Documentação de convênios

URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/173

Trabalhos ténico-científico oriundos de convênios com universidades para oferta de turmas de mestrado e doutorados no Estado do Amazonas

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Filtros

2014 - 20182

Configurações

Tem arquivos: SimAssunto: search.filters.subject.Inteligência computacional

Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    Processamento Primário da Informação Gerada por Registradores de Perturbações
    (INSTITUTO DE TECNOLOGIA, 2014) AZEVEDO, Manoel Socorro Santos; HORTA, Roberto Luis Ballesteros; LEITE, Jandecy Cabral; BEZERRA, Ubiratan Holanda; TOSTES, Maria Emília de Lima; MAGALHÃES, Edilson Marques
    The study focuses on the primary processing of data generated by Digital Fault Recorders (DFRs) in electrical systems, aiming to streamline the analysis of oscillographic records for operators and specialists. Using LabVIEW and the COMTRADE standard, a modular software was developed for data acquisition, processing, storage, and interactive visualization. The system enables quick disturbance searches and lays the groundwork for implementing computational intelligence (CI) techniques to aid decision-making.
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    Aplicação do Método Fuzzy no Controle da Geração de Acetaldeído na Resina PET no Processo de Injeção de Pré-Formas de Embalagens Plásticas
    (Universidade Federal do Pará, 2018) MONTEIRO, Carlos Alberto; MACÊDO, Emanuel Negrão
    In order to control the drying temperature of PET resin in the silo of a plastic injection molding machine during the plastic injection process in industries producing preforms for beverage bottles, it is necessary to carefully regulate the ideal temperature. This impacts the control of Acetaldehyde (AA) generation, a substance that alters the taste of carbonated and non-carbonated drinks. This work aims to develop a tool based on Fuzzy logic to support the control of PET resin drying temperature, allowing specialists to make ideal temperature regulation decisions. The Fuzzy inference model was implemented using Matlab’s Fuzzy toolbox, considering input variables, Fuzzification rules, and output variables based on collected data from the preform injection process. The inference model resulted in more precise management of variables influencing AA generation, estimating an annual cost reduction of R$ 907,200.00 in preform production.