Programa de Pós-Graduação em Engenharia Elétrica e de Computação
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Master Thesis Implementação de um estimador neural de velocidade em um motor de indução trifásico(2019-12-16) Silva, Carlos Yuri Ferreira; Salazar, Andres Ortiz; ; ; Lock, Alberto Soto; ; Araújo, Fábio Meneghetti Ugulino de; ; Paiva, José Álvaro de;This work proposes to perform the speed control of an induction motor (1 cv, 2 poles, 220/380 V) without the use of a mechanical sensor attached to the rotor, avoiding some inconveniences such as a periodic maintenance and increased complexity and number of equipment are always part of the engine running. The three phase induction motor is the most used type of machine for electric drives. Low cost, construction simplicity and reliability are the motives that explains this statement. For the induction motor control was applied the control strategy known as Field Oriented Control and for the estimation of the motor rotor speed was used an artificial neural network, which observer electrical and mechanical system variables. The practical results were satisfatory, since the neural network worked for the measeured and estimated velocity, being possible to perform the control os the motor with the estimated speed in the range of 100 to 170 rad/s.Master Thesis Análise e síntese de superfícies seletivas de frequência bioinspiradas usando redes neurais para aplicações em sistemas de comunicação sem fio(2019-07-01) Paiva, Samuel Belarmino de; D'Assunção, Adaildo Gomes; Silva Neto, Valdemir Praxedes da; ; ; ; D'Assunção Júnior, Adaildo Gomes; ; Fontgalland, Glauco; ; Lins, Hertz Wilton de Castro; ; Costa, José Alfredo Ferreira;This work proposes the analysis of Bioinspired Frequency Selective Surfaces (BFSS) for applications in wireless systems, operating in the C band, Ku band and UWB (ultrawideband). Simple and coupled BFSS structures are considered. The BFSSs have array elements with the four-leaf clover-shaped and maple leaf-shaped, and presented dual-band response, with the operating frequencies in the C and Ku bands. For the development of BFSSs with the ultra-wideband, a cascade structure was developed, in which a FSS with elements with patches with the shape of square loops was coupled to the BFSSs. In addition, the four-leaf clover BFSS synthesis was developed using an artificial neural network with an architecture cascade feedforward and Bayesian regularization training algorithm to obtain the specifications of resonance frequency and respective desired bandwidths. The numerical values obtained by simulations for the projected prototypes were obtained by the ANSYS HFSS software. The prototypes were manufactured and the experimental characterization was performed, whose values were compared to simulation results, which showed good agreement.Master Thesis Análise estatística e técnicas de identificação de pilotos para veículos Baja SAE(2018-08-31) Nunes, Tomaz Filgueira; Martins, Allan de Medeiros; Silva, Ivanovitch Medeiros Dantas da; ; ; ; Dantas, André Felipe Oliveira de Azevedo; ; Nobre, Marcelo Henrique Ramalho;Immersing in the motorsports context, the use of artificial inteligence becomes a great ally to the racing team efficiency by extracting important features from car/driver system and providing feedbacks for a better performance, as it can be found in some Formula 1 teams. From that principle, this work aims to characterize drivers of an off-road Baja SAE vehicle. Through the partnership with the Car-Kará Baja SAE UFRN team, 4 different drivers have been selected in 7 different test tracks. The data has been collected, through an industrial data logger, and analyzed in an offline manner. From the data collection, it has been done a divison of the variable vector in 3 and 5 sections and then it has been computed the statistical analysis for each part, creating the feature vectors. That vector was inserted in an artificial neural archtecture with two hidden layer, obtaining a classification rate of 97% for the variable vector division in 3 parts and 93% for 5 parts.Doctoral Thesis Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons(Universidade Federal do Rio Grande do Norte, 2015-09-04) Silva, Carlos Alberto de Albuquerque; Dória Neto, Adrião Duarte; ; http://lattes.cnpq.br/1987295209521433; ; http://lattes.cnpq.br/7963808444142138; Barbalho, David Simonetti; ; http://lattes.cnpq.br/7208859488227503; Melo, Jorge Dantas de; ; http://lattes.cnpq.br/7325007451912598; Oliveira, José Alberto Nicolau de; ; http://lattes.cnpq.br/2871134011057075; Lopes, Danniel Cavalcante; ; http://lattes.cnpq.br/5342832426660173; Ramos, Karla Darlene Nepomuceno; ; http://lattes.cnpq.br/2751239628595747The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.Master Thesis Ferramenta para avaliação e inferência de parâmetros de redes industriais sem fio(Universidade Federal do Rio Grande do Norte, 2015-07-20) Florêncio, Heitor Medeiros; Dória Neto, Adrião Duarte; ; http://lattes.cnpq.br/1987295209521433; ; http://lattes.cnpq.br/6422930980833254; Brandão, Dennis; ; http://lattes.cnpq.br/6838931677289559; Silva, Ivanovitch Medeiros Dantas da; ; http://lattes.cnpq.br/3608440944832201; Oliveira, Luiz Affonso Henderson Guedes de; ; http://lattes.cnpq.br/7987212907837941Wireless sensor networks (WSN) have gained ground in the industrial environment, due to the possibility of connecting points of information that were inaccessible to wired networks. However, there are several challenges in the implementation and acceptance of this technology in the industrial environment, one of them the guaranteed availability of information, which can be influenced by various parameters, such as path stability and power consumption of the field device. As such, in this work was developed a tool to evaluate and infer parameters of wireless industrial networks based on the WirelessHART and ISA 100.11a protocols. The tool allows quantitative evaluation, qualitative evaluation and evaluation by inference during a given time of the operating network. The quantitative and qualitative evaluation are based on own definitions of parameters, such as the parameter of stability, or based on descriptive statistics, such as mean, standard deviation and box plots. In the evaluation by inference uses the intelligent technique artificial neural networks to infer some network parameters such as battery life. Finally, it displays the results of use the tool in different scenarios networks, as topologies star and mesh, in order to attest to the importance of tool in evaluation of the behavior of these networks, but also support possible changes or maintenance of the system.Master Thesis Classificador neural híbrido para imagens obtidas por sensoriamento remoto(Universidade Federal do Rio Grande do Norte, 2011-08-12) Lima, Alexandre Gomes de; Guerreiro, Ana Maria Guimarães; ; http://lattes.cnpq.br/8556144121380013; ; http://lattes.cnpq.br/4063478137671603; Dória Neto, Adrião Duarte; ; http://lattes.cnpq.br/1987295209521433; Henriques, Antônio de Pádua de Miranda; ; http://lattes.cnpq.br/9855577471019220; Soares, Heliana Bezerra;Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.Master Thesis Sistema não-Intrusivo para Estimação da Direção do olhar utilizando redes neurais artificiais(Universidade Federal do Rio Grande do Norte, 2010-11-26) Peixoto, Helton Maia; Guerreiro, Ana Maria Guimarães; Dória Neto, Adrião Duarte; ; http://lattes.cnpq.br/1987295209521433; ; http://lattes.cnpq.br/8556144121380013; ; http://lattes.cnpq.br/8709900833456787; Soares, Heliana Bezerra; ; Santos, Celso Alberto Saibel; ; http://lattes.cnpq.br/7614206164174151The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.Master Thesis Técnicas inteligentes hídridas para o controle de sistemas não lineares(Universidade Federal do Rio Grande do Norte, 2006-02-17) Rodrigues, Marconi Câmara; Araújo, Fábio Meneghetti Ugulino de; ; http://lattes.cnpq.br/5473196176458886; ; Maitelli, André Laurindo; ; http://lattes.cnpq.br/0477027244297797; Oliveira, Luiz Affonso Henderson Guedes de; ; http://lattes.cnpq.br/7987212907837941A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristicsMaster Thesis Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais(Universidade Federal do Rio Grande do Norte, 2006-06-09) Martins, Rodrigo Siqueira; Maitelli, André Laurindo; ; http://lattes.cnpq.br/0477027244297797; ; http://lattes.cnpq.br/0510960635068771; Dória Neto, Adrião Duarte; ; http://lattes.cnpq.br/1987295209521433This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaksMaster Thesis Reconhecimento de padrões de falhas em motores trifásicos utilizando redes neurais(Universidade Federal do Rio Grande do Norte, 2010-02-19) Reis, Aderson Jamier Santos; Maitelli, André Laurindo; Salazar, Andrés Ortiz; ; http://lattes.cnpq.br/7865065553087432; ; http://lattes.cnpq.br/0477027244297797; ; http://lattes.cnpq.br/6867792015895014; Ferreira, Jossana Maria de Souza; ; http://lattes.cnpq.br/7691693293898376; Paiva, José Alvaro de; ; http://lattes.cnpq.br/6136888701626547This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern