Teses em Engenharia Elétrica (Doutorado) - PPGEE/ITEC
URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/2317
O Doutorado Acadêmico inicio-se em 1998 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) Análise de desempenho de algoritmos para classificação de sequências representando faltas do tipo curto-circuito em linhas de transmissão de energia elétrica(Universidade Federal do Pará, 2019-12-05) FREIRE, Jean Carlos Arouche; MORAIS, Jefferson Magalhães de; http://lattes.cnpq.br/5219735119295290; CASTRO, Adriana Rosa Garcez; http://lattes.cnpq.br/5273686389382860Maintaining power quality in electrical power systems depends on addressing the major disturbances that may arise in their generation, transmission and distribution. Within this context, many studies have been developed aiming to detect and classify short circuit faults in electrical systems through the analysis of the electrical signal behavior. Transmission line fault classification systems can be divided into two types: online and post fault classification systems. In the post-missing scenario the signal sequences to be evaluated for classification have variable length (duration). In sequence classification it is possible to use conventional classifiers such as Artificial Neural Networks, Support Vector Machine, K-nearest neighboors and Random forest. In these cases, the classification process usually requires a sequence preprocessing or a front end stage that converts the raw data into sensitive parameters to feed the classifier, which may increase the computational cost of the classification system. An alternative to this problem is the FBSC-FrameBased-Sequence Classification (FBSC) architecture. The problem with FBSC architecture is that it has many degrees of freedom in designing the model (front end plus classifier) and it should be evaluated using a complete dataset and rigorous methodology to avoid biased conclusions. Considering the importance of using efficient short-circuit fault classification methodologies and mainly with low computational cost, this paper presents the results of the KNN-DTW (K-Nearest Neighbor) algorithm analysis study associated with Dynamic similarity measurement. Time Warping (DTW) and HMM (Hidden Markov Model) algorithm for fault classification task. These two techniques allow the direct use of data without the need for front ends for signal pre-processing, as well as being able to handle multivariate and variable time series, such as signal sequences for the post-miss case. To develop the two proposed systems for classification, simulated data of short-circuit faults from the UFPAFaults public database were used. To compare results with methodologies already presented in the literature for the problem, the FBSC architecture was also evaluated for the same database. In the case of FBSC architecture, different front ends and classifiers were used. The comparative assessment was performed from the measurement of error rate, computational cost and statistical tests. The results showed that the HMM-based classifier was more suitable for the problem of classification of short circuits on transmission lines.Item Acesso aberto (Open Access) Desenvolvimento de metodologias para a localização de intruso em ambientes indoor(Universidade Federal do Pará, 2010-03-30) ARAÚJO, Josivaldo de Souza; SOUZA SOBRINHO, Carlos Leônidas da Silva; http://lattes.cnpq.br/1450994881555781The present study aims to propose methodologies in order to detect the presence and locate of an intruder in indoor environments 2-D and 3-D which uses a cooperative system of antennas with the latter. This system is based on multi-static radars in both cases. For a high resolution, the radar operates with pulses of Ultra Wide Band which have spectral range up to 1GHz for the 2-D environments and pulses of Wide Band of 200MHz and 500 MHz for the 3-D environments. For the two-dimensional environments, the estimated location is made by the Particle Swarm Optimization (PSO) technique, Newton’s method with Gaussian elimination and least squares method with Gaussian elimination. For the three-dimensional environment, it was developed a methodology based on vectors which estimates a possible region of intruder location. For the simulation of electromagnetic waves, it uses the numerical method Finite Difference Time Domain (FDTD) associated with the absorption technique UPML (Uniaxial Perfectly Matched Layer) which is used to truncate the domain of analysis simulating the spread upwards. For the analysis of 2-D environment, it was developed ACOR-UWB-2-D and in order to build environments in 3-D, it was used LANE SAGS software.