Dans une machine à induction, le diagnostic de défauts par analyse du signal du courant électrique nécessite la connaissance du comportement dynamique de la machine. En plus des sources externes d'excitation, le comportement du moteur est gouverné par un ensemble de phénomènes périodiques liés sa géométrie angulairement périodique et couplés par leur caractère multiphysique. En présence d’un défaut de roulement, les grandeurs mesurables présenteront des composantes à sa fréquence caractéristique combinée aux fréquences caractéristiques du moteur. La compréhension des interactions, en particulier de modulation, passe par la mise en place de modèles numériques qui représentent les manifestations des phénomènes couplés. Ce travail de thèse propose donc un modèle électro-magnéto-mécanique d'une machine à induction à cage d'écureuil couplé à un modèle de palier à roulement à billes dans un cadre original d'écriture appelé "Approches Angulaires". En conservant dans la modélisation la relation "Angle-Temps" il est possible d'étendre aisèment la modélisation aux conditions de fonctionnement non-stationnaires et d'introduire un couplage fort entre les modèles mécanique et électromagnétique. Ainsi, on montre que la vitesse angulaire instantanée est la grandeur qui assure la transmission du défaut mécanique localisé aux grandeurs électriques. Le modèle proposé offre ainsi un décryptage des phénomènes de modulation présents sur la voie de transfert et décrits par les couplages de comportements dynamiques cycliques (réseau de perméances, chargement des éléments roulants,...) et/ou périodiques (résonances de structure, résonance électriques, ...). Ces travaux ouvrent la voie à une meilleure compréhension du comportement couplé multiphysique d'une machine électrique pour mieux spécifier les outils de surveillance à mettre en œuvre. Les futurs développements peuvent maintenant s'orienter ver une complexification des modèles ou l'exploitation de comportements dynamiques fins en régime non-stationnaire. / In an induction machine, the diagnosis of defects by analysis of the electrical current signal requires knowledge of the dynamic behavior of the machine. In addition to external excitation sources, the behavior of the motor is governed by a set of periodic phenomena related to its angularly periodic geometry and coupled by their multiphysical character. In the presence of a bearing defect, measurable quantities will have components at its characteristic frequency combined with the characteristic frequencies of the engine. The understanding of interactions, in particular modulation, requires the implementation of numerical models that represent the manifestations of coupled phenomena. This thesis work proposes an electro-magneto-mechanical model of a squirrel-cage induction machine coupled to a rolling bearing model in an original writing frame called "Angular Approaches". By keeping the "Angle-Time" relation in modeling, it is possible to easily extend the modeling to non-stationary operating conditions and to introduce a strong coupling between the mechanical and electromagnetic models. Thus, it is shown that the instantaneous angular speed is the quantity which ensures the transmission of the localized mechanical defect to the electrical quantities. The proposed model thus offers a decryption of the modulation phenomena present on the transfer path and described by the couplings of cyclic dynamic behaviors (permeance network, loading of the rolling elements, etc.) and / or periodic (structural resonances, electrical resonance, etc.). This work opens the way for a better understanding of the multiphysical coupled behaviors of an electrical machine to better specify the monitoring tools to be used. Further developments can now be directed to a complexity of models or to the exploitation of fine dynamic behaviors in a non-steady operating conditions.

Le principe de la maintenance conditionnelle consiste à évaluer en permanence l’intégrité des machines industrielles, à partir des mesures et de traitements du signal appropriés, afin d’intervenir uniquement au moment le plus opportun. Dans ce contexte, l’objectif de cette thèse est de développer une technique de détection, aussi précoce que possible, de l’amorce de dégradation lente d’une structure vibrante, telle que les fissures de fatigue, pour éviter toute défaillance inattendue des machines. Notre approche se base sur les données mesurées à l’aide de deux moyens expérimentaux mis en œuvre au laboratoire. L’étude a démarré avec une poutre encastrée-libre sollicitée en flexion et s’est poursuivie sur un banc d’essais plus représentatif de la problématique industrielle. Dans les deux cas, l'endommagement de la structure a été naturel et progressif, depuis un état réputé sain jusqu’à l’apparition de la fissure. Le comportement dynamique a été suivi à l’aide d’accéléromètres. Ainsi, afin d’identifier des indicateurs sensibles au phénomène d’endommagement, plusieurs pistes ont été envisagées. Nous avons examiné les indicateurs scalaires descriptifs des signaux mesurés, qui sont les moments statistiques, fréquences moyennes et médianes. Ces indicateurs sont utilisés avec succès pour la détection de défaut sur les éléments de machines tournantes, mais ils se sont montrés peu sensibles pour détecter des défaillances structurales. Les fréquences propres identifiées automatiquement à partir des signaux temporels acquis sous chargements opérationnels ont également été étudiées. Ensuite, nous nous sommes orientés vers une approche plus globale pour surveiller les changements spectraux causés par l’apparition d’un défaut sur une structure. En se basant sur les matrices spectrales, fonctions et matrices de transmissibilité, des indicateurs multi-capteurs ont été développés et testés pour les deux cas d’étude. Une Analyse en Composantes Principales a permis d’identifier, entre les indicateurs analysés, ceux qui sont les plus pertinents pour la surveillance de l’intégrité des structures. / The principle of the conditional maintenance consists in continuously evaluating the health state of industrial machines, from measurements and appropriate signal processing, in order to carry out maintenance operations only at the most convenient time. In this context, the objective of this PhD thesis is to implement a technique for detecting as soon as possible slow damage initiation in vibrating structures, such as the fatigue cracks, to avoid the unexpected failure of machines. We have conducted empirical investigations with two experimental setups built in the laboratory. The study started with a cantilever beam subjected to dynamic bending loads, and continued on a test-bench more representative of the industrial problem. In both cases, the structure was naturally and progressively damaged, from a state considered to be healthy, until the crack occurs. Its dynamical behavior was monitored using accelerometers. Therefore, in order to identify damage-sensitive features, many leads were investigated. We have examined the features describing the measured signals waveform, which are statistical moments, mean frequencies and median frequencies. They are successfully used for fault detection on rotating machinery, but they did not demonstrate enough sensitiveness to detect structural damage. The natural frequencies automatically identified from the measured time signals under operational loads have also been studied. Thus, we oriented our work towards a more global approach to monitor the spectral changes caused by the appearance of damage on a structure. Based on the spectral matrices and transmissibility quantities, multi-sensor indicators were developed and tested for the two cases of study. A Principal Component Analysis allowed us to identify, between the surveyed features, the ones most relevant for monitoring the integrity of structures.

Neste trabalho desenvolve-se uma análise sobre o estado da arte e tendências para projeto de geradores elétricos em turbinas eólicas offshore. A conjunção dos requerimentos de alta confiabilidade e potência, criam condições adequadas para a aplicação de máquina elétricas multifásicas nesse setor. Desta forma, optou-se por estudar as características e condições de projeto de máquinas elétricas multifásicas, simétricas ou assimétricas. Com esta finalidade, os métodos analíticos de projeto de máquinas elétricas trifásicas são revisitados e estendidos, quando necessário, para diferentes configurações multifásicas. O foco do trabalho, consiste em desenvolver e explorar temas de projeto de geradores elétricos multifásicos, síncronos de imãs permanentes, com enrolamentos distribuídos de dupla camada. Para estudo de caso, realiza-se a comparação entre o projeto de quatro topologias diferentes. Nomeadamente, compara-se o projeto de geradores de três, seis, nove e dezoito fases para turbinas eólicas offshore de 10 MW. A configuração com gerador de nove fases apresenta os melhores resultados, com densidade de torque 10,96% superior à densidade de torque desenvolvida pela máquina trifásica analisada. Por fim, a metodologia analítica desenvolvida para o projeto de máquinas elétricas multifásicas é verificada usando o método de elementos finitos bidimensional, para o gerador síncrono de imãs permanentes de nove fases. / The state of the art and future trends for offshore wind turbines were reviewed. Due to its fault-tolerant characteristic, multiphase electrical generators were identified as strong candidates to meet the power and resilience targets of the offshore wind sector. In this work, the design aspects of three-phase electrical machines are reviewed and extended to different multiphase configurations. The main focus of the work is to develop an analytical design methodology for multiphase, symmetrical and asymmetrical, synchronous generators with double-layer distributed windings. As a case study, the project of a three-phase, six-phase, nine-phase and eighteen-phase permanent magnet synchronous generators were compared for a 10MW offshore wind turbine. The best results were found for the nine-phase topology, with a torque density 10.96% higher than the torque density of the analysed three-phase machine. The developed design methodology was validated with a finite element analysis of the ninephase permanent magnet generator.

Neste trabalho desenvolve-se uma análise sobre o estado da arte e tendências para projeto de geradores elétricos em turbinas eólicas offshore. A conjunção dos requerimentos de alta confiabilidade e potência, criam condições adequadas para a aplicação de máquina elétricas multifásicas nesse setor. Desta forma, optou-se por estudar as características e condições de projeto de máquinas elétricas multifásicas, simétricas ou assimétricas. Com esta finalidade, os métodos analíticos de projeto de máquinas elétricas trifásicas são revisitados e estendidos, quando necessário, para diferentes configurações multifásicas. O foco do trabalho, consiste em desenvolver e explorar temas de projeto de geradores elétricos multifásicos, síncronos de imãs permanentes, com enrolamentos distribuídos de dupla camada. Para estudo de caso, realiza-se a comparação entre o projeto de quatro topologias diferentes. Nomeadamente, compara-se o projeto de geradores de três, seis, nove e dezoito fases para turbinas eólicas offshore de 10 MW. A configuração com gerador de nove fases apresenta os melhores resultados, com densidade de torque 10,96% superior à densidade de torque desenvolvida pela máquina trifásica analisada. Por fim, a metodologia analítica desenvolvida para o projeto de máquinas elétricas multifásicas é verificada usando o método de elementos finitos bidimensional, para o gerador síncrono de imãs permanentes de nove fases. / The state of the art and future trends for offshore wind turbines were reviewed. Due to its fault-tolerant characteristic, multiphase electrical generators were identified as strong candidates to meet the power and resilience targets of the offshore wind sector. In this work, the design aspects of three-phase electrical machines are reviewed and extended to different multiphase configurations. The main focus of the work is to develop an analytical design methodology for multiphase, symmetrical and asymmetrical, synchronous generators with double-layer distributed windings. As a case study, the project of a three-phase, six-phase, nine-phase and eighteen-phase permanent magnet synchronous generators were compared for a 10MW offshore wind turbine. The best results were found for the nine-phase topology, with a torque density 10.96% higher than the torque density of the analysed three-phase machine. The developed design methodology was validated with a finite element analysis of the ninephase permanent magnet generator.

<p dir="ltr">There is a growing demand for lower-cost, lighter-weight, and more compact electric ma-<br>chines used for vehicle propulsion. In this research, a dual-rotor inert-core machine (ICM) is<br>considered to meet this demand. In the ICM, permanent-magnet-based Halbach arrays are<br>placed on inner and outer rotating structures. This enables one to eliminate magnetic steels<br>used in the stator and rotor of traditional electric machinery. In addition, a stator structure<br>that leverages a thermal plastic is proposed that facilitates straightforward active cooling<br>of phase windings, which greatly increases current density. To support the multi-objective<br>design of the ICM, a multi-physics toolbox has been developed. Within the toolbox, electro-<br>magnetic performance is predicted using a method-of-moments-based field solver. Thermal<br>performance is assessed using a thermal equivalent circuit that includes conductive heat<br>transfer from stator windings to the surrounding environment as well as convective heat<br>transfer to moving fluids. The structural integrity of the stator is assessed using analytical<br>expressions to predict stress from material properties, geometry, and applied external forces.<br>Calculated loss of proposed designs includes those of the stator windings as well as those<br>required for active cooling. Several optimization studies have been conducted to evaluate the<br>performance of the ICM under an expected electric vehicle driving cycle. From the studies,<br>Pareto-optimal fronts are obtained and used to explore the impact of alternative cooling<br>strategies on volumetric power density.</p>

Ce mémoire présente différents outils et approches pour dériver les lois de commande de la machine asynchrone à double alimentation en régime permanent sur toute la plage de vitesse, en mode moteur et générateur. Le but est de dériver les lois de commande de la MADA en termes de tension et angle rotorique (puissance active et réactive) pour différentes stratégies de commande. Le premier outil a été évoqué dans un processus d’optimisation non-linéaire. Puis une approche analytique basée sur le circuit équivalent de la MADA a été étudiée dans le but de contourner les problèmes liés au processus d’optimisation non-linéaire. Un autre outil de simulation développé dans l’environnement MATLAB/Simulink a été mis au point afin de valider les résultats. / This thesis presents various tools and approaches for the determination of the steady-state control laws of the doubly fed induction machine on the whole operation speed range operating as motor and generator. The purpose is to derive the control laws in terms of rotor voltage and control angle voltage (real and reactive power) for different control strategies. A first tool for extracting control laws based on a nonlinear optimization process has been developed. Then an analytical approach based on the equivalent circuit of the DFIM has been used in order to avoid problems related to the process of nonlinear optimization. Another simulation tool developed in the Matlab/Simulink was aimed to validate the results.

Call number: LD2668 .T4 1965 P231 / Master of Science

No description available.

Context: Recent trends show that there is a tremendous shift from IT companies following traditional methods by hosting their applications/systems in self-managed on premise data centers to using the so-called cloud data centers. Cloud computing has received immense popularity due to its architecture and the ease of usage. Due to this increase in demand and shift in practices, there has been a tremendous increase in number of data centers over a period, resulting in increase of energy consumption. In this thesis work, a research is carried out on optimizing the energy consumption of a typical cloud data center. OpenStack cloud computing software is chosen as the platform in this research. We have used live migration as a key aspect in this research. Objectives: In this research, our objectives are as follows: Design an OpenStack testbed to implement the migration of virtual machines. To estimate the energy consumption of the data center. To design a heuristic algorithm to evaluate the performance metrics and to optimize the overall energy consumption. Methods: We have used PowerAPI, a software tool to estimate the energy consumption of hosts as well as virtual machines. A heuristic algorithm is designed and implemented in an instrumental OpenStack testbed to optimize the energy consumption. Server consolidation and load balancing of virtual machines methodologies are used in the heuristic algorithm design. Our research is carried out against the functionality of Nova scheduler of OpenStack. Results: Results section describes the values of performance metrics yielded by carrying out the experiment. The obtained results showed that energy can be optimized significantly by modifying the way OpenStack nova scheduler can work. The experiment is carried out on vanilla OpenStack and OpenStack with the heuristic algorithm in place, In the second case, the nova scheduler algorithms are not used but the heuristic algorithm is used instead. The CPU utilization and CPU load were noticed to be higher than the metrics observed in case of OpenStack with nova scheduler. Energy consumption is observed to be lesser than the consumption in OpenStack design with nova scheduler. Conclusions: The research tells that energy consumption can be optimized significantly using desired algorithms without compromising the service quality it offers. However, the design impacts on CPU slightly as the metrics are observed to be higher when compared to that in case of OpenStack with nova scheduler. Although it won’t have noticeable impact on the system.

This dissertation focuses on the novel learning strategy based on geometric support vector machines to address the difficulties of processing immense data set. Support vector machines find the hyper-plane that maximizes the margin between two classes, and the decision boundary is represented with a few training samples it becomes a favorable choice for incremental learning. The dissertation presents a novel method Geometric Incremental Support Vector Machines (GISVMs) to address both efficiency and accuracy issues in handling massive data sets. In GISVM, skin of convex hulls is defined and an efficient method is designed to find the best skin approximation given available examples. The set of extreme points are found by recursively searching along the direction defined by a pair of known extreme points. By identifying the skin of the convex hulls, the incremental learning will only employ a much smaller number of samples with comparable or even better accuracy. When additional samples are provided, they will be used together with the skin of the convex hull constructed from previous dataset. This results in a small number of instances used in incremental steps of the training process. Based on the experimental results with synthetic data sets, public benchmark data sets from UCI and endoscopy videos, it is evident that the GISVM achieved satisfactory classifiers that closely model the underlying data distribution. GISVM improves the performance in sensitivity in the incremental steps, significantly reduced the demand for memory space, and demonstrates the ability of recovery from temporary performance degradation.