Ce travail de thèse concerne le contrôle santé intégré (SHM : Structural Health Monitoring) de structures composites aéronautiques par ondes guidées avec des transducteurs piézoélectriques (PZT). La majorité des méthodes de détection classiques reposent sur la comparaison de signaux issus de la structure inspectée à l’état courant avec ceux mesurés dans un état sain (la baseline). La température altère significativement les signaux mesurés et le diagnostic associé si son influence n’est pas prise en compte dans la baseline. D’autre part, l’acquisition de la baseline est très contraignante en vue d’un déploiement des systèmes SHM en condition réelles. La première contribution de cette thèse est l’estimation du champ de température à partir des mesures des PZTs (décalage du spectre fréquentiel et capacité statique), qui permet de compenser l’effet de la température dans la baseline sans ajouter de capteurs dédiés. La seconde contribution concerne les méthodes sans état de référence (baseline free). Les performances de détection de quatre méthodes sont comparées (rupture de réciprocité, variation d’amplitude, analyse des modes de Lamb et baseline instantanée) sur un modèle numérique et des cas expérimentaux d’endommagement à différentes températures sur une plaque de composite fortement anisotrope. Les résultats obtenus démontrent que la décomposition des modes de Lamb dans les signaux mesurés par l’intermédiaire de dual PZTs (PZTs constitués de deux électrodes concentriques – un anneau et un disque – sur leur face supérieure) permet d’améliorer de façon significative les performances de détection de ces méthodes. Un processus de dimensionnement du réseau de dual PZTs est proposé pour le déploiement de ces méthodes sur des structures complexes et prenant en compte la forte anisotropie des matériaux. Ces résultats ouvrent des perspectives prometteuses contribuant potentiellement au transfert des technologies de SHM des laboratoires vers l’industrie. / This thesis work concerns the Structural Health Monitoring (SHM) of aeronautical composite structures by guided waves with piezoelectric transducers (PZT). Conventional detection methods are based on the comparison of signals from the inspected structure in the current state with those measured in a healthy state (the baseline). Temperature significantly alters the measured signals and the associated diagnosis if its influence is not considered in the baseline. Also, the acquisition of the baseline is very constraining for the deployment of SHM systems in real conditions. The first contribution of this thesis is the estimation of the temperature field from the PZT measurements (modal frequency shift and static capacity), which allows to compensate the effect of temperature in the baseline without adding dedicated sensors. The second contribution of this thesis concerns baseline free methods. The detection performance of four methods are compared (reciprocity principle, amplitude variation, Lamb mode analysis and instantaneous baseline) on a numerical model and experimental cases of damages at different temperatures on a highly anisotropic composite plate. The results obtained show that the decomposition of Lamb wave modes in signals measured via dual PZTs (PZTs consisting of two concentric electrodes - a ring and a disk - on their upper side) significantly improves the detection performance of these methods. A dimensioning process for the deployment of these methods on complex anisotropic structures is proposed. These results open up promising opportunities that potentially contribute to the transfer of SHM technologies from laboratories to industry.

Distributed fibre optic sensing (DFOS) is essential for structural health monitoring (SHM) of strain changes induced during the lifetime of a structure. Among different DFOS systems, the Brillouin Optical Time Domain Reflectometry (BOTDR) takes the advantages of obtaining full frequency spectrum to provide strain and temperature information along the optic fibre. The key parameters of distributed fibre optic sensors, spatial and frequency resolution, are strongly linked with the time-frequency (T-F) localisation in the system in three parts: pulse, hardware design and optical fibre. T-F localization is fundamentally important for the communication system, whereas in this study the importance of the T-F localisation to the spatial and frequency resolution, repeatability and the measurement speed are introduced in BOTDR. In this dissertation, the development of DFOS is first introduced, including both traditional methods and new developed designs. The literature review shows the signal to noise ratio (SNR) of BOTDR can be improved by investigating its T-F localisation. In the hardware design, in order to improve the T-F localisation in hardware architecture, a Short-Time Fourier Transform-Brillouin Optical Time-Domain Reflectometry (STFT-BOTDR), which implements STFT over the full frequency spectrum to measure the distributed temperature and strain along the optic fibre, is applied so that the conventional frequency sweeping method can be replaced for high resolution and fast speed measurement, providing new research advances in dynamic distributed sensing. The STFT based BOTDR has better T-F localisation, which in turn provides an opportunity for off-line post signal processing that is more adaptable for fast speed measurements. The spatial and frequency resolution of dynamic BOTDR sensing is limited by the Signal to Noise Ratio (SNR) and the T-F localization of the input pulse shape. The T-F localized input pulse shape can enhance the SNR and the spatial and frequency resolution in STFT-BOTDR. In this study, simulation and experiments of T-F localized different pulses shapes are conducted to examine the limitation of the system resolution. The result indicates that a rectangular pulse should be selected to optimize the spatial resolution and a Lorentzian pulse could be chosen to optimize the frequency resolution, while a Gaussian shape pulse can be used in general applications for its balanced performance in both spatial and frequency resolution. Meanwhile, T-F localization is used for pulse T-F localisation optimisation. A set of Kaiser-Bessel functions is used to simulate different pulse shapes and to compare their parameters in terms of T-F localisation and their Brillouin scattering spectrum. A method using an iterative filtering algorithm to achieve the optimised pulse in terms of T-F localisation is introduced to converge the Effective-pulse Width (TEW) in the time-domain and Effective-pulse Linewidth (FEL) in the frequency domain to identify the fundamental limitations. The optimised pulse can be fitted with a 7th order Gaussian (super-Gaussian) shape and it offers the best experimental performance compared to a Rectangular pulse. The sensitivity of a sensor to strain or temperature variations due to distributed Brillouin scattering is closely related to the power distribution on the Brillouin scattering spectrum which is related to the property of the optic fibre. The performance of a highly nonlinear fibre that can generate a higher Brillouin scattering signal is compared to that of a standard single mode fibre. The results show that much higher SNR of the Brillouin scattering spectrum and smaller frequency uncertainties in the sensing measurement can be achieved by using a highly nonlinear fibre for comparable launched powers. With a measurement speed of 4 Hz, the frequency uncertainty can be 0.43 MHz, corresponding to 10 με in strain or 0.43°C in temperature uncertainty for the tested highly nonlinear fibre. In contrast, for a standard single mode fibre, the value would increase to about 1.02 MHz (25 με or 1.02°C), demonstrating the advantage of the tested highly nonlinear fibre for distributed strain/temperature sensing. Results show that, by using a small effective area highly nonlinear fibre, the strain or temperature resolution can be improved because it generates stronger Brillouin scattering signal with high SNR and high Q factor spectrum, both of which determine the optimal averaging time in a single measurement. In general, the STFT-BOTDR can achieve 1 m spatial resolution, 10 με frequency resolution on a 10 km fibre with measurement speed at about 2.5 kHz.

Orientador: Gilberto Pechoto de Melo / Resumo: As metodologias de monitoramento da integridade estrutural baseadas em observadores de estado, em sua grande maioria, utilizam o resíduo obtido a partir da diferença entre a medida e a estimativa de dada resposta dinâmica do sistema para o processo de detecção de danos. Contudo, em determinadas situações, tem-se interesse em realizar o monitoramento através de certa resposta dinâmica que não pode ser medida diretamente. Desta forma, a principal contribuição deste trabalho é propor uma metodologia de detecção de danos para sistemas mecânicos, cujo resíduo é obtido a partir da diferença entre as estimativas do comportamento dinâmico de determinada região do sistema. Estas estimativas são geradas por dois observadores de estado de ordem plena em paralelo, ambos projetados a partir do modelo físico-matemático do sistema em monitoramento sem danos, cujos os ganhos ótimos são determinados pelo método LQR, do inglês Linear Quadratic Regulator. A diferença entre os observadores consiste em serem baseados em conjuntos de medidas distintos. Simulações computacionais são apresentadas para demonstrar a aplicação desta metodologia, de maneira que são discutidas as vantagens e desvantagens em monitorar o sistema utilizando diferentes tipos de força de excitação. Os resultados obtidos são satisfatórios para a detecção dos tipos de dano considerados neste trabalho. / Abstract: Structural health monitoring methodologies based on state observers, for the most part, use the residual obtained from the di erence between the measurement and the estimate of the given dynamic response of the system to the damage detection process. However, in certain situations, it is interesting to carry out the monitoring through a certain dynamic response that can not be measured directly. In this way, the main contribution of this work is to propose a methodology of damage detection for mechanical systems, whose residue is obtained from the di erence between the estimates of the dynamic behavior of a certain region of the system. These estimates are generated by two parallel full-order state observers, both designed from the physical-mathematical model of the monitoring system without damages, whose optimal gains are determined by the LQR (Linear Quadratic Regulator) method. The di erence between observers is that they are based on di erent sets of measures. Computational simulations are presented to demonstrate the application of this methodology, so that the advantages and disadvantages of monitoring the system using di erent types of excitation force are discussed. The results obtained are satisfactory for the detection of the types of damage considered in this work. / Mestre

Concrete highway bridges are important elements of our country's transportation infrastructure; however, only few studies that address their seismic behavior using data collected from instrumented structures are available in the literature. This gap of knowledge impairs full exploitation of structural health monitoring techniques for seismic damage assessment, and improvement of design recommendations. This research is particularly concerned with curved concrete box-girder highway bridges, whose seismic behavior is still widely unexplored due to lack of field monitoring data. By taking advantage of vibration records collected during six earthquake events at the West Street on Ramp, a curved concrete box-girder highway bridge located in Anaheim, California, this research aims at advancing knowledge about the seismic behavior of these bridges. Modal identification of the bridge during the earthquakes is conducted, and sensitivity analysis is carried out to reconcile the observed dynamic characteristics of the bridge with the behavior of its structural elements. Data collected from an instrumented large-scale bridge specimen during shaking table tests are also analyzed to gain insight about the response of the bridge bents during the earthquakes, and propose a strategy to model their seismic behavior. Information from modal identification and the shaking table tests analyses are instrumental in developing a nonlinear finite element model of the bridge, calibrated employing a multistage finite element model updating strategy. In order to evaluate the significance of using the structural-health-monitoring-informed structural model obtained, seismic performance assessment through incremental dynamic analysis is conducted, and results are compared with the predicted performance estimated with a conventional finite element model of the bridge. By advancing knowledge about the seismic behavior of concrete highway bridges, this research may ultimately contribute to improve structural health monitoring practices and design guidelines for this type of structures.

This master thesis is the result of a collaborative work between EMBRAER and the Escola Politécnica da USP for the study of structural health monitoring (SHM) techniques using sensors applied to aircraft structures. The goal was to develop classification techniques to discriminate between different events arising in the aircraft structure during tests; in the short term, improving the current SHM system used by EMBRAER, based on acoustic emission and, in the long term, fostering the development of a fully distributed system. As a result of studying classification methods for immediate use, we developed two techniques: the Spectral Similarity and a Support Vector Machines (SVM) classifier. Both are unsupervised solutions, due to the unlabeled nature of the data provided. The two solutions were delivered as a final product to EMBRAER for prompt use in the existing SHM system. By studying distributed solutions for future implementations, we developed a detection algorithm based on adaptive techniques. The main result was a special initialization for a maximum likelihood (ML) detector that yields an exponential decay rate in the error probability to a nonzero steady state, using adaptive diffusion estimation in a distributed sensor network. The nodes that compose the network must decide, locally, between two concurrent hypotheses concerning the environment state where they are inserted, using local measurements and shared estimates coming from their neighbors. The exponential performance does not depend on the adaptation step size value, provided it is sufficiently small. The results concerning this distributed detector were published in the journal IEEE Signal Processing Letters. / Esta dissertação de mestrado é o resultado de um trabalho colaborativo entre a EMBRAER e a Escola Politécnica da USP no estudo de técnicas de monitoramento do estado de saúde de estruturas (Structural Health Monitoring - SHM) utilizando sensores em estruturas aeronáuticas. O objetivo foi desenvolver técnicas de classificação para discriminar entre diferentes eventos que surgem em estruturas aeronáuticas durante testes; para o curto prazo, aperfeiçoando o atual sistema de SHM utilizado pela EMBRAER, baseado em emissão acústica e, no longo prazo, fomentando o desenvolvimento de um sistema completamente distribuído. Como resultado do estudo de métodos de classificação para uso imediato, desenvolvemos duas técnicas: a Similaridade Espectral e um classificador que utiliza Support Vector Machines (SMV). Ambas as técnicas são soluções não-supervisionadas, devido a natureza não rotulada dos dados fornecidos. As duas soluções foram entregues como um produto final para a EMBRAER para pronta utilização em seu atual sistema de SHM. Ao estudar soluções completamente distribuídas para futuras implementações, desenvolvemos um algoritmo de detecção baseado em técnicas adaptativas. O principal resultado foi uma inicialização especial para um detector de máxima verossimilhança (maximum likelihood - ML) que possui uma taxa de decaimento exponencial na probabilidade de erro até um valor não nulo em regime estacionário, utilizando estimação adaptativa em uma rede distribuída. Os nós que compõem a rede devem decidir, localmente, entre duas hipóteses concorrentes com relação ao estado do ambiente onde eles estão inseridos, utilizando medidas locais e estimativas compartilhadas vindas de nós vizinhos. O desempenho exponencial não depende do valor do passo de adaptação, se este for suficientemente pequeno. Os resultas referentes a este detector distribuído foram publicados na revista internacional IEEE Signal Processing Letters.

O monitoramento remoto da saúde humana envolve basicamente o emprego da tecnologia de rede de sensores como meio de captura dos dados do paciente em observação e todo ambiente em que este se encontra. Esta tecnologia favorece o monitoramento remoto de pacientes com doenças cardíacas, com problemas respiratórios, com complicações pós-operatórias e ainda pessoas em tratamento residencial, dentre outros. Um importante elemento dos sistemas de monitoramento remoto da saúde é a sua capacidade de interagir com o meio no qual está inserido possibilitando-lhe, por exemplo, agir como provedor de informação e serviços relevantes para o usuário. Essa interação com o ambiente imputa a esse sistema características relacionadas com uma aplicação sensível ao contexto, pois esses sistemas reagem e se adaptam às mudanças nos ambientes, provendo-lhes assistência inteligente e proativa. Outro aspecto observado em sistemas de monitoramento remoto da saúde humana está relacionado às incertezas associadas à tecnologia empregada como meio para obtenção e tratamento dos dados e, aos dados que serão apresentados aos usuários especialistas - médicos. Entende-se que incertezas são elementos inevitáveis em qualquer aplicação ubíqua e sensível ao contexto, podendo ser geradas por dados incompletos ou imperfeitos. No âmbito do monitoramento da saúde humana, fatores como a influência mútua entre dados fisiológicos, comportamentais e ambientais também podem ser apontados como potenciais geradores de informação contextual incerta, além daqueles inerentes às aplicações ubíquas e sensíveis ao contexto. Nesta pesquisa, considera-se que cada sensor captura um tipo de dado e o envia para uma estação localizada na residência do paciente. O objetivo deste trabalho é apresentar um processo para a análise das incertezas contextuais presentes no monitoramento da saúde humana através de sensores. O processo empregado baseou-se na Teoria da Evidência de Dempster- Shafer e no Modelo de Fatores de Certeza. No processo denominado PRANINC, cada dado capturado pelos diferentes sensores é considerado uma evidência e o conjunto dessas evidências é considerado na formação das hipóteses. Três classes de incertezas contextuais foram especificadas: as incertezas provenientes da tecnologia empregada na transmissão dos dados capturados por sensores; as incertezas relacionadas aos próprios sensores, que estão sujeitos a erros e defeitos; e, as incertezas associadas à influência mútua entre as variáveis observadas. O método foi empregado a partir da realização de experimentos sobre arquivos com dados fisiológicos de pacientes reais, aos quais foram adicionados elementos comportamentais e ambientais. Como resultado, foi possível confirmar que o contexto influencia nos dados repassados pelo sistema de monitoramento, e que as incertezas contextuais podem influenciar na qualidade das informações fornecidas, devendo estas serem consideradas pelo especialista. / The remote monitoring of human health basically involves the use of sensor network technology as a means of capturing patient data and observation, in every environment. The sensor technology facilitates remote monitoring of patients with heart disease, respiratory problems, postoperative complications and even people in residential treatment. An important element of the health monitoring system is its ability to interact with the environment which allows, for example, act as a provider of relevant information and services to the user. The interaction with the environment provides to the system the characteristics related to a context-aware application, once this kind of system can react and adapt itself in face of environment´s changes, through a proactive and intelligent assistance. Another significant aspect of health monitoring systems is related to the uncertainties associated with the technology used as a means for obtaining and processing the data sensed by sensors, and the data which will be presented to the experts users - physicians. Uncertainties are inevitable elements in any ubiquitous and context-aware application and it can be generated by incomplete or imperfect data. In the human health monitoring by sensors factors, such as the mutual influence between physiological, behavioral and environmental data are mentioned as potential generators of uncertain contextual information. This research take into consideration that each sensor captures a data type and sends it to a station located in the patient\'s home. The objective of this paper is to present a process to analyze the contextual uncertainties present in the monitoring of human health via sensors. The method used was based on the Dempster-Shafer Evidence Theory and The Uncertainty Factor Model. The process named PRANINC, considers each data captured, by different sensors, as evidence and, all of the evidences are considered in the formation of hypotheses. Three contextual classes of uncertainties were specified: the uncertainties arising from the technology employed in transmitting the data captured by sensors, the uncertainties related to the actual sensors, which are subject to errors and defects, and the uncertainties associated with the mutual influence between the observed variables. The method was employed through conducting experiments on files with physiological data of real patients, to which, were added behavioral and environmental factors. As a result was possible to confirm that the context influences the data transferred by the monitoring system and that contextual uncertainties may influence the quality of the information which shall be considered by the specialist.

Submitted by ANA PAULA ALVES GUIMARÃES null (annapaulasun@gmail.com) on 2017-02-04T20:28:04Z No. of bitstreams: 1 dissertação-final.pdf: 4630588 bytes, checksum: 8c2806b890a1b7889d8d26b4a11e97bf (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-02-07T13:18:18Z (GMT) No. of bitstreams: 1 guimaraes_apa_me_ilha.pdf: 4630588 bytes, checksum: 8c2806b890a1b7889d8d26b4a11e97bf (MD5) / Made available in DSpace on 2017-02-07T13:18:18Z (GMT). No. of bitstreams: 1 guimaraes_apa_me_ilha.pdf: 4630588 bytes, checksum: 8c2806b890a1b7889d8d26b4a11e97bf (MD5) Previous issue date: 2016-12-20 / O monitoramento da condição estrutural é uma área que vem sendo bastante estudada por permitir a construção de sistemas que possuem a capacidade de identificar um determinado dano em seu estágio inicial, podendo assim evitar sérios prejuízos futuros. O ideal seria que estes sistemas tivessem o mínimo de interferência humana. Sistemas que abordam o conceito de aprendizagem têm a capacidade de serem autômatos. Acredita-se que por possuírem estas propriedades, os algoritmos de aprendizagem de máquina sejam uma excelente opção para realizar as etapas de identificação, localização e avaliação de um dano, com capacidade de obter resultados extremamente precisos e com taxas mínimas de erros. Este trabalho tem como foco principal utilizar o algoritmo support vector machine no auxílio do monitoramento da condição de estruturas e, com isto, obter melhor exatidão na identificação da presença ou ausência do dano, diminuindo as taxas de erros através das abordagens da aprendizagem de máquina, possibilitando, assim, um monitoramento inteligente e eficiente. Foi utilizada a biblioteca LibSVM para análise e validação da proposta. Desta forma, foi possível realizar o treinamento e classificação dos dados promovendo a identificação dos danos e posteriormente, empregando as predições efetuadas pelo algoritmo, foi possível determinar a localização dos danos na estrutura. Os resultados de identificação e localização dos danos foram bastante satisfatórios. / Structural health monitoring (SHM) is an area that has been extensively studied for allowing the construction of systems that have the ability to identify damages at an early stage, thus being able to avoid serious future losses. Ideally, these systems have the minimum of human interference. Systems that address the concept of learning have the ability to be autonomous. It is believed that by having these properties, the machine learning algorithms are an excellent choice to perform the steps of identifying, locating and assessing damage with ability to obtain highly accurate results with minimum error rates. This work is mainly focused on using support vector machine algorithm for monitoring structural condition and, thus, get better accuracy in identifying the presence or absence of damage, reducing error rates through the approaches of machine learning. It allows an intelligent and efficient monitoring system. LIBSVM library was used for analysing and validation of the proposed approach. Thus, it was feasible to conduct training and classification of data promoting the identification of damages. It was also possible to locate the damages in the structure. The results of identification and location of the damage was quite satisfactory.

O monitoramento remoto da saúde humana envolve basicamente o emprego da tecnologia de rede de sensores como meio de captura dos dados do paciente em observação e todo ambiente em que este se encontra. Esta tecnologia favorece o monitoramento remoto de pacientes com doenças cardíacas, com problemas respiratórios, com complicações pós-operatórias e ainda pessoas em tratamento residencial, dentre outros. Um importante elemento dos sistemas de monitoramento remoto da saúde é a sua capacidade de interagir com o meio no qual está inserido possibilitando-lhe, por exemplo, agir como provedor de informação e serviços relevantes para o usuário. Essa interação com o ambiente imputa a esse sistema características relacionadas com uma aplicação sensível ao contexto, pois esses sistemas reagem e se adaptam às mudanças nos ambientes, provendo-lhes assistência inteligente e proativa. Outro aspecto observado em sistemas de monitoramento remoto da saúde humana está relacionado às incertezas associadas à tecnologia empregada como meio para obtenção e tratamento dos dados e, aos dados que serão apresentados aos usuários especialistas - médicos. Entende-se que incertezas são elementos inevitáveis em qualquer aplicação ubíqua e sensível ao contexto, podendo ser geradas por dados incompletos ou imperfeitos. No âmbito do monitoramento da saúde humana, fatores como a influência mútua entre dados fisiológicos, comportamentais e ambientais também podem ser apontados como potenciais geradores de informação contextual incerta, além daqueles inerentes às aplicações ubíquas e sensíveis ao contexto. Nesta pesquisa, considera-se que cada sensor captura um tipo de dado e o envia para uma estação localizada na residência do paciente. O objetivo deste trabalho é apresentar um processo para a análise das incertezas contextuais presentes no monitoramento da saúde humana através de sensores. O processo empregado baseou-se na Teoria da Evidência de Dempster- Shafer e no Modelo de Fatores de Certeza. No processo denominado PRANINC, cada dado capturado pelos diferentes sensores é considerado uma evidência e o conjunto dessas evidências é considerado na formação das hipóteses. Três classes de incertezas contextuais foram especificadas: as incertezas provenientes da tecnologia empregada na transmissão dos dados capturados por sensores; as incertezas relacionadas aos próprios sensores, que estão sujeitos a erros e defeitos; e, as incertezas associadas à influência mútua entre as variáveis observadas. O método foi empregado a partir da realização de experimentos sobre arquivos com dados fisiológicos de pacientes reais, aos quais foram adicionados elementos comportamentais e ambientais. Como resultado, foi possível confirmar que o contexto influencia nos dados repassados pelo sistema de monitoramento, e que as incertezas contextuais podem influenciar na qualidade das informações fornecidas, devendo estas serem consideradas pelo especialista. / The remote monitoring of human health basically involves the use of sensor network technology as a means of capturing patient data and observation, in every environment. The sensor technology facilitates remote monitoring of patients with heart disease, respiratory problems, postoperative complications and even people in residential treatment. An important element of the health monitoring system is its ability to interact with the environment which allows, for example, act as a provider of relevant information and services to the user. The interaction with the environment provides to the system the characteristics related to a context-aware application, once this kind of system can react and adapt itself in face of environment´s changes, through a proactive and intelligent assistance. Another significant aspect of health monitoring systems is related to the uncertainties associated with the technology used as a means for obtaining and processing the data sensed by sensors, and the data which will be presented to the experts users - physicians. Uncertainties are inevitable elements in any ubiquitous and context-aware application and it can be generated by incomplete or imperfect data. In the human health monitoring by sensors factors, such as the mutual influence between physiological, behavioral and environmental data are mentioned as potential generators of uncertain contextual information. This research take into consideration that each sensor captures a data type and sends it to a station located in the patient\'s home. The objective of this paper is to present a process to analyze the contextual uncertainties present in the monitoring of human health via sensors. The method used was based on the Dempster-Shafer Evidence Theory and The Uncertainty Factor Model. The process named PRANINC, considers each data captured, by different sensors, as evidence and, all of the evidences are considered in the formation of hypotheses. Three contextual classes of uncertainties were specified: the uncertainties arising from the technology employed in transmitting the data captured by sensors, the uncertainties related to the actual sensors, which are subject to errors and defects, and the uncertainties associated with the mutual influence between the observed variables. The method was employed through conducting experiments on files with physiological data of real patients, to which, were added behavioral and environmental factors. As a result was possible to confirm that the context influences the data transferred by the monitoring system and that contextual uncertainties may influence the quality of the information which shall be considered by the specialist.

Orientador: Vera Lucia Pamplona Tonete / Resumo: Introdução: atualmente, embora se constate a redução dos índices de morbimortalidade infantil em todas as regiões do país, ainda há muito que se fazer para promover a saúde de crianças, especialmente daquelas mais vulneráveis. O presente estudo aborda o tema da vigilância à saúde de recém-nascidos de risco, com base em protocolo de organização de serviços. Considera-se que protocolo compõe-se de rotinas de cuidados e ações de gestão de um determinado serviço, equipe ou departamento, elaborado a partir da produção de conhecimentos e práticas dos profissionais envolvidos, com respaldo de evidências científicas. Objetivo: elaborar protocolo de organização de serviços para a redução de óbitos infantis na região de saúde do Vale do Jurumirim, São Paulo, com enfoque na vigilância à saúde de recém-nascidos de risco. Aspectos metodológicos: trata-se de uma pesquisa-intervenção, composta por uma etapa inicial, quando foi realizado estudo transversal e descritivo sobre o perfil epidemiológico regional de recém-nascidos vivos em 2013 e das crianças que foram a óbito nesse mesmo ano, durante o primeiro ano de vida, buscando a correspondência aos critérios de risco ao nascer indicados pelo Ministério da Saúde. Nesta primeira etapa, buscou-se também caracterizar a rede de atenção à saúde materno-infantil disponível na região em foco. Em uma etapa posterior, foi realizada intervenção participativa, que incluiu duas oficinas de oito horas para elaboração do protocolo pretendido, envolvendo 3... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Introduction: Although it is currently noticed a decline in infant mortality rate in all the regions of the country there is still a lot to do to promote child health care, especially those children who are more vulnerable. The current study deals with the topic of health monitoring of newborn babies at risk based on service organizing protocol. It is considered that protocol consists of routine care and management procedure of a particular service, team or department, by putting together healthcare professionals’ knowledge and experience and supported by scientific evidences. Objective: Putting together service organizing protocol to decline infant mortality in the region of Vale do Jurumirim, São Paulo, focused on health care monitoring of newborn babies at risk. Methodological Aspects: It is about intervention survey consisted of an initial stage when it was done a transversal and descriptive study of the regional epidemic profile of newborn babies born in 2013 and one-year-old children or younger who died that year, aiming at the correspondence between risk criteria at birth according to the Department of Health. In this initial stage, attention to maternal-infant health care was given when it was available in that region. In a later stage, participative intervention was carried out, which included two eight-hour workshops to put together intended protocol, involving 34 managers and healthcare professionals and maternal-infant health care monitoring of that particular reg... (Complete abstract click electronic access below) / Mestre

Identifying material parameters in composite plates is a necessary first step in a variety of structural applications. For example, understanding the material parameters of carbon fiber composite is important in investigating sensor and actuator placement on micro-air-vehicle wings for control and wing morphing purposes. Knowing the material parameters can also help examine the health of composite structures and detect wear or defects. Traditional testing methods for finding material parameters such as stiffness and damping require multiple types of experiments such as tensile tests and shaker tests. These tests are not without complications. Methods such as tensile testing can be destructive to the test specimens while use of strain gages and accelerometers can be inappropriate due to the lightweight nature of the structures. The proposed inverse problem testing methods using digital image correlation via high speed cameras can potentially eliminate the disadvantages of traditional methods as well as determine the required material parameters including stiffness and damping by conducting only one type of experiment. These material parameters include stiffness and damping for both isotropic and orthotropic materials, and ply angle layup specifically for carbon fiber materials. A finite element model based on the Kirchoff-Love thin plate theory is used to produce theoretical data for comparison with experimental data collected using digital image correlation. Shaker experiments are also carried out using digital image correlation to investigate the modal frequencies as validation of the results of the inverse problem. We apply these techniques first to an aluminum plate for which material parameters are known to test the performance and efficiency of the method. We then apply the method to a composite plates to determine not only these parameters, but also the layup angle. The inverse problem successfully estimates the Young's modulus and damping for the aluminum material. In addition, the vibration analysis produces consistent resonance frequencies for the first two modes for both theoretical and experimental data. However, carbon fiber plates present challenges due to limitations of the Kirchoff-Love plate theory used as the underlining theoretical model for the finite element approximation used in the inverse problem, resulting in a persistent mismatch of resonance frequencies in experimental data. / Graduation date: 2012