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Localização de faltas de alta impedância em sistemas de distribuição de energia : uma abordagem baseada na estimação de parâmetros associados a modelos no domínio do tempoIurinic, Leonardo Ulises January 2016 (has links)
A detecção de um tipo particular de falta, denominado de alta impedância, tem sido há muito tempo um desafio para a engenharia de proteção. Por outro lado, se a detecção é realizada com sucesso, ações preventivas e de manutenção devem ser tomadas para evitar prejuízos potenciais. Nesse contexto, os métodos de localização de faltas assumem importante papel, pois contribuem para a rápida restauração do sistema. Entretanto, os métodos clássicos, em particular as formulações a um terminal, não consideram modelos realísticos de faltas de alta impedância na sua formulação. Este tipo de falta se caracteriza pelo contato de um condutor energizado com uma superfície de elevada resistência elétrica, em que o comportamento da tensão em função da corrente apresenta uma característica não linear. Desta forma, esta tese propõe uma nova formulação para a localização de faltas de alta impedância em sistemas de distribuição de energia elétrica, com medições a um terminal, que considere tal efeito. A formulação é proposta para estimar a distância da falta em linhas de distribuição utilizando o método de estimação por mínimos quadrados, desenvolvendo um modelo no domínio do tempo do sistema elétrico e um modelo de falta de alta impedância composto por diodos antiparalelos. Mediante o modelo do sistema elétrico, é possível estimar a distância da falta, juntamente com os parâmetros da falta de alta impedância, usando sinais provenientes de um terminal, como um problema de otimização. Primeiramente, não considerando o efeito capacitivo das linhas, um modelo linear no domínio do tempo é obtido e um estimador de mínimos quadrados linear é proposto. Posteriormente, considerando o efeito capacitivo das linhas, um modelo não linear no domínio do tempo é obtido e um algoritmo de descida é proposto para a estimação dos parâmetros. Os estudos de caso foram realizados no sistema de 13 barras da IEEE modelado no Alternative Transient Program. Em todas as condições simuladas, os resultados obtidos mostraram um desempenho similar da técnica proposta com ou sem a consideração da capacitância das linhas, sendo assim, por simplicidade, optou-se pela desconsideração da capacitância. Os resultados evidenciaram que a técnica de localização de faltas proposta não mostra diferença no seu desempenho com variações do ângulo de incidência da falta e melhora quando o carregamento do sistema diminui. O erro relacionado à estimativa da distância da falta mostra-se, em geral, superior ao erro cometido ao estimar os parâmetros da falta de alta impedância. Por outro lado, os estudos de caso mostram um grande potencial para aplicar a técnica proposta como um detector e classificador de faltas de alta impedância. / High impedance fault location has always been a challenge for protection engineering. On the other hand, if this task is successfully realized maintenance action could be performed in order to avoid potential injuries. For an effective protection scheme the high impedance fault location should be performed, but a lack of research on this area is noted. This thesis proposes a new analytical formulation for high impedance fault location in power systems. The approach is developed in time domain, considering a high impedance fault model composed by two antiparallel diodes. Using this model, the fault distance and fault parameters are estimated as a minimization problem, allowing the location of the fault using one terminal signals. Firstly, the line capacitance is not considered and a linear model in time domain is obtained. In this case, the linear least square estimator is used for parameter estimation. In a second moment, the line capacitance is considered and a non-linear model in time domain is obtained. Hence, a steepest descent based estimator is proposed in order to estimate the parameters. Studies were carried out with the IEEE 13 bus modeled in the Alternative Transient Program. In view of the test results, the non-consideration of line capacitance resulted in similar accuracy in relation to its consideration. The method also is insensitive to the fault inception instant and the reduction of system load reduces the errors related to the estimations. The error related to fault distance estimation is in general greater than the estimation of the high impedance fault parameters. On the other hand, case studies shows the great potential of the technique as a high impedance fault detector method.
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Automação e Otimização de Controle via MQ e RNA para Redução das Emissões de Gases Causadores de Efeito Estufa (GHG) Geradas por Plantas de Alumínio. / Automation and optimization of control to consider MQ and RNA for Reducing greenhouse gases emissions (GHG) Generated by aluminum plants.NAGEM, Nilton Freixo 06 February 2009 (has links)
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Previous issue date: 2009-02-06 / Nowadays the regulatory restrictions and global concern with the environment are
leading the aluminum industry to develop a sustainable model production, with
propose to reduce the environmental impacts of its economic activity. Thus, becomes
necessary improvements in the operational and control standards for the aluminium
production. These needs have major objectives, decrease green house gases (GHG)
energy consumption and increase in productive.
As technological alternatives such as smart feeders for Point Feeders pots and
the development of new control for automatic adjust of the number of manifolds to be
broke in the next cycle for Side Break pots will help to improve the decrease of Green
Houses Gases.
The smart feeders had a significant decrease in the anode effect frequency and
consequently a decrease in anode effect time too. For the VSS Side Break pots were
possible to create a decision matrix using the Least Square estimation (LS) of the
resistance slope and curvature to adjust the number of manifolds. Another approach
that showed promising results in the simulation was the neuronal networks for pattern
recognition, especial class knows by probabilistic neural network. / Atualmente a maior regulamentação e preocupação mundial com o ambiente
estão levando as indústrias de alumínio ao desenvolvimento de um modelo
sustentável de produção, com o escopo de reduzir os impactos ambientais de sua
atividade econômica. Assim, tornam-se imprescindíveis melhorias nas práticas
operacionais e de controle de sua produção. Tais necessidades têm como foco
principal a redução dos gases de efeito estufa (Green Houses Gases - GHG), redução
do consumo de energia e aumento de produtividade.
Como alternativas tecnológicas para mitigar o problema ambiental de Green
Houses Gases, os “alimentadores inteligentes” para as cubas com alimentação Point
Feeder e o desenvolvimento de novos controles para o ajuste automático da
quantidade de “manifolds” a serem quebrados durante a alimentação para cubas Side
Break são soluções viáveis.
Os alimentadores “inteligentes” mostram uma redução da freqüência de efeito
anódico e conseqüentemente no tempo em que a cuba fica em efeito anódico. Para as
cubas VSS Side Break foi possível criar uma matriz de decisão através dos valores
dos estimadores MQ utilizando a inclinação e curvatura da resistência para o ajuste de
“manifolds”. Outra abordagem foi a utilização de redes neuronais para determinar a
forma da curva de resistência, com a utilização de redes neuronais probabilísticas.
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Aplicação dos modelos paramétricos ARMAV e ARV na identificação modal de sistemas mecânicos / Application of ARMAV and ARV parametric models in the modal identification of mechanical systemsNeves, Alessandra Teodoro 21 December 2006 (has links)
A análise modal experimental tem contribuído de forma decisiva para caracterização e solução de problemas de engenharia, relacionados à vibração estrutural. Uma das áreas fundamentais da análise modal experimental é a identificação de sistemas, cujo objetivo é determinar as propriedades dinâmicas de uma estrutura, descritas através das freqüências naturais, fatores de amortecimento e modos de vibrar do sistema em análise. Neste trabalho é realizado um estudo sobre as técnicas paramétricas de identificação de sistemas no domínio do tempo utilizando o modelo auto-regressivo de média móvel vetorial (ARMAV) e o modelo auto-regressivo vetorial (ARV). Em ambos os modelos, os procedimentos de identificação dos parâmetros auto-regressivos, responsáveis pela dinâmica do sistema, são estimados utilizando a aproximação dos mínimos quadrados. A partir desses coeficientes um modelo em espaço de estado do sistema é construído, a fim de estimar os parâmetros modais do sistema dinâmico. A ordem do modelo ARMAV, necessária para determinar as características dinâmicas do sistema, é estimada através do critério de informação Bayesiana (BIC). Para o caso do procedimento baseado no modelo ARV, onde apenas as respostas do sistema são consideradas no processo de identificação, uma nova técnica é proposta para solucionar o problema da identificação da ordem do modelo dinâmico. Essa técnica, baseada na estabilidade das freqüências naturais estimadas em várias identificações, contribuiu também para automação do procedimento de identificação. O desempenho dos algoritmos de identificação utilizando o modelo ARMAV, e o modelo ARV juntamente com a nova metodologia desenvolvida, é verificado através de aplicações a dados provenientes de simulações numéricas e de um ensaio experimental realizado em uma placa de alumínio. / The experimental modal analysis has contribued in a decisive way to characterization and solution of engineering problems, related to structural vibration. One of the fundamental areas of the experimental modal analysis is the mechanical systems identification, whose objective is to identify the dynamic properties of a structure, described through the natural frequencies, damping ratios and mode shapes of the system in analysis. In this work a study is accomplished on the parametric techniques of systems identification in time domain using the Auto-Regressive Moving Average Vector (ARMAV) and the Auto-Regressive Vector (ARV) models. In these models, the procedures of the auto-regressive parameters identification that describes the dynamics of the system are estimated using the least square approach. Trough these coefficients a model in state space is built, in order to identify the modal parameters of the dynamic system. The order of the ARMAV model, necessary to determine the dynamic characteristics of the system, is estimated through Bayesian Information Criterion (BIC). For the procedure based on the model ARV, where only the system responses are considered in the identification process, a new technique is proposed to solve the identification problem of the order of the dynamic model. This technique, based on the stability of the natural frequencies in several identifications, also contributed to automation of the identification procedure. The performance of these identification algorithms using the ARMAV model, and the ARV model together with the new developed methodology, is verified using data from numerical simulations and from an experimental test accomplished in an aluminum plate.
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時間數列模式之拔靴模擬法研究郭玉麟 Unknown Date (has links)
本篇文章之主要目的是將Efron於1979年所提出之拔靴法(Bootstrap method)應用在非常態ARMA(p,q)模式上。我們考慮的結構包括AR(1),AR(2),MA(1),MA(2),ARMA(1,1),而考慮的非常態干擾分配則包括對數常態分配,均勻分配,迦瑪分配以及指數分配,對每一個模式,所設定之參數值組合涵蓋了使模式平穩及/或可逆之參數組合中的重要區域。我們比較傳統的最小平方法與利用500個拔靴重複子(Bootstrap repetitions)的拔靴法在參數估計上的差異。進一步我們也以MAE及MAPE等準則比較了這兩種估計模式在預測上的優劣。模擬結果顯示,在參數估計方面,當所設定的參數範圍接近非平穩或非可逆條件時,拔靴法所獲得的參數估計值表現會較佳。然而在預測效益方面,利用往前一期預測法,並配合拔靴法重新改造的數列,在具有非常態干擾項AR(1),AR(2)以及ARMA(1,1)模式的預測效益上的確有較佳的效果。
關鍵詞:拔靴法,非常態ARMA(p,q) ,最小平方法 / In this thesis, the Bootstrap technique proposed by Efron in 1979 is applied to parameter estimation and forecasting of non-normal ARMA(p,q) time series models. A simulation study is conducted where artificial time series are generated from various ARMA structures with different non-normal noise distributions. The ARMA structures considered in the simulation are AR(1), AR(2), MA(1), MA(2) and ARMA(1,1), while the non-normal noise distributions include Log-normal, Uniform, Gamma, and Exponential distributions. For each structure, the parameter values used cover important regions of the stationary and/or invertible parameter space . The conventional least-square estimators of the parameters are compared with the corresponding non-parametric Bootstrap estimator, obtained by using 500 Bootstrap repetitions for each series. Furthermore, forecasts based on these estimated model are also compared by using such criteria as MAE and MAPE .
KEY WORDS bootstrap; non-normal ARMA(p,q); least-square
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Development Of A Multigrid Accelerated Euler Solver On Adaptively Refined Two- And Three-dimensional Cartesian GridsCakmak, Mehtap 01 July 2009 (has links) (PDF)
Cartesian grids offer a valuable option to simulate aerodynamic flows around complex geometries such as multi-element airfoils, aircrafts, and rockets. Therefore, an adaptively-refined Cartesian grid generator and Euler solver are developed. For the mesh generation part of the algorithm, dynamic data structures are used to determine connectivity information between cells and uniform mesh is created in the domain. Marching squares and cubes algorithms are used to form interfaces of cut and split cells. Geometry-based cell adaptation is applied in the mesh generation. After obtaining appropriate mesh around input geometry, the solution is obtained using either flux vector splitting method or Roe&rsquo / s approximate Riemann solver with cell-centered approach. Least squares reconstruction of flow variables within the cell is used to determine high gradient regions of flow. Solution based adaptation method is then applied to current mesh in order to refine these regions and also coarsened regions where unnecessary small cells exist. Multistage time stepping is used with local time steps to increase the convergence rate. Also FAS multigrid technique is used in order to increase the convergence rate. It is obvious that implementation of geometry and solution based adaptations are easier for Cartesian meshes than other types of meshes. Besides, presented numerical results show the accuracy and efficiency of the algorithm by especially using geometry and solution based adaptation. Finally, Euler solutions of Cartesian grids around airfoils, projectiles and wings are compared with the experimental and numerical data available in the literature and accuracy and efficiency of the solver are verified.
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A Study On Symbol Synchronization And Channel Estimation Form-ary Orthogonal TransmissionKaragozlu, Eren 01 September 2011 (has links) (PDF)
In this thesis, two key issues regarding M-ary orthogonal signaling systems, namely channel estimation and symbol timing recovery are investigated. Kasami codes, which are also called quasi orthogonal codes, are used for transmission of the information in place of orthogonal waveforms. In order to achieve symbol synchronization, a timing recovery scheme based on the Maximum Likelihood (ML) estimation of timing offset is proposed and the effects of proposed structure over the receiver performance are examined by using computer simulations. Moreover, the receiver performance of M-ary orthogonal signals transmitted over multipath fading channel is investigated. Least Square (LS) approach, based on the transmission of known training sequence, is used to estimate the channel impulse response. In addition to this, frame synchronization is employed at the receiver to extract the timing information by determining the start time of the received symbols. Computer simulations related to the proposed receiver structure are carried out in order to observe how the system performance is affected under multipath fading channel. Parameter selection guides regarding a good performance are also provided.
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Infrared Spectroscopy in Combination with Advanced Statistical Methods for Distinguishing Viral Infected Biological CellsTang, Tian 17 November 2008 (has links)
Fourier Transform Infrared (FTIR) microscopy is a sensitive method for detecting difference in the morphology of biological cells. In this study FTIR spectra were obtained for uninfected cells, and cells infected with two different viruses. The spectra obtained are difficult to discriminate visually. Here we apply advanced statistical methods to the analysis of the spectra, to test if such spectra are useful for diagnosing viral infections in cells. Logistic Regression (LR) and Partial Least Squares Regression (PLSR) were used to build models which allow us to diagnose if spectral differences are related to infection state of the cells. A three-fold, balanced cross-validation method was applied to estimate the shrinkages of the area under the receiving operator characteristic curve (AUC), and specificities at sensitivities of 95%, 90% and 80%. AUC, sensitivity and specificity were used to gauge the goodness of the discrimination methods. Our statistical results shows that the spectra associated with different cellular states are very effectively discriminated. We also find that the overall performance of PLSR is better than that of LR, especially for new data validation. Our analysis supports the idea that FTIR microscopy is a useful tool for detection of viral infections in biological cells.
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Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIRLuo, Shan 13 July 2009 (has links)
Fourier transform infrared (FTIR) spectroscopy, one method of electromagnetic radiation for detecting specific cellular molecular structure, can be used to discriminate different types of cells. The objective is to find the minimum time (choice among 2 hour, 4 hour and 6 hour) to record FTIR readings such that different viruses can be discriminated. A new method is adopted for the datasets. Briefly, inner differences are created as the control group, and Wilcoxon Signed Rank Test is used as the first selecting variable procedure in order to prepare the next stage of discrimination. In the second stage we propose either partial least squares (PLS) method or simply taking significant differences as the discriminator. Finally, k-fold cross-validation method is used to estimate the shrinkages of the goodness measures, such as sensitivity, specificity and area under the ROC curve (AUC). There is no doubt in our mind 6 hour is enough for discriminating mock from Hsv1, and Coxsackie viruses. Adeno virus is an exception.
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Design and implementation of sensor fusion for the towed synthetic aperture sonarMeng, Rui Daniel January 2007 (has links)
For synthetic aperture imaging, position and orientation deviation is of great concern. Unknown motions of a Synthetic Aperture Sonar (SAS) can blur the reconstructed images and degrade image quality considerably. Considering the high sensitivity of synthetic aperture imaging technique to sonar deviation, this research aims at providing a thorough navigation solution for a free-towed synthetic aperture sonar (SAS) comprising aspects from the design and construction of the navigation card through to data postprocessing to produce position, velocity, and attitude information of the sonar. The sensor configuration of the designed navigation card is low-cost Micro-Electro-Mechanical-Systems (MEMS) Magnetic, Angular Rate, and Gravity (MARG) sensors including three angular rate gyroscopes, three dual-axial accelerometers, and a triaxial magnetic hybrid. These MARG sensors are mounted orthogonally on a standard 180mm Eurocard PCB to monitor the motions of the sonar in six degrees of freedom. Sensor calibration algorithms are presented for each individual sensor according to its characteristics to precisely determine sensor parameters. The nonlinear least square method and two-step estimator are particularly used for the calibration of accelerometers and magnetometers. A quaternion-based extended Kalman filter is developed based on a total state space model to fuse the calibrated navigation data. In the model, the frame transformations are described using quaternions instead of other attitude representations. The simulations and experimental results are demonstrated in this thesis to verify the capability of the sensor fusion strategy.
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Description et prédiction à partir de données structurées en plusieurs tableaux : Application en épidémiologie animale.Bougeard, Stéphanie 11 December 2007 (has links) (PDF)
Ce travail de recherche s'inscrit dans le cadre des méthodes factorielles qui permettent de décrire et prédire des données structurées en plusieurs tableaux. Les objectifs et la nature des données d'épidémiologie analytique dans le domaine vétérinaire ont amené à centrer le travail sur les méthodes de régression multibloc, qui orientent la description de plusieurs tableaux de variables vers l'explication d'un autre tableau. Un des principaux objectifs est de contribuer à la réflexion sur la sensibilité de ces méthodes à la multicolinéarité. Des méthodes statistiques existantes sont présentées et reliées dans un cadre unifié, relevant soit de critères à maximiser comparables, soit d'un continuum général les reliant. De nouvelles méthodes peu vulnérables à l'égard de la multicolinéarité, et s'appliquant au cas de données structurées en deux puis en (K+1) tableaux, sont proposées. L'intérêt de ces méthodes, ainsi que des continuums qui leur sont associés, est illustré sur la base d'études de cas réels en épidémiologie. Ce travail de recherche a permis d'appliquer les méthodes multiblocs au domaine de l'épidémiologie animale, dans lequel elles n'avaient pas encore été utilisées.
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