894 resultados para Synchronous Machine
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.
Resumo:
This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
Workplace accidents involving machines are relevant for their magnitude and their impacts on worker health. Despite consolidated critical statements, explanation centered on errors of operators remains predominant with industry professionals, hampering preventive measures and the improvement of production-system reliability. Several initiatives were adopted by enforcement agencies in partnership with universities to stimulate production and diffusion of analysis methodologies with a systemic approach. Starting from one accident case that occurred with a worker who operated a brake-clutch type mechanical press, the article explores cognitive aspects and the existence of traps in the operation of this machine. It deals with a large-sized press that, despite being endowed with a light curtain in areas of access to the pressing zone, did not meet legal requirements. The safety devices gave rise to an illusion of safety, permitting activation of the machine when a worker was still found within the operational zone. Preventive interventions must stimulate the tailoring of systems to the characteristics of workers, minimizing the creation of traps and encouraging safety policies and practices that replace judgments of behaviors that participate in accidents by analyses of reasons that lead workers to act in that manner.
Resumo:
Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
This paper concerns a type of rotating machine (centrifugal vibrator), which is supported on a nonlinear spring. This is a nonideal kind of mechanical system. The goal of the present work is to show the striking differences between the cases where we take into account soft and hard spring types. For soft spring, we prove the existence of homoclinic chaos. By using the Melnikov's Method, we show the existence of an interval with the following property: if a certain parameter belongs to this interval, then we have chaotic behavior; otherwise, this does not happen. Furthermore, if we use an appropriate damping coefficient, the chaotic behavior can be avoided. For hard spring, we prove the existence of Hopf's Bifurcation, by using reduction to Center Manifolds and the Bezout Theorem (a classical result about algebraic plane curves).
Resumo:
O trabalho teve por objetivo avaliar a demanda energética de uma semeadora-adubadora, em função do tipo e manejo da cultura de cobertura vegetal e da profundidade da haste de deposição de adubo. Foi utilizado um trator Valtra BM100, instrumentado, para tracionar uma semeadora-adubadora de precisão equipada com quatro fileiras de semeadura espaçadas de 0,9 m para cultura de milho. O experimento foi conduzido em parcelas subsubdivididas, na área experimental do Laboratório de Máquinas e Mecanização Agrícola (LAMMA) da UNESP-Jaboticabal, utilizando duas culturas de cobertura (mucuna-preta e crotalária), três manejos dessas coberturas, sendo dois mecânicos (triturador de palhas e rolo-faca) e um químico (pulverização com herbicida), realizados 120 dias após a semeadura das culturas de cobertura e três profundidades da haste de deposição do adubo (0,11; 0,14 e 0,17 m), perfazendo 18 tratamentos, com quatro repetições, totalizando 72 observações. Foram avaliados os parâmetros velocidade de deslocamento, patinagem, força na barra de tração, força de pico, potência na barra de tração, potência de pico e consumo de combustível. Pôde-se concluir que a força na barra de tração foi menor para as profundidades de 0,11 e 0,14 m da haste sulcadora de adubo, o mesmo ocorrendo para força de pico, potência na barra de tração e consumo volumétrico. O consumo específico foi menor na profundidade de 0,17 m da haste sulcadora de adubo. As culturas de cobertura e seus manejos não interferiram no desempenho das máquinas estudadas.
Resumo:
This work will propose the control of an induction machine in field coordinates with imposed stator current based on theory of variable structure control and sliding mode. We describe the model of an induction machine in field coordinates with imposed stator current and we show the design of variable structure control and sliding mode to get a desirable dynamic performance of that plant. To estimate the inaccessible states we will use a state observer (estimator) based on field coordinates induction machine. We will present the results of simulations in any operation condition (start, speed reversal and load) and with parameters variation of the machine compared to a PI control scheme.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
This work aims to present the design and the evaluation of a standard multi-pole machine with permanent magnets inserted in the rotor by two different geometrical forms: aligned and skewed magnets. The design (new analytical method) was based on a standard 250 W three phase 12-pole induction motor (squirrel cage rotor type), beginning with the original stator constructive data to calculate the magnetic flux density to determine the permanent magnets. In the development of the work, a simple and modular rotor was built reusing the original 12-pole stator (concentrated windings). The machine was evaluated in a laboratory for the purpose of checking the quantity and quality of energy produced with the machine operating as a generator and its start, torque, and performance working as a motor. In conclusion, the modular skewed magnet is an option for electrical machines, for the generation of a reasonable quality, in the context of decentralized generation and a motor with high torque and low energetic consumption.
Resumo:
This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. The quadrature axis parameters are obtained with a rejection under an arbitrary reference, reducing the present difficulties.
Resumo:
This work presents an algorithm for the security control of electric power systems using control actions like generation reallocation, determined by sensitivity analysis (linearized model) and optimization by neural networks. The model is developed taking into account the dynamic network aspects. The preventive control methodology is developed by means of sensitivity analysis of the security margin related with the mechanical power of the system synchronous machines. The reallocation power in each machine is determined using neural networks. The neural network used in this work is of Hopfield type. These networks are dedicated electric circuits which simulate the constraint set and the objective function of an optimization problem. The advantage of using these networks is the higher speed in getting the solutions when compared to conventional optimization algorithms due to the great convergence rate of the process and the facility of the method parallelization. Then, the objectives are: formulate and investigate these networks implementations in determining. The generation reallocation in digital computers. Aiming to illustrate the proposed methodology an application considering a multi-machine system is presented.