Orientador: João Zangrandi Filho / Banca: Jose Elias Tomazini / Banca: Carlos Antonio Reis Pereira Baptista / Resumo: Projetar e construir máquinas de pistões axiais são atividades desenvolvidas por poucas empresas no mundo. No Brasil, não se conhece nenhum projeto sobre este tipo de máquina até agora, isto é, um projeto totalmente nacional, apenas são manufaturadas utilizando mão de obra brasileira. Este tipo de máquina tem grande aplicação na área industrial, móbile e aeronáutica. Desenvolver este trabalho é o grande desafio, tendo em vista conquistar tecnologia sobre este produto e, conseqüentemente, livrar-se da dependência tecnológica de outros países. Sendo assim este trabalho procura ir mais longe, pois pretende substituir diretamente os motores comerciais em funcionamento numa etapa muito próxima e subseqüente. Calcular e desenhar uma máquina não são etapas suficientes para que ela funcione e ocupe lugar no mercado. Portanto, um estudo minucioso sobre como cada peça deveria ser usinada foi elaborado, e posteriormente discutido com operadores de máquinas. Esta etapa precisa ser considerada tão importante quanto necessária. Este trabalho além de apresentar um histórico da evolução da hidrostática, também mostra com figuras o funcionamento dos motores de pistões axiais. Um roteiro de cálculos relata como as dimensões da máquina foram determinadas, com a finalidade de se obter o desenho de conjunto. / Abstract: Designing and manufacturing axial piston Swashplate machines are activities that few companies have developed around the world. So far, nothing has been known related to this kind of machine when the focus is on a true national design. In addition, Swashplate machines are fully utilized in industrial, mobile and aeronautical area. Developing this work is the challenge, looking forward to conquer technology in order to manufacture such a product and, consequently, be free from paying royalties to other countries. In this way, the present work goes beyond when one intends to directly substitute those commercial machines in a well next time, it means, just after this work has finished. Calculating and drawing are not sufficient steps to have a machine running. So, a well detailed study was set up in order to know how the parts would be machined and treating and discussing with machine operators was necessary. One should remind that this is a step as important as well necessary. This work presents the history of hydrostatic machines and an explanation relating how the Swashplate motor works. Some calculations are also presented in order to have the assembled view drawing of this machine accomplished. / Mestre

Minimizing cost and optimization of nonlinear problems are important for industries in order to be competitive. The need of optimization strategies provides significant benefits for companies when providing quotes for products. Accurate and easily attained estimates allow for less waste, tighter tolerances, and better productivity. The Nelder-Mead Simplex method with exterior penalty functions was employed to solve optimum machining parameters. Two case studies were presented for optimizing cost and time for a multiple tools scenario. In this study, the optimum machining parameters for milling operations were investigated. Cutting speed and feed rate are considered as the most impactful design variables across each operation. Single tool process and scalable multiple tool milling operations were studied. Various optimization methods were discussed. The Nelder-Mead Simplex method showed to be simple and fast.

Production of micro-scale components is an important emergent field. One underdeveloped area is the production of micro-scale 3D surfaces, which has important applications in micro-optics and fibre optic sensors. One particular application is the production of micro-lenses. With scales of less than 200 ??m these lenses can improve light coupling efficiencies in micro-optic systems. However, current lens production techniques have limitations in accuracy and versatility. Creating these surfaces through mechanical micro-grinding has the potential to improve the precision and variety of profiles that can be produced, thus improving transmission efficiencies and leading to new applications. This work presents a novel micro-grinding method for the production of microscale asymmetric, symmetric and axisymmetric curved components from brittle materials such as glasses. A specialised micro-grinding machine and machining system has been designed, constructed and successfully tested and is presented here. This system is capable of producing complex profiles directly on the tips of optical fibre workpieces. A five degree of freedom centring system is presented that can align and rotate these workpieces about a precision axis, enabling axisymmetric grinding. A machine vision system, utilising a microscope lens system and sub-pixel localisation techniques, is used to provide feedback for the process, image processing techniques are presented which are shown to have a sensing resolution of 300 nm. Using these systems, workpieces are centred to within 500 nm. Tools are mounted on nanometre precise motion stages and motion and infeed are controlled. Tooling configurations with flat and tangential grinding surfaces are presented along with control and path generation algorithms. The capabilities and shortcomings of each are presented along with methods to predict appropriate feed rates based on experimental data. Both asymmetric and axisymmetric flat and curved micro-profiles have been produced on the tips of optical fibres using this system. These are presented and analysed and show that the system, as described, is capable of producing high quality micro-scale components with submicron dimensional accuracy and nanometric surface quality. The advantages of this technique are compared with other processes and discussed. Further development of the system and technique are also considered.

No description available.

<p>Face detection is a preprocessing step for face recognition algorithms. It is the localization of face/faces in an image or image sequence. Once the face(s) are localized, other computer vision algorithms such as face recognition, image compression, camera auto focusing etc are </p><p>applied. Because of the multiple usage areas, there are many research efforts in face processing. Face detection is a challenging computer vision problem because of lighting conditions, a high degree of variability in size, shape, background, color, etc. To build fully </p><p>automated systems, robust and efficient face detection algorithms are required. </p><p> </p><p>Numerous techniques have been developed to detect faces in a single image; in this project we have used a classification-based face detection method using Gabor filter features. We have designed five frequencies corresponding to eight orientations channels for extracting facial features from local images. The feature vector based on Gabor filter is used as the input of the face/non-face classifier, which is a Support Vector Machine (SVM) on a reduced feature </p><p>subspace extracted by using principal component analysis (PCA). </p><p> </p><p>Experimental results show promising performance especially on single face images where 78% accuracy is achieved with 0 false acceptances.</p>

L'objectif de ce travail est d'établir un cadre théorique favorable à la détermination et au contrôle des efforts radiaux dans les moteurs électriques synchrones. Le besoin d'une modélisation susceptible d'être utilisée pour le contrôle en temps réels des efforts écarte naturellement les classiques méthodes numériques de calcul des champs. Aussi, notre volonté de représenter de façon la plus synthétique qui soit l'état magnétique de la machine nous conduit à proposer une modélisation qui intègre de façon intrinsèque un maximum d'informations concernant la machine comme le caractère localisé des courants dans les encoches et les nombreuses symétries liées au bobinage de la machine. Cette modélisation est basée sur une discrétisation du champ d'entrefer qui consiste à considérer le champ constant sous chaque dent statorique.

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There is no abstract available for this dissertation.

Face detection is a preprocessing step for face recognition algorithms. It is the localization of face/faces in an image or image sequence. Once the face(s) are localized, other computer vision algorithms such as face recognition, image compression, camera auto focusing etc are applied. Because of the multiple usage areas, there are many research efforts in face processing. Face detection is a challenging computer vision problem because of lighting conditions, a high degree of variability in size, shape, background, color, etc. To build fully automated systems, robust and efficient face detection algorithms are required. Numerous techniques have been developed to detect faces in a single image; in this project we have used a classification-based face detection method using Gabor filter features. We have designed five frequencies corresponding to eight orientations channels for extracting facial features from local images. The feature vector based on Gabor filter is used as the input of the face/non-face classifier, which is a Support Vector Machine (SVM) on a reduced feature subspace extracted by using principal component analysis (PCA). Experimental results show promising performance especially on single face images where 78% accuracy is achieved with 0 false acceptances.

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.