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Publication Detail
Inferring structural variability using modal analysis in a Bayesian framework
  • Publication Type:
  • Authors:
    Gomes HM, DiazDelaO FA, Mottershead JE
  • Publication date:
  • Pagination:
    363, 373
  • Published proceedings:
    Conference Proceedings of the Society for Experimental Mechanics Series
  • Volume:
  • ISBN-13:
  • Status:
  • Print ISSN:
Dynamic systems with different geometric configurations may present remarkable distinct dynamic behaviour. However, variability is identifiable in the measured modal shapes and modal frequencies. This paper explores a Bayesian framework in order to infer structural variability based on modal parameters. This is relevant in cases of difficult access for inspection in finished products/structures. An approach using a radial basis neural network benchmarked by a Gaussian process meta model is developed and then followed by a test case with experimental data. It is concluded that the proposed methodology shows promise in solving this kind of problems.
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