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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Agora exibindo 1 - 11 de 11

Acesso aberto (Open Access)
Abordagem Inteligente com Combinação de Características Estruturais para Detecção de Novas Famílias de Ransomware
(Universidade Federal do Pará, 2024-03-22) MOREIRA, Caio Carvalho; SALES JUNIOR, Claudomiro de Souza de; País de Nacionalidade Brasi
Ransomware is a malicious software that aims to encrypt user files and demand a ransom to unlock them. It is a cyber threat that can cause significant financial damage, as well as compromise privacy and data integrity. Although signature-based detection scanners commonly combat this threat, they fail to identify unknown ransomware families (variants). One method to detect new threats without the need to execute them is static analysis, which inspects the code and structure of the software, along with classification through intelligent approaches. The Detection of New Ransomware Families (DNFR) can be evaluated in a realistic and challenging scenario by categorizing and isolating families for training and testing. Hence, this thesis aims to develop an effective static analysis model for DNFR, which can be applied in Windows systems as an additional security layer to check executable files upon receipt or before execution. Early ransomware detection is essential to reduce the likelihood of a successful attack. The proposed approach comprehensively analyzes executable binaries, extracting and combining various structural features, and distinguishes them between ransomware or benign software employing a soft voting model comprising three machine learning techniques: Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGB). Results for DNFR demonstrated an average accuracy of 97.53%, precision of 96.36%, recall of 97.52%, and F-measure of 96.41%. Additionally, scanning and predicting individual samples took an average of 0.37 seconds. This performance indicates success in quickly identifying unknown ransomware variants and adapting the model to the constantly evolving landscape, suggesting its applicability in antivirus protection systems, even on resource-limited devices. Therefore, the method offers significant advantages and can assist developers of ransomware detection systems in creating more resilient, reliable, and fast-response solutions.
Acesso aberto (Open Access)
Análise de sistemas não-lineares e síntese de operadores inversos por séries de volterra diagonais
(Universidade Federal do Pará, 2019-08-22) TEIXEIRA, Raphael Barros; BAYMA, Rafael Suzuki; http://lattes.cnpq.br/6240525080111166; COSTA JÚNIOR, Carlos Tavares da; http://lattes.cnpq.br/6328549183075122
This work proposes innovative strategies for the analysis of nonlinear systems and the synthesis of inverse operators using the Volterra diagonal series. By expressing the output explicitly from the input, the Volterra series enable nonlinear analysis in the frequency domain. However, the multidimensional nature of the model confers several difficulties to its systematic use. This work takes a new look at the so-called Volterra series in diagonal coordinates, in which Volterra operators are expressed as a set of linear and one-dimensional filters that process nonlinear polynomial terms of the input. The proposition of the rational form for these filters leads to exact and compact Volterra models, which exhibit a direct connection with modern nonlinear formalisms, notably the Wiener and Hammerstein block structured models, and the non-linear, autoregressive polynomial models with exogenous input (NARX). In particular, it is proposed a strategy to obtain diagonal Volterra models from the polynomial NARX. The strategy is called derivative method, because it depends only on the established results of the differential calculus. This is important because a NARX model can fit relatively well to experimental data to describe a wide variety of practical systems. A subsequent study through the Volterra series comes as an additional natural step of analysis. This result also opens up possibilities for non-linear synthesis. A problem that has received increasing attention in systems engineering is that of the synthesis of inverse nonlinear operators, through which it tries to reverse distortions generated by the underlying system, preserving the integrity of the information of interest. In this case we propose a strategy of synthesis of Volterra inverse diagonal operators for particular classes of nonlinear polynomial models. It is a numerical approach where the synthesis is driven by an optimization problem that is inspired by the classic inverse p-order operator. Keywords: Non-linear systems, Volterra series diagonals, systems identification, nonlinear analysis, dynamic inversion
Acesso aberto (Open Access)
Compressão de sinais em sistemas de rádio sobre fibra digital para redes fronthaul
(Universidade Federal do Pará, 2019-07-23) MATE, Dércio Manuel; TEIXEIRA, António Luis de Jesus; OLIVEIRA, Rosinei de Sousa; http://lattes.cnpq.br/3853897074036715; COSTA, João Crisóstomo Weyl Albuquerque; http://lattes.cnpq.br/9622051867672434
The introduction of technologies such as Carrier Aggregation (CA), Massive Multiple Input Multiple Output (MIMO) and Coordinated Multipoint (CoMP), aiming to improve the performance of LTE and LTE-A systems, increases the challenge for deploying Mobile Fronthaul due to the network capacity limitation to support higher transmission rates. An approach to deal with Frontahul’s capacity limitation is data compression. Several techniques have been developed for signal compression in fronthaul, and most of these techniques compress the signal transmitted in baseband. In this work, a compression technique is developed for specific scenarios of Digital Radio-over-Fiber systems, transmitting the signal in intermediate frequency (IF). This technique uses the radio channel state information (CSI) to control signal compression in the fronthaul. The simulation results with the developed technique demonstrate its ability to reduce the data transmitted onthe network by 45.05%. In addition, this technique allows the transmission of 64 QAM modulated signals using a lower quantizer resolution, e.g., 4 bits per sample, maintaining the EVM below 3GPP recommended threshold (8%). Finally, the performance of the fronthaul network is evaluated experimentally in an optical link of 20-km, considering scenarios with and without signal compression.
Acesso aberto (Open Access)
Contribuição do controle secundário de tensão aplicado em um parque eólico composto de aerogeradores dfig à estabilidade de tensão de longo-prazo
(Universidade Federal do Pará, 2019-08-30) MATOS, Kayt Nazaré do Vale; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720; VIEIRA, João Paulo Abreu; http://lattes.cnpq.br/8188999223769913
This thesis investigates the use of secondary voltage control (SVC) in a wind park based on doubly fed induction generator (DFIG) and its effect on long-term voltage stability. The wind park consists of several wind turbines is modeled as an DFIG equivalent model. Initially, the performance of the SVC applied to wind park is compared with the case when only the primary voltage control (PVC) is adopted. A detailed analysis is conducted with time-domain simulations, considering high and low wind speed regimes, control variable limits of wind generators, static and dynamic loads, as well as dynamic models of overexcitation limiter (OEL) and load tap changing (LTC) transformer. Based on the results, the use of secondary voltage control in a DFIG-based wind park can postpone long-term voltage collapse of power system. Further, an adverse situation was observed showing that SVC can lead the grid-side converter (GSC) of DFIG to absorb reactive power from the electric grid and lose the capability of injecting reactive power in the grid. Thus, two novel auxiliary control strategies inserted in the GSC control loop are presented to prevent reactive reverse flow in the GSC, as well as forcing the provision of reactive power to the system via the GSC. The results indicate the effectiveness of the auxiliary control strategies in postponing the voltage collapse and increase the voltage stability margin of the system.
Acesso aberto (Open Access)
Estimação das parcelas de contribuição de cargas não lineares na distorção harmônica de tensão de um barramento de interesse do sistema elétrico de potência utilizando rede neural artificial
(Universidade Federal do Pará, 2019-09-06) MANITO, Allan Rodrigo Arrifano; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
This work presents a methodology to estimate the non-linear loads contribution on voltage harmonic distortion at a bus of interest in the electric power system. The estimation process is carried out through the development of a model based on artificial neural networks (ANN) added to a sensitivity analysis in neural network input. The ANN model input is constituted by the non-linear loads harmonic currents considered in the studied system, and the ANN output corresponds to the harmonic voltage values in the bus under study, for the same harmonic frequency. The study is carried out for each harmonic order individually and the data required for the construction of the model as well as for the results validation have been obtained from synchronized measurement campaigns and by computational simulation, using harmonic load flow studies. Comparisons between reference results through computational simulation with the results obtained by neural model are carried out and it is observed that the developed methodology is able to classify correctly the impact of non-linear loads in the voltage distortion at a bus of interest of the electric system. Additionally, the effectiveness of the methodology is tested in two real systems in order to verify the good performance of this methodology considering real data obtained during measurement campaigns.
Acesso aberto (Open Access)
Identificação em malha fechada para controle tolerante a falta passivo aplicado a um sistema industrial de bombeamento hidráulico
(Universidade Federal do Pará, 2019-08-30) ROCHA, Erick Melo; BARRA JUNIOR, Walter; http://lattes.cnpq.br/0492699174212608
Fluid pumping systems are part of many industrial applications. From the traditional water supply, to the cooling systems of thermonuclear power plants and the complex aircraft maneuvering system, using pneumatic actuators, we find examples of application of these systems. As any physical system, fluid pumping systems may also be subject to anomalous behaviors or failures that can lead to malfunction or even loss of stability of an entire process. Such faults may cause permanent damage due to the effect of undesirable phenomena such as cavitation and water hammer, for example. Thereby, this work proposes the development of a Fault Tolerant Control System (FTCS) aiming at to mitigate the undesirable effects of pressure oscillation and speed variation that may affect this type of system. This research assumes that, for economic and safety reasons, industrial systems operate by default in closed-loop to ensure stability and desired performance. Therefore, a methodology is introduced to identify the open-loop transfer function of industrial plants, based on data obtained by signal measurement, of the industrial process operating in closed-loop, denominated Two-Stage Method. The identified model is used to design a controller that meets the performance criteria defined by the FTCS instead of the traditional control system, designed for a specific operating point regardless of the fault acting in the system. For experimental evaluation, an industrial fluid pumping bench was used, developed at the Automation and Control Laboratory of Federal University of Pará (UFPA). A passive FTCS was designed using robust control technique based on parametric uncertainties. For that end, it was used a set of uncertain models, obtained by parametric identification, considering a desired operating range for the test plant, with the system operating under both normal and fault conditions. Performance indices were calculated in order to quantitatively evaluate the performance of the FTCS monitored system, with the results obtained for the system operating without the FTCS (using classical controller). The results show the good performance of the proposed methodology.
Acesso aberto (Open Access)
Metodologia integrada utilizando sensoriamento remoto em redes neurais artificiais na quantificação do potencial de biomassa florestal na Amazônia
(Universidade Federal do Pará, 2008-04-08) ALMEIDA, Arthur da Costa; ROCHA, Brigida Ramati Pereira da; http://lattes.cnpq.br/9943372249006341
Pattern recognition and pattern classification in digital images is a very important skill, today. With them, it is possible to recognize and identify target objects in those images. This work proposes an integrated methodology for pattern recognition related to biomass in the Amazon tropical rainforest to extract information about bioenergetics potential for electric energy production for use with isolated Amazonian communities. To achieve this aim, information gathered about forest inventory was mixed with pattern classification and recognition in medium resolution satellite imagery such as those from LANDSAT and CBERS. The approach used in this work comes from the computational intelligence area, using artificial neural networks equipped with radial basis functions and Kohonen´s self organizing maps. The results serve as input to a geographical information system application which creates and manages a geographical database for energetic planning with renewable energy resources applicable to isolated Amazonian communities.
Acesso aberto (Open Access)
Uma metodologia temporal para avaliação do desempenho de códigos concatenados em sistemas OFDM para transmissão de vídeo 4K-UHD
(Universidade Federal do Pará, 2024-08-16) COSTA, Thiago de Araújo; CASTRO, Bruno Souza Lyra; http://lattes.cnpq.br/1897829604434609; BARROS, Fabrício José Brito; http://lattes.cnpq.br/9758585938727609
The communication channel is a critical part of the process of information degradation. In the 4K ultra-resolution video transmission domain, the communication channel is a crucial part where information degradation occurs, inevitably leading to errors during reception. To enhance the transmission process in terms of fidelity, advanced technologies such as digital video broadcasting terrestrial (DVB-T) and its evolutionary successor, digital video broadcasting terrestrial second generation (DVB-T2), are utilized to mitigate the effects of data transmission errors. In the transition, a notable change is the replacement of the concatenated channel coding pairs. Within this scenario, this research presents an innovative methodology for the temporal analysis of 4K ultraresolution video quality under the influence of additive white Gaussian noise (AWGN) and Rayleigh channels. This analytical endeavor is facilitated through the application of concatenated coding schemes, specifically, the Bose-Chaudhuri-Hocquenghem concatenated low-density parity check (BCH-LDPC) and Reed-Solomon concatenated convolutional (RS-CONV) coders. A more comprehensive understanding of video quality can be attained by considering its temporal variations, a crucial aspect of the ongoing evolution of technological paradigms. In this study, the Structural Similarity Index (SSIM) serves as the main metric for quality assessment during simulations. Furthermore, the simulated Peak Signal-to-Noise Ratio (PSNR) values validate these findings, exhibiting consistent alignment with the SSIM-based evaluations. Additionally, the performance of the BCH-LDPC significantly outperforms that of RSCONV under the 64-QAM modulation scheme, yielding superior video quality levels that approximate or surpass those achieved by RS-CONV under QPSK (Quadrature Phase Shift Keying) modulation, leading to an increase in spectral efficiency. This enhancement is evidenced by SSIM gains exceeding 78% on average. The computation of average gains between distinct technologies in video quality analysis furnishes a robust and comprehensive evaluation framework, empowering stakeholders to make informed decisions within this domain.
Acesso aberto (Open Access)
Otimização da detecção de formas de onda de campos eletromagnéticos emitidos por descargas atmosféricas
(Universidade Federal do Pará, 2018-01-23) LEAL, Adônis Ferreira Raiol; RAKOV, Vladimir; ROCHA, Brigida Ramati Pereira da; http://lattes.cnpq.br/9943372249006341
This work aims the application of optimization techniques to detect and record lightning electromagnetic waveforms. As a result of the optimization techniques developed on this Thesis, it is presented the “Lightning Detection and Waveform Storage System - (LDWSS)”. The main optimized points were: cost of the device; improvements of its detection dynamic range; development of a mobile device; possibility to detect in a multi-band way; and calibration in order to infer peak currents from remote measurements of lightning electric fields. The developed system was validated through comparison of a return stroke data in lightning triggered using the rocket-and-wire technique at the International Center for Lightning Research and Testing - ICLRT, of National Lightning Detection Network – NLDN data, and data from the Lightning Observatory in Gainesville - LOG. The main usage of the optimized system is on the investigation of lightning physics and effects, mainly in the Amazon region. As a result of using the system were obtained: a better understanding about Compact Intracloud Discharge - CID; the characteristics of ionosphere heights computed using intraclound and cloud-to-ground lightning electric field waveforms; the conception of a lightning electric field waveform database containing more than 8 thousand waveforms of different types of lightning; and the implementation of the first continuous lightning electric field measurement system in the amazon region, localized at CESIPAM, Belem, PA.
Acesso aberto (Open Access)
Projeto e implementação de um sistema de controle numérico computadorizado: trajetórias suaves através da limitação de snap
(Universidade Federal do Pará, 2019-10-31) ROCHA JÚNIOR, Paulo Augusto Sherring; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148
Computer Numerical Control (CNC) is a technology made up of several blocks. Among these, lies the Trajectory Planning block, responsible for reference profile generation that are fed to position control loops. The need for Trajectory Planning arises from the mechanical constraints inherent to every plant to which CNC technology is applied. The machine’s operational limits must be respected, in order to avoid several issues, such as: loss of precision, early wear of machine’s parts and excessive vibration. This work proposes a novel smooth real-time trajectory generation setup based on an embedded system platform. A real-time snap and jerk bounded control algorithm is proposed, to achieve continuous and smooth feed motion in traditional Numeric Control code file, dealing both with straight lines and arcs. A local motion blending algorithm, applicable to the proposed method, is also presented. The developed algorithm was deployed to a BeagleBone Black, an embedded System-on-Chip, single board computer and tested in a prototype router machine. A comparison between the proposed method against the seven segments and trapezoidal acceleration methods is presented, both in terms of performance and of real-time computing viability. Simulation and Experimental results demonstrate the effectiveness of the proposed method to generate velocity, acceleration, jerk and snap bounded three dimensional trajectories, reducing the RMS error in up to 8:2% and 22:38% when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively. Assessing the error area on straight angles, the proposed method produced error areas 24% and 80% smaller when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively.
Desconhecido
Projeto e síntese de superfície seletiva de frequências para o padrão IEEE 802.15.3C via técnica de otimização híbrida multiobjetivo de alta precisão
(Universidade Federal do Pará, 2019-12-19) MOTA, Raimundo José Santos; CAVALCANTE, Gervásio Protásio dos Santos; http://lattes.cnpq.br/2265948982068382
Artficial Neural Networks (ANN) are inspired by the structure and functional aspects in biological neural networks. They are trained through mechanisms obtained from the physical properties of the processes involved, for example, electromagnetic waves. From the knowledge acquired through that experience and learning, they may be able to provide solutions for predicting users behavior and providing, within a region of interest, accurate strategy data for projects and sizing. Those who criticized the application of ANN acquired by nature-inspired algorithms, argued that the problems to be faced were usually without complexities, although the conventional methods that were proposed to solve these same problems were not eficient. Some spurious successes have occurred in certain well-behaved environments, but without_exibility when encountering diverse constraints. Adding to these developments, there is the evolutionary openness of computational tools, which has given extraordinary support for deepening techniques to solve and optimize previously unthought problems. In many optimization issues, the quality of a solution is defined by its performance against several conficting goals. Such coficting objectives cannot be signi_cantly reduced to a single value, for example using a weighted sum or other methodology, but must be considered independently of each other. To achieve accurate solutions with reduced computational costs and shorter processing times, we present the Multi-Objective Evolutionary Algorithms (MOEA), as well as Bioinspired Computation (BIC). Combining the advantages of the classical algorithms, the Metaheuristic Algorithms emerged irreversibly. In many optimization problems, the quality of a solution is defined by its performance in relation to several, coficting objectives. Such conficting goals cannot be sensibly reduced to a single value using a weighted sum or another aggregate function, but rather they must be considered independently from each other. Multi-Objective Evolutionary Algorithms (MOEAs) are a natural answer of this kind of evolution. In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network _ GRNN with the Multi-Objective Bat Algorithm _ MOBA, for the design and synthesis of the Frequency Selective Surfaces _ FSS, aiming its application in data communication systems by difusion of millimeter waves, speci_cally, in the IEEE 802:15:3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40:0 GHz at 70:0 GHz, i.e., 30:0 GHz bandwidth and 60:0 GHz resonance. The upper and lower cuto_ frequencies, referring to the transmission coe_cients scattering matrix (dB), were obtained at the cuto_ threshold at -10dB, to control the bandwidth of the device.

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