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

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

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

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

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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)

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

Efeitos da estimulação ambiental sobre os aspectos motores, cognitivos e neuronais em um modelo farmacológico progressivo da doença de Parkinson

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