Localização de faltas de alta impedância em sistemas de distribuição de energia : uma metodologia baseada em redes neurais artificiais

O presente trabalho apresenta uma nova metodologia de localização de faltas em sistemas de distribuição de energia. O esquema proposto é capaz de obter uma estimativa precisa da localização tanto de faltas sólidas e lineares quanto de faltas de alta impedância. Esta última classe de faltas representa um grande problema para as concessionárias distribuidoras de energia elétrica, uma vez que seus efeitos nem sempre são detectados pelos dispositivos de proteção utilizados. Os algoritmos de localização de faltas normalmente presentes em relés de proteção digitais são formulados para faltas sólidas ou com baixa resistência de falta. Sendo assim, sua aplicação para localização de faltas de alta impedância resulta em estimativas errôneas da distância de falta. A metodologia proposta visa superar esta deficiência dos algoritmos de localização tradicionais através da criação de um algoritmo baseado em redes neurais artificiais que poderá ser adicionado como uma rotina adicional de um relé de proteção digital. O esquema proposto utiliza dados oscilográficos pré e pós-falta que são processados de modo que sua localização possa ser estimada através de um conjunto de características extraídas dos sinais de tensão e corrente. Este conjunto de características é classificado pelas redes neurais artificiais de cuja saída resulta um valor relativo a distância de falta. Além da metodologia proposta, duas metodologias para localização de faltas foram implementadas, possibilitando a obtenção de resultados comparativos. Os dados de falta necessários foram obtidos através de centenas de simulações computacionais de um modelo de alimentador radial de distribuição. Os resultados obtidos demonstram a viabilidade do uso da metodologia proposta para localização de faltas em sistemas de distribuição de energia, especialmente faltas de alta impedância.

Análise por meio de espectroscopia de emissão óptica das espécies ativas em nitretação iônica e gaiola catódica

Plasma process like ionic nitriding and cathodic cage plasma nitriding are utilized in order to become hard surface of steels. The ionic nitriding is already accepted in the industry while cathodic cage plasma nitriding process is in industrial implementation stage. Those process depend of plasma parameters like electronic and ionic temperature (Te, Ti), species density (ne, ni) and of distribution function of these species. In the present work, the plasma used to those two processes has been observed through Optical Emission Spectroscopy OES technique in order to identify presents species in the treatment ambient and relatively quantify them. So plasma of typical mixtures like N2 H2 has been monitored through in order to study evolution of those species during the process. Moreover, it has been realized a systematic study about leaks, also thought OES, that accomplish the evolution of contaminant species arising because there is flux of atmosphere to inside nitriding chamber and in what conditions the species are sufficiently reduced. Finally, to describe the physic mechanism that acts on both coating techniques ionic nitriding and cathodic cage plasma nitriding

Análise estatística de impedância da pele

In this work we analyze the skin bioimpedance statistical distribution. We focus on the study of two distinct samples: the statistics of impedance of several points in the skin of a single individual and the statistics over a population (many individuals) but in a single skin point. The impedance data was obtained from the literature (Pearson, 2007). Using the Shapiro-Wilk test and the assymmetry test we conclude that the impedance of a population is better described by an assymetric and non-normal distribution. On the other side, the data concerning the individual impedance seems to follow a normal distribution. We have performed a goodnes of fitting test and the better distribution to fit the data of a population is the log-normal distribution. It is interesting to note that our result for skin impedance is in simtony with body impedance from the literature of electrical engeneering. Our results have an impact over the statistical planning and modelling of skin impedance experiments. Special attention we should drive to the treatment of outliers in this kind of dataset. The results of this work are important in the general discussion of low impedance of points of acupuncture and also in the problem of skin biopotentials used in equipments like the Electrodermal Screen Tests.

Análise do vetor de impedância bioelétrico na avaliação da suplementação de zinco em crianças prepuberais e sadias

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Implementação de um algoritmo para a análise de curtos-circuitos de alta impedância baseado no fluxo de carga soma de potências

This work has as main objective to show all the particularities regarding the Three-phase Power Summation Method, used for load flow calculation, in what it says respect to the influence of the magnetic coupling among the phases, as well as to the losses presented in all the existent transformers in the feeder to be analyzed. Besides, its application is detailed in the study of the short-circuits, that happen in the presence of high impedance values, which possess a problem, that is its difficult detection and consequent elimination on the part of common devices of protection. That happens due to the characteristic presented by the current of short¬ circuit, in being generally of the same order of greatness that the load currents. Results of simulations accomplished in several situations will be shown, objectifying a complete analysis of the behavior of the proposed method in several types of short-circuits. Confront of the results obtained by the method with results of another works will be presented to verify its effectiveness

Diagnóstico de descarga de cátodo oco de ar e pós-descarga Ar N2 por espectroscopia de emissão óptica e espectrometria de massa

Many applications require that the plasma discharge is produced apart from the surface to be processed, thus preventing damage caused by bombardment and/or plasma radiation. In the post-discharge regime in various applications thermally sensitive materials can be used. In this work, active species produced by discharge and post-discharge hollow cathode were diagnosed by optical emission spectroscopy and mass spectrometry. The discharge was produced with the gases Ar and Ar - N2 gas flow ranging from 1 to 6 cm3/min and electric current between 150 to 600 mA. It was estimated that the ion density inside the hollow cathode, with 2 mm diameter ranged between 7.71 and 14.1 x 1015 cm-3. It was observed that the gas flow and the electric current changes the emission intensity of Ar and N2 species. The major ionic species detected by quadrupole mass spectrometry were Ar+ and N2+. The ratio of optical emission intensities of N2(1 +)/Ar(811 nm) was related to the partial pressure of N2 after the hollow cathode discharge at low pressure

Monitoramento em tempo real de processos fermentativos por espectroscopia no infravermelho próximo (NIRS)

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

Estudo de coprólito da bacia sedimentar do Araripe por meios de espectroscopia FT-IR e difração de Raios-X

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aplicação da espectroscopia de absorção de raios X no estudo do comportamento do íon Cu2+ em micelas inversas

This work deals with the application of X-Ray Absorption Spectroscopy on the study of the behavior of Cu2+ ions in inverse micelles. The formation of copper nanoparticles in water-in-oil microemulsions in pseudo-ternary systems of cetyl trimethylammonium Bromide (CTAB) surfactant, butanol co-surfactant, heptane as oil phase and aqueous solutions of CuSO4.5H2O, and NaBH4. The microemulsions were prepared with a fixed percentage (60 %) of oil phase and a variable water to tensoative proportion. It was observed an increase on Cu2+ reduction by the sodium borohydride in microemulsions with 13 % of aqueous phase, independent of the reaction time. For the microemulsions in which the aqueous phase is composed only by the CuSO4 solution, it was observed that the color of the solution depends on the water to surfactant ratio. These changes in color were attributed to a competition for the hidratation water between the polar head of the tensoative and Cu2+ ions with the eventual substitution of oxygen by bromine atoms in the first coordination shell of Cu2+ ions

Construção de modelos multivariados para determinação de lipídios totais e unidade em leite em pó comercial utilizando espectroscopia no infravermelho próximo

In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ° C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ± 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ± 0.76%

Determinação do teor de diclofenaco sódico em comprimidos por espectroscopia no infravermelho próximo NIR com calibração multivariada PLS

This work is combined with the potential of the technique of near infrared spectroscopy - NIR and chemometrics order to determine the content of diclofenac tablets, without destruction of the sample, to which was used as the reference method, ultraviolet spectroscopy, which is one of the official methods. In the construction of multivariate calibration models has been studied several types of pre-processing of NIR spectral data, such as scatter correction, first derivative. The regression method used in the construction of calibration models is the PLS (partial least squares) using NIR spectroscopic data of a set of 90 tablets were divided into two sets (calibration and prediction). 54 were used in the calibration samples and the prediction was used 36, since the calibration method used was crossvalidation method (full cross-validation) that eliminates the need for a validation set. The evaluation of the models was done by observing the values of correlation coefficient R 2 and RMSEC mean square error (calibration error) and RMSEP (forecast error). As the forecast values estimated for the remaining 36 samples, which the results were consistent with the values obtained by UV spectroscopy

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Determinação de parâmetros (sólidos solúveis, pH e acidez titulável) em ameixas intactas usando espectroscopia no infravermelho próximo e seleção de comprimento de onda

The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums

Uso da espectroscopia do infravermelho próximo e técnicas multivariadas para diferenciar escherichia coli e salmonella enteritidis inoculadas em polpa de fruta (abacaxi)

Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

Estudo da potencialidade da espectroscopia de infravermelho próximo na análise de cabelo utilizando ferramentas quimiométricas para diferenciar fumantes de não fumantes

This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification