Monitoramento e identificação de falhas em estruturas aeronáuticas e mecânicas utilizando técnicas de computação inteligente

• Ano de defesa: 2014
• Autor(a) principal: Lima, Fernando Parra dos Anjos [UNESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Monitoramento da integridade estrutural; Redes neurais (Computação); Algoritmos; Localização de falhas (Engenharia); Structural health monitoring
• Link de acesso: http://hdl.handle.net/11449/113857

In this dissertation presents two methodologies to develop health monitoring of aircraft structures and mechanical systems, using intelligent computing techniques such as artificial neural networks and artificial immune systems. In this context, uses an ARTMAP-Fuzzy artificial neural network and the negative selection algorithm. Both techniques are used for the analysis, identification and characterization of structural failure due to the structure. The main application of these methods is to assist in the inspection of mechanical and aeronautical structures, to detect and characterize flaws as well, making decisions in order to avoid disasters/accidents. With these proposals one seeks to designing new systems for structural health monitoring that can be modified easily to cater to permanent evolution technologies and industry. To evaluate the proposed methodologies, experiments were performed in the laboratory to generate a database of captured signals in an aluminum beam. The results obtained by the methods are excellent, with robustness and accuracy