Delamination was successfully assessed in composite laminated plates with different delamination locations, in-plane and through different layers. Damage in wind turbine blades was assessed by the damage assessment methodology with a statistical hypothesis inspection phase based on probability distribution functions. Different damage locations and sizes were assessed as well as damage progression. This thesis explores the use of smart materials which enable self-sensing and self-diagnosing of its structural integrity coupled with the data-based VSHM. The results demonstrate the substantial potential of this approach. Overall, the data-based VSHM methodology presented in this thesis is proven to give adequate information about the presence, location and extent of delamination and other defects in different composite laminated structures.
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Boettcher, Dennis N. "A Resistance Based Structural Health Monitoring System for Composite Structure Applications." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/843.
Full textAbstract:
This research effort explored the possibility of using interwoven conductive and nonconductive fibers in a composite laminate for structural health monitoring (SHM). Traditional SHM systems utilize fiber optics, piezoelectrics, or detect defects by nondestructive test methods by use of sonar graphs or x-rays. However, these approaches are often expensive, time consuming and complicated.
The primary objective of this research was to apply a resistance based method of structural health monitoring to a composite structure to determine structural integrity and presence of defects.
The conductive properties of fiber such as carbon, copper, or constantan - a copper-nickel alloy - can be utilized as sensors within the structure. This allows the structure to provide feedback via electrical signals to a user which are essential for evaluating the health of the structure. In this research, the conductive fiber was made from constantan wire which was embedded within a composite laminate; whereas prepreg fiberglass, a nonconductive material, serves as the main structural element of the laminate. A composite laminate was constructed from four layers of TenCate 7781 “E” fiberglass and BT250E-1 resin prepreg. Integrating the constantan within the composite laminate provides a sensory element which supplies measurements of structural behavior. Thus, with fiberglass, epoxy, and a constantan conductive element, a three-part composite laminate is developed.
Test specimens used in this research were fabricated using a composite air press with the recommended manufacturer cure cycle. A TenCate BT250E-1 Resin System and 7781 "E" impregnated glass-fiber/epoxy weave was used. A constantan wire of 0.01” gauge diameter was integrated into the composite structure. The composite laminate specimen with the integrated SHM system was tested under tensile and flexural loads employing test standards specified by ASTM D3039 and D7264, respectively. These test methods were modified to determine the behavior of the laminate in the elastic range only. A tension and flexural delamination test case was also developed to investigate the sensitivity of the SHM system to inherent defects. Moreover, material characteristic tests were completed to validate manufacturer provided material characteristics. The specimens were tested while varying the constantan configurations, such as the sensor length and orientation. A variety of techniques to integrate the sensor were also investigated. Two different measurement methods were used to determine strain. Strain measurements were made with Instron Bluehill 2 software and correlated to strain obtained by the structural health monitoring system with the use of a data acquisition code written to interact with a micro-ohm-meter.
The experimental results showed good agreement between measurements made by the two different methods of measurement. Observations discovered that varying the length of the sensor element improved sensitivity, but resulted in different prediction models when compared to cases with less sensor length. The predictions are based on the gauge factor, which was determined for the each test case. This value provides the essential relationship between resistance and strain. Experiments proved that the measured gauge factor depended greatly on the sensor length and orientation. The correlation was of sufficient accuracy to predict strain values in a composite laminate without the use of any added tools or equipment besides the ohm-meter.
Analytical solutions to the loading cases were developed to validate results obtained during experiments. The solutions were in good agreement with the experimental results.
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Kuok, Sin Chi. "Ambient effects on structural health monitoring of buildings." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2099636.
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Guan, Hong. "Vibration-based structural health monitoring of highway bridges." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC IP addresses, 2006. http://wwwlib.umi.com/cr/ucsd/fullcit?p3211821.
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Hejll, Arvid. "Civil structural health monitoring : strategies, methods and applications /." Luleå : Division of Structural Engineering, Department of Civil and Mining Engineering, Luleå University of Technology, 2007. http://epubl.ltu.se/1402-1544/2007/10/.
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Konstantinidis, Georgios. "Structural health monitoring of plates using lamb waves." Thesis, University of Bristol, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495779.
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It is desirable for any structural health monitoring (SHM) system to achieve maximum sensitivity with minimum sensor density. This may be accomplished using guided waves. The structural health monitoring system described herein is based on the excitation and reception of guided waves using piezoelectric elements as sensors. One of the main challenges faced is that in all but the most simple structures the wave interactions become too complex for the time domain signals to be interpreted directly.
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Amraoui, Mohamed Yacine. "Non-invasive damage detection and structural health monitoring." Thesis, University of Bristol, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271865.
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Jesus, André H. "Modular Bayesian uncertainty assessment for structural health monitoring." Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/109522/.
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Civil infrastructure are critical elements to a society’s welfare and economic thriving. Understanding their behaviour and monitoring their serviceability are relevant challenges of Structural Health Monitoring (SHM). Despite the impressive improvement of miniaturisation, standardisation and diversity of monitoring systems, the ability to interpret data has registered a much slower progression across years. The underlying causes for such disparity are the overall complexity of the proposed challenge, and the inherent errors and lack of information associated with it. Overall, it is necessary to appropriately quantify the uncertainties which undermine the SHM concept. This thesis proposes an enhanced modular Bayesian framework (MBA) for structural identification (st-id) and measurement system design (MSD). The framework is hybrid, in the sense that it uses a physics-based model, and Gaussian processes (mrGp) which are trained against data, for uncertainty quantification. The mrGp act as emulators of the model response surface and its model discrepancy, also quantifying observation error, parametric and interpolation uncertainty. Finally, this framework has been enhanced with the Metropolis–Hastings for multiple parameters st-id. In contrast to other probabilistic frameworks, the MBA allows to estimate structural parameters (which reflect a performance of interest) consistently with their physical interpretation, while highlighting patterns of a model’s discrepancy. The MBA performance can be substantially improved by considering multiple responses which are sensitive to the structural parameters. An extension of the MBA for MSD has been validated on a reduced-scale aluminium bridge subject to thermal expansion (supported at one end with springs and instrumented with strain gauges and thermocouples). A finite element (FE) model of the structure was used to obtain a semi-optimal sensor configuration for stid. Results indicate that 1) measuring responses which are sensitive to the structural parameters and are more directly related to model discrepancy, provide the best results for st-id; 2) prior knowledge of the model discrepancy is essential to capture the latter type of responses. Subsequently, an extension of the MBA for st-id was also applied for identification of the springs stiffness, and results indicate relative errors five times less than other state of the art Bayesian/deterministic methodologies. Finally, a first application to field data was performed, to calibrate a detailed FE model of the Tamar suspension bridge using long-term monitored data. Measurements of temperature, traffic, mid-span displacement and natural frequencies of the bridge, were used to identify the bridge’s main/stay cables initial strain and friction of its bearings. Validation of results suggests that the identified parameters agree more closely with the true structural behaviour of the bridge, with an error that is several orders of magnitude smaller than other probabilistic st-id approaches. Additionally, the MBA allowed to predicted model discrepancy functions to assess the predictive ability of the Tamar bridge FE model. It was found, that the model predicts more accurately the bridge mid-span displacements than its natural frequencies, and that the adopted traffic model is less able to simulate the bridge behaviour during periods of traffic jams. Future developments of the MBA framework include its extension and application for damage detection and MSD with multiple parameter identification.
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Shi, Haichen. "On nonlinear cointegration methods for structural health monitoring." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/22301/.
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Structural health monitoring (SHM) is emerging as a crucial technology for the assessment and management of important assets in various industries. Thanks to the rapid developments of sensing technology and computing machines, large amounts of sensor data are now becoming much easier and cheaper to obtain from monitored structures, which consequently has enabled data-driven methods to become the main work forces for real world SHM systems. However, SHM practitioners soon discover a major problem for in-service SHM systems; that is the effect of environmental and operational variations (EOVs). Most assets (bridges, aircraft engines, wind turbines) are so important that they are too costly to be isolated for testing and examination purposes. Often, their structural properties are heavily in uenced by ambient environmental and operational conditions, or EOVs. So, the most important question raised for an effective SHM system is, how one could tell whether an alarm signal comes from structural damage or from EOVs? Cointegration, a method originating from econometric time series analysis, has proven to be one of the most promising approaches to address the above question. Cointegration is a property of nonstationary time series, it models the long-run relationship among multiple nonstationary time series. The idea of employing the cointegration method in the SHM context relies on the fact that this long-run relationship is immune to the changes caused by EOVs, but when damage occurs, this relationship no longer stands. The work in this thesis aims to further strengthen and extend conventional linear cointegration methods to a nonlinear context, by hybridising cointegration with machine learning and time series models. There are three contributions presented in this thesis: The first part is about a nonlinear cointegration method based on Gaussian process (GP) regression. Instead of using a linear regression, this part attempts to establish a nonlinear cointegrating regression with a GP. GP regression is a powerful Bayesian machine learning approach that can produce probabilistic predictions and avoid overfitting. The proposed method is tested with one simulated case study and with the Z24 Bridge SHM data. The second part concerns developing a regime-switching cointegration approach. Instead of modelling nonlinear cointegration as a smooth function, this part sees cointegration as a piecewise-linear function, which is triggered by some external variable. The model is trained with the aid of the augmented Dickey-Fuller (ADF) test statistics. Two case studies are presented in this part, one simulated mulitidegree-of-freedom system, and also the Z24 Bridge data. The third part of this work introduces a cointegration method for heteroscedastic data. Heteroscedasticity, or time-dependent noise is often observed in SHM data, normally caused by seasonal variations. In order to address this issue, the TBATS (an acronym for key features of the model: Trigonometric, Box-Cox transformation, ARMA error, Trend, Seasonal components) model is employed to decompose the seasonal-corrupted time series, followed by conventional cointegration analysis. A simulated cantilever beam and real measurement data from the NPL Bridge are used to validate the proposed method.
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Yang, Chen. "Vibration-based structural health monitoring of composite laminates." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/vibrationbased-structural-health-monitoring-of-composite-laminates(b762020d-f2c6-49ed-84ba-dfc2e3ece187).html.
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Over the past three decades, carbon-fibre reinforced plastics (CFRP) and glass fibre-reinforced plastics (GFRP) have been increasingly used in modern engineering designs to make composite laminated structures. This increase is due to their attractive mechanical performances and their stable physical and chemical properties. However, these composites are subjected to distinctive failure modes which are different from those of metallic alloys. These failure modes include delamination, matrix cracking and fibre breakage. Therefore, structural health monitoring (SHM) of composite laminated structures during the operational phase has become increasingly important. This thesis presents the development of vibration-based SHM approaches. A non-contact fibre optic sensor is developed for modal testing and structural health monitoring of composite laminate structures. Signal processing methods are used on the acquired modal data to produce a new damage index. The main investigations and contributions of the thesis are summarised as follows,1) A delamination detection method using additional mass loading and modal frequencies is numerically and experimentally studied. The study shows that the interaction between local inertia and delaminations affects the vibration characteristics of composite laminated beams for delaminations located at different depths. 2) A two-step delamination producing technique through mechanical pull-up is proposed and experimentally validated for composite laminated plates. The proposed technique overcomes the inadequate performance of PTFE inserts approach and shows the ability to produce both near surface and far surface delaminations at inaccessible regions from the boundaries. 3) A delamination detection approach using wavelet coefficients of the multiple-mode modal frequency curve for beam-like structures is developed. The method does not require the knowledge of the intact state nor the use of artificial noise filtering procedures.4) The proposed intact-free wavelet coefficients of modal frequency surface are further applied to two-dimensional composite laminate plate-like structures. In conjunction with the wavelet-based edge detection method in imaging processing, the proposed method shows the satisfactory performance in delamination identification and localisation for laminate plates.5) A cost-effective non-contact fibre optic displacement sensor is developed based on the theoretical model. The parameters of the sensor are calibrated following standard procedures. The sensor shows satisfactory performance in structural modal testing. 6) The application of the developed fibre optic sensor in structural health monitoring for composite laminate structures is demonstrated by experiments and its performance is compared with that of commercial sensors.
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Dodson, Jacob Christopher. "Guided Wave Structural Health Monitoring with Environmental Considerations." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27070.
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Damage detection in mechanical and aerospace structures is critical to maintaining safe
and optimal performance. The early detection of damage increases safety and reduces cost
of maintenance and repair. Structural Health Monitoring (SHM) integrates sensor networks
and structures to autonomously interrogate the structure and detect damage. The
development of robust SHM systems is becoming more vital as aerospace structures are
becoming more complex. New SHM methods that can determine the health of the structure
without using traditional non-destructive evaluation techniques will decrease the cost
and time associated with these investigations. The primary SHM method uses the signals
recorded on a pristine structure as a reference and compares operational signals to the
baseline measurement. One of the current limitations of baseline SHM is that environmental
factors, such as temperature and stress, can change the system response so the
algorithm indicates damage when there is none. Many structures which can benefit from
SHM have multiple components and often have connections and interfaces that also can
change under environmental conditions, thus changing the dynamics of the system.
This dissertation addresses some of the current limitations of SHM. First the changes
that temperature variations and applied stress create on Lamb wave propagation velocity
in plates is analytically modeled and validated. Two methods are developed for the
analytical derivative of the Lamb wave velocity; the first uses assumes a thermoelastic material
while the second expands thermoelastic theory to include thermal expansion and
the associated stresses. A model is developed so the baseline measurement can be compensated
to eliminate the false positives due to environmental conditions without storage
of dispersion curves or baseline signals at each environmental state. Next, a wave based
instantaneous baseline method is presented which uses the comparison of simultaneously
captured real time signals and can be used to eliminate the influence of environmental effects
on damage detection. Finally, wave transmission and conversion across interfaces in
prestressed bars is modeled to provide a better understanding of how the coupled axial
and flexural dynamics of a non-ideal preloaded interface change with applied load.Ph. D.
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Anton, Steven Robert. "Baseline-Free and Self-Powered Structural Health Monitoring." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/33731.
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The research presented in this thesis is based on improving current structural health monitoring (SHM) technology. Structural health monitoring is a damage detection technique that involves placing intelligent sensors on a structure, periodically recording data from the sensors, and using statistical methods to analyze the data in order to assess the condition of the structure. This work focuses on improving two areas of SHM; baseline management and energy supplies. Several successful SHM methods have been developed in which prerecorded baseline measurements are compared to current measurements in order to identify damage. The need to compare new data to a prerecorded baseline can present several complications including data management issues and difficulty in controlling the effects of varying environmental conditions on the data. Another potential area for improvement in SHM systems deals with their energy supplies. Many SHM systems currently require wired power supplies or batteries to operate. Practical SHM applications often require inexpensive, stand alone sensors, data acquisition, and processing hardware that does not require maintenance.
To address the issue of baseline management, a novel SHM technique is developed. This new method accomplishes instantaneous baseline measurements by deploying an array of piezoelectric sensors/actuators used for Lamb wave propagation-based SHM such that data recorded from equidistant sensor-actuator paths can be used to instantaneously identify several common features of undamaged paths. Once identified, features from these undamaged paths can be used to form a baseline for real-time damage detection. This method utilizes the concept of sensor diagnostics, a recently developed technique that minimizes false damage identification and measurement distortion caused by faulty sensors. Several aspects of the instantaneous baseline damage detection method are explored in this work including the implementation of sensor diagnostics, determination of the features best used to identify damage, development of signal processing algorithms used to analyze data, and the comparison of two sensor/actuator deployment schemes.
The ultimate goal in the development of practical SHM systems is to create autonomous damage detection systems. A limiting factor in current SHM technology is the energy supply required to operate the system. Many existing SHM systems utilize wired power supplies or batteries to power sensors, data transmission, data acquisition, and data processing hardware. Although batteries eliminate the need to run wires to SHM hardware, their periodic replacement requires components to be placed in easily accessible locations which is not always practical, especially in embedded applications. Additionally, there is a high cost associated with battery monitoring and replacement. In an effort to eliminate replaceable energy supplies in SHM systems, the concept of energy harvesting is investigated. Energy harvesting devices are designed to capture surrounding ambient energy and convert it into usable electrical energy. Several types of energy harvesting exist, including vibration, thermal, and solar harvesting. A solar energy harvesting system is developed for use in powering SHM hardware. Integrating energy harvesting technology into SHM systems can provide autonomous health monitoring of structures.
Master of Science
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Simmers, Garnett E. Jr. "Impedance-Based Structural Health Monitoring to Detect Corrosion." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/32636.
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Corrosion begins as moisture penetrates the protective barrier of a surface, starting an electrochemical process which over time leads to surface pitting. The combined action of mechanical stresses and corrosion induced pitting reduces structural integrity as the pits enlarge to form nucleation sites for surface cracks, which propagate into through-thickness cracks. In most cases, the total mass loss due to corrosion within the structure is small; however, significant reductions in mechanical strength and fatigue life can occur in the corroded material leading to advanced crack growth rates or fast fracture. Since the structural damage due to localized corrosion pitting is small and the crack growth rates may be large, traditional inspections methods and â find it and fix itâ maintenance approaches may lead to catastrophic mechanical failures.
Therefore, precise structural health monitoring of pre-crack surface corrosion is paramount to understanding and predicting the effect corrosion has on the fatigue life and integrity of a structure. In this first third of this study, the impedance method was experimentally tested to detect and the onset and growth of the earliest stages of pre-crack surface corrosion in beam and plate like structures. Experimental results indicate the impedance method is an effective detection tool for corrosion induced structural damage in plates and beams. For corrosion surface coverages less than 1.5% and pit depths of less than 25 microns (light corrosion), the impedance method could successfully detect corrosion on plates and beams at distances up to 150 cm from the sensor location.
Since the impedance method is a proven tool for corrosion detection, it makes sense to determine how well the method can quantify and track key corrosion variables like location, pit depth, and surface coverage. In order to make fatigue life adjustments for corroded structures it is necessary to quantify those variables. Thus, the second portion of this study uses the impedance method to quantify corrosion location, pit depth, and location. Three separate tests are conducted on beam-like structures to determine how well the damage metrics from the impedance method correlate to the key corrosion variables. From the three tests, it is found that the impedance method correlates best with the changes in corrosion pit depth, so if combined with data from routine maintenance it would be possible to use the impedance method data in a predictive or tracking manner. The impedance method can be correlated to location and surface coverage changes, but the relationship is not as strong. Other NDE techniques like Lamb Waves could use the same sensors to quantify corrosion location, and perhaps surface coverage.
The impedance method can detect and quantify pre-crack surface corrosion which leads to shortened fatigue life in structures; however, the sensors must be robust enough to withstand corrosive environments. The last portion of this study tests the following: corrosive effect on Lead Zirconate Titnate (PZT) and Macro Fiber Composites (MFC) sensors, Kapton protected MFC actuators for corrosion detection, and determines if corrosion damage can be sensed on the side of the structure opposite the damage. Sensor recommendations regarding the use of piezoelectric sensors in corrosive environments are made.Master of Science
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Shiryayev, Oleg V. "Improved Structural Health Monitoring Using Random Decrement Signatures." Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1214234132.
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Cicero, Tindaro. "Signal processing for guided wave structural health monitoring." Thesis, Imperial College London, 2009. http://hdl.handle.net/10044/1/5302.
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The importance of Structural Health Monitoring (SHM) in several industrial fields has been continuously growing in the last few years with the increasing need for the development of systems able to monitor continuously the integrity of complex structures. In order to be competitive with conventional non destructive evaluation techniques, SHM must be able to effectively detect the occurrence of damage in the structure, giving information regarding the damage location. Ultrasonic guided waves offer the possibility of inspecting large areas of structures from a small number of sensor positions. However, inspection of complex structures is difficult as the reflections from different features overlap. Therefore damage detection becomes an extremely challenging problem and robust signal processing is required in order to resolve strongly overlapping echoes. In our work we have considered at first the possibility of employing a deconvolution approach for enhancing the resolution of ultrasonic time traces and the potential and the limitations of this approach for reliable SHM applications have been shown. The effects of noise on the bandwidth of the typical signals in SHM and the effects of frequency dependent phase shifts are the main detrimental issues that strongly reduce the performance of deconvolution in SHM applications. The second part of this thesis is concerned with the evaluation of a subtraction approach for SHM when changes of environmental conditions are taken into account. Temperature changes result in imperfect subtraction even for an undamaged structure, since temperature changes modify the mechanical properties of the material and therefore the velocity of propagation of ultrasonic guided waves. Compensation techniques have previously been used effectively to overcome temperature effects, in order to reduce the residual in the subtraction. In this work the performance of temperature compensation techniques has been evaluated also in the presence of other detrimental effects, such as liquid loading and different temperature responses of materials in adhesive joints. Numerical simulations and experiments have been conducted and it has been shown that temperature compensation techniques can cope in principle with non temperature effects. It is concluded that subtraction approach represents a promising method for reliable Structural Health Monitoring. Nonetheless the feasibility of a subtraction approach for SHM depends on environmental conditions.
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Sharma, Vinod K. "Laser doppler vibrometer for efficient structural health monitoring." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26708.
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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009.Committee Chair: Hanagud, Sathya; Committee Member: Apetre, Nicole; Committee Member: Engelstad, Steve; Committee Member: Glass, Brian; Committee Member: Kardomateas, George; Committee Member: Ruzzene, Massimo. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Zhang, Jian. "Advanced signal processing technique for structural health monitoring." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/136142.
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Fan, Xingyu. "Electromechanical Impedance-based Techniques for Structural Health Monitoring." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/75614.
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New developments on electromechanical impedance (EMI) based structure health monitoring techniques are presented in this thesis. Time frequency auto-regressive moving average (TFARMA) model based damage indicator is developed to enhance the sensitivity of EMI based method for structural damage detection. An innovative approach by using impedance sensitivity-based model updating and sparse regularization techniques is developed for structural damage localization and quantification. Numerical and experimental studies are conducted to verify the performance of the proposed approaches.
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Zonzini, Federica <1994>. "Intelligent Sensor Systems for Structural Health Monitoring Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10141/4/Zonzini_Federica_Tesi.pdf.
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The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner.
To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing.
In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.
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Cappello, Carlo. "Theory of Decision Based on Structural Health Monitoring." Doctoral thesis, Università degli studi di Trento, 2017. https://hdl.handle.net/11572/368420.
Full textAbstract:
The average age of strategic constructions in the Western world is becoming higher and higher. Many of these structures need inspection, maintenance or replacement, resulting in significant costs. The accurate estimate of structural condition can make operators optimize the allocation of resources. Nowadays, the progress of technology and machine learning has made structural health monitoring appealing to the agencies that manage important structures. This has encouraged the research community in the study of new structural health monitoring methods. In spite of this, the use of monitoring data is often disregarded by practitioners, who still prefer to gather more information and then act based on experience. Similarly, unlike the design of civil structures, the design of structural health monitoring systems is carried out based on heuristics rather than on rigorous evaluations of the expected monitoring system effectiveness. In this doctoral thesis, I apply expected utility theory for the development of decision support systems to be used in structural health monitoring and I develop a procedure for the design of structural health monitoring systems that follows the scheme of semi-probabilistic structural design. The use of monitoring data in a decision support system that implements expected utility theory financially optimizes the management of civil structures. The proposed monitoring system design method enables practitioners to design monitoring systems using their experience and guarantees that the installation of a monitoring solution is financially convenient. I present the mathematical formulation for monitoring-based decision support systems and monitoring system design. Then, I propose the numerical algorithms for the development of monitoring-based decision support systems and solutions for monitoring data analysis. Finally, the proposed methods are applied to three case studies, which enabled me to discuss the application in real life and the hypotheses. The applications show also the feasibility of the proposed approaches and test the numerical algorithms.
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Cappello, Carlo. "Theory of Decision Based on Structural Health Monitoring." Doctoral thesis, University of Trento, 2017. http://eprints-phd.biblio.unitn.it/2570/1/Theory_of_Decision_Based_on_Structural_Health_Monitoring_-_PhD_thesis_by_Carlo_Cappello.pdf.
Full textAbstract:
The average age of strategic constructions in the Western world is becoming higher and higher. Many of these structures need inspection, maintenance or replacement, resulting in significant costs. The accurate estimate of structural condition can make operators optimize the allocation of resources. Nowadays, the progress of technology and machine learning has made structural health monitoring appealing to the agencies that manage important structures. This has encouraged the research community in the study of new structural health monitoring methods. In spite of this, the use of monitoring data is often disregarded by practitioners, who still prefer to gather more information and then act based on experience. Similarly, unlike the design of civil structures, the design of structural health monitoring systems is carried out based on heuristics rather than on rigorous evaluations of the expected monitoring system effectiveness. In this doctoral thesis, I apply expected utility theory for the development of decision support systems to be used in structural health monitoring and I develop a procedure for the design of structural health monitoring systems that follows the scheme of semi-probabilistic structural design. The use of monitoring data in a decision support system that implements expected utility theory financially optimizes the management of civil structures. The proposed monitoring system design method enables practitioners to design monitoring systems using their experience and guarantees that the installation of a monitoring solution is financially convenient. I present the mathematical formulation for monitoring-based decision support systems and monitoring system design. Then, I propose the numerical algorithms for the development of monitoring-based decision support systems and solutions for monitoring data analysis. Finally, the proposed methods are applied to three case studies, which enabled me to discuss the application in real life and the hypotheses. The applications show also the feasibility of the proposed approaches and test the numerical algorithms.
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Thiene, Marco. "Study of Innovative Techniques for Structural Health Monitoring." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423520.
Full textAbstract:
This thesis aims at developing new methodologies to determine the structural integrity of aeronautical components. The increasing use of composite materials, which present damage initiation and evolution different from the homogeneous ones, requires the development of new techniques to determine the performance of the most critical components. Structural health monitoring (SHM) is a field of research which aims at developing new methods to perform this task. One of the main concerns is given by initially barely visible impact damage (BVID), which can grow during operational time and eventually lead to catastrophic failures. The monitoring can be accomplished both with active and passive methods. In this thesis the part of SHM which concerns the development of algorithms for damage and impact detection is addressed. First a damage detection approach based on the proper orthogonal decomposition (POD) is developed. Analyses on different components are performed, in particular detecting defects without needing any baseline. Particularly important is the application of the proposed approach to a stiffened panel, which has not been deeply analysed in literature. The second part of the thesis concerns impact detection and force reconstruction. In particular the attention is focused on large mass impacts, which can produce geometrical nonlinearities in the dynamics of the system. Finally a novel impact location algorithm, based on the POD is proposed. This represents a novelty in impact location algorithms, which have previously been focused on the triangulation method. In particular the proposed approach is not dependent on the wave velocity, which is a major limitation in the application of the triangulation on composite panels. Remarkable results are obtained in this thesis. In particular experimental verifications are performed on damage detection using only data coming from a damaged system and on force reconstruction on a composite panel.Numerosi fattori spingono l‟industria aeronautica verso l‟utilizzo di materiali innovativi da impiegare nelle struttutre dei veivoli. In particolare l‟esigenza di contenere il consumo di carburante, con la conseguente riduzione dei costi e delle emissioni, ha portato allo sviluppo di nuovi aerei in cui una parte della struttura è da realizzata in materiali compositi; l‟esempio più recente è rappresentato dal Boeing 787 Dreamliner in cui oltre il 50% della struttura è costituito da materiale composito. Le elevate caratteristiche meccaniche di questi materiali sono tuttavia accompagnate da meccanismi di danneggiamento non ancora del tutto conosciuti. Questo fa sì che il loro utilizzo richieda un programma di manutenzione dedicato, che influisce in maniera considerevole sui costi di gestione del singolo veivolo. Per questo motivo la ricerca scientifica si è concentrata negli ultimi anni sullo sviluppo di nuove metodologie per monitorare l‟integrità strutturale dei principali componenti dei veivoli. L‟obbiettivo finale di questa ricerca è sviluppare un sistema di controllo che funzioni in tempo reale, che possa cioè individuare eventuali danni nella struttura mentre il veivolo è in volo. In questo modo non solo si potrebbero evitare catastrofici incidenti, ma anche limitare le manutenzioni programmate, che spesso risultano essere non necessarie in quanto la struttura potrebbe non presentare alcuna criticità. Il campo ingengeristico che si occupa di questa innovazione è definito structural health monitoring (SHM). Dal punto di vista del rilevamento di un possible danno nella struttura, due differenti approcci possono essere seguiti. Il primo, chiamato attivo, richiede l‟utilizzo di uno stimolo che ecciti la dinamica della struttura. Dalla risposta, raccolta mediante un certo numero di sensori, è possibile determinare se un danno è presente. Il secondo approccio, denominato passivo, non richiede alcuno stimolo, in quanto un‟eventuale forzante esterna è proprio l‟evento che si vuole monitorare; la tipica applicazione di questo metodo riguarda il montoraggio di impatti. La ricerca svolta in questa tesi prevede lo studio di entrambi gli approcci. Nella prima parte, una tecnica attiva, basata sulla proper orthogonal decomposition (POD) e sul gapped smoothing method (GSM), è analizzata con lo scopo di localizzare un possibile danno all‟interno di tipici componenti aeronautici. Diverse posizioni del danno sono analizzate. La principale innovazione consiste nello studio di un pannello rinforzato, che in letteratura non è mai stato trattato in dettaglio con metodi basati su forme modali. Nella seconda parte della tesi è studiato un metodo passivo. Sono trattati due casi: la ricostruzione della forza d‟impatto e la localizzazione dello stesso. Nel primo caso il metodo sviluppato risulta in grado di predire correttamente la forza anche nel caso in cui la risposta del componente sia nonlineare. Nel secondo caso l‟applicazione della POD per localizzare impatti rappresenta una novità nel relativo campo di ricerca. La tesi è articolata nel modo seguente. Il primo capitolo fornisce un panorama generale sul perché il monitoraggio strutturale sia importante in ambito aeronautico. I Capitoli 2 e 3 introducono la formulazione matematica utilizzata per il rileamento del danno. Nel Capitolo 4 vengono presentati i risultati relativi all‟individuazione del danno mediante POD e GSM. Nel Capitolo 5 si illustra la formulazione matematica relativa ai metodi passivi. In particolare sono descritti in dettaglio gli innovativi algoritmi utilizzati. Il Capitolo 6 presenta i risultati relativi al monitoraggio d‟impatti. I miglioramenti rispetto ad approcci classici sono evidenziati in modo particolare . Nelle conclusioni vengono riproposti i principali risultati ottenuti nei capitoli precedenti. Alla fine della tesi numerose appendici approfondiscono alcuni argomenti che vengono parzialmente trattati nel corso dei vari capitoli.
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Pawar, Prashant M. "Structural Health Monitoring Of Composite Helicopter Rotor Blades." Thesis, Indian Institute of Science, 2006. https://etd.iisc.ac.in/handle/2005/273.
Full textAbstract:
Helicopter rotor system operates in a highly dynamic and unsteady aerodynamic environment leading to severe vibratory loads on the rotor system. Repeated exposure to these severe loading conditions can induce damage in the composite rotor blade which may lead to a catastrophic failure. Therefore, an interest in the structural health monitoring (SHM) of the composite rotor blades has grown markedly in recent years. Two important issues are addressed in this thesis; (1) structural modeling and aeroelastic analysis of the damaged rotor blade and (2) development of a model based rotor health monitoring system. The effect of matrix cracking, the first failure mode in composites, is studied in detail for a circular section beam, box-beam and two-cell airfoil section beam. Later, the effects of further progressive damages such as debonding/delamination and fiber breakage are considered for a two-cell airfoil section beam representing a stiff-inplane helicopter rotor blade. It is found that the stiffness decreases rapidly in the initial phase of matrix cracking but becomes almost constant later as matrix crack saturation is reached. Due to matrix cracking, the bending and torsion stiffness losses at the point of matrix crack saturation are about 6-12 percent and about 25-30 percent, respectively. Due to debonding/delamination, the bending and torsion stiffness losses are about 6-8 percent and about 40-45 percent after matrix crack saturation, respectively. The stiffness loss due to fiber breakage is very rapid and leads to the final failure of the blade. An aeroelastic analysis is performed for the damaged composite rotor in forward flight and the numerically simulated results are used to develop an online health monitoring system. For fault detection, the variations in rotating frequencies, tip bending and torsion response, blade root loads and strains along the blade due to damage are investigated. It is found that peak-to-peak values of blade response and loads provide a good global damage indicator and result in considerable data reduction. Also, the shear strain is a useful indicator to predict local damage. The structural health monitoring system is developed using the physics based models to detect and locate damage from simulated noisy rotor system data. A genetic fuzzy system (GFS) developed for solving the inverse problem of detecting damage from noise contaminated measurements by hybridizing the best features of fuzzy logic and genetic algorithms. Using the changes in structural measurements between the damaged and undamaged blade, a fuzzy system is generated and the rule-base and membership functions optimized by genetic algorithm. The GFS is demonstrated using frequency and mode shape based measurements for various beam type structures such as uniform cantilever beam, tapered beam and non-rotating helicopter blade. The GFS is further demonstrated for predicting the internal state of the composite structures using an example of a composite hollow circular beam with matrix cracking damage mode. Finally, the GFS is applied for online SHM of a rotor in forward flight. It is found that the GFS shows excellent robustness with noisy data, missing measurements and degrades gradually in the presence of faulty sensors/measurements. Furthermore, the GFS can be developed in an automated manner resulting in an optimal solution to the inverse problem of SHM. Finally, the stiffness degradation of the composite rotor blade is correlated to the life consumption of the rotor blade and issues related to damage prognosis are addressed.
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Pawar, Prashant M. "Structural Health Monitoring Of Composite Helicopter Rotor Blades." Thesis, Indian Institute of Science, 2006. http://hdl.handle.net/2005/273.
Full textAbstract:
Helicopter rotor system operates in a highly dynamic and unsteady aerodynamic environment leading to severe vibratory loads on the rotor system. Repeated exposure to these severe loading conditions can induce damage in the composite rotor blade which may lead to a catastrophic failure. Therefore, an interest in the structural health monitoring (SHM) of the composite rotor blades has grown markedly in recent years. Two important issues are addressed in this thesis; (1) structural modeling and aeroelastic analysis of the damaged rotor blade and (2) development of a model based rotor health monitoring system. The effect of matrix cracking, the first failure mode in composites, is studied in detail for a circular section beam, box-beam and two-cell airfoil section beam. Later, the effects of further progressive damages such as debonding/delamination and fiber breakage are considered for a two-cell airfoil section beam representing a stiff-inplane helicopter rotor blade. It is found that the stiffness decreases rapidly in the initial phase of matrix cracking but becomes almost constant later as matrix crack saturation is reached. Due to matrix cracking, the bending and torsion stiffness losses at the point of matrix crack saturation are about 6-12 percent and about 25-30 percent, respectively. Due to debonding/delamination, the bending and torsion stiffness losses are about 6-8 percent and about 40-45 percent after matrix crack saturation, respectively. The stiffness loss due to fiber breakage is very rapid and leads to the final failure of the blade. An aeroelastic analysis is performed for the damaged composite rotor in forward flight and the numerically simulated results are used to develop an online health monitoring system. For fault detection, the variations in rotating frequencies, tip bending and torsion response, blade root loads and strains along the blade due to damage are investigated. It is found that peak-to-peak values of blade response and loads provide a good global damage indicator and result in considerable data reduction. Also, the shear strain is a useful indicator to predict local damage. The structural health monitoring system is developed using the physics based models to detect and locate damage from simulated noisy rotor system data. A genetic fuzzy system (GFS) developed for solving the inverse problem of detecting damage from noise contaminated measurements by hybridizing the best features of fuzzy logic and genetic algorithms. Using the changes in structural measurements between the damaged and undamaged blade, a fuzzy system is generated and the rule-base and membership functions optimized by genetic algorithm. The GFS is demonstrated using frequency and mode shape based measurements for various beam type structures such as uniform cantilever beam, tapered beam and non-rotating helicopter blade. The GFS is further demonstrated for predicting the internal state of the composite structures using an example of a composite hollow circular beam with matrix cracking damage mode. Finally, the GFS is applied for online SHM of a rotor in forward flight. It is found that the GFS shows excellent robustness with noisy data, missing measurements and degrades gradually in the presence of faulty sensors/measurements. Furthermore, the GFS can be developed in an automated manner resulting in an optimal solution to the inverse problem of SHM. Finally, the stiffness degradation of the composite rotor blade is correlated to the life consumption of the rotor blade and issues related to damage prognosis are addressed.
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Jaswal, Priya. "Health Monitoring of Large Composite Structures." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562842764406158.
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Tibaduiza, Burgos Diego Alexander. "Design and validation of a structural health monitoring system for aeronautical structures." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/116811.
Full textAbstract:
Structural Health Monitoring (SHM) is an area where the main objective is the verification of the state or the health of the structures in order to ensure proper performance and maintenance cost savings using a sensor network attached to the structure, continuous monitoring and algorithms. Different benefits are derived from the implementation of SHM, some of them are: knowledge about the behavior of the structure under different loads and different environmental changes, knowledge of the current state in order to verify the integrity of the structure and determine whether a structure can work properly or whether it needs to be maintained or replaced and, therefore, to reduce maintenance costs. The paradigm of damage identification (comparison between the data collected from the structure without damages and the current
structure in orderto determine if there are any changes) can be tackled as a pattern recognition problem. Some statistical techniques as Principal Component Analysis (PCA) or Independent Component Analysis (ICA) are very useful for this purpose because they allow obtaining the most relevant information from a large amount of variables.
This thesis uses an active piezoelectric system to develop statistical data driven approaches for the detection, localization and classification of damages in structures. This active piezoelectric system is permanently attached to the surface of the structure under test in order to apply vibrational excitations and sensing the dynamical responses propagated through the structure at different points. As pattern recognition technique, PCA is used to perform the main task of the proposed methodology: to build a base-line model of the structure without damage and subsequentlyto compare the data from the current structure (under test) with this model. Moreover, different damage indices are calculated to detect abnormalities in the structure under test. Besides, the localization of the damage can be determined by means of the contribution of each sensor to each index. This contribution is calculated by several different methods and their comparison is performed. To classify different damages, the damage detection methodology is extended using a Self-Organizing Map (SOM), which is properly trained and validated to build a pattern baseline model using projections of the data onto the PCAmodel and damage detection indices. This baseline is further used as a reference for blind diagnosis tests of structures. Additionally, PCA is replaced by ICAas pattern recognition technique. A comparison between the two methodologies is performed highlighting advantages and disadvantages. In order to study the performance of the damage classification methodology under different scenarios, the methodology is tested using data from a structure under several different temperatures.
The methodologies developed in this work are tested and validated using different structures, in particular an aircraft turbine blade, an aircraft wing skeleton, an aircraft fuselage,some aluminium plates and some composite matarials plates.La monitorización de daños en estructuras (SHM por sus siglas en inglés) es un área que tiene como principal objetivo la verificación del estado o la salud de la estructura con el fin de asegurar el correcto funcionamiento de esta y ahorrar costos de mantenimiento. Para esto se hace uso de sensores que son adheridos a la estructura, monitorización continua y algoritmos. Diferentes beneficios se obtienen de la aplicación de SHM, algunos de ellos son: el conocimiento sobre el desempeño de la estructura cuando esta es sometida a diversas cargas y cambios ambientales, el conocimiento del estado actual de la estructura con el fin de determinar la integridad de la estructura y definir si esta puede trabajar adecuadamente o si por el contrario debe ser reparada o reemplazada con el correspondiente beneficio del ahorro de gastos de mantenimiento. El paradigma de la identificación de daños (comparación entre los datos obtenidos de la estructura sin daños y la estructura en un estado posterior para determinar cambios) puede ser abordado como un problema de reconocimiento de patrones. Algunas técnicas estadísticas tales como Análisis de Componentes Principales (PCA por sus siglas en inglés) o Análisis de Componentes Independientes (ICA por sus siglas en ingles) son muy útiles para este propósito puesto que permiten obtener la información más relevante de una gran cantidad de variables. Esta tesis hace uso de un sistema piezoeléctrico activo para el desarrollo de algoritmos estadísticos de manejo de datos para la detección, localización y clasificación de daños en estructuras. Este sistema piezoeléctrico activo está permanentemente adherido a la superficie de la estructura bajo prueba con el objeto de aplicar señales vibracionales de excitación y recoger las respuestas dinámicas propagadas a través de la estructura en diferentes puntos. Como técnica de reconocimiento de patrones se usa Análisis de Componentes Principales para realizar la tarea principal de la metodología propuesta: construir un modelo PCA base de la estructura sin daño y posteriormente compararlo con los datos de la estructura bajo prueba. Adicionalmente, algunos índices de daños son calculados para detectar anormalidades en la estructura bajo prueba. Para la localización de daños se usan las contribuciones de cada sensor a cada índice, las cuales son calculadas mediante varios métodos de contribución y comparadas para mostrar sus ventajas y desventajas. Para la clasificación de daños, se amplia la metodología de detección añadiendo el uso de Mapas auto-organizados, los cuales son adecuadamente entrenados y validados para construir un modelo patrón base usando proyecciones de los datos sobre el modelo PCA base e índices de detección de daños. Este patrón es usado como referencia para realizar un diagnóstico ciego de la estructura. Adicionalmente, dentro de la metodología propuesta, se utiliza ICA en lugar de PCA como técnica de reconocimiento de patrones. Se incluye también una comparación entre la aplicación de las dos técnicas para mostrar las ventajas y desventajas. Para estudiar el desempeño de la metodología de clasificación de daños bajo diferentes escenarios, esta se prueba usando datos obtenidos de una estructura sometida a diferentes temperaturas. Las metodologías desarrolladas en este trabajo fueron probadas y validadas usando diferentes estructuras, en particular un álabe de turbina, un esqueleto de ala y un fuselaje de avión, así como algunas placas de aluminio y de material compuesto