Otimização do controle do diagrama de radiação de radares de varredura para rastreio de foguetes usando o método GAMMC para o Caso Planar (GAMMC-P)

Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Análise de falhas em rolamentos por análise de vibração aplicado a aerogeradores

With the heavy use of bearings in various segments of the industry, there are a large number of necessary interruptions in industrial processes to perform maintenance on these devices, with the case study wind turbines. The growth of the wind energy sector, encouraged to conduct research that helps to solve this problem. To contribute to predictive maintenance has been carried out a signal analysis using techniques which allow detection and location of the problem in order to prevent accidents caused and losses due to unexpected equipment failures, whereas low system rotation complicates the detection of the failure. To work around this problem, there was the indication of standard signals for defects in the bearings, making diagnosis of possible failures. With this diagnosis can be performed predictive maintenance, identifying the failure of the system that were tested, such as the introduction of grains of sand in the bearing, wear on the outer race of the bearing and bearing rust. By processing signals it is possible to construct graphs developing a mapping of defects by different peaks in the frequency band.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Avaliação do comportamento ingestivo utilizando eletromiografia de superfície do músculo masseter

Physiologists and animal scientists try to understand the relationship between ruminants and their environment. The knowledge about feeding behavior of these animals is the key to maximize the production of meat and milk and their derivatives and ensure animal welfare. Within the area called precision farming, one of the goals is to find a model that describes animal nutrition. Existing methods for determining the consumption and ingestive patterns are often time-consuming and imprecise. Therefore, an accurate and less laborious method may be relevant for feeding behaviour recognition. Surface electromyography (sEMG) is able to provide information of muscle activity. Through sEMG of the muscles of mastication, coupled with instrumentation techniques, signal processing and data classification, it is possible to extract the variables of interest that describe chewing activity. This work presents a new method for chewing pattern evaluation, feed intake prediction and for the determination of rumination, food and daily rest time through ruminant animals masseter muscle sEMG signals. Short-term evaluation results are shown and discussed, evidencing employed methods viability.

Arquitetura para o desenvolvimento de unidades de medição fasorial sincronizada no monitoramento a nível de distribuição

This work presents a low cost architecture for development of synchronized phasor measurement units (PMU). The device is intended to be connected in the low voltage grid, which allows the monitoring of transmission and distribution networks. Developments of this project include a complete PMU, with instrumentation module for use in low voltage network, GPS module to provide the sync signal and time stamp for the measures, processing unit with the acquisition system, phasor estimation and formatting data according to the standard and finally, communication module for data transmission. For the development and evaluation of the performance of this PMU, it was developed a set of applications in LabVIEW environment with specific features that let analyze the behavior of the measures and identify the sources of error of the PMU, as well as to apply all the tests proposed by the standard. The first application, useful for the development of instrumentation, consists of a function generator integrated with an oscilloscope, which allows the generation and acquisition of signals synchronously, in addition to the handling of samples. The second and main, is the test platform, with capabality of generating all tests provided by the synchronized phasor measurement standard IEEE C37.118.1, allowing store data or make the analysis of the measurements in real time. Finally, a third application was developed to evaluate the results of the tests and generate calibration curves to adjust the PMU. The results include all the tests proposed by synchrophasors standard and an additional test that evaluates the impact of noise. Moreover, through two prototypes connected to the electrical installation of consumers in same distribution circuit, it was obtained monitoring records that allowed the identification of loads in consumer and power quality analysis, beyond the event detection at the distribution and transmission levels.

Estudo experimental do escoamento bifásico líquido gás em golfadas com leve mudança de direção

Gas-liquid two-phase flow is very common in industrial applications, especially in the oil and gas, chemical, and nuclear industries. As operating conditions change such as the flow rates of the phases, the pipe diameter and physical properties of the fluids, different configurations called flow patterns take place. In the case of oil production, the most frequent pattern found is slug flow, in which continuous liquid plugs (liquid slugs) and gas-dominated regions (elongated bubbles) alternate. Offshore scenarios where the pipe lies onto the seabed with slight changes of direction are extremely common. With those scenarios and issues in mind, this work presents an experimental study of two-phase gas-liquid slug flows in a duct with a slight change of direction, represented by a horizontal section followed by a downward sloping pipe stretch. The experiments were carried out at NUEM (Núcleo de Escoamentos Multifásicos UTFPR). The flow initiated and developed under controlled conditions and their characteristic parameters were measured with resistive sensors installed at four pipe sections. Two high-speed cameras were also used. With the measured results, it was evaluated the influence of a slight direction change on the slug flow structures and on the transition between slug flow and stratified flow in the downward section.

Arquitetura híbrida com DSP e FPGA para implementação de controladores de filtros ativos de potência

The presence of non-linear loads at a point in the distribution system may deform voltage waveform due to the consumption of non-sinusoidal currents. The use of active power filters allows significant reduction of the harmonic content in the supply current. However, the processing of digital control structures for these filters may require high performance hardware, particularly for reference currents calculation. This work describes the development of hardware structures with high processing capability for application in active power filters. In this sense, it considers an architecture that allows parallel processing using programmable logic devices. The developed structure uses a hybrid model using a DSP and an FPGA. The DSP is used for the acquisition of current and voltage signals, calculation of fundamental current related controllers and PWM generation. The FPGA is used for intensive signal processing, such as the harmonic compensators. In this way, from the experimental analysis, significant reductions of the processing time are achieved when compared to traditional approaches using only DSP. The experimental results validate the designed structure and these results are compared with other ones from architectures reported in the literature.

Adsorção de corantes têxteis aniônicos e catiônicos em resíduos do processamento de fios de algodão modificados quimicamente

The textile industry generates a large volume of high organic effluent loading whoseintense color arises from residual dyes. Due to the environmental implications caused by this category of contaminant there is a permanent search for methods to remove these compounds from industrial waste waters. The adsorption alternative is one of the most efficient ways for such a purpose of sequestering/remediation and the use of inexpensive materials such as agricultural residues (e.g., sugarcane bagasse) and cotton dust waste (CDW) from weaving in their natural or chemically modified forms. The inclusion of quaternary amino groups (DEAE+) and methylcarboxylic (CM-) in the CDW cellulosic structure generates an ion exchange capacity in these formerly inert matrix and, consequently, consolidates its ability for electrovalent adsorption of residual textile dyes. The obtained ionic matrices were evaluated for pHpcz, the retention efficiency for various textile dyes in different experimental conditions, such as initial concentration , temperature, contact time in order to determine the kinetic and thermodynamic parameters of adsorption in batch, turning comprehensive how does occur the process, then understood from the respective isotherms. It was observed a change in the pHpcz for CM--CDW (6.07) and DEAE+-CDW (9.66) as compared to the native CDW (6.46), confirming changes in the total surface charge. The ionized matrices were effective for removing all evaluated pure or residual textile dyes under various tested experimental conditions. The kinetics of the adsorption process data had best fitted to the model a pseudosecond order and an intraparticle diffusion model suggested that the process takes place in more than one step. The time required for the system to reach equilibrium varied according to the initial concentration of dye, being faster in diluted solutions. The isotherm model of Langmuir was the best fit to the experimental data. The maximum adsorption capacity varied differently for each tested dye and it is closely related to the interaction adsorbent/adsorbate and dye chemical structure. Few dyes obtained a linear variation of the balance ka constant due to the inversion of temperature and might have influence form their thermodynamic behavior. Dyes that could be evaluated such as BR 18: 1 and AzL, showed features of an endothermic adsorption process (ΔH° positive) and the dye VmL presented exothermic process characteristics (ΔH° negative). ΔG° values suggested that adsorption occurred spontaneously, except for the BY 28 dye, and the values of ΔH° indicated that adsorption occurred by a chemisorption process. The reduction of 31 to 51% in the biodegradability of the matrix after the dye adsorption means that they must go through a cleaning process before being discarded or recycled, and the regeneration test indicates that matrices can be reused up to five times without loss of performance. The DEAE+-CDW matrix was efficient for the removal of color from a real textile effluent reaching an UV-Visible spectral area decrease of 93% when applied in a proportion of 15 g ion exchanger matrix L-1 of colored wastewater, even in the case of the parallel presence of 50 g L-1 of mordant salts in the waste water. The wide range of colored matter removal by the synthesized matrices varied from 40.27 to 98.65 mg g-1 of ionized matrix, obviously depending in each particular chemical structure of the dye upon adsorption.

Processamento e análise de imagens na caracterização da superfície do titânio submetido a um ensaio de cultura de células

This work aims to develop a methodology for analysis of images using overlapping, which assists in identification of microstructural features in areas of titanium, which may be associated with its biological response. That way, surfaces of titanium heat treated for 08 (eight) different ways have been subjected to a test culture of cells. It was a relationship between the grain, texture and shape of grains of surface of titanium (attacked) trying to relate to the process of proliferation and adhesion. We used an open source software for cell counting adhered to the surface of titanium. The juxtaposition of images before and after cell culture was obtained with the aid of micro-hardness of impressions made on the surface of samples. From this image where there is overlap, it is possible to study a possible relationship between cell growth with microstructural characteristics of the surface of titanium. This methodology was efficient to describe a set of procedures that are useful in the analysis of surfaces of titanium subjected to a culture of cells

Estudo sobre o efeito dos parâmetros de processamento dos pós e sinterização do aço inox 316l reforçado com NbC

This masther dissertation presents a contribution to the study of 316L stainless steel sintering aiming to study their behavior in the milling process and the effect of isotherm temperature on the microstructure and mechanical properties. The 316L stainless steel is a widely used alloy for their high corrosion resistance property. However its application is limited by the low wear resistance consequence of its low hardness. In previous work we analyzed the effect of sintering additives as NbC and TaC. This study aims at deepening the understanding of sintering, analyzing the effect of grinding on particle size and microstructure and the effect of heating rate and soaking time on the sintered microstructure and on their microhardness. Were milled 316L powders with NbC at 1, 5 and 24 hours respectively. Particulates were characterized by SEM and . Cylindrical samples height and diameter of 5.0 mm were compacted at 700 MPa. The sintering conditions were: heating rate 5, 10 and 15◦C/min, temperature 1000, 1100, 1200, 1290 and 1300◦C, and soaking times of 30 and 60min. The cooling rate was maintained at 25◦C/min. All samples were sintered in a vacuum furnace. The sintered microstructure were characterized by optical and electron microscopy as well as density and microhardness. It was observed that the milling process has an influence on sintering, as well as temperature. The major effect was caused by firing temperature, followed by the grinding and heating rate. In this case, the highest rates correspond to higher sintering.

Síntese e caracterização de cerâmicas nanométricas para produção de gás de síntese

In this work, ceramic powders belonging to the system Nd2-xSrxNiO4 (x = 0, 0.4, 0.8, 1.2 and 1.6) were synthesized for their use as catalysts to syngas production partial. It was used a synthesis route, relatively new, which makes use of gelatin as organic precursor. The powders were analyzed at several temperatures in order to obtain the perovskite phase and characterized by several techniques such as thermal analysis, X-rays diffraction, Rietveld refinement method, specific surface area, scanning electron microscopy, energy dispersive spectroscopy of X-rays and temperature programmed reduction. The results obtained using these techniques confirmed the feasibility of the synthesis method employed to obtain nanosized particles. The powders were tested in differential catalytic conditions for dry reforming of methane (DRM) and partial oxidation of methane (POM), then, some systems were chosen for catalytic integrals test for (POM) indicating that the system Nd2-xSrxNiO4 for x = 0, 0.4 and 1.2 calcined at 900 °C exhibit catalytic activity on the investigated experimental conditions in this work without showing signs of deactivation

Estudo do efeito da adição da escória de aciaria no processamento e propriedades finais de telhas cerâmicas

This research presents an overview of the addition steelwork dust of ceramic shingles in order to contribute to the utilization use of such residue. The ceramic industry perspective in the Brazilian State of Piauí is quite promising. Unlike other productive sectors, the ceramic industry uses basically natural raw materials. Its final products are, in short, the result of transforming clay compounds. These raw materials are composed primarily of aluminum oxide, silicon, iron, sodium, magnesium, end calcium, among others. It was verified that steelwork dust is composed primarily of these same oxides, so that its incorporation in to structural ceramics is a very reasonable idea. Both clay and steelwork powder were characterized by AG, XRF, XRD, TGA and DTA. In addition, steelwork dust samples containing (0%, 5%, 10%, 15%, 20% and 25%) were extruded and burned at 800°C, 850°C, 900°C and 950°C. Then t echnological tests of linear shrinkage, water uptake, apparent porosity, apparent density and flexural strengthwere carried at. The results showed the possibility of using steelwork powder in ceramic shingles until 15% significant improvement in physical and mechanical properties. This behavior shows the possibility of burning at temperatures lower than 850ºC, thus promoting a product final cost reduction

Comportamento magnético de compósitos de matriz polimérica com adição de ferritas

Polymer matrix composites offer advantages for many applications due their combination of properties, which includes low density, high specific strength and modulus of elasticity and corrosion resistance. However, the application of non-destructive techniques using magnetic sensors for the evaluation these materials is not possible since the materials are non-magnetizable. Ferrites are materials with excellent magnetic properties, chemical stability and corrosion resistance. Due to these properties, these materials are promising for the development of polymer composites with magnetic properties. In this work, glass fiber / epoxy circular plates were produced with 10 wt% of cobalt or barium ferrite particles. The cobalt ferrite was synthesized by the Pechini method. The commercial barium ferrite was subjected to a milling process to study the effect of particle size on the magnetic properties of the material. The characterization of the ferrites was carried out by x-ray diffraction (XRD), field emission gun scanning electron microscopy (FEG-SEM) and vibrating sample magnetometry (VSM). Circular notches of 1, 5 and 10 mm diameter were introduced in the composite plates using a drill bit for the non-destructive evaluation by the technique of magnetic flux leakage (MFL). The results indicated that the magnetic signals measured in plates with barium ferrite without milling and cobalt ferrite showed good correlation with the presence of notches. The milling process for 12 h and 20 h did not contribute to improve the identification of smaller size notches (1 mm). However, the smaller particle size produced smoother magnetic curves, with fewer discontinuities and improved signal-to-noise ratio. In summary, the results suggest that the proposed approach has great potential for the detection of damage in polymer composites structures