In modern times, the ability to investigate the aeroelastic behavior of dynamic components on rotorcraft has become essential for the prediction of their useful fatigue life. At the same time, the aeroelastic modeling of a rotorcraft is particularly complex and costly. Inaccuracies in numerical predictions are mostly due to imprecisions in the structural modeling, to the presence of structural degradation or to the limited information on aerodynamic loads. The integration of experimental measurements on dynamic components such as rotor blades has the potential to improve fatigue estimation, augment the knowledge of the dynamic behavior and inform numerical models. The objective of this research is the development of a combined numerical and experimental approach, named Confluence Algorithm, that accurately predicts the response of dynamic components with a limited set of experimental data. The integration of experimental measurements into a numerical algorithm enables the continuous and accurate tracking of the dynamic strain and stress fields. The Confluence Algorithm systematically updates the numerical model of the external loads, and mass and stiffness distributions to improve the representation and extrapolation of the experimental data, and to extract information on the response of the system at non-measured locations. The capabilities of this algorithm are first verified in a numerical framework and with well-controlled lab experiments. Numerical results from a comprehensive UH-60A multibody model are then compared with available experimental data. These analyses demonstrate that the integration of the Confluence Algorithm improves the accuracy of the numerical prediction of the dynamic response of systems characterized by a periodic behavior, even in presence of non-linearities. The algorithm enables the use of simplified models that are corrected through experimental data to achieve accurate tracking of the system.

The total electricity consumption of plugged-in electric loads (PELs) currently accounts for more usage than any other single end-use service in residential and commercial buildings. Compared with other categories of electric loads, PELs possess significant potential to be efficiently controlled and managed in buildings. Therefore, accurate and reliable PEL identification methods that are used to collect identity and performance information are desired for many purposes. However, few existing electric load identification methods are designed for PELs to handle unique challenges such as the diversity within each type of PEL and similarity between different types of PELs equipped by similar front-end power supply units. The objective of this dissertation is to develop non-intrusive, accurate, robust, and applicable PEL identification algorithms utilizing voltage and current measurements. Based on the literature review of almost all existing features that describe electric loads and five types of existing methods for electric load identification, a two-level framework for PELs classification and identification is proposed. First, the supervised self-organizing map (SSOM) is adopted to classify a large number of PELs of different models and brands into several groups by their inherent similarities. Therefore, PELs with similar front-end power supply units or characteristics fall into the same group. The partitioned groups are verified by their power supply unit topology. That is, different groups should have different topologies. This dissertation proposes a novel combination of the SSOM framework and the Bayesian framework. Such a hybrid identifier can provide the probability of an unknown PEL belonging to a specific type of load. Within each classified group by the SSOM, both static and dynamic methods are proposed to distinguish PELs with similar characteristics. Static methods extract steady-state features from the voltage and current waveforms to train different computational intelligence algorithms such as the SSOM itself and the support vector machine (SVM). An unknown PEL is then presented to the trained algorithm for identification. In contrast to static methods, dynamic methods take into consideration the dynamics of long-term (minutes instead of milliseconds) waveforms of PELs and extract elements such as spikes, oscillations, steady-state operations, as well as similarly repeated patterns.

Ce manuscrit traite de la problématique de la surveillance des structures depuis la mesure en service jusqu'à la caractérisation des champs mécaniques. La technologie des systèmes de mesure est étudiée dans la première partie. Les spécifications d'un système de mesure embarqué sont identifiées à partir d'essais en service sur des structures et à partir des applications envisagées. Ces spécifications définissent les hypothèses de résolution du problème inverse lié à l'interprétation des mesures.La deuxième partie présente la formulation du problème inverse de surveillance des structures à partir des hypothèses précédemment énoncées. Le principe est de reconstruire les champs mécaniques à partir de l'identification des conditions aux limites. Seul le chargement est considéré et le principe de Saint-Venant permet de restreindre le nombre de paramètres nécessaires à sa modélisation. La difficulté réside alors dans le choix des bonnes bases de chargement et dans le positionnement des capteurs. Cette méthode est appliquée aux structures poutres dans la troisième partie. Les bases de chargement sont obtenues à partir d'une projection des solutions analytiques du problème de poutre sur les bords des structures. Le positionnement des capteurs est ensuite étudié sur des structures poutres élémentaires qui réduisent le problème inverse à une identification polynomiale. La décomposition des structures poutres complexes en structures élémentaires simplifie alors la définition des bases de chargement et le positionnement des capteurs. La dernière partie présente les résultats obtenus sur des structures plaques. Les bases de chargement sont construites par projection des solutions analytiques pour les domaines étoilés. L'extension à des domaines quelconques est faite en considérant seulement les bords chargés des structures pour se ramener à des domaines étoilés équivalents. Bien que ces bases ne soient plus complètes, les résultats obtenus sur des plaques trouées montrent leur intérêt. Ces résultats servent ensuite à la construction des bases de chargement et au positionnement des capteurs pour les structures complexes modélisées par des assemblages de plaques. / This thesis tackles the problem of structural monitoring from integrated measurements to full-field reconstruction.In a first part, the technology of measurement systems is studied. An integrated measurement system is specified from some structural tests in-service and its future applications. These specifications define the mechanical framework of structural monitoring.The inverse problem associated with structural monitoring is expressed in a second part. The mechanical hypothesis result from the previously defined framework. The boundary conditions are identified in order to reconstruct the mechanical fields. The loads are considered only and the Saint-Venant's principle allows to limit the number of the loading parameters. The main issue is then to find the right loading basis and then to optimize the sensor locations.This method for structural monitoring is applied to beams in the third part. The analytical solutions of the mechanical equations for beams are projected on the boundary of the structures in order to obtain the loading basis. The optimal sensor locations are then estimate from elementary structures, what reduces the inverse problem to a polynomial identification. The complex beam structures are then decomposed into elementary ones, what drastically simplifies the construction of the loading bases and the sensor locations.In a last part, plate structures are considered. The loading basis are firstly defined by the projection of the analytical solutions of star-shaped domain. These basis are then extended to any plate structures using some loaded boundaries only in order to design an equivalent star-shaped domain. Even if these loading basis are incomplete sets, the results are in good agreement. The same principle is used to obtain the loading basis for complex structures modeled by plate assemblies.

Este trabalho consiste em apresentar o desenvolvimento de um Smart meter, integrado a um analisador de qualidade de energia, para análise de distorções harmônicas, utilizando método de redes neurais artificiais embarcado em hardware. Tal Smart meter está incluído dentro dos conceitos de Smart Grid, que serão apresentados também neste trabalho. O intuito do desenvolvimento do Smart meter para análise de distorções harmônicas é auxiliar concessionárias de energia elétrica a identificar que tipo de carga o consumidor utiliza em sua residência, a fim de contribuir para a tomada de decisões apropriadas, tais como a diminuição da emissão de correntes harmônicas, demanda de energia, detecção de falhas no fornecimento de energia elétrica e faturas diferenciadas de acordo com a quantidade de harmônicas injetadas na rede elétrica. Adicionalmente, observou-se que o Smart meter desenvolvido pode ser ainda utilizado para detectar fenômenos de VTCD, como elevação, afundamento e interrupção de energia. Todo o processo de desenvolvimento do Smart meter é apresentado no decorrer desta tese de doutorado. / This thesis consists to present the development of a Smart Meter integrated to power quality analyzer for the analysis of harmonic distortion, using methods based on artificial neural networks in embedded hardware. This Smart Meter is included within the concepts of Smart Grid, which will be also presented in this work. The intention of the development of the Smart Meter for analysis of harmonic distortion is to assist utilities companies to identify what loads type the consumer uses at your residence in order to contribute for supporting decisions, such as reducing the emission of the harmonic currents, power demand and faults detection in electric energy supply and distinct bills according to the amount of harmonics injected into the power grid. In addition, it was observed that this developed Smart Meter can be even used to detect the VTCD phenomena, such as swell, sag and interruption of the energy supply. All development steps of this Smart Meter is presented in this doctoral thesis.

Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul / Electricity consumption in homes and workplaces has been growing steadily over the decades and attitudes to reduce these costs should be taken. An interesting solution is to provide to electricity users, and also to the energy company, detailed data of individual consumption of each electrical appliance. To accomplish this, researchers in the field have focused their efforts on non-intrusive methods of load identification, where a single energy meter is able to desagreggate the appliances by monitoring the total consumption of electricity of that location. Non-intrusive methods are easy to install and demand little maintenance, but require a robust method for identifying these loads. Therefore, the aim of this work is to investigate nonintrusive methods of recognition of electrical appliances to find the desaggregated consumption of these loads. Among these methods, there are the already widely used image recognition pattern methods, that now are been used also to detect electrical devices. In this paper, two of these techniques are discussed, the Principal Component Analisys, a classical method in the literature, and the Vector Projection Length, a completely new method and never used in the loads recognition field before. Current and voltage data were collected from 16 residential appliances, involving all types of loads (resistive, inductive, electronic and hybrid/other types). These data were used as training samples and test samples (unknown samples). A study is carried out using the current and also the power, independently, as load signatures. Also, a comparative analysis of the results of signatures in the time domain and time-frequency (Stowkwell transform) is conducted. As the main contributions to this work, we verified that the Vector Projection Length for load identification is quite feasible, with results up to 96% of tested appliances being identified. However, the results with Principal Component Analisys did not presented the same performance, reaching only 81% of accuracy rate. Comparing the signatures, it became clear that one should use the current in the time-frequency domain for better performance. Neither the use of power, or the time domain obtained satisfactory results of load identification when applying image pattern recognition techniques to load recognition. / O consumo de eletricidade em residências e ambientes de trabalho vem crescendo continuamente ao longo das décadas e atitudes para reduzir estes gastos devem ser tomadas. Uma solução interessante é fornecer aos usuários de energia elétrica, e também à própria concessionária, dados detalhados de consumo individual de cada equipamento elétrico. Para alcançar este objetivo, pesquisadores na área tem focado seus esforços em métodos não-intrusivos de identificação das cargas (equipamentos elétricos), onde um único medidor de energia é capaz de desagregar os equipamentos através do monitoramento do consumo total de energia elétrica daquele local. Métodos não-intrusivos são de fácil instalação e de pouca manutenção, porém requerem um robusto método de identificação destas cargas. Portanto, o objetivo deste trabalho é investigar métodos não-intrusivos de reconhecimento de equipamentos elétricos para encontrar o consumo desagregado destas cargas. Dentre estes métodos, existem os já muito utilizados no reconhecimento de padrões em imagens, mas que agora tem sido também usados para detectar cargas elétricas. Neste trabalho duas destas técnicas são abordadas, a Principal Component Analisys, método clássico na literatura, e o Vector Projection Length, um método completamente novo e nunca usado no reconhecimento de cargas. Coletou-se dados de corrente e tensão de 16 equipamentos elétricos residenciais dos mais variados tipos, envolvendo todos os tipos de cargas existentes (resistivas, indutivas, eletrônicas e híbridas/outros tipos). Estes dados coletados foram utilizados como amostras de treinamento e amostras de teste (amostras desconhecidas). Como assinatura das cargas é realizado um estudo empregando corrente e também potência, de forma independente. Ainda, uma análise comparativa de resultados das assinaturas no domínio do tempo e do tempo-frequência (Transformada de Stowkwell) é conduzido. Como principais contribuições para este trabalho obteve-se que o uso do Vector Projection Length na identificação de equipamentos é bastante viável, com resultados de até 96% dos equipamentos testados sendo identificados. Já os resultados com o Principal Component Analisys ficaram abaixo de seu concorrente, atingindo 81% de taxa de acertos. Comparando as assinaturas, ficou claro que deve-se utilizar a corrente no domínio do tempo-frequência para uma melhor performance. Nem o uso da potência, nem o domínio do tempo obtiveram resultados satisfatórios de identificação quando empregados.

Dans le domaine de l'ingénierie, connaitre le chargement appliqué sur une structure permet de résoudre des problèmes directs dont le résultat est le champ de déplacement, de déformation dans une structure. Il est alors possible d'effectuer un dimensionnement. Cependant, parfois ce chargement doit être identifie a posteriori. Malheureusement, il n'est pas toujours possible de mesurer ce chargement : ainsi, par exemple, on ne sait pas a priori où aura lieu le chargement, ou bien il n'est pas possible de placer un capteur sans l'endommager ou encore il peut nécessiter un encombrement trop important. On a alors recours à des mesures indirectes de déplacement, de déformation, d'accélération et on est alors amené à résoudre des problèmes inverses, qui sont en général mal posés. Il est alors nécessaire d'ajouter une (des) conditions supplémentaire(s) pour obtenir une solution unique et stable : c'est la régularisation du problème. Ces techniques sont bien connues et leur essor est dû à l'utilisation des décompositions en valeurs singulières des matrices de transfert. Toutefois, elles nécessitent l'utilisation d'un paramètre additionnel qui pondère cette condition supplémentaire : la détermination de ce paramètre est délicate. Peu de travaux ayant été réalisé pour tester de façon intensive les méthodes usuelles de régularisation (Tikhonov et troncature de la (G)SVD), en association avec les différents critères de détermination du paramètre de régularisation et les différentes réponses possibles, on a effectué un tel travail pour tirer des conclusions sur la méthodologie optimale. On a pu mettre en évidence que la mesure de l'accélération associée à un critère faisant intervenir les dérivées du signal à reconstruire donne en général les meilleurs résultats sous réserve d'utiliser le critère GCV pour déterminer le paramètre de régularisation. Ces méthodes supposent que la localisation de la zone de chargement est connue. Aussi on s'est intéressé à déduire cette zone de chargement en tentant de reconstruire des chargements identiquement nuls. Cette identification a été effectuée aisément sous réserve qu'on ait peu de forces à identifier par rapport au nombre de mesures disponibles. En revanche une telle identification est délicate lorsqu'on n'a pas plus de mesures que de forces à identifier. Finalement on s'est tourné vers l'identification de chargement ayant plastifié la structure étudiée. On a alors essayé de reconstruire le chargement en supposant que la structure reste linéaire élastique, alors qu'elle a été plastifiée : on a utilisé la méthode du double chargement et effectue des simulations à l'aide du logiciel de simulation Ls-dyna.La force reconstruite fait alors apparaitre une composante statique traduisant la déformation résiduelle dans la structure. Dans ce cas, la réponse à utiliser pour identifier le chargement est une déformation dans une zone non plastifiée / In the field of the engineering, knowing the load applied on the structure which allows to solve the direct problem of which the results are given the field of displacement and strain in a structure. It is possible to perform a dimensioning. However, sometimes this load must be identified a posteriori. Unfortunately, it is not always possible to measure this load. Thus, for example, we do not know a priori where it will be loaded, either it is not possible to place a sensor without damaging it or needs too much space. We then have to use indirect measures of displacement, strain, acceleration and then we are lead to solve the inverse problems which are generally an ill-posed. It is then necessary to add one (or more) conditions to obtain a unique and stable solution: it is the regularization of the problem. These techniques are well known and their development is due to the use of the singular value decomposition of the transfer matrix. However, they require the use of an additional parameter that weights this additional condition: the determination of this parameter is difficult. Few studies having been realized in way the usual regularization methods of (Tikhonov and truncation of the (G)SVD), in association with the various criteria for determining the regularization parameter and the various possible responses, we conducted a such work, to draw conclusions on the optimal methodology. It has been highlighted that the measurement of the acceleration associated with a criterion involving the derived signal to reconstruct generally gives the best results via the GCV criterion to determine the regularization parameter. These methods suppose that the location of the loading area is known. We also were interested to deduct this loading area while trying to reconstruct load that is identically zero. This identification was performed easily that has little load to identify compared to the number of measurements available. However such identification is difficult when there are no more measures than loads to identify. Finally we turned to the identification of loading with the plastic structure. We then tried to reconstruct the load assuming that the structure remains linear-elastic, while it was plasticized: we used the method of the double load and performed simulations using the software ls-dyna. The reconstructed load then shows a static component reflecting the residual strain in the structure. In this case, the response used to identify the load is a strain in a non-plasticized zone

Este trabalho consiste em apresentar o desenvolvimento de um Smart meter, integrado a um analisador de qualidade de energia, para análise de distorções harmônicas, utilizando método de redes neurais artificiais embarcado em hardware. Tal Smart meter está incluído dentro dos conceitos de Smart Grid, que serão apresentados também neste trabalho. O intuito do desenvolvimento do Smart meter para análise de distorções harmônicas é auxiliar concessionárias de energia elétrica a identificar que tipo de carga o consumidor utiliza em sua residência, a fim de contribuir para a tomada de decisões apropriadas, tais como a diminuição da emissão de correntes harmônicas, demanda de energia, detecção de falhas no fornecimento de energia elétrica e faturas diferenciadas de acordo com a quantidade de harmônicas injetadas na rede elétrica. Adicionalmente, observou-se que o Smart meter desenvolvido pode ser ainda utilizado para detectar fenômenos de VTCD, como elevação, afundamento e interrupção de energia. Todo o processo de desenvolvimento do Smart meter é apresentado no decorrer desta tese de doutorado. / This thesis consists to present the development of a Smart Meter integrated to power quality analyzer for the analysis of harmonic distortion, using methods based on artificial neural networks in embedded hardware. This Smart Meter is included within the concepts of Smart Grid, which will be also presented in this work. The intention of the development of the Smart Meter for analysis of harmonic distortion is to assist utilities companies to identify what loads type the consumer uses at your residence in order to contribute for supporting decisions, such as reducing the emission of the harmonic currents, power demand and faults detection in electric energy supply and distinct bills according to the amount of harmonics injected into the power grid. In addition, it was observed that this developed Smart Meter can be even used to detect the VTCD phenomena, such as swell, sag and interruption of the energy supply. All development steps of this Smart Meter is presented in this doctoral thesis.

Engineers have long been inspired by nature's flyers. Such animals navigate complex environments gracefully and efficiently by using a variety of evolutionary adaptations for high-performance flight. Biologists have discovered a variety of sensory adaptations that provide flow state feedback and allow flying animals to feel their way through flight. A specialized skeletal wing structure and plethora of robust, adaptable sensory systems together allow nature's flyers to adapt to myriad flight conditions and regimes. In this work, motivated by biology and the successes of bio-inspired, engineered aerial vehicles, linear quadratic control of a flexible, morphing wing design is investigated, helping to pave the way for truly autonomous, mission-adaptive craft. The proposed control algorithm is demonstrated to morph a wing into desired positions. Furthermore, motivated specifically by the sensory adaptations organisms possess, this work transitions to an investigation of aircraft wing load identification using structural response as measured by distributed sensors. A novel, recursive estimation algorithm is utilized to recursively solve the inverse problem of load identification, providing both wing structural and aerodynamic states for use in a feedback control, mission-adaptive framework. The recursive load identification algorithm is demonstrated to provide accurate load estimate in both simulation and experiment. / Graduation date: 2012

The aim of this diploma thesis is to describe localization and calculation load identification of dynamic systems using piezoelectric sensors. Finding methods, which would allow us to evaluate loads on simple systems is the key to their application in the structural health monitoring of more complex systems. A theory necessary for understanding and application in aerospace, civil engineering, automobile industry, and train traffic of presented methods is given in the first part of the thesis. In these applications, the methods of wave propagation and different types of neural network methods are used to evaluate load identification. It is possible to evaluate loads by using a time reverse method, a method based on signal deconvolution, and a method based on a voltage amplitude ratio of the piezoelectric sensor. In the next part, the methods are described, the suitable place for gluing of a sensor, and the number of sensors for using method is given. These methods were verified and compared to a simple experimental system. In the following part, the model of the piezoelectric sensor is presented. It is possible to use the model for calculating voltage output from the strain. For methods verification, the problem of train passage in a specific place of the railway is chosen. The speed of the train and its load on the railway was calculated by using these methods.

[ES] El acceso a una atención sanitaria de alta calidad es un marcador importante del desarrollo de las sociedades humanas. Los aportes tecnológicos a la medicina han mostrado un potencial relevante para descubrir procedimientos efectivos a nivel preventivo, diagnóstico y terapéutico. En particular, los métodos computacionales permiten el procesamiento eficaz de datos médicos y, por tanto, pueden modelar sistemas biológicos complejos. Esto ha influido en el desarrollo de la Medicina Personalizada (MP) durante las últimas décadas, donde la obtención de conocimiento específico de cada caso permite realizar intervenciones a medida, todo ello a un coste de recursos accesible. La simulación de remodelación ósea es un campo prometedor en el contexto de la MP. Predecir un proceso de adaptación ósea en un caso concreto puede dar lugar a numerosas aplicaciones en el campo de las enfermedades óseas, tanto a nivel clínico como experimental. Mediante la combinación del Método de Elementos Finitos (FEM) y los algoritmos de remodelación ósea, es posible obtener modelos numéricos de un hueso específico a partir de datos médicos (por ejemplo, una tomografía computarizada). Todo ello puede dar lugar a una revolución en la medicina personalizada. / [CA] L'accés a una atenció sanitària d'alta qualitat és un marcador important del desenvolupament de les societats humanes. Les aportacions tecnològiques a la medicina han mostrat un potencial rellevant per a descobrir procediments efectius a nivell preventiu, diagnòstic i terapèutic. En particular, els mètodes computacionals permeten el processament eficaç de dades mèdiques i, per tant, poden modelar sistemes biològics complexos. Això ha influït en el desenvolupament de la Medicina Personalitzada (MP) durant les últimes dècades, on l'obtenció de coneixement específic de cada cas permet realitzar intervencions a mesura, tot això a un cost de recursos accessible. La simulació de remodelació òssia és un camp prometedor en el context de la MP. Predir un procés d'adaptació òssia en un cas concret pot donar lloc a nombroses aplicacions en el camp de les malalties òssies, tant a nivell clínic com experimental. Mitjançant la combinació del Mètode d'Elements Finits (*FEM) i els algorismes de remodelació òssia, és possible obtindre models numèrics d'un os específic a partir de dades mèdiques (per exemple, una tomografia computada). Tot això pot donar lloc a una revolució en la medicina personalitzada. / [EN] Access to high-quality healthcare is an important marker of the development of human societies. Technological contributions to medicine have shown relevant potential to discover effective procedures at a preventive, diagnostic and therapeutic level. In particular, computational methods enable efficient processing of medical data and can therefore model complex biological systems. This has influenced the development of Personalized Medicine (PM) over recent decades, where obtaining specific knowledge of each case allows for tailored interventions, all at an affordable resource cost. Simulation of bone remodeling is a promising field in the context of PM. Predicting a bone adaptation process in a specific case can lead to numerous applications in the field of bone diseases, both clinically and experimentally. By combining the Finite Element Method (FEM) and bone remodeling algorithms, it is possible to obtain numerical models of a specific bone from medical data (for example, a CT scan). All of this can lead to a revolution in personalized medicine. / Thanks to the Valencian funding programme FDGENT/2018, for providing economic resources to develop this long-term work. / Gutiérrez Gil, J. (2023). Personalization of Bone Remodelling Simulation Models for Clinical Applications [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202059