583 resultados para Engenharia eletrica - Matematica


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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 continuous gas lift method is the main artificial lifting method used in the oil industry for submarine wells, due to its robustness and the large range of flow rate that the well might operate. Nowadays, there is a huge amount of wells producing under this mechanism. This method of elevation has a slow dynamics due to the transients and a correlation between the injected gas rate and the of produced oil rate. Electronics controllers have been used to adjust many parameters of the oil wells and also to improve the efficiency of the gas lift injection system. This paper presents a intelligent control system applied to continuous gas injection in wells, based in production s rules, that has the target of keeping the wells producing during the maximum period of time, in its best operational condition, and doing automatically all necessary adjustments when occurs some disturbance in the system. The author also describes the application of the intelligent control system as a tool to control the flow pressure in the botton of the well (Pwf). In this case, the control system actuates in the surface control valve

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There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

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Fuel is a material used to produce heat or power by burning, and lubricity is the capacity for reducing friction. The aim of this work is evaluate the lubricity of eight fossil and renewable fuels used in Diesel engines, by means of a HFRR tester, following the ASTM D 6079-04 Standard. In this conception, a sphere of AISI 52100 steel (diameter of 6,000,05 mm, Ra 0,050,005 μm, E = 210 GPa, HRC 624, HV0,2 63147) is submitted to a reciprocating motion under a normal load of 2 N and 50 Hz frequency to promote a wear track length of 1.10.1mm in a plan disc of AISI 52100 steel (HV0,05 18410, Ra 0,020,005 μm). The testing extent time was 75 minutes, 225,000 cycles. Each one test was repeated six times to furnish the results, by means of intrinsic signatures from the signals of the lubricant film percentage, friction coefficient, contact heating, Sound Pressure Level, SPL [dB]. These signal signatures were obtained by two thermocouples and a portable decibelmeter coupled to a data acquisition system and to the HFRR system. The wettability of droplet of the diesel fuel in thermal equilibrium on a horizontal surface of a virgin plan disc of 52100 steel, Ra 0,02  0,005 μm, were measured by its contact angle of 7,0  3,5o, while the results obtained for the biodiesel B5, B20 and B100 blends originated by the ethylic transesterification of soybean oil were, respectively, 7,5  3,5o, 13,5  3,5o e 19,0  1,0o; for the distilled water, 78,0  6,0o; the biodiesel B5, B20 and B100 blends originated by the ethylic transesterification of sunflower oil were, respectively, 7,0  4,0o, 8,5  4,5o e 19,5  2,5o. Different thickness of lubricant film were formed and measured by their percentage by means of the contact resistance technique, suggesting several regimes, since the boundary until the hydrodynamic lubrication. All oils analyzed in this study promoted the ball wear scars with diameters smaller than 400 μm. The lowest values were observed in the scar balls lubricated by mixtures B100, B20 and B5 of sunflower and B20 and B5 of soybean oils (WSD < 215 μm)

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A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

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All around the world, naturally occurring hydrocarbon deposits, consisting of oil and gas contained within rocks called reservoir rocks , generally sandstone or carbonate exists. These deposits are in varying conditions of pressure and depth from a few hundred to several thousand meters. In general, shallow reservoirs have greater tendency to fracture, since they have low fracture gradient, ie fractures are formed even with relatively low hydrostatic columns of fluid. These low fracture gradient areas are particularly common in onshore areas, like the Rio Grande do Norte basin. During a well drilling, one of the most favorable phases for the occurrence of fractures is during cementing, since the cement slurry used can have greater densities than the maximum allowed by the rock structure. Furthermore, in areas which are already naturally fractured, the use of regular cement slurries causes fluid loss into the formation, which may give rise to failures cementations and formation damages. Commercially, there are alternatives to the development of lightweight cement slurries, but these fail either because of their enormous cost, or because the cement properties were not good enough for most general applications, being restricted to each transaction for which the cement paste was made, or both reasons. In this work a statistical design was made to determine the influence of three variables, defined as the calcium chloride concentration, vermiculite concentration and nanosilica concentration in the various properties of the cement. The use of vermiculite, a low density ore present in large amounts in northeastern Brazil, as extensor for cementing slurries, enabled the production of stable cements, with high water/cement ratio, excellent rheological properties and low densities, which were set at 12.5 lb / gal, despite the fact that lower densities could be achieved. It is also seen that the calcium chloride is very useful as gelling and thickening agent, and their use in combination with nanosilica has a great effect on gel strength of the cement. Hydrothermal Stability studies showed that the pastes were stable in these conditions, and mechanical resistance tests showed values of the order of up to 10 MPa

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Neste trabalho, um controlador adaptativo backstepping a estrutura variável (Variable Structure Adaptive Backstepping Controller, VS-ABC) é apresentado para plantas monovariáveis, lineares e invariantes no tempo com grau relativo unitário. Ao invés das tradicionais leis integrais para estimação dos parâmetros da planta, leis chaveadas são utilizadas com o objetivo de aumentar a robustez em relação a incertezas paramétricas e distúrbios externos, bem como melhorar o desempenho transitório do sistema. Adicionalmente, o projeto do novo controlador é mais intuitivo quando comparado ao controlador backstepping original, uma vez que os relés introduzidos apresentam amplitudes diretamente relacionadas com os parâmetros nominais da planta. Esta nova abordagem, com uso de estrutura variável, também reduz a complexidade das implementações práticas, motivando a utilização de componentes industriais, tais como, FPGAs (Field Programmable Gate Arrays ), MCUs (Microcontrollers) e DSPs (Digital Signal Processors). Simulações preliminares para um sistema instável de primeira e segunda ordem são apresentadas de modo a corroborar os estudos. Um dos exemplos de Rohrs é ainda abordado através de simulações, para os dois cenários adaptativos: o controlador backstepping adaptativo original e o VS-ABC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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The great interest observed in wireless communication systems has required the development of new configurations of microstrip antennas, because they are easily built and integrated to other microwave circuit components, which is suitable for the construction and development of planar antenna arrays and microwave integrated circuits. This work presents a new configuration of tapered microstrip antenna, which is obtained by impressing U-slots on the conducting patch combined with a transmission line matching circuit that uses an inset length. It is shown that the use of U-slots in the microstrip antenna conducting patch excites new resonating modes, that gives a multiband characteristic for the slotted microstrip antenna, that is suitable for applications in communication systems that operates several frequencies simultaneously. Up to this date, the works reported in the literature deals with the use of Uslotted microstrip rectangular antennas fed by a coaxial probe. The properties of a linear array of microstrip patch tapered antennas are also investigated. The main parameters of the U slotted tapered microstrip antennas are investigated for different sizes and locations of the slots impressed on the conducting patch. The analysis of the proposed antenna is performed by using the resonant cavity and equivalent transmission line methods, in combination with a parametric study, that is conducted by the use of the Ansoft Designer, a commercial computer aided microwave software well known by its accuracy and efficiency. The mentioned methods are used to evaluate the effect in the antennas parameters, like resonant frequency and return loss, produced by variations of the antenna structural parameters, accomplished separately or simultaneously. An experimental investigation is also developed, that consists of the design, construction and measurement of several U slotted microstrip antenna prototypes. Finally, theoretical and simulated results are presented that are in agreement with the measured ones. These results are related to the resonating modes identification and to the determination of the main characteristics of the investigated antennas, such as resonant frequency, return loss, and radiation pattern

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This work presents contributions in the detection and identication of faults in multilevel inverters through the study of the converters behavior under these operation conditions. Basically, the approached fault consists of an open-circuit in any switch of a three-level clamped diode inverter. The converter operation is characterized in the pre and post-fault states. A wave form behavior analysis of the pole voltage, phase current and dc-bus current is also done, which highlights characteristics that allow the detection of failure and, even, under favorable conditions, the identication of the faulty device. A compensation strategy of the approached fault (open-switch) is also investigated with the purpose of maintaining the driving system operational when a failure occurs. The proposed topology uses SCRs in parallel with the internal switches of the inverter, which allows, in some occasions, the full utilization of the dc-bus

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The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.

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This work an algorithm for fault location is proposed. It contains the following functions: fault detection, fault classification and fault location. Mathematical Morphology is used to process currents obtained in the monitored terminals. Unlike Fourier and Wavelet transforms that are usually applied to fault location, the Mathematical Morphology is a non-linear operation that uses only basic operation (sum, subtraction, maximum and minimum). Thus, Mathematical Morphology is computationally very efficient. For detection and classification functions, the Morphological Wavelet was used. On fault location module the Multiresolution Morphological Gradient was used to detect the traveling waves and their polarities. Hence, recorded the arrival in the two first traveling waves incident at the measured terminal and knowing the velocity of propagation, pinpoint the fault location can be estimated. The algorithm was applied in a 440 kV power transmission system, simulated on ATP. Several fault conditions where studied and the following parameters were evaluated: fault location, fault type, fault resistance, fault inception angle, noise level and sampling rate. The results show that the application of Mathematical Morphology in faults location is very promising

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Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

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The robustness and performance of the Variable Structure Adaptive Pole Placement Controller are evaluated in this work, where this controller is applied to control a synchronous generator connected to an infinite bus. The evaluation of the robustness of this controller will be accomplished through simulations, where the control algorithm was subjected to adverse conditions, such as: disturbances, parametric variations and unmodeled dynamic. It was also made a comparison of this control strategy with another one, using classic controllers. In the simulations, it is used a coupled model of the synchronous generator which variables have a high degree of coupling, in other words, if there is a change in the input variables of the generator, it will change all outputs simultaneously. The simulation results show which control strategy performs better and is more robust to disturbances, parametric variations and unmodeled dynamics for the control of Synchronous Generator

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The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances