Este trabalho propõe a análise de curtos-circuitos trifásicos em geradores de indução duplamente alimentados (DFIG Doubly Fed Induction Generator). Os DFIGs voltam à pauta de hidrogeração devido aos recentes investimentos em usinas hidrelétricas reversíveis com velocidade variáveis empregando DFIGs. Esta configuração de geração, que permite velocidade do eixo diferente da frequência da rede, também é uma opção para usinas hidrelétricas convencionais, trazendo benefícios em termos de eficiência energética, estabilidade e otimização do sistema de potência. As pesquisas envolvendo este tipo de gerador tem se concentrado em aplicações para energia eólica. Os estudos são focados em aspectos de controle e otimização da geração não havendo muitos trabalhos voltados ao estudo de curto-circuito do ponto de vista da máquina principalmente relativos à solução analítica. Os trabalhos voltados a transitórios tratam em geral de afundamentos de tensão na linha de transmissão e metodologias para manter o gerador conectado ao sistema durante estes transitórios. Na área de hidrogeração, na maioria dos casos, os estudos tratam de aspectos de controle, de otimização da operação e de ganhos para o sistema de potência quando do uso do DFIG. Assim, faz-se necessário aumentar a gama de estudos do comportamento desses geradores frente a transientes elétricos, mais especificamente a curtos-circuitos. Para o estudo de transientes do curto-circuito trifásico foi desenvolvida a solução analítica e um modelo baseado no proposto por Krause (KRAUSE, 2002) para simulação em Simulink do Matlab para comparação de resultados. / This work proposes the analysis of three-phase short circuit on doubly fed induction generator, DFIG. This generator is again a subject of study for hydrogeneration as per recent investments on variable-speed Pumped Storage Power Plants. This configuration, which allows asynchronous shaft speed, is also an alternative for conventional hydro power plants, providing improvements on energy efficiency and stability and optimization of power system. Current studies on this subject are focused on wind power applications, covering mostly control and generation optimization aspects while there aren\'t so many studies on short-circuit especially with analytical solution. Electrical transient studies are usually covering voltage dips or sags on transmission line and associated methods to maintain power unit connected to power system during such. The researches on hydro power are also about control, operational optimization and power system improvements when DFIGs are installed. Thus, it is necessary to contribute to research regarding behavior of such generators under electrical transient conditions, more specifically under short circuits. The analytical equation for three-phase short circuit was developed as well the electric model based on the one proposed by Krause (KRAUSE, 2002) for simulations on Simulink of Matlab.

The way our brain works is still an open question, but one thing seems to be clear: biological neural systems are computationally powerful, robust and noisy. Natural nervous system are able to control limbs in different scenarios with high precision. As neural networks in living beings communicate through spikes, modern neuromorphic systems try to mimic them by using spike-based neuron models. This thesis is focused on the advancement of neurorobotics or brain inspired robotic arm controllers based on artificial neural network architectures. The architecture chosen to implement those controllers was the spike neuron version of Reservoir Computing framework, called Liquid State Machines. The main goal is to explore the possibility of using brain inspired neural networks to control a robot by demonstration. Moreover, it aims to achieve systems robust to environmental noise and internal structure destruction presenting a graceful degradation. As the validation, a series of action learning experiments are presented where simulated robotic arms are controlled. The investigation starts with a 2 degrees of freedom arm and moves to the research version of the Rethink Robotics Inc. collaborative humanoid robot Baxter. Moreover, a proof-of- concept experiment is also done using the real Baxter robot. The results show Liquid State Machines, when endowed with an extra external feedback loop, can be also employed to control more complex humanoid robotic arms than a simple planar 2 degrees of freedom one. Additionally, the new parallel architecture presented here was capable to withstand noise and internal destruction better than a simple use of multiple columns also presenting a graceful degradation behaviour.

Support vector machines (SVMs) are a set of supervised learning methods that have recently been applied for structural damage detection due to their ability to form an accurate boundary from a small amount of training data. During training, they require data from the undamaged and damaged structure. The unavailability of data from the damaged structure is a major challenge in such methods due to the irreversibility of damage. Recent methods create data for the damaged structure from finite element models. In this thesis we propose a new method to derive the dataset representing the damage structure from the dataset measured on the undamaged structure without using a detailed structural finite element model. The basic idea is to reduce the values of a copy of the data from the undamaged structure to create the data representing the damaged structure. The performance of the method in the presence of measurement noise, ambient base excitation, wind loading is investigated. We find that SVMs can be used to detect small amounts of damage in the structure in the presence of noise. The ability of the method to detect damage at different locations in a structure and the effect of measurement location on the sensitivity of the method has been investigated. An online structural health monitoring method has also been proposed to use the SVM boundary, trained on data measured from the damaged structure, as an indicator of the structural health condition.

"Many assembly machines for consumer products suffer from the fact that the mechanisms used to impart the necessary assembly motions to the product are orders of magnitude more massive than the product payloads that they carry. This characteristic subsequently limits the operating speed of the machine. If the follower train could be made less massive without sacrificing accuracy and control, it would therefore allow higher speeds. It is well-known that structures that carry only tensile loads can be much less massive than those that must also carry compressive loads. This concept is demonstrated in many structures, such as the suspension bridge. This master’s project set out to investigate the feasibility of a tension-member follower train for a generic cam-driven pick and place mechanism. This system was first dynamically simulated using a computer model, and then tested by constructing a proof of concept prototype. A cam-driven, low-mass tension member (in this case a spring steel strip over pulleys) under spring preload was used to replace the bellcranks and connecting rods typical of a conventional follower train. The system was determined to be feasible and will allow for increased operating speeds at potentially lower costs as an additional benefit."

As the backbone of many computing environments today, it is important that process virtual machines be both performant and robust in mobile, personal desktop, and enterprise applications. This thesis focusses on code generation within these virtual machines, particularly addressing situations where redundant work is being performed. The goal is to exploit information sharing in order to improve the performance and robustness of virtual machines that are accelerated by native code generation. First, the thesis investigates the potential to share generated code between multiple threads in a dynamic binary translator used to perform instruction set simulation. This is done through a code generation design that allows native code to be executed by any simulated core and adding a mechanism to share native code regions between threads. This is shown to improve the average performance of multi-threaded benchmarks by 1.4x when simulating 128 cores on a quad-core host machine. Secondly, the ahead-of-time code generation system used for executing Android applications is improved through the use of profiling. The thesis investigates the potential for profiles produced by individual users of applications to be shared and merged together to produce a generic profile that still provides a lot of benefit for a new user who is then able to skip the expensive profiling phase. These profiles can not only be used for selective compilation to reduce code-size and installation time, but can also be used for focussed optimisation on vital code regions of an application in order to improve overall performance. With selective compilation applied to a set of popular Android applications, code-size can be reduced by 49.9% on average, while installation time can be reduced by 31.8%, with only an average 8.5% increase in the amount of sequential runtime required to execute the collected profiles. The thesis also shows that, among the tested users, the use of a crowd-sourced and merged profile does not significantly affect their estimated performance loss from selective compilation (0.90x-0.92x) in comparison to when they they perform selective compilation with their own unique profile (0.93x). Furthermore, by proposing a new, more powerful code generator for Android’s virtual machine, these same profiles can be used to perform focussed optimisation, which preliminary results show to increase runtime performance across a set of common Android benchmarks by 1.46x-10.83x. Finally, in such a situation where a new code generator is being added to a virtual machine, it is also important to test the code generator for correctness and robustness. The methods of execution of a virtual machine, such as interpreters and code generators, must share a set of semantics about how programs must be executed, and this can be exploited in order to improve testing. This is done through the application of domain-aware binary fuzzing and differential testing within Android’s virtual machine. The thesis highlights a series of actual code generation and verification bugs that were found in Android’s virtual machine using this testing methodology, as well as comparing the proposed approach to other state-of-the-art fuzzing techniques.

Desenvolvimento de uma máquina síncrona trifásica com ímãs de Nd-Fe-B e núcleo do rotor a partir de ferro sinterizado para aplicação em aerogeradores de 7,5 kW, verificando a viabilidade do protótipo. Partindo de um projeto anteriormente desenvolvido, foi realizada alteração no ângulo das chapas do estator em 10º, com o intuito de minimizar o efeito de correntes parasitas, sendo esse um dos fatores que influenciam os resultados. Para avaliação de desempenho, foi utilizada uma bancada de testes composta de analisador de energia, sensor de torque e instrumentos de medição, sendo o acionamento do protótipo realizado através de um motor de indução controlado por um inversor de frequência. Entre os resultados encontrados, foi constatada a presença de harmônicas que impactam sobre os valores obtidos do protótipo. Os testes realizados, de simulação e parâmetros elétricos, indicaram resultados apropriados ao desempenho de uma máquina elétrica trifásica, porém mostram-se necessárias alterações para um melhor desempenho do protótipo. / Development of a three-phase synchronous machine with Nd-Fe-B magnets and rotor core from sintered iron for application in 7.5 kW wind turbines, verifying the feasibility of the prototype. Starting from a previously developed design, a change in the angle of the stator plates was made in 10º, in order to minimize the effect of the parasite currents, being one of the factors that influence the results. For performance evaluation, a test bench composed of energy analyzer, torque sensor and measuring instruments was used, and the drive of the prototype was carried out through an induction motor controlled by a frequency inverter. Among the results found, it was verified the presence of harmonics that impact on the values obtained from the prototype. The tests performed, simulation and electrical parameters, indicated results appropriate to the performance of a three-phase electric machine, however changes are needed for a better performance of the prototype.

Escalonamento de processos é um tipo de problema de otimização combinatória no qual devemos alocar máquinas à tarefas por períodos específicos de tempo. A literatura contém diversos estudos propondo técnicas para resolver modelos de escalonamento de processos como o job shop e o open shop. Esses modelos permitem que os passos no processo produtivo sejam ou completamente ordenados ou sem ordenação alguma. Com o aumento da complexidade das aplicações industriais no encontramos, mais recentemente, diversos trabalhos que propõe problemas de escalonamento de processos mais gerais para modelar mais precisamente os processos produtivos. O mixed shop, group shop e partial shop são exemplos de tais modelos. Nesse trabalho nós propomos uma busca tabu iterada para o partial shop, que é um modelo geral que inclui diversos modelos mais restritivos. Os componentes novos mais importantes da técnica são o gerador de solução inicial, a vizinhança e o limite inferior para a vizinhança. Em experimentos computacionais nós conseguimos demonstrar que a heurística genérica e única é capaz de competir, e as vezes superar, as técnicas de estado de arte desenvolvidas especificamente para partial, open, mixed e group shop. Algumas vezes uma máquina é o gargalo de um processo produtivo, e é replicada. Na literatura o caso das máquinas paralelas foi incluído em diversas extensões de problemas de escalonamento de processos. Nessa tese nós também propomos uma técnica para escalonar as máquinas paralelas, sem incluí-las explicitamente na representação do problema. Nós usamos técnicas gerais para os casos sem máquinas paralelas para produzir uma busca heurística tabu rápida, e estado da arte, para o caso do job shop com máquinas paralelas. / Shop scheduling is a combinatorial optimization type of problem in which we must allocate machines to jobs for specific periods time. A set of constraints defines which schedules are valid, and we must select one that minimizes or maximizes an objective function. In this work we use the makespan, which is the time the last job finishes. The literature contains several studies proposing techniques to solve shop problems such as the job shop and open shop. These problems allow the steps of the production processes to be either fully ordered or not ordered at all. With increasing complexity and size of industrial applications we find, more recently, several works which propose more general shop problems to model the production processes more accurately. The mixed shop, group shop and partial shop are examples of such problems In this work we propose an iterated tabu search for the partial shop, which is a general problem and includes several other more restrictive shop problems. The most important novel components of the solver are the initial solution generator, the neighbourhood, and the lower bound for the neighbourhood. In computational experiments we were able to show that the general partial shop solver is able to compete with, and sometimes surpass, the state-of-the-art solvers developed specifically for the partial, open, mixed and group shops. Sometimes a machine is a bottleneck in the production process, and is replicated. In the literature the parallel machines case has being included in several extensions of shop problems. In this thesis we also propose a technique to schedule the parallel machines heuristically, without including them explicitly in the representation of the problem. We use general techniques for the non-parallel machine cases to produce a fast tabu search heuristic results for the job shop with parallel machines.

Sistemas para assistência de pessoas com sequelas de Acidente Vascular Cerebral (AVC) como, por exemplo, a Disartria apresenta interesse crescente devido ao aumento da parcela da população com esses distúrbios. Este trabalho propõe a aquisição e o processamento dos biosinais de Eletromiografia de Superficie (sEMG) no músculos do rosto ligados ao processo da fala e de Eletroencefalografia (EEG), sincronizados no tempo mediante um arquivo de áudio. Para isso realizaram-se coletas em voluntários saudáveis no Laboratório IEE e com voluntários com Disartria, previamente diagnosticados com AVC, no departamento de Fisioterapia do Hospital de Clínicas de Porto Alegre. O objetivo principal é classificar esses biosinais frente a comandos verbais estabelecidos, mediante o método computacional Support Vector Machine (SVM) para o sinal de sEMG e Naive Bayes (NB) para o sinal de EEG, visando o futuro estudo e classificação do grau de Disartria do paciente. Estes métodos foram comparados com o Linear Discriminant Analysis (LDA), que foi implementado para os sinais de sEMG e EEG. As características extraídas do sinal de sEMG foram: desvio padrão, média aritmética, skewness, kurtosis e RMS; para o sinal de EEG as características extraídas na frequência foram: Mínimo, Máximo, Média e Desvio padrão e Skewness e Kurtosis, no domínio do tempo. Como parte do pré-processamento também foi empregado o filtro espacial Common Spatial Pattern (CSP) de forma a aumentar a atividade discriminativa entre as classes de movimento no sinal de EEG. Foi avaliado através de um Projeto de Experimentos Fatorial, a natureza das coletas, o sujeito, o método computacional, o estado do sujeito e a banda de frequência filtrada para EEG. Os comandos verbais definidos: “Direita”, “Esquerda”, “Para Frente” e “Para Trás”, possibilitaram a identificação de tarefas mentais em sujeitos saudáveis e com Disartria, atingindo-se Accuracy de 77,6% - 80,8%. / Assistive technology for people with Cerebrovascular Accident (CVA) aftereffects, such as Dysarthria, is gaining interest due to the increasing proportion of the population with these disorders. This work proposes the acquisition and processing of Surface Electromyography (sEMG) signal from the speech process face muscles and Electroencephalography (EEG) signal, synchronized in time by an audio file. For that reason assays were carried out with healthy volunteers at IEE Laboratory and with dysarthric volunteers, previously diagnosed with CVA, at the physiotherapy department of the Porto Alegre University Hospital. The main objective is to classify these biosignals in front of verbal commands established, by computational method of Support Vector Machine (SVM) for the sEMG and Naive Bayes (NB) for EEG, regarding the future study and classification of pacient degree of Dysarthria. These methods were compared with Linear Discriminant Analysis (LDA), who was implemented for sEMG and EEG. The extracted features of sEMG signal were: standard deviation, arithmetic mean, skewness, kurtosis and RMS; for EEG signal extracted features in frequency domain were: minimum, maximum, average and standard deviation, skewness and kurtosis, were used for time domain extraction. As part of pre-processing, Common Spatial Pattern (CSP) filter was also employed, in order to increase the discriminating activity between motion classes in the EEG signal. Data were evaluated in a factorial experiment project, with nature of assays, subject, computational method, subject health state and specifically for EEG were evaluated frequency band filtered. Defined verbal commands, "Right", "Left", "Forward" and "Back", allowed the identification of mental tasks in healthy subjects and dysarthric subjects, reaching Accuracy of 77.6% - 80.8%.

Ce travail a pour objectif de développer des techniques de surveillance non-invasives sur des machines électriques tournantes de sorte que leurs mises en place soient aisées en environnement industriel. A cet effet, deux méthodes indépendantes sont décrites dans ce mémoire : un diagnostic de défaillances électriques dans des alternateurs connectés au réseau et une étude exploratoire afin d'évaluer la température interne de machines électriques industrielles.La première méthode repose sur l'analyse de deux grandeurs physiques : le champ magnétique rayonné à l'extérieur de la carcasse et les vibrations de la machine tournante. Des modèles mathématiques ont été développés afin de corréler des phénomènes magnétiques et mécaniques qui interviennent dans trois états de la machine : sain et en deux défauts de courts-circuits au stator et au rotor. Ces résultats ont ensuite été validés expérimentalement en laboratoire ainsi que sur des machines de grande puissance en environnement industriel. Un prototype de diagnostic capable de réaliser un examen de défaillance de courts-circuits sur des machines à fort courant a été proposé.Dans un deuxième temps, la méthode d'estimation de la température s'appuie sur des constats relatifs à la variation des caractéristiques des matériaux qui composent un enroulement lorsque la température augmente. Ainsi, la localisation des fréquences de résonances de l'impédance sont impactées. Ce dernier constat a été vérifié expérimentalement.Ce travail de thèse a permis de vérifier la faisabilité des méthodes de diagnostic et de surveillance en ligne dans des machines tournantes avec un minimum d'intrusivité, ceci dans un environnement industriel. / This work aims to develop non-invasive monitoring techniques on AC rotating machines so that their implementation is easy in an industrial environment. For this purpose, two independent methods are described: a fault diagnosis in alternators connected to the local power gird and an exploratory study to evaluate the internal temperature of AC rotating machines.The first method relies on the analysis of two physical magnitudes: the stray magnetic field radiated outside from the external frame and the vibrations content of machine structure. Mathematical models have been developed in order to correlate magnetic and mechanical phenomena which occur in three different machine states: healthy and in two winding short-circuit faults both in the stator and in the rotor. These results were then validated experimentally in laboratory as well as on large machines in industrial environment. A first diagnostic prototype is presented capable to be implemented in industrial environment in order to detect short-circuit faults in larges alternators.In a second time, a temperature estimation method is proposed based on observations concerning variations in material characteristics of windings as temperature increases. Thus, the localizations of impedance resonant frequencies are impacted, which was verified experimentally as well.This thesis work allowed to verify diagnostic feasibility and on-line monitoring methods in rotating machines in a non-invasive way in industrial environments.

Thesis (M.S.)--Massachusetts Institute of Technology, Alfred P. Sloan School of Management, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY. / Bibliography: leaves 128-129. / by Bruce William Lamar. / M.S.