79 resultados para Resposta em frequencia (Egenharia Elétrica)


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Relevant researches have been growing on electric machine without mancal or bearing and that is generally named bearingless motor or specifically, mancal motor. In this paper it is made an introductory presentation about bearingless motor and its peripherical devices with focus on the design and implementation of sensors and interfaces needed to control rotor radial positioning and rotation of the machine. The signals from the machine are conditioned in analogic inputs of DSP TMS320F2812 and used in the control program. This work has a purpose to elaborate and build a system with sensors and interfaces suitable to the input and output of DSP TMS320F2812 to control a mancal motor, bearing in mind the modularity, simplicity of circuits, low number of power used, good noise imunity and good response frequency over 10 kHz. The system is tested at a modified ordinary induction motor of 3,7 kVA to be used with a bearingless motor with divided coil

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Due to the large amount of television content, which emerged from the Digital TV, viewers are facing a new challenge, how to find interesting content intuitively and efficiently. The Personalized Electronic Programming Guides (pEPG) arise as an answer to this complex challenge. We propose TrendTV a layered architecture that allows the formation of social networks among viewers of Interactive Digital TV based on online microblogging. Associated with a pEPG, this social network allows the viewer to perform content filtering on a particular subject from the indications made by other viewers of his network. Allowing the viewer to create his own indications for a particular content when it is displayed, or to analyze the importance of a particular program online, based on these indications. This allows any user to perform filtering on content and generate or exchange information with other users in a flexible and transparent way, using several different devices (TVs, Smartphones, Tablets or PCs). Moreover, this architecture defines a mechanism to perform the automatic exchange of channels based on the best program that is showing at the moment, suggesting new components to be added to the middleware of the Brazilian Digital TV System (Ginga). The result is a constructed and dynamic database containing the classification of several TV programs as well as an application to automatically switch to the best channel of the moment

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This work shows a study about the Generalized Predictive Controllers with Restrictions and their implementation in physical plants. Three types of restrictions will be discussed: restrictions in the variation rate of the signal control, restrictions in the amplitude of the signal control and restrictions in the amplitude of the Out signal (plant response). At the predictive control, the control law is obtained by the minimization of an objective function. To consider the restrictions, this minimization of the objective function is done by the use of a method to solve optimizing problems with restrictions. The chosen method was the Rosen Algorithm (based on the Gradient-projection). The physical plants in this study are two didactical systems of water level control. The first order one (a simple tank) and another of second order, which is formed by two tanks connected in cascade. The codes are implemented in C++ language and the communication with the system to be done through using a data acquisition panel offered by the system producer

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A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use

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Attacks to devices connected to networks are one of the main problems related to the confidentiality of sensitive data and the correct functioning of computer systems. In spite of the availability of tools and procedures that harden or prevent the occurrence of security incidents, network devices are successfully attacked using strategies applied in previous events. The lack of knowledge about scenarios in which these attacks occurred effectively contributes to the success of new attacks. The development of a tool that makes this kind of information available is, therefore, of great relevance. This work presents a support system to the management of corporate security for the storage, retrieval and help in constructing attack scenarios and related information. If an incident occurs in a corporation, an expert must access the system to store the specific attack scenario. This scenario, made available through controlled access, must be analyzed so that effective decisions or actions can be taken for similar cases. Besides the strategy used by the attacker, attack scenarios also exacerbate vulnerabilities in devices. The access to this kind of information contributes to an increased security level of a corporation's network devices and a decreased response time to occurring incidents

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Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections

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The opening of the Brazilian market of electricity and competitiveness between companies in the energy sector make the search for useful information and tools that will assist in decision making activities, increase by the concessionaires. An important source of knowledge for these utilities is the time series of energy demand. The identification of behavior patterns and description of events become important for the planning execution, seeking improvements in service quality and financial benefits. This dissertation presents a methodology based on mining and representation tools of time series, in order to extract knowledge that relate series of electricity demand in various substations connected of a electric utility. The method exploits the relationship of duration, coincidence and partial order of events in multi-dimensionals time series. To represent the knowledge is used the language proposed by Mörchen (2005) called Time Series Knowledge Representation (TSKR). We conducted a case study using time series of energy demand of 8 substations interconnected by a ring system, which feeds the metropolitan area of Goiânia-GO, provided by CELG (Companhia Energética de Goiás), responsible for the service of power distribution in the state of Goiás (Brazil). Using the proposed methodology were extracted three levels of knowledge that describe the behavior of the system studied, representing clearly the system dynamics, becoming a tool to assist planning activities

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This work proposes a new technique for phasor estimation applied in microprocessor numerical relays for distance protection of transmission lines, based on the recursive least squares method and called least squares modified random walking. The phasor estimation methods have compromised their performance, mainly due to the DC exponential decaying component present in fault currents. In order to reduce the influence of the DC component, a Morphological Filter (FM) was added to the method of least squares and previously applied to the process of phasor estimation. The presented method is implemented in MATLABr and its performance is compared to one-cycle Fourier technique and conventional phasor estimation, which was also based on least squares algorithm. The methods based on least squares technique used for comparison with the proposed method were: forgetting factor recursive, covariance resetting and random walking. The techniques performance analysis were carried out by means of signals synthetic and signals provided of simulations on the Alternative Transient Program (ATP). When compared to other phasor estimation methods, the proposed method showed satisfactory results, when it comes to the estimation speed, the steady state oscillation and the overshoot. Then, the presented method performance was analyzed by means of variations in the fault parameters (resistance, distance, angle of incidence and type of fault). Through this study, the results did not showed significant variations in method performance. Besides, the apparent impedance trajectory and estimated distance of the fault were analysed, and the presented method showed better results in comparison to one-cycle Fourier algorithm

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The generation of electricity in Brazil is predominantly renewable, with internal hydraulic generation being more than 70% of its energy matrix. The electricity rationing occurred in 2001 due to lack of rain, led the country to increase the participation of alternative energy sources. This need for new sources of energy makes the regional potential to be exploited, which configures the change of generation model from centralized generation to distributed generation. Among the alternative sources of energy, the solar energy is presented as very promising for Brazil, given that most of its territory is located near to the equator line, which implies days with greater number of hours of solar radiation. The state of Rio Grande do Norte (RN) has one of the highest levels of solar irradiation of the Brazilian territory, making it eligible to receive investments for the installation of photovoltaic solar plants. This thesis will present the state-of-the-art in solar photovoltaic power generation and will examine the potential for generation of solar photovoltaic power in Brazil and RN, based on solarimetrics measurements conducted by various institutions and also measurements performed in Natal, the state capital

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Atualmente há uma grande preocupação em relação a substituição das fontes não renováveis pelas fontes renováveis na geração de energia elétrica. Isto ocorre devido a limitação do modelo tradicional e da crescente demanda. Com o desenvolvimento dos conversores de potência e a eficácia dos esquemas de controle, as fontes renováveis têm sido interligadas na rede elétrica, em um modelo de geração distribuída. Neste sentido, este trabalho apresenta uma estratégia de controle não convencional, com a utilização de um controlador robusto, para a interconexão de sistemas fotovoltaicos com à rede elétrica trifásica. A compensação da qualidade de energia no ponto de acoplamento comum (PAC) é realizada pela estratégia proposta. As técnicas tradicionais utilizam detecção de harmônicos, já neste trabalho o controle das correntes é feita de uma forma indireta sem a necessidade desta detecção. Na estratégia indireta é de grande importância que o controle da tensão do barramento CC seja efetuado de uma forma que não haja grandes flutuações, e que a banda passante do controlador em regime permanente seja baixa para que as correntes da rede não tenham um alto THD. Por este motivo é utilizado um controlador em modo dual DSM-PI, que durante o transitório se comporta como um controlador em modo deslizante SM-PI, e em regime se comporta como um PI convencional. A corrente é alinhada ao ângulo de fase do vetor tensão da rede elétrica, obtido a partir do uso de um PLL. Esta aproximação permite regular o fluxo de potência ativa, juntamente com a compensação dos harmônicos e também promover a correção do fator de potência no ponto de acoplamento comum. Para o controle das correntes é usado um controlador dupla sequencia, que utiliza o princípio do modelo interno. Resultados de simulação são apresentados para demonstrar a eficácia do sistema de controle proposto

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Currently, there are several power converter topologies applied to wind power generation. The converters allow the use of wind turbines operating at variable speed, enabling better use of wind forces. The high performance of the converters is being increasingly demanded, mainly because of the increase in the power generation capacity by wind turbines, which gave rise to various converter topologies, such as parallel or multilevel converters. The use of converters allow effective control of the power injected into the grid, either partially, for the case using partial converter, or total control for the case of using full converter. The back-to-back converter is one of the most used topologies in the market today, due to its simple structure, with few components, contributing to robust and reliable performance. In this work, is presented the implementation of a wind cogeneration system using a permanent magnet synchronous generator (PMSG) associated with a back-to-back power converter is proposed, in order to inject active power in an electric power system. The control strategy of the active power delivered to the grid by cogeneration is based on the philosophy of indirect control

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Frequency selective surfaces (Frequency Selective Surface - FSS) are often used in various applications in telecommunications. Some of these applications may require that these structures have response with multiple resonance bands. Other applications require that the FSS response have large frequency range, to meet the necessary requirements. FSS to design with these features there are numerous techniques cited in the scientific literature. Thus, the purpose of this paper is to examine some common techniques such as: Overlap of FSS; Elements combined; Elements Elements convolucionados and fractals. And designing multiband FSS and / or broadband selecting simple ways in terms of construction and occupy the smallest possible space, aiming at practical applications. Given these requirements, three projects FSS were performed: a technology applied to IEEE 802.11 a/b/g/n and two projects for application in UWB. In project development, commercial software Ansoft DesignerTM and experimental results were satisfactory was used

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This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas

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The conversion of solar energy in electric with photo-voltaic cells has been carried through exclusively with devices of semiconducting junction. To put this situation comes moving for better in them last years, thanks to a new technology of production of known solar cells as Dye Solar Cell. This proposal aims at to develop a DSC having as dye lavonoides of the Capsicum frutescens (malagueta pepper). Front is considered to evaluate the photo-voltaic parameters varies it regions of the visible specter, as well as a good efficiency of conversion