Este trabalho avalia a aplicação de inversores de freqüência realizada em estações elevatórias de água tratada da cidade de São José dos Campos que são monitoradas pelo Centro de Controle Operacional da Sabesp. Foram estudadas as características técnicas de quatro sistemas de bombeamento que operam com velocidade variável. O trabalho apresenta uma proposta de metodologia para a seleção de inversores de freqüência, com base na metodologia recomendada pelo EUROPUMP e HYDRAULIC INSTITUTE (2004) aplicada em quatro sistemas da cidade de São José dos Campos. Essa proposta de metodologia foi executada através da avaliação seqüencial de um fluxograma e da análise gráfica das informações instantâneas e históricas dos parâmetros de vazão, pressão e freqüência de rotação, existentes no banco de dados dos servidores de supervisão e controle do Centro de Controle Operacional de São José dos Campos. Após a aplicação dessa metodologia, conclui-se que, a aplicação de inversores de freqüência nos sistemas estudados estava adequada e recomenda-se a sua aplicação em sistemas de bombeamento semelhantes. / The main purpose of this work is to evaluate the application of Variable Frequency Drives ? VFD, carried out in water pumping stations managed by SABESP ? Companhia de Saneamento Básico do Estado de São Paulo, located in the city of Sâo José dos Campos that are monitored by the Operational Control Center ? O.C.C. Technical characteristics of four pumping systems were studied, mainly those operating with fixed or changeable speed. It proposes a new methodology for VFD selection, based on the methodology recommended by EUROPUMP and HYDRAULIC INSTITUTE (2004), used on the systems mentioned before. This proposal of methodology were done using instantaneous and historical information of flow, pressure and rotation frequency parameters stored on data base installed on supervision and control servers installed. After this application, we also concluded that the use of VFD on the evaluated systems was correct and through this we recommend its use on similar pumping systems.

Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Includes bibliographical references. / M.S.

This thesis analyses, develops and implements a very fast on-line parameter identification algorithm for both rotor and stator resistances of a rotor flux oriented induction motor drive, with the best possible convergence results using artificial neural networks and fuzzy logic systems. The thesis focuses mainly on identifying the rotor resistance, which is the most critical parameter for RFOC. Limitations of PI and fuzzy logic based estimators were identified. Artificial neural network based estimators were found to track the rotor and stator resistances of the drive accurately and fast. The rotor flux of the induction motor estimated with a classical voltage model was the key input of the rotor resistance estimator. Because, pure digital integrators were unable to play this role, an alternative rotor flux synthesizer using a programmable cascaded filter was developed. This rotor flux synthesizer has been used for all of the resistance estimators. It was found that the error in rotor resistance estimation using an ANN was contributed to by error in the stator resistance (caused by motor heating). Several stator resistance estimators using the stator current measurements were developed. The limitations of a PI and a fuzzy estimator for stator resistance estimation were also established. A new stator resistance identifier using an ANN was found to be much superior to the PI and fuzzy estimators, both in terms of dynamic estimation times and convergence problems. The rotor resistance estimator developed for this thesis used a feedforward neural network and the stator resistance estimator used a recurrent neural network. Both networks exhibited excellent learning capabilities; the stator resistance estimator network was very fast as it had a feedback input. A speed estimator was also developed with the state estimation principles, with the updated motor parameters supplied by the ANN estimators. Analysis for speed sensorless operation has shown that the stator and rotor resistances could be updated on-line.

Induction motors are widely used in industrial processes. The malfunction of a motor may not only lead to high repair costs, but also cause immense financial losses due to unexpected process downtime. Since thermal overload is one of the major root causes of stator winding insulation failure, an accurate and reliable monitoring of the stator winding temperature is crucial to increase the mean time to catastrophic motor breakdown, and to reduce the extraordinary financial losses due to unexpected process downtime. To provide a reliable thermal protection for induction motors fed by motor control devices, a dc signal-injection method is proposed for in-service induction motors fed by soft-starter and variable-frequency drives. The stator winding temperature can be monitored based on the estimated stator winding resistance using the dc model of induction motors. In addition, a cooling capability monitoring technique is proposed to monitor the cooling capability of induction motors and to warn the user for proactive inspection and maintenance in the case of cooling capability deterioration. The proposed cooling capability monitoring technique, combined with the proposed stator winding temperature monitoring technique, can provide a complete thermal protection for in-service induction motors fed by motor control devices. Aside from online thermal protection during a motor's normal operation, the thermal protection of de-energized motors is also essential to prolong a motor's lifetime. Moisture condensation is one of the major causes to motor degradation especially in high-humidity environments. To prevent moisture condensation, a non-intrusive motor heating technique is proposed by injecting currents into the motor stator winding using soft-starters. A motor's temperature can be kept above the ambient temperature due to the heat dissipation, so that the moisture condensation can be avoided. To sum up, active stator winding temperature estimation techniques for induction motors under both operating and de-energization conditions are proposed in this dissertation for both thermal protection and optimizing the operation of a motor system. The importance of these proposed techniques lies in their non-intrusive nature: only the existing hardware in a motor control device is required for implementation; a motor's normal operation is not interrupted.

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: The focus of this thesis is position sensorless control of a transverse-laminated reluctance synchronous machine. Rotor position information is required for high-performance closedloop control of the reluctance synchronous machine and is conventionally supplied by unreliable hardware position resolvers. In addition a FPGA-based rapid prototyping system is completed as part of the research term for control of the machine drive system. For the first time the unified active- ux (AF) method is investigated and implemented for position sensorless control of the transverse-laminated reluctance synchronous machine in this study. The method is based on the torque equation of the machine and is basically the same for any AC machine. The estimation scheme is implemented for closed-loop position sensorless control from low- to rated speed in the entire rated load range with simulation and measured results confirming its capabilities. A number of characteristics of the machine (including generator operation) have implications for implementation of the active- ux (AF) method and are therefore investigated. Another position estimation method investigated is the arbitrary injection (AI) scheme which is derived to be completely machine parameter independent. The method simply requires a current progression at each calculation step allowing use of a smaller injection voltage. This method is implemented again on the reluctance synchronous machine and is shown to be capable of position sensorless current and speed control of the drive from standstill to rated speed with simulation and measured results. However, when the machine is operating above low speeds it is shown that this technique is only capable of position sensorless control at low loads. To deliver position sensorless control in the entire rated speed and load range a new hybrid controller scheme is designed and implemented. The hybrid scheme is speed and load dependent with hysteresis regions for stability at specific working points. The active- ux (AF) method is implemented in the low to rated speed range at medium to rated loads while the arbitrary injection (AI) method is implemented elsewhere. Measured results show that the scheme is capable of position sensorless control in the entire rated speed and load range with some limitations on dynamics. Because of the limitations on dynamics of the hybrid scheme an assisted fundamental model position estimation scheme was investigated. Simulation results show that this controller requires further investigation. / AFRIKAANSE OPSOMMING: Die fokus in hierdie tesis is die posisie-sensorlose beheer van 'n transvers-gelamineerde reluktansie sinchroonmasjien. Rotor posisie inligting word benodig vir geslote-lus beheer van die reluktansie sinchroonmasjien met ho e-werkverrigting, en word normaalweg deur onbetroubare hardeware sensors verskaf. As deel van die navorsings-termyn is 'n FPGAgebaseerde beheerstelsel vir die masjien stelsel voltooi. Die \aktiewe-vloed" posisie-afskattings metode is ondersoek en vir die eerste keer ge mplementeer vir posisie-sensorlose beheer van die transvers-gelamineerde reluktansie sinchroonmasjien. Die metode is dieselfde in konsep vir alle WS masjiene en word basseer op die vergelyking vir wringkrag van die masjien. Vollas geslote-lus posisie-sensorlose beheer van die masjien in die lae tot ho e spoedbereik is suksesvol ge mplementeer met simulasie en gemete resultate. Verkskeie inherente eienskappe van die masjien het implikasies vir gebruik van die \aktiewe-vloed" metode (insluitend generator werking) en is dus ondersoek. Die \arbitr^ere injeksie" metode wat afgelei is om onafhanklik van masjien parameters te wees is ook odersoek. Hierdie metode verlang slegs 'n stroom-afgeleide by elke tydstip en benodig dus 'n kleiner injeksie-spanning. Hierdie metode is weer ge mplementeer op die reluktansie sinchroon masjien met suksesvolle posisie-sensorlose beheer in die hele spoed bereik getoon in simulasie en praktiese resultate. Dit word egter getoon dat hierdie metode slegs onder lae-las toestande posisie sensorlose beheer bo lae-spoed kan bewerkstellig. Ten einde posisie-sensorlose beheer in die hele spoed en wringkrag bereik te verkry is 'n nuwe hibriede beheerskema ontwerp en ge mplementeer. Die skema is spoed en las afhanklik met histerese vir stabiliteit by 'n spesi eke werkpunt. Die \aktiewe-vloed" metode word gebruik bo lae spoed teen 'n minimum las terwyl die \arbitr^ere injeksie" andersins ge mplementeer word. Gemete resultate toon dat die skema posisie-sensorlose beheer van die masjien in die hele spoed en las bereik toelaat met sommige beperkings op dinamika. Met inagneming van die beperkings op die hibriede metode is 'n ondersteunde fundamentele model afskattingskema ondersoek. Simulasie resulate toon dat hierdie beheerder verdere ondersoek benodig.

Conselho Nacional do Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná / Nos dias atuais, um enfoque considerável tem sido dado por pesquisas científicas aos acionamentos de motores elétricos, em destaque aos motores de indução trifásicos com rotor gaiola de esquilo, por serem comumente empregados em aplicações do dia-a-dia, principalmente em ambientes industriais, devido às suas inúmeras e bem conhecidas vantagens. Dentre algumas estratégias existentes para o acionamento destes motores, encontra-se o Controle Direto de Torque, um acionamento vetorial que proporciona um bom desempenho para aplicações de médias e baixas potências. Uma topologia dessa estratégia que envolve a utilização de um algoritmo de Modulação por Vetores Espaciais, denominada de DTC-SVM, tem sido amplamente considerada devido às suas vantagens frente à estrutura convencional. Contudo, em seu algoritmo existem malhas de controle de torque, fluxo e velocidade, que adotam geralmente controladores Proporcional-Integral. Neste trabalho, um estimador de fluxo baseado em modelo de tensão e corrente é considerado, no qual sua estrutura também contém um controlador Proporcional- Integral. Diante desse cenário, este trabalho visa contribuir com o aspecto de sintonia destes controladores, empregando metaheurísticas de otimização para efetuar o ajuste otimizado dos ganhos. Três algoritmos metaheurísticos são considerados: a Otimização por Colônia de Formigas, o Evolução Diferencial e a Otimização por Enxame de Partículas. Basicamente, intervalos de busca para as variáveis envolvidas, ou seja, os ganhos dos controladores, assim como uma função objetivo, que relacione os principais aspectos desejados de melhoria do sistema, devem ser definidos para o processo de otimização, o qual é realizado via simulação computacional. Visando avaliar a eficiência da metodologia proposta, neste trabalho são feitas algumas análises do sistema de acionamento DTC-SVM operando com as sintonias otimizadas e também com uma sintonia inicial, obtida com base em ajustes empíricos. Tais análises são feitas tanto em um ambiente de simulações computacionais, utilizando o software MATLAB/Simulink, quanto em um ambiente experimental, considerando um protótipo desenvolvido, no qual o sistema opera com reversão de velocidade, assim como com distúrbios de carga. Os resultados evidenciam desempenhos eficientes do acionamento operando com as sintonias otimizadas, principalmente durante os regimes transitórios e em operações de baixas velocidades. / Nowadays, a considerable focus has been given by scientific research to the electric motors drive, particularly to the three-phase induction motors with squirrel cage rotor, being commonly used in day-to-day applications, especially in industrial environments, due to its numerous and well known advantages. Among some strategies surveyed for driving these motors, there is the Direct Torque Control, a vector drive which provides good performance for medium and low power applications. A topology of this strategy involving the use of a Space Vector Modulation algorithm, called DTC-SVM, has been considered due to its advantages in comparison to conventional structure. However, in their algorithm there are torque, flux and speed control loops which generally consider Proportional-Integral controllers. In this work, a stator linkage flux estimator based on model of voltage and current is considered, in which its structure also contains a Proportional-Integral controller. Given this scenario, this work aims to contribute with the tuning aspect of these controllers, employing optimization metaheuristics aiming an optimized adjustment of the gains. Three metaheuristic algorithms are considered: Ant Colony Optimization, Differential Evolution and Particle Swarm Optimization. Basically, search ranges to the variables involved, ie. Proportional-Integral controller gains, as well as an objective function, which lists the main desired aspects of improving the system, must be set to the optimization process, which is performed by the computational simulation. Aiming to evaluate the effectiveness of this proposed methodology, in this work were made some analysis at the DTC-SVM drive system operating with the optimized tunings and a initial tuning, obtained by empiric adjusts. Such analysis were carried out either in a computer simulation environment, using MATLAB/Simulink software, as in a laboratory environment, considering a prototype developed, in which the system operates with speed reversal, as well as load disturbances. The results show efficient performances of the drive operating with the optimized tunings, especially during the transient periods and low speed operations.

Fundação Araucária; CNPQ / As máquinas-ferramentas são encontradas em diversas indústrias do setor metal mecânico e oficinas. Estas são acionadas por motores de indução trifásicos, os quais estão sujeitos a problemas relacionados à carga aplicada em seus eixos bem como aos distúrbios da alimentação de energia elétrica na rede. No processo de usinagem os parâmetros relacionados à máquina ferramenta, às propriedades do material da peça, à geometria e ao material da ferramenta e ao próprio processo em si, podem interferir no acabamento superficial das peças usinadas. A rugosidade é considerada um dos principais índices de qualidade do produto final nos processos de usinagem, podendo apresentar variações com as alterações do conjugado eletromagnético no eixo do motor. A proposta deste trabalho é apresentar um preditor de rugosidade superficial de peças baseado exclusivamente na corrente eficaz que alimenta o motor de indução trifásico num processo de torneamento, utilizando redes neurais artificiais para analisar o comportamento da rugosidade em função das condições de usinagem empregadas. Resultados de simulação são apresentados e mostram o desempenho da Rede Neural Artificial (RNA) proposta para diversas situações de operação com desequilíbrios de tensões (entre +10% à -10%) e degraus de torque de carga (25 degraus de 1 em 1 Nm) com erro relativo médio (ERM) de 0,0120%. Os resultados experimentais conforme o método da (RNA) proposta para diversas situações de alimentação da rede elétrica: equilibrado, falta de fase e desequilíbrios de tensões (sobretensão e subtensão), mostram elevada capacidade em aproximar o comportamento da variável de saída (rugosidade Ra) com relação aos valores de entrada (correntes RMS das fases A, B e C). O maior erro relativo médio verificado foi de 0,001754%. / The machine tools are found in various metal and mechanical industries as well as garages. They are operated by three phase induction motors, which are subject to problems related to the applied load on their rotors and disturbances concerning to the quality of electrical supply network. Within the machining process the parameters related to the machine tool, the properties of the workpiece material, geometry and material tool and the process itself, may affect the surface completion of the machined parts. The roughness is considered one of the main indexes of the final product quality in machining processes which may produce changes in the electromagnetic torque on the motor shaft. The purpose of this work is to present a predictor of superficial roughness of parts based on the dynamics of the effective current that feeds the induction motor in the turning process using artificial neural networks to analyze the roughness actions according to the machining conditions employed (speed cutting feed and range of the tool tip). Simulation results are presented and show the performance of the Artificial Neural Network (ANN) proposed several operating situations with imbalances of tensions (between +10% to -10%) and load torque steps (25 steps in 1 1 Nm) with mean relative error (MRE) of 0.0120%. Experimental results depending on the method of (RNA) proposed for various situations power grid: balanced, phase loss and voltage imbalances (overvoltage and undervoltage), show high ability to approximate the behavior of the output variable (roughness Ra) with respect to input values (RMS currents of phases a, B and C). The greatest mean relative error of 0.001754% was observed.

Fundação Araucária, CNPq / O motor de indução trifásico ocupa uma posição de destaque na produção de força eletromotriz e isso o torna vastamente utilizado em aplicações industriais. Consequentemente, também fica submetido às condições de funcionamento e manutenção das máquinas como um todo, bem como das falhas que os mesmos estão sujeitos. Assim, este trabalho propõe um método alternativo aos tradicionais para detecção de falhas em rolamentos de motores de indução trifásicos ligados diretamente a rede elétrica. Os objetivos consistem na utilização de uma abordagem neural capaz de classificar a existência de falha de rolamento com um alto percentual de acerto. Analisando para isto, no domínio do tempo, um semiciclo das tensões de alimentação e das correntes de estator dos motor em estudo. A proposta é validada através de ensaios experimentais num computador e de forma on-line embarcada num DSP. Como conseqüência do trabalho tem-se a criação de um banco de dados de falhas, com mais de mil ensaios envolvendo as principais falhas encontradas em motores de indução trifásicos. Estes ensaios são realizados contemplando as condições de desbalanço de tensão de alimentação e com várias situações de carga mecânica no eixo da máquina. / The three phase induction motor occupies a prominent position in the production of electromotive force and this makes it widely used in industrial applications. Consequently, it is also subjected to the conditions of operation and maintenance of the machines as a whole, as well as faults which they are subject. Thus, this paper proposes an alternative method to traditional in fault detection in bearing of induction motors connected directly to the power grid. The objectives consist in using a neural approach able to classify the existence of bearing fault with a high percentage of correct. Analyzing for this, in the time domain, one half cycle of the voltages and currents of stator the motor in study. The proposal is validated through experimental tests on a computer and monitoring on-line embedded in a DSP. As a result, the work has the creation of a database of failure, with more than a thousand trials involving the main flaws found in three phase induction motors. These tests are performed considering the conditions of voltage supply unbalanced and with several situations of mechanical load on the machine shaft.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná / O motor de indução trifásico do tipo gaiola de esquilo é a principal máquina de conversão eletromecânica devido a sua robustez e facilidade de manutenção, sendo indispensável nos processos produtivos industriais. Por sua grande importância, pesquisas na área de identificação de falhas são realizadas constantemente com o objetivo de diminuir as taxas de manutenções corretivas e permitir uma manutenção programada, diminuindo perdas no processo produtivo, decorrentes de paradas indesejadas. Com esse propósito, o presente trabalho propõe o estudo e desenvolvimento de uma metodologia alternativa que utiliza a Evolução Diferencial para identificação de falhas de curto-circuito de estator em motores de indução conectados diretamente à rede elétrica, por meio dos sinais de tensão e corrente aquisitados no domínio do tempo. O algoritmo de Evolução Diferencial é utilizado para estimar os parâmetros elétricos do motor de indução, a partir do modelo do circuito elétrico equivalente e a identificação da falha ocorre a partir do cálculo da variação percentual da indutância de magnetização estimada com o motor sem falhas. A base de dados utilizada para o trabalho foi obtida por meio de experimentos laboratoriais realizados com dois motores diferentes de 1 CV e um motor de 2 CV, sob condições de variação de conjugado, tensões equilibradas e desequilibradas. / The squirrel cage three-phase induction motor is the main electromechanical conversion machine due to its robustness and easy maintenance, therefore it is indispensable in the industrial production processes. Due to its great importance, surveys related to its fault identification are conducted constantly, in order to reduce the corrective maintenance rates and allow a scheduled maintenance, reducing the losses in the production process, due to unexpected stops. With this purpose, this work proposes the study and development of an alternative methodology based on Differential Evolution algorithm to identify stator short-circuit failures in induction motors connected directly on the electric grid, through its voltage and current signals acquired in the time domain. This Differential Evolution algorithm is used to estimate the induction motor electric parameters based on its equivalent electric circuit model and the fault identification occurs in result of the calculation of the estimated magnetization inductance percentage variation considering a healthy motor. The database used for this work was obtained through laboratory experiments performed with two different types of 1 CV motor and a 2 CV motor under different conditions of torque variation and unbalanced voltages.

O Motor de Indução Trifásico é a máquina elétrica mais utilizada no ambiente industrial. Trata-se de um equipamento que apresenta construção robusta, facilidade de manutenção, baixo custo de aquisição e confiabilidade. Contudo, em ambiente fabril, o mesmo está exposto a esforços térmicos, elétricos e mecânicos indesejáveis, os quais, com o passar do tempo, resultam em uma falha. A presente pesquisa consiste em analisar a falha de curto-circuito de estator, uma das falhas mais recorrentes em motores de indução. Para tanto, são investigadas as peculiaridades refletidas nos sinais de corrente estatórica, a fim de correlacionar as características do sinal à falha em questão. Para tanto, os sinais de corrente são processados por meio das transformadas de Fouriere Wavelet, buscando-se isolar frequências características de uma falha de curto-circuito, as quais possam auxiliar na detecção de uma falha. Posteriormente, a classificação a partir das informações ex traídas é efetuado por meio de Redes Neurais Artificiais, especificamente, a perceptron multicamadas e a Radial Basis Function. / The Three-Phase Induction Motor is the most utilized electrical machine in industrial envi- ronments. It is an equipment that shows robust construction, ease maintenance, low cost and reliability. However, frequently, machines are exposed to thermal, electrical and mecha- nical efforts, which, over time, result in a failure. This work aims to analize the stator short circuit fault, one of the most frequent induction motor failures. Therefor, the peculiarities of the signals that are reflected in stator current are investigated, in order to correlate the signal characteristics to the failure in question. Current signals are processed through the Fourier and Wavelet transform in order to analyse short-circuit specific frequencies. Subse- quently, the classification is performed through two artificial neural networks, the multilayer perceptron and the Radial Basis Function.