Dissertações em Engenharia Elétrica (Mestrado) - PPGEE/ITEC
URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/2316
O Mestrado Acadêmico inicou-se em 1986 e pertence ao Programa de Pós-Graduação em Engenharia Elétrica (PPGEE) do Instituto de Tecnologia (ITEC) da Universidade Federal do Pará (UFPA).
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Item Acesso aberto (Open Access) Desenvolvimento e implementação de um sistema de monitoramento de integridade estrutural baseado em rede de sensores(Universidade Federal do Pará, 2016-08-12) NUNES, Flávio Hernan Figueiredo; KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha; http://lattes.cnpq.br/1596629769697284The objective of this dissertation is show the design of a structural integrity monitoring system, employing sensor network. The project of sensor node allows many kind of sensors, such as electrical strain gage, accelerometer, temperature sensor, humidit sensor, also the sensor node is capable of communicating via wireless and wired technology. In contrast to conventional systems that are centralized and employ long cables, the use of a sensor network is a decentralized approach, allowing the sensors are closer to the conditioning circuit, this brings certain bene_ts, such as reducing the length of the sensor cables decreasing the uptake of electromagnetic noise and decrease the impedance of the cable, improving the response signals generated by sensors. They will be presented details of the circuit and the sensor node communication.Item Acesso aberto (Open Access) Estimação da porcentagem de flúor em alumina fluoretada proveniente de uma planta de tratamento de gases por meio de um sensor virtual neural(Universidade Federal do Pará, 2011-06-22) SOUZA, Alan Marcel Fernandes de; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720The industries have been often seeking to reduce operating expenses, as to increase profits and competitiveness. To achieve this goal, it must take into account, among other factors, the design and implementation of new tools that accurately, efficiently and inexpensively allow access to information relevant to process. Soft sensors have been increasingly applied in industry. Since it offers flexibility, it can be adapted to make estimations of any measurement, thus a reducing in operating costs without compromising the measurements, and in some cases even improve the quality of generated information. Since they are completely softwarebased, they are not subjected to physical damage as the real sensors, and are better adaptated to harsh environments with hard access. The success of this king of sensors is due to the use of computational intelligence techniques, which have been widely used in the modeling of several nonlinear complex processes. This work aims to estimate the quality of alumina fluoride from a Gas Treatment Center (GTC), which is the result of gaseous adsorption on alumina virgin, using a soft sensor. The model that emulates the behavior of a alumina quality sensor the plant was created using an artificial intelligence technique known as Artificial Neural Network. The motivations of this work are: perform virtual simulations without compromising the GTC and make accurate decisions based not only on the operator's experience, to diagnose potential problems before they can interfere with the quality of alumina fluoride; maintain the aluminum reduction pot control variables within normal limits, since the production from low quality alumina strongly affects the reaction of breaking the molecule that contains this metal. The benefits this project brings include: increasing the GTC efficiency, producing high quality fluoridated alumina and emitting fewer greenhouse gases into the atmosphere and increasing the pot lifespan.Item Acesso aberto (Open Access) Um método para classificação de imagens de satélite usando Transformada Cosseno Discreta com detecção e remoção de nuvens e sombras(Universidade Federal do Pará, 2011-04-28) SIRAVENHA, Ana Carolina Quintão; PELAES, Evaldo Gonçalves; http://lattes.cnpq.br/0255430734381362This work proposes a supervised algorithm for classi cation of remote sensing images. It is composed by three stages: removal or smoothing of clouds, segmentation and classi cation. The removing clouds method uses homomorphic ltering to deal with obstructions caused by the presence of clouds and the Inpainting method to remove or soften the presence of dense clouds and shadows. The proposed segmentation and classi cation approaches are based on AC power coe cients of the Discrete Cosine Transform (DCT). Classi cation is used in the supervised mode. An image database is used to evaluate the implemented algorithm. This database is composed by 14 images obtained from various sensors, which 12 have some kind of obstruction. The Peak Signal-to-Noise Ratio (PSNR) and Kappa coe cient metrics are used to evaluate the removal or smoothing of clouds and shadows method. In this stage, several high-pass lters were compared to choose the most e cient. The image segmentation task is evaluated by the Edge Border Con dence (EBC) and the classi cation task is evaluated by the measure of the relative entropy and by the mean squared error (MSE). The resulting images are presented to allow the subjective evaluation by visual comparison. The experimental results show the e ciency of the proposed algorithm, especially when compared to the Spring software, distributed by the Instituto Nacional de Pesquisas Espaciais (INPE).Item Acesso aberto (Open Access) Proposta de gerenciamento de dados para monitoramento de saúde estrutural utilizando redes de sensores ópticos FBG(Universidade Federal do Pará, 2014-06-09) SANTOS, Adam Dreyton Ferreira dos; SALES JUNIOR, Claudomiro de Souza de; http://lattes.cnpq.br/4742268936279649; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434Due to their unique characteristics, optical sensor networks have found application in many fields, such as in Civil and Geotechnical Engineering, Aeronautics, Energy and Oil & Gas Industries. Monitoring solutions based on this technology have proven particularly cost effective and can be applied to large scale structures where hundreds of sensors must be deployed for long term measurement of different mechanical and physical parameters. Sensors based on Fiber Bragg gratings (FBGs) are the most common solution used in Structural Health Monitoring (SHM) and the measurements are performed by special instruments known as optical interrogators. Acquisition rates increasingly higher have been possible using the latest optical interrogators, which gives rise to a large volume of data whose manipulation, storage, management and visualization can demand special software applications. This work presents two real-time software applications developed for these purposes: Interrogator Abstraction (InterAB) and Web-based System (WbS). The innovations in this work include the integration, synchronization, independence, security, processing and real-time visualization, and data persistence or storage provided by joint work of developed applications. The results obtained during tests in laboratory and real environment demonstrate the efficiency, robustness and flexibility of these softwares for different types of sensors and optical interrogators, ensuring atomicity, consistency, isolation and durability of data persisted by InterAB and displayed by WbS.