Monitoramento de integridade estrutural utilizando inteligência artificial
Desafios, avanços e aplicações
DOI:
https://doi.org/10.35699/2965-6931.2023.47533Palavras-chave:
Detecção de danos estruturais, Inteligência Computacional, Aprendizado de Máquina, Aprendizado ProfundoResumo
Este artigo apresenta uma revisão sistemática e traz reflexões críticas acerca da utilização de técnicas de inteligência artificial para identificação de deterioração estrutural por meio de sinais de vibração (i.e., acelerações, deslocamentos, etc). Abordagens baseadas em aprendizado de máquina e aprendizado profundo são consideradas promissoras para aumentar a segurança e otimizar os cronogramas de manutenção preventiva. Entretanto, alguns autores reconhecem as preocupações decorrentes de métodos estritamente supervisionados, da natureza do tipo “caixa-preta” dos modelos e de suas interpretabilidades por operadores humanos. A contribuição deste trabalho consiste, portanto, em fornecer informações relevantes sobre o atual paradigma de detecção de danos, possibilitando previsões em tempo real, não destrutivas e confiáveis sobre a segurança da construção no âmbito da Indústria 4.0. Além disso, os desafios relacionados ao emprego de inteligência computacional para reconhecimento de padrões e tomada de decisão no monitoramento de anomalias estruturais são relatados e examinados em estudos de casos recentes.
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