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    <title>DSpace Coleção: PPGEE</title>
    <link>https://repositorio.ufpb.br/jspui/handle/tede/4457</link>
    <description>PPGEE</description>
    <pubDate>Sat, 16 May 2026 07:28:29 GMT</pubDate>
    <dc:date>2026-05-16T07:28:29Z</dc:date>
    <item>
      <title>Desenvolvimento de um sensor virtual de vazão utilizando redes neurais para macromedição de uma estação de distribuição de água</title>
      <link>https://repositorio.ufpb.br/jspui/handle/123456789/38049</link>
      <description>Título: Desenvolvimento de um sensor virtual de vazão utilizando redes neurais para macromedição de uma estação de distribuição de água
Autor(es): Gonçalves, Luiz Felipe Rodrigues
Orientador: Villanueva, Juan Moises Maurício
Abstract: Law No. 14,026/2020, which established the new legal framework for sanitation in Brazil,&#xD;
introduced significant changes for water and sewage distribution companies by imposing&#xD;
stricter regulations and increasing competition in the sector. One of its key objectives is&#xD;
to reduce water losses and improve macromeasurement rates. According to the National&#xD;
Sanitation Information System (SNIS), the average water loss in Brazil is around 40%,&#xD;
while only 70% of the distributed water is properly measured. However, the high cost of&#xD;
sensors, especially flow macrometers, limits their widespread deployment, leading many&#xD;
companies to focus monitoring efforts on metropolitan areas. To address this issue, indirect&#xD;
measurement methods allow flow estimation based on network pressure and reservoir level&#xD;
data, reducing the need for physical sensors across the entire distribution system. In this&#xD;
context, artificial intelligence (AI) has been increasingly applied to improve the efficiency&#xD;
of water supply systems, enabling the reconstruction of missing data, fault detection, and&#xD;
forecasting of operational variables. Soft sensors based on neural networks allow continuous&#xD;
system monitoring and anomaly detection, enhancing operational decision-making and&#xD;
minimizing resource waste. This study presents the development and implementation of&#xD;
a soft sensor based on Long Short-Term Memory (LSTM) neural networks to estimate&#xD;
flow rates in a water supply system. The model was trained using flow, pressure, and&#xD;
reservoir level data collected by the Companhia de Água e Esgotos da Paraíba (CAGEPA)&#xD;
in the municipality of Salgado de São Félix, through an MQTT broker and cloud-based&#xD;
monitoring. The model validation was performed by comparing the estimated values with&#xD;
real measurements from physical sensors, resulting in a mean absolute percentage error&#xD;
lower than 5%, demonstrating the reliability of the proposed approach.
Editor: Universidade Federal da Paraíba
Tipo: Dissertação</description>
      <pubDate>Mon, 15 Dec 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repositorio.ufpb.br/jspui/handle/123456789/38049</guid>
      <dc:date>2025-12-15T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Modelagem e acionamento de uma máquina de indução dodecafásica com injeção harmônica para ganho de conjugado eletromagnético</title>
      <link>https://repositorio.ufpb.br/jspui/handle/123456789/37641</link>
      <description>Título: Modelagem e acionamento de uma máquina de indução dodecafásica com injeção harmônica para ganho de conjugado eletromagnético
Autor(es): Quirino, Marcos Lázaro de Andrade
Orientador: Freitas, Isaac Soares de
Abstract: The electromagnetic torque can be increased, with significant gain, through the harmonic&#xD;
injection technique. With this procedure, it is possible we use a induction machine with a&#xD;
&#xD;
number of stator phases more than, reducing their dimensions when compared with the three-&#xD;
phase machines, widely used today and easily found on the market. By using multiphase&#xD;
&#xD;
machines we were able to obtain larger conjugates to meet heavier loads, improving the&#xD;
efficiency of certain electromechanical systems, thus taking up less space and increasing the&#xD;
reliability. The present work proposes a mathematical modeling for a twelve-phase induction&#xD;
machine with cage rotor, considering the spatial flow harmonics and the harmonic injection&#xD;
analysis in time. It is presented that using from the fundamental component up to the eleventh&#xD;
harmonic it is possible to produce dc torque, improving the mechanical torque density of a&#xD;
drive system. It is presented the dynamic model of the machine, the steady state analysis and&#xD;
the set of experimental results.
Editor: Universidade Federal da Paraíba
Tipo: Dissertação</description>
      <pubDate>Thu, 29 Aug 2019 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repositorio.ufpb.br/jspui/handle/123456789/37641</guid>
      <dc:date>2019-08-29T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Sistema integrado com comunicação LoRa para monitoramento e transmissão de dados em redes e reservatórios de água da CAGEPA</title>
      <link>https://repositorio.ufpb.br/jspui/handle/123456789/37132</link>
      <description>Título: Sistema integrado com comunicação LoRa para monitoramento e transmissão de dados em redes e reservatórios de água da CAGEPA
Autor(es): Córdula, Márcio Miranda
Orientador: Souto, Cícero da Rocha
Abstract: Efficient water resource management is one of the greatest challenges faced by sanitation&#xD;
companies in Brazil. This study presents the development and implementation of an&#xD;
integrated system for monitoring and transmitting data in water distribution networks&#xD;
and reservoirs, utilizing Internet of Things (IoT)-based technologies. The research was&#xD;
conducted at the Companhia de Água e Esgotos da Paraíba (CAGEPA) with the objective of&#xD;
reducing water losses, improving operational efficiency, and meeting the targets established&#xD;
by the Legal Framework for Basic Sanitation (Law No. 14,026/2020). The proposed system&#xD;
employs LoRa (Long Range) modules in conjunction with pressure, flow, and level sensors,&#xD;
which are integrated into a SCADA (Supervisory Control and Data Acquisition) platform.&#xD;
This combination enables real-time data transmission over long distances with low power&#xD;
consumption and reduced costs, allowing continuous monitoring even in remote and hardto-&#xD;
reach areas. This project presents a replicable model for other sanitation companies&#xD;
facing similar challenges, standing out for its scalability, energy efficiency, and economic&#xD;
viability. The findings indicate that the integration of IoT, LoRa, and supervisory systems&#xD;
represents a significant advancement in Brazil’s sanitation sector, fostering sustainability,&#xD;
natural resource preservation, and improvements in service quality for the population.
Editor: Universidade Federal da Paraíba
Tipo: Dissertação</description>
      <pubDate>Fri, 25 Jul 2025 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repositorio.ufpb.br/jspui/handle/123456789/37132</guid>
      <dc:date>2025-07-25T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Estimação paramétrica da impedância de uma rede elétrica conectada a uma geração fotovoltaica</title>
      <link>https://repositorio.ufpb.br/jspui/handle/123456789/36932</link>
      <description>Título: Estimação paramétrica da impedância de uma rede elétrica conectada a uma geração fotovoltaica
Autor(es): Gomes, Andréia da Silva
Orientador: Fernandes, Darlan Alexandria
Abstract: Better knowledge of grid impedance is essential to assess stability, improve power quality&#xD;
and control of Distributed Generation Systems (SGDs), as well as perform safe connection&#xD;
or reconnection to the grid grid. As a result of increased network impedance variability,&#xD;
interest in impedance estimation techniques has increased considerably. This work presents&#xD;
a computational method that performs a parametric impedance test on the electrical grid&#xD;
side and online, for a system that contains a photovoltaic generation connected to an&#xD;
electrical grid. The method used in this work requires variations in power injection by the&#xD;
inverter and calculation of network parameters based on numerical analysis on changes in&#xD;
positive sequence phasors extracted from the orientation depth and system currents in&#xD;
the PAC. The numerical search of the network parameters is carried out using classic and&#xD;
recent iterative optimization methods, in order to find a solution for the non-linear search&#xD;
system arising from the technique used. The numerical methods of Newton-Raphson,&#xD;
Broyden, Levemberg-Marquardt, Potra-Pták, Ponto Meio and Chun are used to determine&#xD;
the network parameters and for a subsequent performance comparison between them.&#xD;
A simulation platform containing the entire electrical network together with numerical&#xD;
methods was built in a Simulink/MATLAB®&#xD;
environment to estimate the impedance as&#xD;
the final result of the process. Finally, the results were corroborated with the help of a&#xD;
real-time simulator available in the laboratory
Editor: Universidade Federal da Paraíba
Tipo: Dissertação</description>
      <pubDate>Tue, 27 Feb 2024 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repositorio.ufpb.br/jspui/handle/123456789/36932</guid>
      <dc:date>2024-02-27T00:00:00Z</dc:date>
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