Desenvolvimento de antenas de microfita e antenas DRA Broadband

The search for ever smaller device and without loss of performance has been increasingly investigated by researchers involving applied electromagnetics. Antennas using ceramics materials with a high dielectric constant, whether acting as a substract element of patch radiating or as the radiant element are in evidence in current research, that due to the numerous advantages offered, such as: low profile, ability to reduce the its dimensions when compared to other devices, high efficiency of ratiation, suitability the microwave range and/or millimeter wave, low temperature coefficient and low cost. The reason for this high efficiency is that the dielectric losses of ceramics are very low when compared to commercially materials sold used in printed circuit boards, such as fiberglass and phenolite. These characteristics make ceramic devices suitable for operation in the microwave band. Combining the design of patch antennas and/or dielectric resonator antenna (DRA) to certain materials and the method of synthesis of these powders in the manufacture of devices, it s possible choose a material with a dielectric constant appropriate for the design of an antenna with the desired size. The main aim of this work is the design of patch antennas and DRA antennas on synthesis of ceramic powders (synthesis by combustion and polymeric precursors - Pe- chini method) nanostructured with applications in the microwave band. The conventional method of mix oxides was also used to obtain nanometric powders for the preparation of tablets and dielectric resonators. The devices manufactured and studied on high dielectric constant materials make them good candidates to have their small size compared to other devices operating at the same frequency band. The structures analyzed are excited by three different techniques: i) microstrip line, ii) aperture coupling and iii) inductive coupling. The efficiency of these techniques have been investigated experimentally and compared with simulations by Ansoft HFSS, used in the accurate analysis of the electromagnetic behavior of antennas over the finite element method (FEM). In this thesis a literature study on the theory of microstrip antennas and DRA antenna is performed. The same study is performed about the materials and methods of synthesis of ceramic powders, which are used in the manufacture of tablets and dielectric cylinders that make up the devices investigated. The dielectric media which were used to support the analysis of the DRA and/or patch antennas are analyzed using accurate simulations using the finite difference time domain (FDTD) based on the relative electrical permittivity (er) and loss tangent of these means (tand). This work also presents a study on artificial neural networks, showing the network architecture used and their characteristics, as well as the training algorithms that were used in training and modeling some parameters associated with the devices investigated

Um algoritmo para estimação de estado em alimentadores de distribuição de energia elétrica com base no método da soma de potências

Most algorithms for state estimation based on the classical model are just adequate for use in transmission networks. Few algorithms were developed specifically for distribution systems, probably because of the little amount of data available in real time. Most overhead feeders possess just current and voltage measurements at the middle voltage bus-bar at the substation. In this way, classical algorithms are of difficult implementation, even considering off-line acquired data as pseudo-measurements. However, the necessity of automating the operation of distribution networks, mainly in regard to the selectivity of protection systems, as well to implement possibilities of load transfer maneuvers, is changing the network planning policy. In this way, some equipments incorporating telemetry and command modules have been installed in order to improve operational features, and so increasing the amount of measurement data available in real-time in the System Operation Center (SOC). This encourages the development of a state estimator model, involving real-time information and pseudo-measurements of loads, that are built from typical power factors and utilization factors (demand factors) of distribution transformers. This work reports about the development of a new state estimation method, specific for radial distribution systems. The main algorithm of the method is based on the power summation load flow. The estimation is carried out piecewise, section by section of the feeder, going from the substation to the terminal nodes. For each section, a measurement model is built, resulting in a nonlinear overdetermined equations set, whose solution is achieved by the Gaussian normal equation. The estimated variables of a section are used as pseudo-measurements for the next section. In general, a measurement set for a generic section consists of pseudo-measurements of power flows and nodal voltages obtained from the previous section or measurements in real-time, if they exist -, besides pseudomeasurements of injected powers for the power summations, whose functions are the load flow equations, assuming that the network can be represented by its single-phase equivalent. The great advantage of the algorithm is its simplicity and low computational effort. Moreover, the algorithm is very efficient, in regard to the accuracy of the estimated values. Besides the power summation state estimator, this work shows how other algorithms could be adapted to provide state estimation of middle voltage substations and networks, namely Schweppes method and an algorithm based on current proportionality, that is usually adopted for network planning tasks. Both estimators were implemented not only as alternatives for the proposed method, but also looking for getting results that give support for its validation. Once in most cases no power measurement is performed at beginning of the feeder and this is required for implementing the power summation estimations method, a new algorithm for estimating the network variables at the middle voltage bus-bar was also developed

Análise e síntese de antenas e superfícies seletivas de frequência utilizando computação evolucionária e inteligência de enxames

The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm

Navegação cooperativa de um robô humanóide e um robô com rodas usando informação visual

This work presents a cooperative navigation systemof a humanoid robot and a wheeled robot using visual information, aiming to navigate the non-instrumented humanoid robot using information obtained from the instrumented wheeled robot. Despite the humanoid not having sensors to its navigation, it can be remotely controlled by infra-red signals. Thus, the wheeled robot can control the humanoid positioning itself behind him and, through visual information, find it and navigate it. The location of the wheeled robot is obtained merging information from odometers and from landmarks detection, using the Extended Kalman Filter. The marks are visually detected, and their features are extracted by image processing. Parameters obtained by image processing are directly used in the Extended Kalman Filter. Thus, while the wheeled robot locates and navigates the humanoid, it also simultaneously calculates its own location and maps the environment (SLAM). The navigation is done through heuristic algorithms based on errors between the actual and desired pose for each robot. The main contribution of this work was the implementation of a cooperative navigation system for two robots based on visual information, which can be extended to other robotic applications, as the ability to control robots without interfering on its hardware, or attaching communication devices

Análise de Agrupamentos Com Base na Teoria da Informação: Uma Abordagem Representativa

Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

Antenas de microfita com patch quase-fractal para aplicações em Redes WPAN/WLAN

The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

Implantação de um sistema de detecção de vazamentos em oleodutos com tratamento de alarmes falsos

The pumping of fluids in pipelines is the most economic and safe form of transporting fluids. That explains why in Europe there was in 1999 about 30.000 Km [7] of pipelines of several diameters, transporting millíons of cubic meters of crude oil end refined products, belonging to COCAWE (assaciation of companies of petroleum of Europe for health, environment and safety, that joint several petroleum companies). In Brazil they are about 18.000 Km of pipelines transporting millions of cubic meters of liquids and gases. In 1999, nine accidents were registered to COCAWE. Among those accidents one brought a fatal victim. The oil loss was of 171 m3, equivalent to O,2 parts per million of the total of the transported volume. Same considering the facts mentioned the costs involved in ao accident can be high. An accident of great proportions can bríng loss of human lives, severe environmental darnages, loss of drained product, loss . for dismissed profit and damages to the image of the company high recovery cost. In consonance with that and in some cases for legal demands, the companies are, more and more, investing in systems of Leak detection in pipelines based on computer algorithm that operate in real time, seeking wíth that to minimize still more the drained volumes. This decreases the impacts at the environment and the costs. In general way, all the systems based on softWare present some type of false alarm. In general a commitment exists betWeen the sensibílity of the system and the number of false alarms. This work has as objective make a review of thé existent methods and to concentrate in the analysis of a specific system, that is, the system based on hydraulic noise, Pressure Point Analyzis (PPA). We will show which are the most important aspects that must be considered in the implementation of a Leak Detection System (LDS), from the initial phase of the analysis of risks passing by the project bases, design, choice of the necessary field instrumentation to several LDS, implementation and tests. We Will make na analysis of events (noises) originating from the flow system that can be generator of false alarms and we will present a computer algorithm that restricts those noises automatically

Estudo do efeito de dipolos em arranjos de antenas adaptativas de sistemas de comunicação DS-CDMA

This master dissertation introduces a study about some aspects that determine the aplication of adaptative arrays in DS-CDMA cellular systems. Some basics concepts and your evolution in the time about celular systems was detailed here, meanly the CDMA tecnique, specialy about spread-codes and funtionaly principies. Since this, the mobile radio enviroment, with your own caracteristcs, and the basics concepts about adaptive arrays, as powerfull spacial filter was aborded. Some adaptative algorithms was introduced too, these are integrants of the signals processing, and are answerable for weights update that influency directly in the radiation pattern of array. This study is based in a numerical analysis of adaptative array system behaviors related to the used antenna and array geometry types. All the simulations was done by Mathematica 4.0 software. The results for weights convergency, square mean error, gain, array pattern and supression capacity based the analisis made here, using RLS (supervisioned) and LSDRMTA (blind) algorithms

Síntese de superfícies seletivas de frequência atráves de técnicas de computação natural

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Uma proposta de regulador nebuloso para geradores eólicos de indução

This work presents a proposal for a voltage and frequency control system for a wind power induction generator. It has been developed na experimental structure composes basically by a three phase induction machine, a three phase capacitor and a reactive static Power compensator controlled by histeresys. lt has been developed control algorithms using conventional methods (Pl control) and linguistic methods (using concepts of logic and fuzzy control), to compare their performances in the variable speed generator system. The control loop was projected using the ADJDA PCL 818 model board into a Pentium 200 MHz compu ter. The induction generator mathematical model was studied throught Park transformation. It has been realized simulations in the Pspice@ software, to verify the system characteristics in transient and steady-state situations. The real time control program was developed in C language, possibilish verify the algorithm performance in the 2,2kW didatic experimental system

Técnicas neuronais de agrupamentos aplicadas à detecção de anomalias em mamogramas digitais

This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities

Especificação de um bloco funcional implementando rede neural para redes industriais foundations fieldbus

This work proposes the specification of a new function block according to Foundation Fieldbus standards. The new block implements an artificial neural network, which may be useful in process control applications. The specification includes the definition of a main algorithm, that implements a neural network, as well as the description of some accessory functions, which provide safety characteristics to the block operation. Besides, it also describes the block attributes emphasizing its parameters, which constitute the block interfaces. Some experimental results, obtained from an artificial neural network implementation using actual standard functional blocks on a laboratorial FF network, are also shown, in order to demonstrate the possibility and also the convenience of integrating a neural network to Fieldbus devices

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Técnicas de computação natural para segmentação de imagens médicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Análise de desempenho de estratégias de retransmissão para o mecanismo HCCA do padrão de redes sem fio IEEE 802.11e

This paper presents the performanee analysis of traffie retransmission algorithms pro¬posed to the HCCA medium aeeess meehanism of IEEE 802.11 e standard applied to industrial environmen1. Due to the nature of this kind of environment, whieh has eleetro¬magnetic interferenee, and the wireless medium of IEEE 802.11 standard, suseeptible to such interferenee, plus the lack of retransmission meehanisms, refers to an impraetieable situation to ensure quality of service for real-time traffic, to whieh the IEEE 802.11 e stan¬dard is proposed and this environment requires. Thus, to solve this problem, this paper proposes a new approach that involves the ereation and evaluation of retransmission al-gorithms in order to ensure a levei of robustness, reliability and quality of serviee to the wireless communication in such environments. Thus, according to this approaeh, if there is a transmission error, the traffie scheduler is able to manage retransmissions to reeo¬ver data 10s1. The evaluation of the proposed approaeh is performed through simulations, where the retransmission algorithms are applied to different seenarios, whieh are abstrae¬tions of an industrial environment, and the results are obtained by using an own-developed network simulator and compared with eaeh other to assess whieh of the algorithms has better performanee in a pre-defined applieation