Supervisión de la integridad estructural mediante inteligencia artificial

retos, avances y aplicaciones

Autores/as

DOI:

https://doi.org/10.35699/2965-6931.2023.47533

Palabras clave:

detección de daños estructurales, inteligencia computacional, aprendizaje automático, aprendizaje profundo

Resumen

Este artículo presenta una revisión sistemática y aporta reflexiones críticas sobre el uso de técnicas de inteligencia artificial para identificar el deterioro estructural a través de señales de vibración (es decir, aceleraciones, desplazamientos, etc.). Los enfoques basados ​​en el aprendizaje automático y el aprendizaje profundo se consideran prometedores para aumentar la seguridad y optimizar los programas de mantenimiento preventivo. Sin embargo, algunos autores reconocen las preocupaciones que surgen de los métodos estrictamente supervisados, la naturaleza de "caja negra" de los modelos y su interpretación por parte de los operadores humanos. La aportación de este trabajo es, por tanto, aportar información relevante sobre el paradigma actual de detección de daños, posibilitando predicciones en tiempo real, no destructivas y fiables sobre la seguridad en la construcción en el ámbito de la Industria 4.0. Además, los desafíos relacionados con el uso de inteligencia computacional para el reconocimiento de patrones y la toma de decisiones en el monitoreo de anomalías estructurales se informan y examinan en estudios de casos recientes.

Biografía del autor/a

  • Victor Higino Meneguitte Alves, Universidade Federal de Juiz de Fora (UFJF)

    Graduando em Engenharia Civil pela Universidade Federal de Juiz de Fora. Técnico em Eletromecânica pelo Centro Federal de Educação Tecnológica, CEFET-MG. Divulgador científico no CIDENG-CNPq, Grupo de Pesquisa em Ciência de Dados aplicada à Engenharia. Atualmente realiza iniciação científica no Departamento de Mecânica Aplicada e Computacional, com ênfase em detecção e localização de danos estruturais à partir de dados dinâmicos.

  • Vinicius Antonio Meneguitte Alves, Universidade Federal de Juiz de Fora (UFJF)

    Graduando em Engenharia Civil pela Universidade Federal de Juiz de Fora (UFJF). Técnico em Eletromecânica pelo Centro Federal de Educação Tecnológica (CEFET-MG).

  • Alexandre Abrahão Cury, Universidade Federal de Juiz de Fora (UFJF)

    Engenheiro Civil (2006) e mestre em Modelagem Computacional pela Universidade Federal de Juiz de Fora (2008). Doutor em Engenharia Civil pela Universidade Paris-Est (2010). Atua nos temas: monitoramento de integridade estrutural, análise de vibrações, detecção de danos, identificação modal e confiabilidade estrutural. Professor associado no Departamento de Mecânica Aplicada e Computacional. Pesquisador de Produtividade do CNPq desde 2013.

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Publicado

2024-02-21

Número

Vol. 30 (2023): Inteligencia e Inteligencia Artificial

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Supervisión de la integridad estructural mediante inteligencia artificial: retos, avances y aplicaciones. Revista da Universidade Federal de Minas Gerais, Belo Horizonte, v. 30, n. fluxo contínuo, 2024. DOI: 10.35699/2965-6931.2023.47533. Disponível em: https://periodicos.ufmg.br/index.php/revistadaufmg/article/view/47533. Acesso em: 22 dec. 2024.