CREEM2024

CREEM 2024 - XXX Congresso Nacional de Estudantes de Engenharia Mecânica

Desenvolvimento de uma Ferramenta de Diagnóstico para Sistemas de Refrigeração Comerciais e Industriais Utilizando Inteligência Artificial

Submission Author: José Ricardo Ferreira Oliveira , MG
Co-Authors: Amanda Aparecida Alves Silva , Dimas Jose Rua Orozco, Osvaldo Jose Venturini, José Ricardo Ferreira Oliveira, Euler Horta, Tiago Mendes
Presenter: Amanda Aparecida Alves Silva

doi://10.26678/ABCM.CREEM2024.CRE2024-0142

 

Abstract

The use of Artificial Intelligence (AI) in the diagnosis of commercial and industrial refrigeration systems is a powerful tool to improve their performance and reliability. By integrating real-time operational data with AI techniques, it is possible to detect degradations and failures, contributing to the energy performance of these systems. Mathematical and computational models are used to predict the behavior of systems under different operating conditions, allowing the training of AI algorithms to monitor them and identify problems. This not only helps reduce energy consumption and sustainability, but also predicts failures and integrates with technologies such as the Internet of Things (IoT) and automation. The proposed work aims to provide a methodology to monitor and diagnose the performance of refrigeration system.

Keywords

Sistemas Térmicos, Refrigeração industrial, Detecção de Falhas, termoeconomia

 

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