995 resultados para CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
Resumo:
This work presents the specification and the implementation of a language of Transformations in definite Models specification MOF (Meta Object Facility) of OMG (Object Management Group). The specification uses a boarding based on rules ECA (Event-Condition-Action) and was made on the basis of a set of scenes of use previously defined. The Parser Responsible parser for guaranteeing that the syntactic structure of the language is correct was constructed with the tool JavaCC (Java Compiler Compiler) and the description of the syntax of the language was made with EBNF (Extended Backus-Naur Form). The implementation is divided in three parts: the creation of the interpretative program properly said in Java, the creation of an executor of the actions specified in the language and its integration with the type of considered repository (generated for tool DSTC dMOF). A final prototype was developed and tested in the scenes previously defined
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Wireless sensor networks are reality nowadays. The growing necessity of connectivity between existing industrial plant equipments pushes the research and development of several technologies. The IEEE 802.15.4 LR-WPAN comes as a low-cost and powersaving viable solution, which are important concerns while making decisions on remote sensoring projects. This study intends to propose a wireless communication system which makes possible the monitoring of analogic and/or digital variables (i. e., the pressure studied) involved on the artificial methods for oil and gas lifting. The main issues are: To develop a software based on SMAC Standard in order to create a wireless network to monitoring analogic and/or digital variables; To evaluate the communication link based on the number of lost packets tested in different environments (indoor and outdoor) and To propose an instrumentation system consisting of wireless devices
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Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures
Análise espectral de reflectarrays com substrato de duas camadas dielétricas anisotrópicas uniaxiais
Resumo:
Recently, an amazing development has been observed in telecommunication systems. Two good examples of this development are observed in mobile communication and aerospace systems. This impressive development is related to the increasing need for receiving and transmitting communication signals. Particularly, this development has required the study of new antennas and filters. This work presents a fullwave analysis of reflectarrays. The considered structures are composed by arrays of rectangular conducting patches printed on multilayer dieletric substrates, that are mounted on a ground plane. The analysis is developed in the spectral domain, using an equivalent transmission line method in combination with Galerkin method. Results for the reflection coefficient of these structures are presented and compared to those available in the literature. A good agreement was observed. Particularly, the developed analysis uses the transmission lines theory in combination with the incident potentials and the field continuity equations, at the structures interfaces, for obtaining the scattered field components expressions as function of the patch surface currents and of the incident field. Galerkin method is used to determine the unknown coefficients in the boundary value problem. Curves for the reflection coefficient of several reflectarray geometries are presented as function of frequency and of the structural parameters
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This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results
Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR
Resumo:
Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents
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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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Navigation based on visual feedback for robots, working in a closed environment, can be obtained settling a camera in each robot (local vision system). However, this solution requests a camera and capacity of local processing for each robot. When possible, a global vision system is a cheapest solution for this problem. In this case, one or a little amount of cameras, covering all the workspace, can be shared by the entire team of robots, saving the cost of a great amount of cameras and the associated processing hardware needed in a local vision system. This work presents the implementation and experimental results of a global vision system for mobile mini-robots, using robot soccer as test platform. The proposed vision system consists of a camera, a frame grabber and a computer (PC) for image processing. The PC is responsible for the team motion control, based on the visual feedback, sending commands to the robots through a radio link. In order for the system to be able to unequivocally recognize each robot, each one has a label on its top, consisting of two colored circles. Image processing algorithms were developed for the eficient computation, in real time, of all objects position (robot and ball) and orientation (robot). A great problem found was to label the color, in real time, of each colored point of the image, in time-varying illumination conditions. To overcome this problem, an automatic camera calibration, based on clustering K-means algorithm, was implemented. This method guarantees that similar pixels will be clustered around a unique color class. The obtained experimental results shown that the position and orientation of each robot can be obtained with a precision of few millimeters. The updating of the position and orientation was attained in real time, analyzing 30 frames per second
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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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This work purposes the application of a methodology to optimize the implantation cost of an wind-solar hybrid system for oil pumping. The developed model is estimated the implantation cost of system through Multiple Linear Regression technique, on the basis of the previous knowledge of variables: necessary capacity of storage, total daily energy demand, wind power, module power and module number. These variables are gotten by means of sizing. The considered model not only can be applied to the oil pumping, but also for any other purposes of electric energy generation for conversion of solar, wind or solar-wind energy, that demand short powers. Parametric statistical T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind, F by Snedecor in the variance analysis to test if the coefficients of the considered model are significantly different of zero and test not-parametric statistical by Friedman, toverify if there is difference in the system cost, by being considered the photovoltaic module powers. In decision of hypothesis tests was considered a 5%-significant level. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 3 HP. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 5 HP only to wind speed of 4m/s and 6 m/s in wind of 3 m, 4m and 5 m of diameter. There was not significant difference in costs to diameters of winds of 3 m and 4m. The mathematical model and the computational program may be used to others applications which require electrical between 2.250 W and 3.750 W. A computational program was developed to assist the study of several configurations that optimizes the implantation cost of an wind-solar system through considered mathematical model
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The processing of materials through plasma has been growing enough in the last times in several technological applications, more specifically in surfaces treatment. That growth is due, mainly, to the great applicability of plasmas as energy source, where it assumes behavior thermal, chemical and/or physical. On the other hand, the multiplicity of simultaneous physical effects (thermal, chemical and physical interactions) present in plasmas increases the complexity for understanding their interaction with solids. In that sense, as an initial step for the development of that subject, the present work treats of the computational simulation of the heating and cooling processes of steel and copper samples immersed in a plasma atmosphere, by considering two experimental geometric configurations: hollow and plane cathode. In order to reach such goal, three computational models were developed in Fortran 90 language: an one-dimensional transient model (1D, t), a two-dimensional transient model (2D, t) and a two-dimensional transient model (2D, t) which take into account the presence of a sample holder in the experimental assembly. The models were developed based on the finite volume method and, for the two-dimensional configurations, the effect of hollow cathode on the sample was considered as a lateral external heat source. The main results obtained with the three computational models, as temperature distribution and thermal gradients in the samples and in the holder, were compared with those developed by the Laboratory of Plasma, LabPlasma/UFRN, and with experiments available in the literature. The behavior showed indicates the validity of the developed codes and illustrate the need of the use of such computational tool in that process type, due to the great easiness of obtaining thermal information of interest
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The potential market of the metropolitan area of Salvador accounts for the estimated consumption of roughly 800 million horizontally perforated extruded clay bricks a year. The growing demand of consumers along with the competitiveness of the structural ceramic sector has driven forward a number of recent efforts and investments towards improving the quality of structural ceramics. In this scenario, the present study focused on sampling and evaluating the conformity of 8-hole horizontally perforated extruded clay bricks manufactured by different plants (A, B and C) in the metropolitan area of Salvador. In addition, representative clay and sandy-clay materials were collected from each plant and characterized by conventional physical, chemical and mineralogical techniques. Finally, experimental compositions designated as A, B and C, according to the source, were prepared by mixing different contents of the raw materials collected in the plants, fired at different temperatures and characterized. The results revealed a series of non conformities regarding ABNT guidelines. The characterization of raw materials revealed the presence of kaolinite and ilite in concentrations ranging from 64 to 90 wt.% along with free quartz (10 - 25%). The sandy-clay samples consisted basically of kaolinite. All raw materials depicted low contents of organics, amorphous constituents, alkaline oxides and feldspar. An analysis of the firing behavior of all different ceramic compositions revealed that the linear contraction of composition A was rather significant considering the temperature range evaluated, and it justifies the significant dimensional non conformity that was shown by bricks made with the ceramic A
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The generation for termoeletricity is characterized as a solid process of conversion of thermal energy (heat) in electric without the necessity of mobile parts. Although the conversion process is of low efficiency the system presents high degree of trustworthiness and low requisite of maintenance and durability. Its principle is based on the studies of termogeneration carried through by Thomas Seebeck in 1800. The frank development of the technologies of solid state for termoeletricity generation, the necessity of the best exploitation of the energy, also with incentive the cogeneration processes, the reduction of the ambient impact allies to the development of modules semiconductors of high efficiency, converge to the use of the thermoeletric generation through components of solid state in remote applications. The work presents the development, construction and performance evaluation of an prototype, in pilot scale, for energy tri-generation aiming at application in remote areas. The unit is composed of a gas lamp as primary source of energy, a module commercial semiconductor for thermoelectric generation and a shirt for production of the luminosity. The project of the device made compatible a headstock for adaptation in the gas lamp, a hot source for adaptation of the module, an exchanger of to be used heat as cold source and to compose first stage of cogeneration, an exchanger of tubular heat to compose second stage of cogeneration, the elaboration of a converter dc-dc type push pull, adequacy of a system of acquisition of temperature. It was become fullfilled assembly of the prototype in group of benches for tests and assay in the full load condition in order to evaluate its efficiency, had been carried through energy balance of the unit. The prototype presented an electric efficiency of 0,73%, thermal of 56,55%, illumination of 1,35% and global of 58,62%. The developed prototype, as the adopted methodology of assay had also taken care of to the considered objectives, making possible the attainment of conclusive results concerning to the experiment. Optimization in the system of setting of the semicondutor module, improvement in the thermal insulation and design of the prototype and system of protection to the user are suggestions to become it a commercial product
Resumo:
The study of the physical and mechanic properties is an analysis of unquestioned importance on the production of the ceramic materials. In the region of the Recôncavo Baiano, there are ceramic and small brick factories, that still use rudimentary techniques, where the necessity of characterization of raw materials is denounced by the quality of the final product. The present work has for objective to study the behavior of the clay proceeding from the region of the Recôncavo, between the cities of Candeias and Camaçari/Ba, with addition of 5, 10 and 15% by weight of brick scraps, trying to optimize the physic and mechanical properties of the final product, aiming a better possibility of being manufactured, mechanic resistance, low linear retraction and water absorption. The brick scraps and the clay were characterized by FRX, DRX, TG, ATD and the granulometric analysis. Samples for testing where prepared by uniaxial pressing at 25Mpa, in 60x20x5mm size. The evaluated technological properties were: linear retraction, water absorption, apparent porosity and flexural strength. The samples were burned in electric oven in the temperatures of 850º, 950º and 1050ºC and compared its mechanical properties and the gresification. With addition of 15% by weight of brick scraps and burning at 900º-1000ºC the samples showed properties superior to that clay