Aplicação dos mapas auto-organizáveis associado ao monitoramento da integridade estrutural baseado na impedância eletromecânica
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Data
2018-07-04
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Universidade Federal de Goiás
Resumo
Structural Health Monitoring (SHM) is a very cost-effective technique to reduce costs, increase life-cycle, and improve the performance of engineering structures. The impedancebased methodology uses the electromechanical behavior of piezoelectric materials (PZTs) to detect structural anomalies and damages. This technique uses high frequencies and excites the local modes, thus providing the monitoring of any change of the structural mechanical impedance in the region of influence of PZT. From the variation of the impedance signals, it can be concluded whether or not there is a damage. Artificial neural networks (RNA) are part of a broad concept called artificial systems. The foundation of neural networks is associated with the functioning of the human brain, which after training has the ability to perform associations. This science has great applicability in the solution of artificial intelligence problems, through the modeling of systems that use connections that make it possible to simulate the human nervous system. This work uses Kohonen’s self-organizing maps (SOM) associated to SHM based on electromechanical impedance for the detection and classification of damages in an aluminum beam. Based on the system under analysis, the network was trained to five different failure and severity positions. Through the neural network model of self-organizing maps, the network provided 30 maps as answers to the training and learning process. With this, it was realized qualitatively based on the concentration of energy of the maps that the grouping and classification of the different conditions of damages in which the engineering structure was submitted, happened with success. In order to establish a quantitative analysis proving the potential of the SOM network, the Hamming distance formula was applied, in which the results confirmed its accuracy.
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Monitoramento da integridade estrutural, Impedância eletromecânica, Pastilha PZT, Redesneurais, Electromechanical impedance, Mapas auto-organizáveis, PZT patch, Neural networks, SOM, SHM
Citação
DURVAL, M. S. Aplicação dos mapas auto-organizáveis associado ao monitoramento da integridade estrutural baseado na impedância eletromecânica. 2018. 82 f. Dissertação (Mestrado em Modelagem e Otimização) - Universidade Federal de Goiás, Catalão, 2018.