Graphene nanoplatelets have been introduced into the interphase between electrically insulating glass fibre and polymer matrix to functionalize the traditional composite. Owing to the distribution of network structure of GNPs, the interphase can transfer the signals about various internal change of material. Consequently, due to the novel bio-inspired overlapping structure, our GNPs-glass fibre shows a unique opportunity as a micro-scale multifunctional sensor. The following conclusions can be drawn from present research: • We prepared GNPs solution via a scalable and highly effective liquid-phase exfoliation method. This method produces high-quality, unoxidized graphene flakes from flake graphite. We control the thickness and size of GNPs by varying the centrifugation rate. • A simple fibre oriented capillary flow which can suppress ‘coffee ring’ effect to deposit GNPs onto the curved glass fibre surface. The GNPs form continuous fish scales like overlapping structure. • The electrical conductivity of our GNPs-glass fibre shows semiconductive property. The electrical resistance value scattering and the advancing contact angle value scattering indicate a uniform deposit structure. The uniform overlapping structure is a key factor for higher electrical conductivity compared with our previous work with CNTs. • The contact angles of our GNPs-glass fibre with water indicate that the GNPs are almost unoxidized, so the inert GNPs coating decreases the interfacial shears strength. • A micro scale GNPs-glass fibre sensor for gas sensing is achieved by deposit GNPs onto glass fibre surface. This sensor can be used to detect solvents vapours, such as water, ethanol and acetone. All these vapours work as electron acceptor when reacting with GNPs. The acetone shows the highest sensitivity (45000%) compared with water and ethanol. • The doping-dedoping of GNPs-glass fibres during adsorption-desorption cycles of acetone result in the efficient “break-junction” (GNPs lost electron carrier concentration) mechanism, which provides the possibility to fabricate the electrochemical “switch” in a simple and unique way. • The resistance of our GNPs-glass fibre shows exponential relationship with RH. This is attributed to two points. Firstly, the water vapours show similar exponential adsorption on carbon surface; secondly, the bandgap of GNPs increases with the increase of adsorbed water vapour concentration. • Due to the weak van der Waals interaction when water molecules are adsorbed on GNPs surface, our GNPs-glass fibre shows extreme fast response and recovery time with RH. It is potential for our GNPs-glass fibre being used to monitor the breath frequency. • Utilizing the negative temperature coefficient of GNPs, our GNPs-glass fibre can be used as temperature sensor with a sensing region of -150 to 30 °C. • Through the observed abnormal resistance change at a temperature of about – 18 °C, we discovered a phase change of the trance confined water in graphene layers. Based on the resistance change, we can study the interaction of water and carbon nanoparticles. • The bio-inspired novel overlapped multilayer structure of GNPs coating shows structural colours. Even more, our GNPs-glass fibre can be used to monitor the loading force in the interphase when it is embedded into epoxy resin. • Our GNPs-glass fibre shows an excellent piezoresistive property, the single GNPs-glass fibre shows a larger gauge factor than the commercial strains sensor. • The semiconductive interphase was formed when the GNPs-glass fibre was embedded in polymer matrix. This semiconductive interphase is very sensitive to the deformation of material, therefore, an in-situ strain sensor was manufactured to real-time monitor the microcracks in a composite instead of external sensors. The area of resistance ‘jump’ increase can be seen as the feature area for damage’s early warning. • Monitoring the resistance variation of the single fibre composite was conducted under cyclic loading with progressively increasing the strain peaks in order to further investigate the response of in-situ sensor to the interphase damage process. The deviation of resistance/strain when the stress is larger than 2 % highlights the accumulation of damage, which gives insight into the mechanism of resistance change.

During vibration of engineering structures, fatigue cracks may exhibit repetitive crack open-close breathing like phenomenon. In this thesis, the concept of entropy is employed to quantify this bi-linearity/irregularity of the vibration response so as to evaluate crack severity. To increase the sensitivity of the entropy calculation to detect the damage severity, entropy is merged with wavelet transformation (WT). A cantilever beam with a breathing crack is studied to asses proposed crack identification method under two vibration conditions: sinusoidal and random excitations. Through numerical simulations and experimental testing, the breathing crack identification under sinusoidal excitation is studied first and proven to be effective. Then, the crack identification sensitivity under lower excitation frequencies is further improved by parametric optimization of sample entropy and WT. Finally, breathing crack identification under general random excitations are experimentally studied and realized using frequency response functions (FRFs) as an add-in tool with the proposed crack identification technique. / October 2016

Orientador: Fábio Roberto Chavarette / Resumo: Redes Neurais Artificiais (RNAs) são algoritmos de aprendizado, geralmente estruturados em torno de categorização de dados de entrada e/ou seu agrupamento por similaridade. Tendo em vista características desejáveis como aprendizado rápido e estabilidade frente a vetores de entrada altamente mutáveis, adotou-se uma RNA do tipo Fuzzy ARTMAP como mecanismo central de um método de monitoramento de saúde estrutural para detectar e categorizar falhas em dados experimentais provenientes de um sistema mecânico similar a um pequeno prédio de dois andares. Mais especificamente, com o objetivo de detectar alterações das frequências naturais da estrutura, fenômeno ligado à deterioração da mesma, e determinar qual(is) andar(es) está(ão) ligado(s) ao comportamento anômalo, se detectado. A acurácia da rede foi avaliada, sendo realizado um estudo da quantidade de dados necessárias para o desempenho satisfatório da rede. Observou-se desempenho satisfatório, a acurácia do método tendendo a aproximadamente 94% a partir de certas quantidades de dados. / Abstract: Artificial Neural Networks (ANNs) are learning algorithms, largely revolving around categorizing data sets based on measures of similarity between its members. Due to desirable characteristics such as fast learning and stability when dealing with highly mutable input vectors, a Fuzzy ARTMAP ANN was selected as the core mechanism of a structural health monitoring method. Its goal was to detect and categorize faults in experimental data collected from a mechanical system akin to a small two-story building. More specifically, to detect disturbances on the structure's natural frequencies, phenomenon linked to its deterioration, and to determine which story or stories are linked to anomalous behavior, if any. The accuracy of the method was evaluated, and the amount of data needed for optimal operation was determined. Satisfactory performance was observed; the method's accuracy tended towards 94% with enough training samples. / Mestre

La détection d'impacts est une préoccupation majeure pour suivre l'intégrité d'une structure évoluant dans un environnement comportant des risques de collision. Ce travail consiste à développer une méthode d’identification d'impact applicable à une structure composite de grandes dimensions qui soit à la fois robuste, peu coûteuse en temps de calcul, et qui nécessite peu de capteurs. Dans un premier temps, la démarche a été de décrire l'image du point d'impact dans la réponse vibratoire par un vecteur de participations modales. L'idée a ensuite été d'introduire l'hypothèse d'existence d'une famille de modes discriminants permettant d'établir le lien bijectif entre les participations modales et le point d'impact. Une procédure d'estimation de ces participations modales à partir d'un unique point de mesure a été proposée. Dans un second temps, la démarche a été d'étendre la procédure à l'identification d'une loi décrivant les paramètres principaux d'une force d'impact. Des conditions portant sur les paramètres de mesure et les propriétés modales de la structure sont déterminées pour garantir la précision et la robustesse de l'identification. Ce travail a permis de développer une approche en rupture par rapport à l'état de l'art, en ce sens qu'elle ne nécessite, en théorie, qu'un seul point de mesures vibratoires pour identifier un impact. Des essais expérimentaux sur un pavillon d'A350 ont permis de valider cette approche sur une structure composite de grandes dimensions. / Many industrial structures operate in an environment with a high risk of collision. The detection of impacts and the assessment of their severity is a major preoccupation in Structural Health Monitoring. This work deals with the development of an impact identification technique that is applicable to a large composite structure, numerically robust and time efficient, and that requires a low number of sensors. The first step was to describe the image of the impact point in the vibration response as a modal participation vector. The idea was to introduce the existence of a discriminating modes familly to make a bijective link between the modal participations and the impact point. A least-squares procedure is developed to estimate those modal participations by measuring the vibration response of a single point on the structure. The second step was to extend the procedure to the identification of a parametric law representing the impact load history. Some conditions on measurement parameters and modal properties of the structure are identified to guarantee both the accuracy and the robustness of the procedure. The approach developed in this work is new regarding the state of the art: only one measurement point is considered for identifying an impact event. An experimental validation on an A350 crown panel indicates that the methodology is valid for large composite structures.

Soumise à une sollicitation sismique importante, une structure de génie civil peut être endommagée. Cela se traduit par l'apparition de fissures et donc une réduction de ses propriétés élastiques de la structure. Cependant, dans le cas d'un événement sismique d'amplitude inférieure, la variation observée est seulement transitoire. Elle consiste en une perturbation brutale de la fréquence et de l'amortissement suivie d'un recouvrement lent vers leurs valeurs initiales. Ce phénomène non linéaire de relaxation est appelé Dynamique Lente. Il s'explique par la fermeture progressive des fissures initialement présentes dans la structure et qui ont été ouvertes par la sollicitation. Nous avons observé en laboratoire que l'analyse de la Dynamique Lente dans une poutre avant et après son endommagement permet de détecter cette augmentation de la densité de fissures. La sensibilité différentielle des modes à une dégradation locale indique, de plus, une piste pour le développement d'une méthode de localisation de l'endommagement. L'étude de la Dynamique Lente que nous avons menée dans deux structures de génie civil a montré que nous pouvions également y détecter l'apparition de l'endommagement. Le suivi de l'amortissement de manière continue a mis en évidence une relation linéaire entre l'amortissement et l'intensité des vibrations ambiantes à la fois dans les poutres et les structures de génie civil. Nous expliquons celle-ci via l'application du théorème Fluctuation-Dissipation à ces systèmes. Les résultats en laboratoire et la proximité de l'expression de la relation avec les équations utilisées dans le cas de la Dynamique Lente suggère une dépendance de ce phénomène vis à vis de la densité des hétérogénéités dans le matériau composant la structure. De plus amples recherches sont cependant nécessaires afin d'expliquer complètement nos observations et ainsi pouvoir les utiliser dans le cadre de la surveillance des structures uniquement à partir de données de très faible amplitude. / During strong seismic loadings, a structure may be damaged. This results in the appearing of cracks and then a reduction of the elastic properties of the structure. The degradation remains only transitory in the case of smaller seismic events. It consists in a sharp disruption of both the frequency and damping followed by their slow recovery to their initial values. This non linear phenomenon is called Slow Dynamics. It is explained by the gradual closing of the cracks which were initially present in the material and which were opened during the loading. We observed in the laboratory that the analysis of the Slow Dynamics in a beam before and after it is damaged allows to detect the increase of the crack density. The different sensitivties of the modes regarding a local damaging indicates a track to develop a method to locate the damages. The study of the Slow Dynamics in civil engineering structures demonstrated the possibility to detect the damaging also in this kind of system. The continuous monitoring of the damping highlighted a linear relationship between damping and the intensity of the ambiante vibration in the case of both the beams and real case structures. We explain this relation by applying the Fluctuation-Dissipation to these systems. Laboratory results and the proximity of the expression of the linear relationship wit hthe equations used in the theory of the Slow Dynamics suggest a dependency of this phenonmenon on the density of heterogeneities in the structure. Further research is however required in order to fully explain our observations and thus, to use them to monitor the state of health of structures.

Orientador: Michael John Brennan / Abstract: The guarantee of security in transport vehicles, buildings, bridges and critical structures is extremely important for people and the environment. Therefore, in the last decades, several Structural Health Monitoring (SHM) techniques have been proposed and developed for many areas. One technique to detect corrosion could be the use of guided waves. Considering one wave travelling in a structure and impinging on a discontinuity (damage), this wave will interact with this discontinuity and will be scattered. Thus wave motion in structures may be a powerful way to indicate the presence of damage in a structure. This work aims to investigate wave propagation in a thin Euler-Bernoulli infinite beam, and the way in which these waves interact with simulated corrosion damage (symmetric and asymmetric). The studies show the importance to know the behavior of waves before chose main frequencies to used for a SHM system. Piezoelectric elements are used to excite and sense the waves. The behavior of the systems studied are widely discussed in frequency and time domains. In order to detect and quantify the damage, reflected waves showed better sensitivity and proportionality with damage severity for all configuration studied. The longitudinal wave incident in the damage is easier to be used in a SHM system than flexural waves because longitudinal waves present simplicity compared to flexural. However, is important to choose appropriate frequency range in order to generate good levels of th... (Complete abstract click electronic access below) / Resumo: A garantia de segurança em veículos de transporte, edifícios, pontes e estruturas críticas é extremamente importante para as pessoas e o meio ambiente. Portanto, nas últimas décadas, várias técnicas de Monitoramento da Integridade Estrutural (SHM) foram propostas e desenvolvidas para diversas áreas. Uma técnica para detectar corrosão pode ser o uso de ondas guiadas. Considerando uma onda propaganda em uma estrutura e se chocando a uma descontinuidade (dano), esta onda irá interagir com esta descontinuidade e será transformada (parte é refletida e parte transmitida). Assim, o movimento de ondas em estruturas pode ser uma maneira poderosa de indicar a presença de dano em estruturas. Este trabalho tem como objetivo investigar a propagação de ondas em uma viga de Euler-Bernoulli e a forma como estas ondas interagem com danos simulados de corrosão (simétricos e assimétricos). Os estudos mostram a importância de conhecer o comportamento das ondas antes de escolher as freqüências principais a serem usadas em um sistema SHM. Elementos piezelétricos são usados para gerar sensoriar as ondas. O comportamento dos sistemas estudados é amplamente discutido nos domínios de frequência e tempo. Para detectar e quantificar os danos, as ondas refletidas apresentaram melhor sensibilidade e proporcionalidade com a severidade do dano para todas as configurações estudadas. As ondas longitudinais incidentes no dano são mais recomendadas pelo sistema SHM por apresentarem maior simplicidade em relação... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

Most existing structural health monitoring (SHM) techniques are based on measured acceleration data. Such practice, however, is highly expensive to operate, mainly due to cumbersome, time-consuming and expensive installation of sensors and their data acquisition systems. As an emerging noncontact method, the vision-based displacement sensor systems have attracted significant research interests and offered a promising alternative to the conventional sensors for SHM. However, most existing vision-based sensors require physical access to the structure to install a predesigned target panel, which has a higher contrast and thus is easier to track. Besides, most studies are carried out in controlled laboratory environments. The accuracy and robustness of vision sensors in the outdoor field conditions have not been fully investigated. It is also noted that current researches are mainly focusing on the measurement performance evaluation of vision sensors, without discussing the use of the measured displacement data for SHM. This dissertation develops a high-precision vision sensor system for remote and real-time measurement of multipoint structural displacements by tracking natural targets on structural surfaces. Two sets of software packages are developed respectively based on two advanced template matching algorithms (i.e., the upsampled cross correlation and the orientation code matching) incorporated with different subpixel techniques. Comprehensive experiments, including laboratory shaking table tests and field bridge tests, are carried out to evaluate its performance. Satisfactory agreements are observed between the displacements measured by the proposed vision sensor and those measured by high-performance reference displacement sensors. Moreover, this study examines the robustness of the vision sensor against ill environmental conditions such as dim light, background image disturbance and partial template occlusion. This dissertation further explores the potentials of the vision sensor for fast and inexpensive SHM applications, by demonstrating the usefulness of the displacement data for experimental modal analysis, finite element (FE) model updating, damage detection, etc. For a three-story frame structure, the modal analysis shows that the obtained natural frequencies and mode shapes from displacement measurements by using one camera match well with those by using four accelerometers. In fact, the vision sensor can achieve smoother mode shapes which would make damage localization more accurate, while the resolution of mode shapes from accelerometers is limited by the sensor number. This has been demonstrated from the damage detection result of beam structures based on the mode shape curvature (MSC) index. To address the needs for monitoring aging railway and highway bridges, coupled train-track-bridge and vehicle-bridge FE models are firstly developed to study the dynamic interactions between bridges and moving trains/vehicles. Subsequently, a time-domain model updating approach for railway bridges is proposed based on the in-situ measurement of the bridges’ dynamic displacement histories by the proposed vision sensor. This dissertation further proposes a bridge damage detection procedure that utilizes vehicle-induced displacement response and the MSC index without requiring prior knowledge about the traffic excitation.

abstract: This dissertation presents the development of structural health monitoring and prognostic health management methodologies for complex structures and systems in the field of mechanical engineering. To overcome various challenges historically associated with complex structures and systems such as complicated sensing mechanisms, noisy information, and large-size datasets, a hybrid monitoring framework comprising of solid mechanics concepts and data mining technologies is developed. In such a framework, the solid mechanics simulations provide additional intuitions to data mining techniques reducing the dependence of accuracy on the training set, while the data mining approaches fuse and interpret information from the targeted system enabling the capability for real-time monitoring with efficient computation. In the case of structural health monitoring, ultrasonic guided waves are utilized for damage identification and localization in complex composite structures. Signal processing and data mining techniques are integrated into the damage localization framework, and the converted wave modes, which are induced by the thickness variation due to the presence of delamination, are used as damage indicators. This framework has been validated through experiments and has shown sufficient accuracy in locating delamination in X-COR sandwich composites without the need of baseline information. Besides the localization of internal damage, the Gaussian process machine learning technique is integrated with finite element method as an online-offline prediction model to predict crack propagation with overloads under biaxial loading conditions; such a probabilistic prognosis model, with limited number of training examples, has shown increased accuracy over state-of-the-art techniques in predicting crack retardation behaviors induced by overloads. In the case of system level management, a monitoring framework built using a multivariate Gaussian model as basis is developed to evaluate the anomalous condition of commercial aircrafts. This method has been validated using commercial airline data and has shown high sensitivity to variations in aircraft dynamics and pilot operations. Moreover, this framework was also tested on simulated aircraft faults and its feasibility for real-time monitoring was demonstrated with sufficient computation efficiency. This research is expected to serve as a practical addition to the existing literature while possessing the potential to be adopted in realistic engineering applications. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2019

This dissertation develops a new concept for performance-based monitoring (PBM) of instrumented buildings subjected to earthquakes. This concept is achieved by simultaneously combining and advancing existing knowledge from structural mechanics, signal processing, and performance-based earthquake engineering paradigms. The PBM concept consists of 1) optimal sensor placement, 2) dynamic response reconstruction, 3) damage estimation, and 4) loss analysis. Within the proposed concept, the main theoretical contribution is the derivation of a nonlinear model-based observer (NMBO) for state estimation in nonlinear structural systems. The NMBO employs an efficient iterative algorithm to combine a nonlinear model and limited noise-contaminated response measurements to estimate the complete nonlinear dynamic response of the structural system of interest, in the particular case of this research, a building subject to an earthquake. The main advantage of the proposed observer over existing nonlinear recursive state estimators is that it is specifically designed to be physically realizable as a nonlinear structural model. This results in many desirable properties, such as improved stability and efficiency. Additionally, a practical methodology is presented to implement the proposed PBM concept in the case of instrumented steel, wood-frame, and reinforced concrete buildings as the three main types of structural systems used for construction in the United States. The proposed methodology is validated using three case studies of experimental and real-world large-scale instrumented buildings. The first case study is an extensively instrumented six-story wood frame building tested in a series of full-scale seismic tests in the final phase of the NEESWood project at the E-Defense facility in Japan. The second case study is a 6-story steel moment resisting frame building located in Burbank, CA, and uses the recorded acceleration data from the 1991 Sierra Madre and 1994 Northridge earthquakes. The third case is a seven-story reinforced concrete structure in Van Nuys, CA, which was severely damaged during the 1994 Northridge earthquake. The results presented in this dissertation constitute the most accurate and the highest resolution seismic response and damage measure estimates obtained for instrumented buildings. The proposed PBM concept will help structural engineers make more informed and swift decisions regarding post-earthquake assessment of critical instrumented building structures, thus improving earthquake resiliency of seismic-prone communities.

Mechanical durability of the structures should be continuously monitored during their operation. Structural health monitoring (SHM) techniques are typically used for gathering the information which can be used for evaluating the current condition of a structure regarding the existence, location, and severity of the damage. Damage can occur in a structure after long-term operating under service loads or due to incidents. By detection of these defects at the early stages of their growth and nucleation, it would be possible to not only improve the safety of the structure but also reduce the operating costs. The main goal of this dissertation is to develop a reliable and cost-effective SHM system for inspection of composite and metallic structures. The Surface Response to Excitation (SuRE) method is one of the SHM approaches that was developed at the FIU mechatronics lab as an alternative for the electromechanical impedance method to reduce the cost and size of the equipment. In this study, firstly, the performance of the SuRE method was evaluated when the conventional piezoelectric elements and scanning laser vibrometer were used as the contact and non-contact sensors, respectively, for monitoring the presence of loads on the surface. Then, the application of the SuRE method for the characterization vii of the milling operation for identical aluminum plates was investigated. Also, in order to eliminate the need for a priori knowledge of the characteristics of the structure, some advanced signal processing techniques were introduced. In the next step, the heterodyne method was proposed, as a nonlinear baseline free, SHM approach for identification of the debonded region and evaluation of the strength of composite bonds. Finally, the experimental results for both methods were validated via a finite element software. The experimental results for both SuRE and heterodyning method showed that these methods can be considered as promising linear and nonlinear SHM approaches for monitoring the health of composite and metallic structures. In addition, by validating the experimental results using FEM, the path for further improvement of these methods in future researches was paved.