Sistema para detecção e diagnóstico de falhas em motores elétricos de indução utilizando lógica fuzzy

Induction motors are one of the most important equipment of modern industry. However, in many situations, are subject to inadequate conditions as high temperatures and pressures, load variations and constant vibrations, for example. Such conditions, leaving them more susceptible to failures, either external or internal in nature, unwanted in the industrial process. In this context, predictive maintenance plays an important role, where the detection and diagnosis of faults in a timely manner enables the increase of time of the engine and the possibiity of reducing costs, caused mainly by stopping the production and corrective maintenance the motor itself. In this juncture, this work proposes the design of a system that is able to detect and diagnose faults in induction motors, from the collection of electrical line voltage and current, and also the measurement of engine speed. This information will use as input to a fuzzy inference system based on rules that find and classify a failure from the variation of thess quantities

Sistema especialista para detecção de falhas em comandos elétricos

This work consists of the creation of a Specialist System which utilizes production rules to detect inadequacies in the command circuits of an operation system and commands of electric engines known as Direct Start. Jointly, three other modules are developed: one for the simulation of the commands diagram, one for the simulation of faults and another one for the correction of defects in the diagram, with the objective of making it possible to train the professionals aiming a better qualification for the operation and maintenance. The development is carried through in such a way that the structure of the task allows the extending of the system and a succeeding promotion of other bigger and more complex typical systems. The computational environment LabView is employed to enable the system

Desenvolvimento de software para simulação de motores com dispositivos de partida baseada na integração do atp com o toprede

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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)

Motor de indução trifásico sem mancais com bobinado dividido: otimização do sistema de posicionamento radial

This dissertation dea1s with the active magnetic suspension controI system of an induction bearingIess motor configured with split windings. It analyses a dynamic modeI for the radial magnetic forces actuating on the rotor. From that, it proposes a new approach for the composition of the currents imposed to the machine's stator. It shows the tests accomplished with a prototype, proving the usefulness of the new actuating structure for the radial positioning controI. Finnaly, it points out the importance of adapting this structure to well-known rotational controI techniques, continuing this kind of equipment research, which is carried out at Federal University of Rio Grande do Norte since 2000

Caracterização de escovas de grafite e avaliação do seu desempenho em função da microestrutura

The electric can be converted into thermal, luminous, electromagnetic, and also in mechanical energy. In this context the electric engines plays a fundamental role, specially that they work very below of its nominal capacity, with consequent decrease load density. In industrial environment, these characteristics of work of DC engines had also generated an extreme consumption of coal brushs and attack in the commutator reducing the useful life of the engine and increasing maintenance demand and cost. The general objective of the present work is to study the influence of the granulometry of the coal brush used in DC engines with the resistance to the consumption of the same ones, as well as in the performance presented by the commutator of the engine. Additionally, determining the measurable and not measurable profits when the brush used is adjusted to the application. The brushes had been produced by an industry of the sector and tested in industrial environment to evaluate their performance and consumption. Preliminary results evidence a substantial improvement in the performance of these brushes in function of its microstructure and the application in which it is used

Utilização da lógica difusa no controle inteligente de sistemas eletro-hidráulicos

Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as deadzone due to valve spool overlap on the passage´s orifice of the fluid. This work describes the development of a nonlinear controller based on the feedback linearization method and including a fuzzy compensation scheme for an electro-hydraulic actuated system with unknown dead-band. Numerical results are presented in order to demonstrate the control system performance

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Reconhecimento de padrões de falhas em motores trifásicos utilizando redes neurais

This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

Desenvolvimento de Modelos no Programa DigSILENT PowerFactoryTM para o Estudo de Estabilidade Transitória em Sistemas Elétricos de Potência com Aerogerador

This work presents a description of models development at DigSILENT PowerFactoryT M program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryT M and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryT M program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doublyfed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances

Desenvolvimento de modelos no programa digSILENT powerfactoryTM para o estudo de estabilidade transitória em sistemas elétricos de potência com aerogerador

This work presents a description of models development at DigSILENT PowerFactoryTM program for the transient stability study in power systems with wind turbine. The main goal is to make available means to use a dynamic simulation program in power systems, widely published, and utilize it as a tool that helps in programs results evaluations used for this intent. The process of simulations and analyses results starts after the models setting description phase. The results obtained by the DigSILENT PowerFactoryTM and ATP, program chosen to the validation also international recognized, are compared during this phase. The main tools and guide lines of PowerFactoryTM program use are presented here, directing these elements to the solution of the approached problem. For the simulation it is used a real system which it will be connected a wind farm. Two different technologies of wind turbines were implemented: doubly-fed induction generator with frequency converter, connecting the rotor to the stator and to the grid, and synchronous wind generator with frequency converter, interconnecting the generator to the grid. Besides presenting the basic conceptions of dynamic simulation, it is described the implemented control strategies and models of turbine and converters. The stability of the wind turbine interconnected to grid is analyzed in many operational conditions, resultant of diverse kinds of disturbances

Estimação de Fasores para Proteção de Sistemas Elétricos Baseada em Mínimos Quadrados e Morfologia Matemática

This work proposes a new technique for phasor estimation applied in microprocessor numerical relays for distance protection of transmission lines, based on the recursive least squares method and called least squares modified random walking. The phasor estimation methods have compromised their performance, mainly due to the DC exponential decaying component present in fault currents. In order to reduce the influence of the DC component, a Morphological Filter (FM) was added to the method of least squares and previously applied to the process of phasor estimation. The presented method is implemented in MATLABr and its performance is compared to one-cycle Fourier technique and conventional phasor estimation, which was also based on least squares algorithm. The methods based on least squares technique used for comparison with the proposed method were: forgetting factor recursive, covariance resetting and random walking. The techniques performance analysis were carried out by means of signals synthetic and signals provided of simulations on the Alternative Transient Program (ATP). When compared to other phasor estimation methods, the proposed method showed satisfactory results, when it comes to the estimation speed, the steady state oscillation and the overshoot. Then, the presented method performance was analyzed by means of variations in the fault parameters (resistance, distance, angle of incidence and type of fault). Through this study, the results did not showed significant variations in method performance. Besides, the apparent impedance trajectory and estimated distance of the fault were analysed, and the presented method showed better results in comparison to one-cycle Fourier algorithm

Estudo das propriedades físico-químicas do biodiesel e suas influências na deterioração dos elastômeros aplicados no sistema de injeção dos motores diesel

The biodiesel use has become important due to its renewable character and to reduce environmental impacts during the fuel burning. Theses benefit will be valid if the fuel shows good performance, chemistry stability and compatibility with engines. Biodiesel is a good fuel to diesel engines due to its lubricity. Then, the aimed of this study was to verify the physicalchemistry properties of biodiesel and their correlations with possible elastomers damage after biodiesel be used as fuel in an injection system. The methodology was divided in three steps: biodiesels synthesis by transesterification of three vegetable oil (soybean, palm and sunflower) and their physical-chemistry characterization (viscosity, oxidative stability, flash point, acidity, humidity and density); pressurized test of compatibility between elastomers (NBR and VITON) and biodiesel, and the last one, analyze of biodiesels lubricity by tribological test ball-plan( HFRR). Also, the effect of mixture of biodiesel and diesel in different concentrations was evaluated. The results showed that VITON showed better compatibility with all biodiesel blends in relation to NBR, however when VITON had contact with sunflower biodiesel and its blends the swelling degree suffer higher influences due to biodiesel humidity. For others biodiesels and theirs blends, this elastomer kept its mechanical properties constant. The better tribological performance was observed for blends with high biodiesel concentration, lower friction coefficient was obtained when palm biodiesel was used. The main mechanisms observed during the HFRR tests were abrasive and oxidative wear

Administração repetida de baixas doses de reserpina: um possível modelo para o estudo de déficits cognitivos e motores associados à Doença de Parkinson

Parkinson's disease (PD) is one of the most common neurodegenerative brain disorders and is characterized primarily by a progressive degeneration of dopaminergic neurons nigroestriatais. The main symptoms of this disease are motor alterations (bradykinesia, rigidity, tremor at rest), which can be highly disabling in advanced stages of the condition. However, there are symptomatic manifestations other than motor impairment, such as changes in cognition, mood and sensory systems. Animal models that attempt to mimic clinical features of PD have been used to understand the behavioral and neural mechanisms underlying neurophysiological disturbance of this disease. However, most models promote an intense and immediate motor impairment, consistent with advanced stages of the disease, invalidating these studies for the evaluation of its progressive nature. The administration of reserpine (a monoamine depletor) in rodents has been considered an animal model for studying PD. Recently we found that reserpine (in doses lower than those usually employed to produce the motor symptoms) promotes a memory deficit in an aversive discrimination task, without changing the motor activity. It was suggested that the administration of this drug in low doses can be useful for the study of memory deficits found in PD. Corroborating this data, in another study, acute subcutaneous administration of reserpine, while preserving motor function, led to changes in emotional context-related (but not neutral) memory tasks. The goal of this research was to study the cognitive and motor deficits in rats repeatedly treated with low doses of reserpine, as a possible model that simulates the progressive nature of the PD. For this purpose, 5-month-old male Wistar rats were submitted to a repeated treatment with vehicle or different doses of reserpine on alternate days. Cognitive and motor parameters and possible changes in neuronal function were evaluated during treatment. The main findings were: repeated administration of 0.1 mg / kg of reserpine in rats is able to induce the gradual appearance of motor signs compatible with progressive features found in patients with PD; an increase in striatal levels of oxidative stress and changes in the concentrations of glutamate in the striatum were observed five days after the end of treatment; in animals repeatedly-treated with 0. 1 mg/kg, cognitive deficits were observed only after the onset of motor symptoms, but not prior to the onset of these symptoms; 0.2 mg / kg reserpine repeated treatment has jeopardized the cognitive assessment due to the presence of severe motor deficits. Thus, we suggest that the protocol of treatment with reserpine used in this work is a viable alternative for studies of the progressive appearance of parkinsonian signs in rats, especially concerning motor symptoms. As for the cognitive symptoms, we suggest that more studies are needed, possibly using other behavioral models, and / or changing the treatment regimen