Recent years have seen an influx of medical technologies capable of remotely monitoring the health and behaviours of individuals to detect, manage and prevent health problems. Known collectively as personal health monitoring (PHM), these systems are intended to supplement medical care with health monitoring outside traditional care environments such as hospitals, ranging in complexity from mobile devices to complex networks of sensors measuring physiological parameters and behaviours. This research project assesses the potential ethical implications of PHM as an emerging medical technology, amenable to anticipatory action intended to prevent or mitigate problematic ethical issues in the future. PHM fundamentally changes how medical care can be delivered: patients can be monitored and consulted at a distance, eliminating opportunities for face-to-face actions and potentially undermining the importance of social, emotional and psychological aspects of medical care. The norms evident in this movement may clash with existing standards of 'good' medical practice from the perspective of patients, clinicians and institutions. By relating utilitarianism, virtue ethics and theories of surveillance to Habermas' concept of colonisation of the lifeworld, a conceptual framework is created which can explain how PHM may be allowed to change medicine as a practice in an ethically problematic way. The framework relates the inhibition of virtuous behaviour among practitioners of medicine, understood as a moral practice, to the movement in medicine towards remote monitoring. To assess the explanatory power of the conceptual framework and expand its borders, a qualitative interview empirical study with potential users of PHM in England is carried out. Recognising that the inherent uncertainty of the future undermines the validity of empirical research, a novel epistemological framework based in Habermas' discourse ethics is created to justify the empirical study. By developing Habermas' concept of translation into a procedure for assessing the credibility of uncertain normative claims about the future, a novel methodology for empirical ethical assessment of emerging technologies is created and tested. Various methods of analysis are employed, including review of academic discourses, empirical and theoretical analyses of the moral potential of PHM. Recommendations are made concerning ethical issues in the deployment and design of PHM systems, analysis and application of PHM data, and the shortcomings of existing research and protection mechanisms in responding to potential ethical implications of the technology.

Le domaine aéronautique connait de nos jours un engouement sans précédent autour de l’avion plus électrique. L’importance du nombre d’équipements électriques est à un tel point que l’amélioration de leur fiabilité devient incontournable. Actuellement, les composants passifs occupent 75 % des éléments électroniques utilisés en avionique dont la moitié correspond à des condensateurs. Ces derniers doivent donc répondre aux exigences environnementales avioniques assez contraignantes. C’est dans ce contexte que nous nous sommes intéressés particulièrement à l’étude des condensateurs à technologie film utilisant le polypropylène ou le polyester comme diélectrique. Afin de mieux comprendre le comportement fréquentiel de cette technologie, deux modèles fins de condensateurs films ont été développés, permettant ainsi de suivre les évolutions de leurs grandeurs électriques dans des conditions cohérentes avec l’application. Dans un deuxième temps, l’effet des contraintes en tension et en température constantes a été étudié sous la forme de facteurs d’accélération du vieillissement. Cela a été établi par l’intermédiaire de plusieurs essais, permettant d’établir les lois d’évolutions temporelles des paramètres électriques des condensateurs. Comme ces contraintes constantes ne sont pas toujours représentatives des conditions réelles d’utilisation, les cinétiques de dégradation ont été comparées à celles où les condensateurs sont sollicités par de fortes ondulations de courant, seules ou associées à une tension continue. Enfin, la dernière partie de notre travail expose l’utilisation des données expérimentales issues des essais de vieillissement dans un objectif de diagnostic en ligne. Les techniques utilisées assurent l'analyse de la dégradation de ces composants, étape essentielle dans la prédiction de l’état de santé des condensateurs en ligne / Nowadays, aeronautic research field is moving towards a more electric aircraft. Although this evolutionary path offers many advantages from a financial and ecological point of view, the increased power source usage sets additional constraints on the different electrical systems used onboard. Currently, passive components occupy 75% of the overall electronic equipments used in avionics, whose 50% corresponds to capacitors. Consequently, these latter must be able to withstand the harsh avionic operating conditions. In this thesis we were particularly interested in the study of metallized film capacitors technology using polyester or polypropylene as dielectric. A first approach consisted on the modeling of these components as function of frequency in order to study the evolution of their electrical parameters under consistent avionic stresses. These models were also developed on the purpose of tracking the degradation of the capacitors parameters over time. This operation was done by the means of accelerated floating ageing tests, where capacitors were subjected to different constant voltages and temperatures. Original capacitance ageing laws were thus proposed based on the identification of voltage and temperature degradation kinetics. However, since traditional floating ageing tests, do not reflects the normal ageing of the component, degradation kinetics of metallized films capacitors under high ripple currents, alone or combined with a DC voltage across the devices terminals where also studied, and the associated failure mechanisms were identified. A final step consisted on the health monitoring of metallized film capacitors online based on the experimental ageing data

In den vorliegenden Untersuchungen wurde das Ziel verfolgt die Nutzbarkeit des Milchinhaltsstoffes Laktose als praxistaugliche Managementhilfe zu prüfen. Die Primärdaten stammen aus drei israelischen Hochleistungsherden, über mehrere Laktationen erhoben. Der Parameter Laktosegehalt wurde in der Datenaufbereitung dahingehend geprüft, ob dieser zur Gesundheits- und Leistungsvorhersage ausreicht oder welche zusätzlichen Merkmale für die Verwendung in einem Prognose-Modell von Bedeutung sein könnten. Als leistungs- bzw. gesundheitsrelevante Ereignisse (Events) wurden Brunst, Diarrhoe, Endometritis, Fieber, Infektionen, Klauenerkrankungen, Mastitis, Stress, Stoffwechselstörungen sowie Verletzungen zugeordnet. Die Bewertung der Nützlichkeit einzelner Merkmale für die Prädiktion erfolgte anhand der Erkennungsraten. Zwei- und dreistufige Entscheidungsbäume wurden entwickelt, um diese Events zu identifizieren. Ein einzelnes Merkmal ist oft nicht ausreichend, weshalb verschiedene Kombinationen von Variablen analysiert wurden. Die wichtigste Erkenntnis der vorliegenden Arbeit besteht darin, dass der Abfall der Laktosekonzentration und Laktosemenge immer ein kritisches Ereignis darstellt. Das Hauptziel eines Gesundheitsmonitorings im Milchkuhbestand sollte deshalb darin bestehen, frühzeitig eine Stoffwechselüberlastung "sichtbar" oder "erkennbar" zu machen. Unabhängig davon, welche Erkrankung sich anbahnt, muss das Herdenmanagement darauf hinwirken, die Glukoseversorgungssituation des Einzeltieres zu verbessern. Aus der Analyse für die einzelnen Herden und Laktationen kann grundlegend abgeleitet werden, dass die Ergebnisse der Milchkontrolldaten, die im Zuge der datengestützten Herdenüberwachung erhoben wurden, sich verwenden lassen, um den Leistungs- und Gesundheitsstatus der Kühe im Laktationsverlauf einzuschätzen und zu prognostizieren. Die Verwendung von Informationen zum Laktosegehalt des Gemelks verbesserten in jedem Fall die Erkennungsraten. / The aim of the current studies was to investigate whether the milk ingredient lactose can be used as a practical support management. The primary data comes from three Israeli high-performance herds, collected over several lactations. In the data preparation, the parameter "lactose content" was examined to see whether it is sufficient for a health and performance prediction or whether additional features may be of importance for usage in a forecasting model. Oestrus, diarrhea, endometritis, fever, infections, hoof diseases, mastitis, stress, metabolic disorders, and injuries have been assigned to the performance- and/or health-affecting events. The usefulness of individual features for the prediction was evaluated on the basis of the recognition rates. Thus two- and three-level decision trees have been developed to identify these events. As one single feature is often insufficient, different combinations of variables were analyzed. The most important finding of this study is that the drop in the lactose concentration and lactose quantity always represents a critical event. The main objective of a health monitoring in the dairy herd should therefore be to make a metabolic overload "visible" or "recognisable" at an early stage. Whichever disease begins to take shape, the herd management must work on improving the glucose supply situation of the individual animal. In conclusion from the analysis of the individual herds and lactations it can be inferred that the results of the milk control data collected in the course of the data-based herd monitoring can be used in order to assess and to predict the performance and health status of the cows in the course of lactation. The use of information on the lactose content of the milk improved in any case the recognition rates.

Ce manuscrit présente une méthode d’imagerie quantitative et sans état de référence, de défauts de corrosion d’une plaque mince, exploitant de manière passive un réseau embarqué de capteurs d’ondes élastiques guidées. Les applications visées sont le contrôle santé intégré (SHM) de structures critiques qui amènent de fortes contraintes à la fois d’intrusivité des capteurs et de fiabilité du diagnostic. Une solution prometteuse, permettant de multiplier la densité de points de mesure sans augmenter l’intrusivité du système, est offerte par les réseaux de Bragg sur fibre optique (FBG). Toutefois, contrairement aux transducteurs piézoélectriques (PZT) classiquement employés en SHM, les FBG ne permettent pas d’émettre d’ondes élastiques. L’idée consiste à utiliser des méthodes dites « passives » permettant de retrouver la fonction de Green entre deux capteurs à partir du bruit ambiant, naturellement présent dans la structure, mesuré simultanément entre ces deux capteurs. Nous étudions dans ce manuscrit deux méthodes passives : la corrélation de bruit et le filtre inverse passif. Nous verrons que ce dernier a plus de potentiel lorsqu’il est couplé à l’imagerie par tomographie. Différents algorithmes de tomographie sont évalués par simulation numérique puis lors d’expériences comparatives actives et passives à l’aide d’un réseau de PZT. Afin de rendre la tomographie passive robuste, nous présentons une méthode clé de détection de temps de vol, basée sur une représentation temps-fréquence. Enfin, nous décrivons une première démonstration expérimentale de mesures passives par FBG qui laisse à penser que la tomographie passive par FBG est prometteuse. / This manuscript presents a baseline-free quantitative method for the imaging of corrosion flaws present in thin plates. This method only requires an embedded guided waves sensors network in a fully passive way. The field ofapplications are Structural Health Monitoring (SHM) of critical structures with heavy constrains on both sensors intrusiveness and diagnostic reliability. A promising solution allowing to increase the number of measurement points without increasing the intrusiveness of the system is provided by the Fiber Bragg Gratings (FBGs). However, unlike piezoelectric transducers generally used in SHM, the FBGs cannot emit elastic waves. The idea consists in using passive methods in order to retrieve the Green function from elastic diffuse fields - naturally present in structures - measured simultaneously between two sensors. In this manuscript, two passive methods are studied: the ambient noise correlation and the passive inverse filter. It is shown that the latter gives better results when coupled with tomography. Several tomography algorithms are assessed with numerical simulations and then applied to active and passive datasets measured by a PZT network. In order to make passive tomography robust, a time of flight identification method is proposed, based on a time-frequency representation. Finally, a novel experimental demonstration of passive measurements with FBGs only is presented, suggesting high potential for FBGs passive tomography.

Monitoring the mechanical integrity of critical structures is extremely important, as mechanical defects can potentially have adverse impacts on their safe operability throughout their service life. Structural defects can be detected by using active structural health monitoring (SHM) approaches, in which a given structure is excited with harmonic mechanical waves generated by actuators. The response of the structure is then collected using sensor(s) and is analyzed for possible defects, with various active SHM approaches available for analyzing the response of a structure to single- or multi-frequency harmonic excitations. In order to identify the appropriate excitation frequency, however, the majority of such methods require a priori knowledge of the characteristics of the defects under consideration. This makes the whole enterprise of detecting structural defects logically circular, as there is usually limited a priori information about the characteristics and the locations of defects that are yet to be detected. Furthermore, the majority of SHM techniques rely on sensors for response collection, with the very same sensors also prone to structural damage. The Surface Response to Excitation (SuRE) method is a broadband frequency method that has high sensitivity to different types of defects, but it requires a baseline. In this study, initially, theoretical justification was provided for the validity of the SuRE method and it was implemented for detection of internal and external defects in pipes. Then, the Comprehensive Heterodyne Effect Based Inspection (CHEBI) method was developed based on the SuRE method to eliminate the need for any baseline. Unlike traditional approaches, the CHEBI method requires no a priori knowledge of defect characteristics for the selection of the excitation frequency. In addition, the proposed heterodyne effect-based approach constitutes the very first sensor-less smart monitoring technique, in which the emergence of mechanical defect(s) triggers an audible alarm in the structure with the defect. Finally, a novel compact phased array (CPA) method was developed for locating defects using only three transducers. The CPA approach provides an image of most probable defected areas in the structure in three steps. The techniques developed in this study were used to detect and/or locate different types of mechanical damages in structures with various geometries.

The past 30 years have witnessed major developments in vibration based damage detection and identification, also collectively referred to as damage diagnosis. Moreover, the past 10 years have seen a rapid increase in the amount of research related to Structural Health Monitoring (SHM) as quantified by the significant escalation in papers published on this subject. Thus, the increased interest in this engineering field and its associated potential constitute the main motive for this thesis. The goal of the thesis is the development and introduction of novel advanced functional and sequential statistical time series methods for vibration based damage diagnosis and SHM. After the introduction of the first chapter, Chapter II provides an experimental assessment and comparison of vibration based statistical time series methods for Structural Health Monitoring (SHM) via their application on a lightweight aluminum truss structure and a laboratory scale aircraft skeleton structure. A concise overview of the main non-parametric and parametric methods is presented, including response-only and excitation-response schemes. Damage detection and identification are based on univariate (scalar) versions of the methods, while both scalar (univariate) and vector (multivariate) schemes are considered. The methods' effectiveness for both damage detection and identification is assessed via various test cases corresponding to different damage scenarios, multiple experiments and various sensor locations on the considered structures. The results of the chapter confirm the high potential and effectiveness of vibration based statistical time series methods for SHM. Chapter III investigates the identification of stochastic systems under multiple operating conditions via Vector-dependent Functionally Pooled (VFP) models. In many applications a system operates under a variety of operating conditions (for instance operating temperature, humidity, damage location, damage magnitude and so on) which affect its dynamics, with each condition kept constant for a single commission cycle. Typical examples include mechanical structures operating under different environmental conditions, aircrafts under different flight conditions (altitude, velocity etc.), structures under different structural health states (various damage locations and magnitudes). In this way, damage location and magnitude may be considered as parameters that affect the operating conditions and as a result the structural dynamics. This chapter's work is based on the novel Functional Pooling (FP) framework, which has been recently introduced by the Stochastic Mechanical Systems \& Automation (SMSA) group of the Mechanical Engineering and Aeronautics Department of University of Patras. The main characteristic of Functionally Pooled (FP) models is that their model parameters and innovations sequence depend functionally on the operating parameters, and are projected on appropriate functional subspaces spanned by mutually independent basis functions. Thus, the fourth chapter of the thesis addresses the problem of identifying a globally valid and parsimonious stochastic system model based on input-output data records obtained under a sample of operating conditions characterized by more than one parameters. Hence, models that include a vector characterization of the operating condition are postulated. The problem is tackled within the novel FP framework that postulates proper global discrete-time linear time series models of the ARX and ARMAX types, data pooling techniques, and statistical parameter estimation. Corresponding Vector-dependent Functionally Pooled (VFP) ARX and ARMAX models are postulated, and proper estimators of the Least Squares (LS), Maximum Likelihood (ML), and Prediction Error (PE) types are developed. Model structure estimation is achieved via customary criteria (Bayesian Information Criterion) and a novel Genetic Algorithm (GA) based procedure. The strong consistency of the VFP-ARX least squares and maximum likelihood estimators is established, while the effectiveness of the complete estimation and identification method is demonstrated via two Monte Carlo studies. Based on the postulated VFP parametrization a vibration based statistical time series method that is capable of effective damage detection, precise localization, and magnitude estimation within a unified stochastic framework is introduced in Chapter IV. The method constitutes an important generalization of the recently introduced Functional Model Based Method (FMBM) in that it allows, for the first time in the statistical time series methods context, for complete and precise damage localization on continuous structural topologies. More precisely, the proposed method can accurately localize damage anywhere on properly defined continuous topologies on the structure, instead of pre-defined specific locations. Estimator uncertainties are taken into account, and uncertainty ellipsoids are provided for the damage location and magnitude. To achieve its goal, the method is based on the extended class of Vector-dependent Functionally Pooled (VFP) models, which are characterized by parameters that depend on both damage magnitude and location, as well as on proper statistical estimation and decision making schemes. The method is validated and its effectiveness is experimentally assessed via its application to damage detection, precise localization, and magnitude estimation on a prototype GARTEUR-type laboratory scale aircraft skeleton structure. The damage scenarios considered consist of varying size small masses attached to various continuous topologies on the structure. The method is shown to achieve effective damage detection, precise localization, and magnitude estimation based on even a single pair of measured excitation-response signals. Chapter V presents the introduction and experimental assessment of a sequential statistical time series method for vibration based SHM capable of achieving effective, robust and early damage detection, identification and quantification under uncertainties. The method is based on a combination of binary and multihypothesis versions of the statistically optimal Sequential Probability Ratio Test (SPRT), which employs the residual sequences obtained through a stochastic time series model of the healthy structure. In this work the full list of properties and capabilities of the SPRT are for the first time presented and explored in the context of vibration based damage detection, identification and quantification. The method is shown to achieve effective and robust damage detection, identification and quantification based on predetermined statistical hypothesis sampling plans, which are both analytically and experimentally compared and assessed. The method's performance is determined a priori via the use of the analytical expressions of the Operating Characteristic (OC) and Average Sample Number (ASN) functions in combination with baseline data records, while it requires on average a minimum number of samples in order to reach a decision compared to most powerful Fixed Sample Size (FSS) tests. The effectiveness of the proposed method is validated and experimentally assessed via its application on a lightweight aluminum truss structure, while the obtained results for three distinct vibration measurement positions prove the method's ability to operate based even on a single pair of measured excitation-response signals. Finally, Chapter VI contains the concluding remarks and future perspectives of the thesis. / Κατά τη διάρκεια των τελευταίων 30 ετών έχει σημειωθεί σημαντική ανάπτυξη στο πεδίο της ανίχνευσης και αναγνώρισης βλαβών, το οποίο αναφέρεται συνολικά και σαν διάγνωση βλαβών. Επίσης, κατά την τελευταία δεκαετία έχει σημειωθεί σημαντική πρόοδος στον τομέα της παρακολούθησης της υγείας (δομικής ακεραιότητας) κατασκευών. Στόχος αυτής της διατριβής είναι η ανάπτυξη εξελιγμένων συναρτησιακών και επαναληπτικών μεθόδων χρονοσειρών για τη διάγνωση βλαβών και την παρακολούθηση της υγείας κατασκευών υπό ταλάντωση. Αρχικά γίνεται η πειραματική αποτίμηση και κριτική σύγκριση των σημαντικότερων στατιστικών μεθόδων χρονοσειρών επί τη βάσει της εφαρμογής τους σε πρότυπες εργαστηριακές κατασκευές. Εφαρμόζονται μη-παραμετρικές και παραμετρικές μέθοδοι που βασίζονται σε ταλαντωτικά σήματα διέγερσης και απόκρισης των κατασκευών. Στη συνέχεια αναπτύσσονται στοχαστικά συναρτησιακά μοντέλα για την στοχαστική αναγνώριση κατασκευών υπό πολλαπλές συνθήκες λειτουργίας. Τα μοντέλα αυτά χρησιμοποιούνται για την αναπαράσταση κατασκευών σε διάφορες καταστάσεις βλάβης (θέση και μέγεθος βλάβης), ώστε να είναι δυνατή η συνολική μοντελοποίσή τους για όλες τις συνθήκες λειτουργίας. Τα μοντέλα αυτά αποτελούν τη βάση στην οποία αναπτύσσεται μια συναρτησιακή μέθοδος η οποία είναι ικανή να αντιμετωπίσει συνολικά και ενιαία το πρόβλημα της ανίχνευσης, εντοπισμού και εκτίμησης βλαβών σε κατασκευές. Η πειραματική αποτίμηση της μεθόδου γίνεται με πολλαπλά πειράματα σε εργαστηριακό σκελετό αεροσκάφους. Στο τελευταίο κεφάλαιο της διατριβής προτείνεται μια καινοτόμος στατιστική επαναληπτική μέθοδο για την παρακολούθηση της υγείας κατασκευών. Η μέθοδος κρίνεται αποτελεσματική υπό καθεστώς λειτουργικών αβεβαιοτήτων, καθώς χρησιμοποιεί επαναληπτικά και στατιστικά τεστ πολλαπλών υποθέσεων. Η αποτίμηση της μεθόδου γίνεται με πολλαπλά εργαστηριακά πειράματα, ενώ η μέθοδος κρίνεται ικανή να λειτουργήσει με τη χρήση ενός ζεύγους ταλαντωτικών σημάτων διέγερσης-απόκρισης.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / The basic concept of impedance-based structure health monitoring is measuring the variation of the electromechanical impedance of the structure as caused by the presence of damage by using patches of piezoelectric material bonded on the surface of the structure (or embedded into). The measured electrical impedance of the PZT patch is directly related to the mechanical impedance of the structure. That is why the presence of damage can be detected by monitoring the variation of the impedance signal. In order to quantify damage, a metric is specially defined, which allows to assign a characteristic scalar value to the fault. This study initially evaluates the influence of environmental conditions in the impedance measurement, such as temperature, magnetic fields and ionic environment. The results show that the magnetic field does not influence the impedance measurement and that the ionic environment influences the results. However, when the sensor is shielded, the effect of the ionic environment is significantly reduced. The influence of the sensor geometry has also been studied. It has been established that the shape of the PZT patch (rectangular or circular) has no influence on the impedance measurement. However, the position of the sensor is an important issue to correctly detect damage. This work presents the development of a low-cost portable system for impedance measuring to automatically measure and store data from 16 PZT patches, without human intervention. One fundamental aspect in the context of this work is to characterize the damage type from the various impedance signals collected. In this sense, the techniques of artificial intelligence known as neural networks and fuzzy cluster analysis were tested for classifying damage of aircraft structures, obtaining satisfactory results. One last contribution of the present work is the study of the performance of the electromechanical impedance-based structural health monitoring technique to detect damage in structures under dynamic loading. Encouraging results were obtained for this aim. / O conceito básico da técnica de integridade estrutural baseada na impedância tem a ver com o monitoramento da variação da impedância eletromecânica da estrutura, causada pela presença alterações estruturais, através de pastilhas de material piezelétrico coladas na superfície da estrutura ou nela incorporadas. A impedância medida se relaciona com a impedância mecânica da estrutura. A partir da variação dos sinais de impedância pode-se concluir pela existência ou não de uma falha. Para quantificar esta falha, métricas de dano são especialmente definidas, permitindo atribuir-lhe um valor escalar característico. Este trabalho pretende inicialmente avaliar a influência de algumas condições ambientais, tais como os campos magnéticos e os meios iônicos na medição de impedância. Os resultados obtidos mostram que os campos magnéticos não tem influência na medição de impedância e que os meios iônicos influenciam os resultados; entretanto, ao blindar o sensor, este efeito se reduz consideravelmente. Também foi estudada a influencia da geometria, ou seja, do formato do PZT e da posição do sensor com respeito ao dano. Verificou-se que o formato do PZT não tem nenhuma influência na medição e que a posição do sensor é importante para detectar corretamente o dano. Neste trabalho se apresenta o desenvolvimento de um sistema de medição de impedância de baixo custo e portátil que tem a capacidade de medir e armazenar a medição de 16 PZTs sem a necessidade de intervenção humana. Um aspecto de fundamental importância no contexto deste trabalho é a caracterização do dano a partir dos sinais de impedância coletados. Neste sentido, as técnicas de inteligência artificial conhecidas como redes neurais e análises de cluster fuzzy, foram testadas para classificar danos em estruturas aeronáuticas, obtendo resultados satisfatórios para esta tarefa. Uma última contribuição deste trabalho é o estudo do comportamento da técnica de monitoramento de integridade estrutural baseado na impedância eletromecânica na detecção de danos em estruturas submetidas a carregamento dinâmico. Os resultados obtidos mostram que a técnica funciona adequadamente nestes casos. / Doutor em Engenharia Mecânica

Composite structures are extremely useful for aerospace, automotive, marine and civil applications due to their very high specific structural properties. These structures are subjected to severe dynamic loading in their service life. Repeated exposure to these severe loading conditions can induce structural damage which ultimately may precipitate a catastrophic failure. Therefore, an interest in the continuous inspection and maintenance of engineering structures has grown tremendously in recent years. Sensitive aerospace applications can have small design margins and any inadequacy in knowledge of the system may cause design failure. Structures made from composite materials posses complicated failure mechanism as compared to those made from conventional metallic materials. In composite structural design, it is hence very important to properly model geometric intricacies and various imperfections such as delaminations and cracks. Two important issues are addressed in this thesis: (1) structural modeling of nonlinear delamination and uncertainty propagation in nonlinear characteristics of composite plate structures and (2) development of a model based damage detection system to handle uncertainty issues. An earlier proposed shear deformable C0 composite plate finite element is modified to alleviate modeling uncertainty issues associated with a damage detection problem. Parabolic variation of transverse shear stresses across the plate thickness is incorporated into the modified formulation using mixed shear interpolation technique. Validity of the proposed modification is established through available literature. Correction of the transverse shear stress term in the formulation results in about 2 percent higher solution accuracy than the earlier model. It is found that the transverse shear effect increases with higher modes of the plate deformation. Transverse shear effects are more prominent in sandwich plates. This refined composite plate finite element is used for large deformation dynamic analysis of delaminated composite plates. The inter-laminar contact at the delaminated region in composite plates is modeled with the augmented Lagrangian approach. Numerical simulations are carried out to investigate the effect of delamination on the nonlinear transient behavior of composite plates. Results obtained from these studies show that widely used unconditionally stable β-Newmark method presents numerical instability problems in the transient simulation of delaminated composite plate structures with large deformation. To overcome this instability issue, an energy and momentum conserving composite implicit time integration scheme presented by Bathe and Baig is used for the nonlinear dynamic analysis. It is also found that a proper selection of the penalty parameter is very crucial in the simulation of contact condition. It is shown that an improper selection of penalty parameter in the augmented Lagrangian formulation may lead to erroneous prediction of dynamic response of composite delaminated plates. Uncertainties associated with the mathematical characterization of a structure can lead to unreliable damage detection. Composite structures also show considerable scatter in their structural response due to large uncertainties associated with their material properties. Probabilistic analysis is carried out to estimate material uncertainty effects in the nonlinear frequencies of composite plates. Monte Carlo Simulation with Latin Hypercube Sampling technique is used to obtain the variance of linear and nonlinear natural frequencies of the plate due to randomness in its material properties. Numerical results are obtained for composite plates with different aspect ratio, stacking sequence and oscillation amplitude ratio. It is found that the nonlinear frequencies show increasing non-Gaussian probability density function with increasing amplitude of vibration and show dual peaks at high amplitude ratios. This chaotic nature of the dispersion of nonlinear eigenvalues is also revealed in eigenvalue sensitivity analysis. For fault isolation, variations in natural frequencies, modal curvatures and curvature damage factors due to damage are investigated. Effects of various physical uncertainties like, material and geometric uncertainties on the success of damage detection is studied. A robust structural damage detection system is developed based on the statistical information available from the probabilistic analysis carried out on beam type structures. A new fault isolation technique called sliding window defuzzifier is proposed to maximize the success rate of a Fuzzy Logic System (FLS) in damage detection. Using the changes in structural measurements between the damaged and undamaged state, a fuzzy system is generated and the rule-base and membership functions are generated using probabilistic informations. The FLS is demonstrated using frequency and mode shape based measurements for various beam type structures such as uniform cantilever beam, tapered beam in single as well as in multiple damage conditions. The robustness of the FLS is demonstrated with respect to the highly uncertain input information called measurement deltas (MDs). It is said, if uncertainty level is larger than or close to the changes in damage indicator due to damage, the true information would be submerged in the noise. Then the actual damaged members may not be identified accurately and/or the healthy members may be wrongly detected as damaged giving false warning. However, this being the case, the proposed FLS with new fault isolation technique tested with these noisy data having large variation and overlaps shows excellent robustness. It is observed that the FLS accurately predicts and isolates the damage levels up-to considerable uncertainty and noise levels in single as well as multiple damage conditions. The robustness of the FLS is also demonstrated for delamination detection in composite plates having very high material property uncertainty. Effects of epistemic uncertainty on damage detection in composite plates is addressed. The effectiveness of the proposed refined Reddy type shear deformable composite plate element is demonstrated for reducing the modeling or epistemic uncertainty in delamination detection.

This thesis focuses on the development of a new method for the continuous<p>monitoring of civil engineering structures in order to locate small damages automatically. A<p>review of the very wide literature on Structural Health Monitoring (SHM) points first out that<p>the methods can be grouped in four categories based on their need or not of a numerical model,<p>as well as their need or not of information of the damaged structure to be applied. This state<p>of the art of the SHM methods highlights the requirement to reach each levels of SHM, which<p>is in particular for the localization of small damages in civil engineering structures the needs<p>for a non-model based output-only damage sensitive feature extraction technique. The origin of<p>the local sensitivity of strains to damages is also analyzed, which justifies their use for damage<p>localization.<p>A new method based on the modal filtering technique which consists in combining linearly<p>the sensor responses in a specific way to mimic a single degree of freedom system and which<p>was previously developed for damage detection is proposed. A very large network of dynamic<p>strain sensors is deployed on the structure and split into several independent local sensor networks.<p>Low computational cost and fast signal processing techniques are coupled to statistical<p>control charts for robust and fully automated damage localization.<p>The efficiency of the method is demonstrated using time-domain simulated data on a simply<p>supported beam and a three-dimensional bridge structure. The method is able to detect and<p>locate very small damages even in the presence of noise on the measurements and variability<p>of the baseline structure if strain sensors are used. The difficulty to locate damages from acceleration<p>sensors is also clearly illustrated. The most common classical methods for damage<p>localization are applied on the simply supported beam and the results show that the modal filtering<p>technique presents much better performances for an accurate localization of small damages<p>and is easier to automate.<p>An improvement of the modal filters method referred to as adaptive modal filters is next<p>proposed in order to enhance the ability to localize small damages, as well as to follow their<p>evolution through modal filters updating. Based on this study, a new damage sensitive feature<p>is proposed and is compared with other damage sensitive features to detect the damages with<p>modal filters to demonstrate its interest. These expectations are verified numerically with the<p>three-dimensional bridge structure, and the results show that the adaptation of the modal filters<p>increases the sensitivity of local filters to damages.<p>Experimental tests have been led first to check the feasibility of modal filters to detect damages<p>when they are used with accelerometers. Two case studies are considered. The first work<p>investigates the experimental damage detection of a small aircraft wing equipped with a network<p>of 15 accelerometers, one force transducer and excited with an electro-dynamic shaker. A<p>damage is introduced by replacing inspection panels with damaged panels. A modified version<p>of the modal filtering technique is applied and compared with the damage detection based principal<p>component analysis of FRFs as well as of transmissibilities. The three approaches succeed<p>in the damage detection but we illustrate the advantage of using the modal filtering algorithm as<p>well as of the new damage sensitive feature. The second experimental application aims at detecting<p>both linear and nonlinear damage scenarios using the responses of four accelerometers<p>installed on the three-storey frame structure previously developed and studied at Los Alamos<p>National Labs. In particular, modal filters are shown to be sensitive to both types of damages,<p>but cannot make the distinction between linear and nonlinear damages.<p>Finally, the new method is tested experimentally to locate damages by considering cheap<p>piezoelectric patches (PVDF) for dynamic strain measurements. Again, two case studies are investigated.<p>The first work investigates a small clamped-free steel plate equipped with 8 PVDFs sensors, and excited with a PZT patch. A small damage is introduced at different locations by<p>fixing a stiffener. The modal filters are applied on three local filters in order to locate damage.<p>Univariate control charts allow to locate automatically all the damage positions correctly.<p>The last experimental investigation is devoted to a 3.78m long I-steel beam equipped with 20<p>PVDFs sensors and excited with an electro-dynamic shaker. Again, a small stiffener is added to<p>mimic the effect of a small damage and five local filters are defined to locate the damage. The<p>damage is correctly located for several positions, and the interest of including measurements<p>under different environmental conditions for the baseline as well as overlapping the local filters<p>is illustrated.<p>The very nice results obtained with these first experimental applications of modal filters<p>based on strains show the real interest of this very low computational cost method for outputonly<p>non-model based automated damage localization of real structures. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

The poly(glycidyl methacrylate)-modified magnetite nanoparticles, Fe3O4-PGMA NPs, were investigated and applied in nondestructive flaw detection of polymeric materials in this research. The Fe3O4 endowed magnetic property to the materials for flaw detection while the PGMA promoted colloidal stability and prevented particle aggregation. The magnetite nanoparticles (Fe3O4 NPs) were successfully synthesized by coprecipitation and then surface-modified with PGMA to form PGMA-modified Fe3O4 NPs by both grafting-from and grafting-to approaches. For the grafting-from approach, the Fe3O4 NPs were surface-functionalized with α-bromo isobutyryl bromide (BIBB) to form BIB-modified Fe3O4 NPs (Fe3O4-BIB NPs) with covalent linkage. The resultant Fe3O4-BIB NPs were used as surface-initiators to grow PGMA by surface-initiated atom transfer radical polymerization (SI-ATRP). For the grafting-to approach, the Fe3O4 NP were surface-functionalized with (3-mercaptopropyl)triethoxysilane (MCTES) to form MCTES-modified Fe3O4 NPs (Fe3O4-MCTES NPs). The PGMA with Br-end group was pre-synthesized by ATRP and then was grafted to the surface of the Fe3O4-MCTES NPs by coupling reaction. Both bare and modified Fe3O4 NPs exhibited superparamagnetism and the existence of iron oxide in the form of Fe3O4 was confirmed. The particle size of individual Fe3O4 NPs was about 8 – 24 nm but they aggregated to form clusters. The PGMA-modified NPs formed stable dispersion in chloroform and had larger cluster sizes than the unmodified ones because of the PGMA polymer layer. However, the uniformity of the NP clusters could be improved with PGMA surface grafting. The PGMA surface layer of the grafting-from (Fe3O4-gf-PGMA) NPs was thin and dense while that of the grafting-to (Fe3O4-gt-PGMA) NPs was thick and loose. The hydrodynamic diameters (Zave) of Fe3O4-gf-PGMA NP clusters could be controlled between 176 to 643 nm, dependent on the PGMA contents and reaction conditions. During SI-ATRP, side reactions happened and caused NP aggregation as well as increase of size of NP clusters. However, the aggregation has been minimized through optimization of reaction conditions. Oppositely, Zave values of Fe3O4-gt-PGMA NPs had little variation of about 120 – 190 nm. And the PGMA content of the Fe3O4-gt-PGMA NPs was limited to 12.5% because of the spatial hindrance during grafting process. The saturation magnetization (Ms) of the unmodified Fe3O4 NPs was about 77 emu/g, while those of the grafting-from and grafting-to Fe3O4-PGMA NPs were 50 – 66 emu/g and 63 – 70 emu/g, respectively. For Fe3O4-PGMA NPs with similar Fe3O4 contents, the grafting-to NPs had slightly higher Ms than the grafting-from counterparts. In addition, the Ms of both kinds of the Fe3O4-PGMA NPs with higher Fe3O4 content (> 87%) were also higher than that of the fluidMAG-Amine, the commercially available amine-modified MNPs. Besides, both kinds of Fe3O4-PGMA NPs also had much higher Fe3O4 contents and Ms values than most of the reported PGMA-modified MNPs. The magnetic epoxy nanocomposites (MENCs) were prepared by blending the modified Fe3O4 NPs into bisphenol A diglycidyl ether (BADGE)-based epoxy system and the distributions of both kinds of the PGMA-modified NPs were much better than that of the oleic acid-modified Fe3O4 NPs. Similar to the NPs, the MENCs also exhibited superparamagnetism. By cross-section TEM observation, the grafting-to Fe3O4-PGMA NPs formed more homogeneous distributions with smaller cluster size than the grafting-from counterparts and gave higher Ms of the MENCs. Nondestructive flaw detection of surface and sub-surface defects could be successfully achieved by brightness contrast of images given through eddy current testing (ET) method, which is firstly reported. The mechanical properties of the materials were influenced very slightly when 2.5% or lower Fe3O4-gt-PGMA NPs were present while the presence of the Fe3O4-gf-PGMA NPs (1 – 2.5 %) gave mild improvement of the storage modulus and increase of the glass-rubber transition temperature(Tg) of the MENCs. Furthermore, the Fe3O4-PGMA NPs could be evenly coated onto the functionalized ultra-high molecular weight poly(ethylene) (UHMWPE) textiles. The Fe3O4-gt-PGMA NPs were coated on the textile in order to prepare NP-coated textile-reinforced composite. Preliminary result of ET measurement showed that the Fe3O4-gt-PGMA NPs coated on the textiles could visualize the structure of the textile hidden inside and their relative depth. Accordingly, the incorporation of MNPs to polymers opens a new pathway of damage-free structural health monitoring of polymeric materials.