Detecção e isolamento de falhas em sistemas dinâmicos baseados em redes neurais

This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

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

Extração supercrítica do óleo de linhaça: construção do extrator, estudo de parâmetros de processo, avaliação química e antioxidante do produto

The aim of the present study was to extract vegetable oil from brown linseed (Linum usitatissimum L.), determine fatty acid levels, the antioxidant capacity of the extracted oil and perform a rapid economic assessment of the SFE process in the manufacture of oil. The experiments were conducted in a test bench extractor capable of operating with carbon dioxide and co-solvents, obeying 23 factorial planning with central point in triplicate, and having process yield as response variable and pressure, temperature and percentage of cosolvent as independent variables. The yield (mass of extracted oil/mass of raw material used) ranged from 2.2% to 28.8%, with the best results obtained at 250 bar and 50ºC, using 5% (v/v) ethanol co-solvent. The influence of the variables on extraction kinetics and on the composition of the linseed oil obtained was investigated. The extraction kinetic curves obtained were based on different mathematical models available in the literature. The Martínez et al. (2003) model and the Simple Single Plate (SSP) model discussed by Gaspar et al. (2003) represented the experimental data with the lowest mean square errors (MSE). A manufacturing cost of US$17.85/kgoil was estimated for the production of linseed oil using TECANALYSIS software and the Rosa and Meireles method (2005). To establish comparisons with SFE, conventional extraction tests were conducted with a Soxhlet device using petroleum ether. These tests obtained mean yields of 35.2% for an extraction time of 5h. All the oil samples were sterilized and characterized in terms of their composition in fatty acids (FA) using gas chromatography. The main fatty acids detected were: palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2n-6) and α-linolenic (C18:3n-3). The FA contents obtained with Soxhlet dif ered from those obtained with SFE, with higher percentages of saturated and monounsaturated FA with the Soxhlet technique using petroleum ether. With respect to α-linolenic content (main component of linseed oil) in the samples, SFE performed better than Soxhlet extraction, obtaining percentages between 51.18% and 52.71%, whereas with Soxhlet extraction it was 47.84%. The antioxidant activity of the oil was assessed in the β-carotene/linoleic acid system. The percentages of inhibition of the oxidative process reached 22.11% for the SFE oil, but only 6.09% for commercial oil (cold pressing), suggesting that the SFE technique better preserves the phenolic compounds present in the seed, which are likely responsible for the antioxidant nature of the oil. In vitro tests with the sample displaying the best antioxidant response were conducted in rat liver homogenate to investigate the inhibition of spontaneous lipid peroxidation or autooxidation of biological tissue. Linseed oil proved to be more efficient than fish oil (used as standard) in decreasing lipid peroxidation in the liver tissue of Wistar rats, yielding similar results to those obtained with the use of BHT (synthetic antioxidant). Inhibitory capacity may be explained by the presence of phenolic compounds with antioxidant activity in the linseed oil. The results obtained indicate the need for more detailed studies, given the importance of linseed oil as one of the greatest sources of ω3 among vegetable oils

Análise sísmica usando transformada de Curvelet

Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation

Obtenção de organovermiculitas utilizando tensoativos e microemulsões e suas aplicações na separação de isômeros do Xileno

Surfactants are versatile organic compounds that have, in a single molecule, double chemical affinity. The surfactant molecule is composed by a hy drophobic tail group, a hydrocarbon chain (linear, branched, or mixed), and by a hydrophilic head group, which contains polar groups that makes it able to be applied in the organophilization process of natural clays. Microemulsions are microheterogeneous b lends composed by: a surfactant, an oily phase (non - polar solvent), an aqueous phase, and, sometimes, a co - surfactant (short - chain alcohol). They are systems with thermodynamic stability, transparent, and have high solubility power. Vermiculite is a clay m ineral with an expandable crystalline structure that has high cation exchange capacity. In this work vermiculite was used to obtain organoclays. The ionic surfactants dodecyl ammonium chlori de (DDAC) and cetyltrimethylammonium bromide (C 16 TAB) were used in the organophilization process. They were used as surfactant aqueous solutions and, for DDAC, as a microemulsion system. The organoclays were used to promote the separation of binary mixtures of xylene isomers (ortho - and meta - xylene). Dif ferent analytical techniques were used to characterize microemulsion systems and also the nanoclays. It was produced a water - rich microemulsion system with 0.92 nm droplet average diameter. The vermiculite used in this work has a cationic exchange capacity of 172 meq/100g and magnesium as main cation (24.25%). The basal spacing of natural vermiculite and organo - vermiculites were obtained by X - ray Diffraction technique. The basal spacing was 1.48nm for natural vermiculite, 4.01nm for CTAB - vermiculite (CTAB 4 ) , and 3.03nm for DDAC - vermiculite (DDAC M1A), that proves the intercalation process. Separation tests were carried out in glass columns using three binary mixtures of xylene (ortho - xylene and meta - xylene). The results showed that the organovermiculite pre sented an enhanced chemical affinity by the mixture of hydrocarbons, when compared with the natural vermiculite, and also its preference by ortho - xylene. A factorial experimental design 2 2 with triplicate at the central point was used to optimize the xylen e separation process. The experimental design revealed that the initial concentration of isomers in the mixture and the mass of organovermiculite were the significant factors for an improved separation of isomers. In the experiments carried out using a bin ary mixture of ortho - xylene and meta - xylene (2:1), after its percolating through the organovermiculite bed (DDAC M1), it was observed the preference of the organoclay by the ortho - xylene isomer, which was retained in greater quantity than the meta - xylene o ne. At the end of the treatment, it was obtained a final concentration in meta - xylene of 47.52%.