Identificação de uma planta de corrente de um motor de indução utilizando redes de base radial

The present work describes the use of a mathematical tool to solve problems arising from control theory, including the identification, analysis of the phase portrait and stability, as well as the temporal evolution of the plant s current induction motor. The system identification is an area of mathematical modeling that has as its objective the study of techniques which can determine a dynamic model in representing a real system. The tool used in the identification and analysis of nonlinear dynamical system is the Radial Basis Function (RBF). The process or plant that is used has a mathematical model unknown, but belongs to a particular class that contains an internal dynamics that can be modeled.Will be presented as contributions to the analysis of asymptotic stability of the RBF. The identification using radial basis function is demonstrated through computer simulations from a real data set obtained from the plant

Avaliação do módulo de elasticidade da madeira com uso de método não-destrutivo de vibração transversal

Numerosas pesquisas têm estudado os métodos não-destrutivos de avaliação de materiais e sua aplicação àqueles de matrizes complexas, como é o caso da madeira. Um dos primeiros métodos não-destrutivos investigados para aplicação nesses casos foi o da vibração transversal. Apesar de sua concepção simples, e a despeito dos grandes avanços obtidos nessa área com outros métodos, como, por exemplo, o ultra-som, o método de vibração transversal para a determinação do módulo de elasticidade da madeira revela-se como de grande potencial de aplicação, sobretudo pela precisão do modelo matemático a ele associado e pela possibilidade de sua aplicação a peças de dimensões estruturais (in-grade testing). Neste trabalho, apresenta-se o uso desse método na determinação do módulo de elasticidade de três espécies de eucalipto. Foram ensaiados não-destrutivamente e por ensaios mecânicos convencionais de flexão corpos-de-prova de 2 cm x 2 cm x 46 cm de E. grandis, E. saligna e E. citriodora. Os ensaios não-destrutivos foram conduzidos com uso do sistema BING - Beam Identification by Non-destructive Grading, que permite a análise das vibrações do material nos domínios do tempo e da freqüência. Os resultados obtidos revelaram boa correlação entre os dois tipos de ensaios empregados, justificando o início dos ensaios com peças de dimensões estruturais, para a viabilização da técnica nas práticas de classificação estrutural.

Investment recovery period in electric motor of higher efficiency in pumping for irrigation

Neste trabalho, ajustou-se um modelo matemático para quantificar o efeito do rendimento do motor elétrico sobre os custos de um sistema de bombeamento para irrigação na estrutura tarifária de energia elétrica convencional e horo-sazonal verde, bem como calcular o tempo de recuperação do capital investido no equipamento de maior rendimento. em seguida, o mesmo foi aplicado a um sistema de irrigação tipo pivô central em duas opções de rendimento do motor elétrico: 92,6% (linha padrão) e 94,3% (linha alto rendimento), sendo que o custo de aquisição do primeiro correspondeu a 70% do segundo. A potência do motor elétrico era de 100 cv. Os resultados mostraram que o modelo permitiu avaliar se um motor de alto rendimento era viável economicamente em relação ao motor-padrão em cada estrutura tarifária. Nas duas estruturas tarifárias, o motor de alto rendimento não foi viável. Na tarifa horo-sazonal verde, somente seria viável se seu rendimento fosse 4,46% superior ao do motor-padrão. Na tarifa convencional, somente seria viável se o ganho de rendimento superasse 2,71%.

Modelo de programação linear para seleção de pulverizadores agrícolas de barras

A seleção de pulverizadores agrícolas que se adaptem às necessidades da propriedade, é um processo trabalhoso, sendo uma das etapas mais importantes dentro do processo produtivo. O objetivo do presente trabalho foi o de desenvolver e utilizar um modelo de programação linear para auxiliar na seleção de pulverizadores agrícolas de barras, baseado no menor custo horário do equipamento. Foram utilizadas as informações técnicas referentes a 20 modelos de pulverizadores disponíveis no mercado, sendo quatro autopropelidos, oito de arrasto e oito do tipo montado. A análise de sensibilidade dos componentes dos custos operacionais mostrou que as taxas de reparo e depreciação foram os fatores que mais interferiram na variação do custo horário do conjunto trator-pulverizador. O modelo matemático desenvolvido facilitou a realização da análise de sensibilidade que foi processada em um tempo muito pequeno.

Algoritmos genéricos para otimização de uma arquitetura de controle inteligente híerárquico

A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use

Caracterização de circuitos planares de micro-ondas pelo método iterativo das ondas

The planar circuits are structures that increasingly attracting the attention of researchers, due the good performance and capacity to integrate with other devices, in the prototyping of systems for transmitting and receiving signals in the microwave range. In this context, the study and development of new techniques for analysis of these devices have significantly contributed in the design of structures with excellent performance and high reliability. In this work, the full-wave method based on the concept of electromagnetic waves and the principle of reflection and transmission of waves at an interface, Wave Concept Iterative Procedure (WCIP), or iterative method of waves is described as a tool with high precision study microwave planar circuits. The proposed method is applied to the characterization of planar filters, microstrip antennas and frequency selective surfaces. Prototype devices were built and the experimental results confirmed the proposed mathematical model. The results were also compared with simulated results by Ansoft HFSS, observing a good agreement between them.

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Br-IndustrialExpert: um framework para análise de dependabilidade de processos industriais

There is a growing need to develop new tools to help end users in tasks related to the design, monitoring, maintenance and commissioning of critical infrastructures. The complexity of the industrial environment, for example, requires that these tools have flexible features in order to provide valuable data for the designers at the design phases. Furthermore, it is known that industrial processes have stringent requirements for dependability, since failures can cause economic losses, environmental damages and danger to people. The lack of tools that enable the evaluation of faults in critical infrastructures could mitigate these problems. Accordingly, the said work presents developing a framework for analyzing of dependability for critical infrastructures. The proposal allows the modeling of critical infrastructure, mapping its components to a Fault Tree. Then the mathematical model generated is used for dependability analysis of infrastructure, relying on the equipment and its interconnections failures. Finally, typical scenarios of industrial environments are used to validate the proposal

Modelo matemático para otimização dos custos de um sistema híbrido eólico-solar : aplicação no bombeamento de petróleo

This work purposes the application of a methodology to optimize the implantation cost of an wind-solar hybrid system for oil pumping. The developed model is estimated the implantation cost of system through Multiple Linear Regression technique, on the basis of the previous knowledge of variables: necessary capacity of storage, total daily energy demand, wind power, module power and module number. These variables are gotten by means of sizing. The considered model not only can be applied to the oil pumping, but also for any other purposes of electric energy generation for conversion of solar, wind or solar-wind energy, that demand short powers. Parametric statistical T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind, F by Snedecor in the variance analysis to test if the coefficients of the considered model are significantly different of zero and test not-parametric statistical by Friedman, toverify if there is difference in the system cost, by being considered the photovoltaic module powers. In decision of hypothesis tests was considered a 5%-significant level. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 3 HP. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 5 HP only to wind speed of 4m/s and 6 m/s in wind of 3 m, 4m and 5 m of diameter. There was not significant difference in costs to diameters of winds of 3 m and 4m. The mathematical model and the computational program may be used to others applications which require electrical between 2.250 W and 3.750 W. A computational program was developed to assist the study of several configurations that optimizes the implantation cost of an wind-solar system through considered mathematical model

Análise do comportamento mecânico de espumas cerâmicas a base de alumina obtidas pelo método da réplica

Ceramics with porous cellular structure, called ceramic foams, have a potential use in several applications, such as: thermal insulation, catalyst supports, filters, and others. Among these techniques to obtain porous ceramics the replication method is an important process. This method consists of impregnation of a sponge (usually polymer) with ceramic slurry, followed by a heat treatment, which will happen the decomposition of organic material and sintering the ceramic material, resulting in a ceramic structure which is a replica of impregnated sponge. Knowledge of the mechanical properties of these ceramics is important for these materials can be used commercially. Gibson and Ashby developed a mathematical model to describe the mechanical behavior of cellular solids. This model wasn´t for describing the ceramics behavior produced by the replica method, because it doesn´t consider the defects from this type of processing. In this study were researched mechanical behavior of porous alumina ceramics obtained by the replica method and proposed modifications to the model of Gibson and Ashby to accommodate this material. The polymer sponge used in processing was characterized by thermogravimetric analysis and scanning electron microscopy. The materials obtained after sintering were characterized by mechanical strength tests on 4-point bending and compression, density and porosity and by scanning electron microscopy. From these results it was evaluated the mechanical strength behavior compared to Gibson and Ashby model for solid cellular structure and was proposed a correction of this model through a factor related to struts integrity degree, which consider fissures present in the structure of these materials besides defects geometry within the struts

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Medição e modelagem da resposta de um sensor de pig perfilométrico sob diferentes solicitações dinâmicas

Ensure the integrity of the pipeline network is an extremely important factor in the oil and gas industry. The engineering of pipelines uses sophisticated robotic inspection tools in-line known as instrumented pigs. Several relevant factors difficult the inspection of pipelines, especially in offshore field which uses pipelines with multi-diameters, radii of curvature accentuated, wall thickness of the pipe above the conventional, multi-phase flow and so on. Within this context, appeared a new instrumented Pig, called Feeler PIG, for detection and sizing of thickness loss in pipelines with internal damage. This tool was developed to overcome several limitations that other conventional instrumented pigs have during the inspection. Several factors influence the measurement errors of the pig affecting the reliability of the results. This work shows different operating conditions and provides a test rig for feeler sensors of an inspection pig under different dynamic loads. The results of measurements of the damage type of shoulder and holes in a cyclic flat surface are evaluated, as well as a mathematical model for the sensor response and their errors from the actual behavior

Extração do óleo e caracterização dos resíduos da borra de petróleo para fins de reuso

The petroleum industry, in consequence of an intense activity of exploration and production, is responsible by great part of the generation of residues, which are considered toxic and pollutants to the environment. Among these, the oil sludge is found produced during the production, transportation and refine phases. This work had the purpose to develop a process to recovery the oil present in oil sludge, in order to use the recovered oil as fuel or return it to the refining plant. From the preliminary tests, were identified the most important independent variables, like: temperature, contact time, solvents and acid volumes. Initially, a series of parameters to characterize the oil sludge was determined to characterize its. A special extractor was projected to work with oily waste. Two experimental designs were applied: fractional factorial and Doehlert. The tests were carried out in batch process to the conditions of the experimental designs applied. The efficiency obtained in the oil extraction process was 70%, in average. Oil sludge is composed of 36,2% of oil, 16,8% of ash, 40% of water and 7% of volatile constituents. However, the statistical analysis showed that the quadratic model was not well fitted to the process with a relative low determination coefficient (60,6%). This occurred due to the complexity of the oil sludge. To obtain a model able to represent the experiments, the mathematical model was used, the so called artificial neural networks (RNA), which was generated, initially, with 2, 4, 5, 6, 7 and 8 neurons in the hidden layer, 64 experimental results and 10000 presentations (interactions). Lesser dispersions were verified between the experimental and calculated values using 4 neurons, regarding the proportion of experimental points and estimated parameters. The analysis of the average deviations of the test divided by the respective training showed up that 2150 presentations resulted in the best value parameters. For the new model, the determination coefficient was 87,5%, which is quite satisfactory for the studied system

Automação de um sistema rotatório para secagem do rejeito de maracujá

The rotary dryer is one of the most used equipments in processing industries. Its automatic control mode of operation is important specially to keep the moisture content of the final product in the desired value. The classical control strategies, like PID (proportional integral derivative) control, are largely used in the industrial sector because of its robustness and because they are easy to be implemented. In this work, a data acquisition system was implemented for monitoring the most relevant process variables, like: both inlet and outlet drying air temperature, dryer rotation, outlet air speed and humidity, and mass of the final product. Openloop tests were realized to identify a mathematical model able to represent the drying process for the rotary system. From this model, a PID controller was tuned using a direct synthesis method, assuming a first order trajectory. The PID controller was implemented in the system in order to control the inlet drying air temperature. By the end, closedloop tests (operating in automatic mode) were realized to observe the controller performance, and, after setting the best tune, experiments were realized using passion fruit seeds as raw material. The experiments realized in closedloop showed a satisfactory performance by the implemented control strategy for the drying air temperature of the rotary system

Remoção do cobre de efluente galvânico aplicando tensoativos derivado de óleos vegetais

Copper is one of the most used metals in platingprocesses of galvanic industries. The presence of copper, a heavy metal, in galvanic effluents is harmful to the environment.The main objective of this researchwas the removal ofcopperfromgalvanic effluents, using for this purpose anionic surfactants. The removal process is based on the interaction between the polar head group of the anionic surfactant and the divalent copper in solution. The surfactants used in this study were derived from soybean oil (OSS), coconut oil (OCS), and sunflower oil (OGS). It was used a copper synthetic solution (280 ppm Cu+2) simulating the rinse water from a copper acid bath of a galvanic industry. It were developed 23and 32 factorial designs to evaluate the parameters that have influence in theremoval process. For each surfactant (OSS, OCS, and OGS), the independent variables evaluated were: surfactant concentration (1.25 to 3.75 g/L), pH (5 to 9) and the presence of an anionic polymer (0 to 0.0125 g/L).From the results obtained in the 23 factorial design and in the calculus for estimatingthe stoichiometric relationship between surfactants and copper in solution, it were developed new experimental tests, varying surfactant concentration in the range of 1.25 to 6.8 g/L (32 factorial design).The results obtained in the experimental designs were subjected to statistical evaluations to obtain Pareto charts and mathematical modelsfor Copper removal efficiency (%). The statistical evaluation of the 23 and 32factorial designs, using saponifiedcoconut oil (OCS), presented the mathematical model that best described the copper removal process.It can be concluded that OCS was the most efficient anionic surfactant, removing 100% of the copper present in the synthetic galvanic solution