428 resultados para Engenharia Elétrica
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This work proposes hardware architecture, VHDL described, developed to embedded Artificial Neural Network (ANN), Multilayer Perceptron (MLP). The present work idealizes that, in this architecture, ANN applications could easily embed several different topologies of MLP network industrial field. The MLP topology in which the architecture can be configured is defined by a simple and specifically data input (instructions) that determines the layers and Perceptron quantity of the network. In order to set several MLP topologies, many components (datapath) and a controller were developed to execute these instructions. Thus, an user defines a group of previously known instructions which determine ANN characteristics. The system will guarantee the MLP execution through the neural processors (Perceptrons), the components of datapath and the controller that were developed. In other way, the biases and the weights must be static, the ANN that will be embedded must had been trained previously, in off-line way. The knowledge of system internal characteristics and the VHDL language by the user are not needed. The reconfigurable FPGA device was used to implement, simulate and test all the system, allowing application in several real daily problems
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The aim of this work is to characterize and use the characteristic parameters of the planar structures constructed with fin lines looking for their applications in devices, using PBG Photonic Band Gap photonic materials as substrate, operating in the millimeter and optic wave bands.The PBG theory will be applied for the relative permittivity attainment for the PBG photonic substrate s and p polarizations. The parameters considered in the structures characterization are the complex propagation constant and the characteristic impedance of unilateral and bilateral fin lines that were obtained by the use of the TTL Transverse Transmission Line Method, together with the Method of the Moments. The final part of this work comprises studies related to the behavior of the asymmetric unilateral fin line coupler with photonic substrate. This research opens perspectives for new works in this modern area. Numerical results are shown by means of bi-dimensional and three-dimensional graphics. Conclusions and suggestions for future works are also presented
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This work presents a description of models development at DigSILENT PowerFactoryT M program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryT M and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryT M program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doublyfed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances
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Antenna arrays are able to provide high and controlled directivity, which are suitable for radiobase stations, radar systems, and point-to-point or satellite links. The optimization of an array design is usually a hard task because of the non-linear characteristic of multiobjective, requiring the application of numerical techniques, such as genetic algorithms. Therefore, in order to optimize the electronic control of the antenna array radiation pattem through genetic algorithms in real codification, it was developed a numerical tool which is able to positioning the array major lobe, reducing the side lobe levels, canceling interference signals in specific directions of arrival, and improving the antenna radiation performance. This was accomplished by using antenna theory concepts and optimization methods, mainly genetic algorithms ones, allowing to develop a numerical tool with creative genes codification and crossover rules, which is one of the most important contribution of this work. The efficiency of the developed genetic algorithm tool is tested and validated in several antenna and propagation applications. 11 was observed that the numerical results attend the specific requirements, showing the developed tool ability and capacity to handle the considered problems, as well as a great perspective for application in future works.
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This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks
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The development of wireless telecommunication in the last years has been great. It has been taking academics to conceive new ideas and techniques. Their aims are to increase the capacity and the quality of the system s services. Cells that are smaller every time, frequencies that are every time higher and environments that get more and more complex, all those facts deserve more accurate models the propagation prediction techniques are inserted in this context and results with a merger of error that is compatible with the next generations of communication systems. The objective of this Work is to present results of a propagation measurement campaign, aiming at pointing the characteristics of the mobile systems covering in the city of Natal (state of Rio Grande do Norte, Brazil). A mobile laboratory was set up, using the infra-structure available and frequently used by ANATEL. The measures were taken in three different areas: one characterized by high buildings, high relief, presence of trees and towers of different highs. These areas covered the city s central zone, a suburban / rural zone and a section of coast surrounded by sand dunes. It is important to highlight that the analysis was made taking into consideration the actual reality of cellular systems with covering ranges by reduced cells, with the intent of causing greater re-use of frequencies and greater capacity of telephone traffic. The predominance of telephone traffic by cell in the city of Natal occurs within a range inferior to 3 (three) km from the Radio-Base Station. The frequency band used was 800 MHz, corresponding to the control channels of the respective sites, which adopt the FSK modulation technique. This Dissertation starts by presenting a general vision of the models used for predicting propagation. Then, there is a description of the methodology used in the measuring, which were done using the same channels of control of the cellular system. The results obtained were compared with many existing prediction models, and some adaptations were developed by using regression techniques trying to obtain the most optimized solutions. Furthermore, according to regulations from the old Brazilian Holding Telebrás, a minimum covering of 90% of a determined previously area, in 90% of the time, must be obeyed when implanting cellular systems. For such value to be reached, considerations and studies involving the specific environment that is being covered are important. The objective of this work is contribute to this aspect
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In this work, we propose a Geographical Information System that can be used as a tool for the treatment and study of problems related with environmental and city management issues. It is based on the Scalable Vector Graphics (SVG) standard for Web development of graphics. The project uses the concept of remate and real-time mar creation by database access through instructions executed by browsers on the Internet. As a way of proving the system effectiveness, we present two study cases;.the first on a region named Maracajaú Coral Reefs, located in Rio Grande do Norte coast, and the second in the Switzerland Northeast in which we intended to promote the substitution of MapServer by the system proposed here. We also show some results that demonstrate the larger geographical data capability achieved by the use of the standardized codes and open source tools, such as Extensible Markup Language (XML), Document Object Model (DOM), script languages ECMAScript/ JavaScript, Hypertext Preprocessor (PHP) and PostgreSQL and its extension, PostGIS
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A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics
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This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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Foundation Fieldbus Industrial networks are the high standard technology which allows users to create complex control logic and totally decentralized. Although being so advanced, they still have some limitations imposed by their own technology. Attempting to solve one of these limitations, this paper describes how to design a Fuzzy controller in a Foundation Fieldbus network using their basic elements of programming, the functional blocks, so that the network remains fully independent of other devices other than the same instruments that constitute it. Moreover, in this work was developed a tool that aids this process of building the Fuzzy controller, setting the internal parameters of functional blocks and informing how many and which blocks should be used for a given structure. The biggest challenge in creating this controller is exactly the choice of blocks and how to arrange them in order to effectuate the same functions of a Fuzzy controller implemented in other kind of environment. The methodology adopted was to divide each one of the phases of a traditional Fuzzy controller and then create simple structures with the functional blocks to implement them. At the end of the work, the developed controller is compared with a Fuzzy controller implemented in a mathematical program that it has a proper tool for the development and implementation of Fuzzy controllers, obtaining comparatives graphics of performance between both
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Following the new tendency of interdisciplinarity of modern science, a new field called neuroengineering has come to light in the last decades. After 2000, scientific journals and conferences all around the world have been created on this theme. The present work comprises three different subareas related to neuroengineering and electrical engineering: neural stimulation; theoretical and computational neuroscience; and neuronal signal processing; as well as biomedical engineering. The research can be divided in three parts: (i) A new method of neuronal photostimulation was developed based on the use of caged compounds. Using the inhibitory neurotransmitter GABA caged by a ruthenium complex it was possible to block neuronal population activity using a laser pulse. The obtained results were evaluated by Wavelet analysis and tested by non-parametric statistics. (ii) A mathematical method was created to identify neuronal assemblies. Neuronal assemblies were proposed as the basis of learning by Donald Hebb remain the most accepted theory for neuronal representation of external stimuli. Using the Marcenko-Pastur law of eigenvalue distribution it was possible to detect neuronal assemblies and to compute their activity with high temporal resolution. The application of the method in real electrophysiological data revealed that neurons from the neocortex and hippocampus can be part of the same assembly, and that neurons can participate in multiple assemblies. (iii) A new method of automatic classification of heart beats was developed, which does not rely on a data base for training and is not specialized in specific pathologies. The method is based on Wavelet decomposition and normality measures of random variables. Throughout, the results presented in the three fields of knowledge represent qualification in neural and biomedical engineering
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This work treats of an implementation OFDMA baseband processor in hardware for LTE Downlink. The LTE or Long Term Evolution consist the last stage of development of the technology called 3G (Mobile System Third Generation) which offers an increasing in data rate and more efficiency and flexibility in transmission with application of advanced antennas and multiple carriers techniques. This technology applies in your physical layer the OFDMA technical (Orthogonal Frequency Division Multiple Access) for generation of signals and mapping of physical resources in downlink and has as base theoretical to OFDM multiple carriers technique (Orthogonal Frequency Division Multiplexing). With recent completion of LTE specifications, different hardware solutions have been developed, mainly, to the level symbol processing where the implementation of OFDMA processor in base band is commonly considered, because it is also considered a basic architecture of others important applications. For implementation of processor, the reconfigurable hardware offered by devices as FPGA are considered which shares not only to meet the high requirements of flexibility and adaptability of LTE as well as offers possibility of an implementation quick and efficient. The implementation of processor in reconfigurable hardware meets the specifications of LTE physical layer as well as have the flexibility necessary for to meet others standards and application which use OFDMA processor as basic architecture for your systems. The results obtained through of simulation and verification functional system approval the functionality and flexibility of processor implemented
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In a real process, all used resources, whether physical or developed in software, are subject to interruptions or operational commitments. However, in situations in which operate critical systems, any kind of problem may bring big consequences. Knowing this, this paper aims to develop a system capable to detect the presence and indicate the types of failures that may occur in a process. For implementing and testing the proposed methodology, a coupled tank system was used as a study model case. The system should be developed to generate a set of signals that notify the process operator and that may be post-processed, enabling changes in control strategy or control parameters. Due to the damage risks involved with sensors, actuators and amplifiers of the real plant, the data set of the faults will be computationally generated and the results collected from numerical simulations of the process model. The system will be composed by structures with Artificial Neural Networks, trained in offline mode using Matlab®
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This work aims to predict the total maximum demand of a transformer that will be used in power systems to attend a Multiple Unit Consumption (MUC) in design. In 1987, COSERN noted that calculation of maximum total demand for a building should be different from that which defines the scaling of the input protection extension in order to not overestimate the power of the transformer. Since then there have been many changes, both in consumption habits of the population, as in electrical appliances, so that this work will endeavor to improve the estimation of peak demand. For the survey, data were collected for identification and electrical projects in different MUCs located in Natal. In some of them, measurements were made of demand for 7 consecutive days and adjusted for an integration interval of 30 minutes. The estimation of the maximum demand was made through mathematical models that calculate the desired response from a set of information previously known of MUCs. The models tested were simple linear regressions, multiple linear regressions and artificial neural networks. The various calculated results over the study were compared, and ultimately, the best answer found was put into comparison with the previously proposed model