Estimativa do comportamento de máquinas assíncronas sujeitas a afundamentos de tensão

Os afundamentos de tensão são reduções de curta duração entre o 10% a 90% da magnitude de tensão eficaz. Usualmente, estes afundamentos são associados com falhas no sistema de energia elétrica, mas podem ser causados pela elevada corrente de partida de motores de indução ou energização de transformadores. Apesar de sua curta duração, tais eventos podem causar sérios problemas para alguns equipamentos. As conseqüências dos afundamentos de tensão sobre a máquina assíncrona são: perda de velocidade durante o afundamento e picos de corrente e de conjugado que aparecem na queda de tensão e no instante de restabelecimento. Este estudo visa analisar o comportamento da máquina assíncrona diante de afundamentos de tensão e as características destes, devido à influência do motor assíncrono como carga. Enfocando-se neste ponto, é que foram considerados diferentes tipos de afundamentos devido a diferentes falhas, que produziram quedas de tensão nos terminais da máquina assíncrona com variações na magnitude e no argumento de tensão. As simulações foram realizadas aplicando um método numérico tradicional e um método simplificado, o método simplificado lineariza as equações diferenciais elétricas da máquina assíncrona considerando a velocidade mecânica constante, para o cálculo dos transitórios elétricos no início da queda de tensão e no restabelecimento da mesma. Os transitórios obtidos pelo método numérico tradicional (Runge Kutta quarta ordem) e o método simplificado foram comparados, para verificar a precisão deste método com respeito ao numérico tradicional, concluindo-se, que o método simplificado poderá aplicar-se em máquinas de baixo escorregamento e elevada constante de inércia. Além disso, foram realizados experimentos, submetendo o sistema a diferentes quedas de tensão, considerando diferentes magnitudes e durações no afundamento.

Indústria de máquinas agrícolas no Brasil: um modelo para estimação da demanda de tratores para o triênio 2016 – 2018

O objetivo desta dissertação foi estimar a demanda de tratores agrícolas para o mercado brasileiro no triênio 2016-2018, utilizando-se para isto de técnicas de econometria de séries temporais, neste caso, modelos univariados da classe ARIMA e SARIMA e ou multivariados SARIMAX. Justifica-se esta pesquisa quando se observa a indústria de máquinas agrícolas no Brasil, dados os ciclos econômicos e outros fatores exógenos aos fundamentos econômicos da demanda, onde esta enfrenta muitos desafios. Dentre estes, a estimação de demanda se destaca, pois exerce forte impacto, por exemplo, no planejamento e custo de produção de curto e médio prazo, níveis de inventários, na relação com fornecedores de materiais e de mão de obra local, e por consequência na geração de valor para o acionista. Durante a fase de revisão bibliográfica foram encontrados vários trabalhos científicos que abordam o agronegócio e suas diversas áreas de atuação, porém, não foram encontrados trabalhos científicos publicados no Brasil que abordassem a previsão da demanda de tratores agrícolas no Brasil, o que serviu de motivação para agregar conhecimento à academia e valor ao mercado através deste. Concluiu-se, após testes realizados com diversos modelos que estão dispostos no texto e apêndices, que o modelo univariado SARIMA (15,1,1) (1,1,1) cumpriu as premissas estabelecidas nos objetivos específicos para escolha do modelo que melhor se ajusta aos dados, e foi escolhido então, como o modelo para estimação da demanda de tratores agrícolas no Brasil. Os resultados desta pesquisa apontam para uma demanda de tratores agrícolas no Brasil oscilando entre 46.000 e 49.000 unidades ano entre os anos de 2016 e 2018.

Impacto do tráfego de máquinas na qualidade física do solo e produtividade de milho em Argissolo

Este estudo teve o objetivo de avaliar o impacto do tráfego de máquinas na qualidade física do solo e produtividade de milho em Argissolo. O delineamento experimental foi inteiramente casualizado, com seis tratamentos e oito repetições representadas por parcelas de 14 m². Os tratamentos foram: T0) sem tráfego; T1*) uma passada de trator de 3,0 t, uma ao lado da outra; T1) uma passada; T2) duas passadas; T4) quatro passadas; T8) oito passadas de um trator de 8,0 t. Utilizou-se o milho (Zea mays L.) híbrido master, que foi avaliado quanto à produtividade de grãos. No solo, foram avaliados a porosidade, a densidade do solo, a resistência à penetração, o intervalo hídrico ótimo e a densidade do solo relativa. O tráfego de máquinas compactou o solo até 0,25 m de profundidade e reduziu a produtividade de milho em até 22%. O intervalo hídrico ótimo diminuiu com o aumento do tráfego de máquinas indicando decréscimo da qualidade física do solo para o milho. A densidade do solo relativa limitante à produtividade de milho é de 0,89.

Implementação e avaliação de máquinas de comitê em um ambiente com múltiplos processadores embarcados em um único chip

The number of applications based on embedded systems grows significantly every year, even with the fact that embedded systems have restrictions, and simple processing units, the performance of these has improved every day. However the complexity of applications also increase, a better performance will always be necessary. So even such advances, there are cases, which an embedded system with a single unit of processing is not sufficient to achieve the information processing in real time. To improve the performance of these systems, an implementation with parallel processing can be used in more complex applications that require high performance. The idea is to move beyond applications that already use embedded systems, exploring the use of a set of units processing working together to implement an intelligent algorithm. The number of existing works in the areas of parallel processing, systems intelligent and embedded systems is wide. However works that link these three areas to solve any problem are reduced. In this context, this work aimed to use tools available for FPGA architectures, to develop a platform with multiple processors to use in pattern classification with artificial neural networks

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Caracterização física do solo e desempenho operacional de máquinas agrícolas na implantação da cultura do sorgo forrageiro

Forage sorghum can be grown in areas presenting dry and hot environmental situations where the yield of other grasses can often be uneconomical. The objective of this study was to analyze the operating performance of agricultural machines in the deployment of sorghum forage in four tillage systems, as follows: no-tillage system, disk harrow + seeding, disk harrow + two light disking + seeding, minimum tillage + seeding and four seeding different speeds, as follows: 3, 5, 6 and 9 km h(-1). The study was performed under field conditions in FCA/UNESP, Botucatu County, SP, Brazil. The data were subjected to variance analysis in a simple factorial 4 x 4, and a random block design with split plots. Operational performance of the agricultural machinery, physical characteristics the soil, its water content and the yield of dry matter and green sorghum were determined. The operational performance of agricultural machines in the deployment of sorghum forage is influenced by the sowing speed and the soil tillage system used. Chisel plow was the equipment that required the highest mean traction force, mean traction and slip, as well as the lowest mean speed for the studied tillage system. Forage sorghum showed higher yields in no-tillage systems at a seeding speed of 5 km h(-1).

Desenvolvimento de um Sistema de Automação e Supervisão de Máquinas Dispensadoras Através da Internet

This paper aims to design and develop a control and monitoring system of vending machines, based on a Central Processing Unit with peripheral Internet communication. Coupled with the condom vending machines, a data acquisition module will be connected to the original circuits in order to collect and send, via internet, the information to the healthy government agencies, in the form of charts and reports. In the face of this, such agencies may analyze these data and compare them with the rates of reduction, in medium or long term, of the STD/AIDS in their respective regions, after the implementation of these vending machines, together with the conventional preventing programs. Reading the methodology, this paper is about an explaining and bibliography research, with the aspect of a qualitative-quantitative methodology, presenting a deductive method of approach and an indirect documentation technique research. About the results of the tests and simulations, we concluded that the implementation of this system will have the same success in any other type of dispenser machine

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Viabilidade da Utilização de Máquinas de Indução Convencionais como Motores sem Mancais Mecânicos

Electrical Motors transform electrical energy into mechanic energy in a relatively easy way. In some specific applications, there is a need for electrical motors to function with noncontaminated fluids, in high speed systems, under inhospitable conditions, or yet, in local of difficult access and considerable depth. In these cases, the motors with mechanical bearings are not adequate as their wear give rise to maintenance. A possible solution for these problems stems from two different alternatives: motors with magnetic bearings, that increase the length of the machine (not convenient), and the bearingless motors that aggregate compactness. Induction motors have been used more and more in research, as they confer more robustness to bearingless motors compared to other types of machines building with others motors. The research that has already been carried out with bearingless induction motors utilized prototypes that had their structures of stator/rotor modified, that differ most of the times from the conventional induction motors. The goal of this work is to study the viability of the use of conventional induction Motors for the beringless motors applications, pointing out the types of Motors of this category that can be more useful. The study uses the Finite Elements Method (FEM). As a means of validation, a conventional induction motor with squirrel-cage rotor was successfully used for the beringless motor application of the divided winding type, confirming the proposed thesis. The controlling system was implemented in a Digital Signal Processor (DSP)

Estabilizador de sistema de potência para máquinas síncronas de polos salientes utilizando a transformada Wavelet

The power system stabilizers are used to suppress low-frequency electromechanical oscillations and improve the synchronous generator stability limits. This master thesis proposes a wavelet-based power system stabilizer, composed of a new methodology for extraction and compensation of electromechanical oscillations in electrical power systems based on the scaling coefficient energy of the maximal overlap discrete wavelet transform in order to reduce the effects of delay and attenuation of conventional power system stabilizers. Moreover, the wavelet coefficient energy is used for electric oscillation detection and triggering the power system stabilizer only in fault situations. The performance of the proposed power system stabilizer was assessed with experimental results and comparison with the conventional power system stabilizer. Furthermore, the effects of the mother wavelet were also evaluated in this work