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Fast Bayesian Approach for Stochastic Model Updating using Modal Information from Multiple Setups
Yan, W.; Katafygiotis, L.; Papadimitriou, C.
2021-11-01
Source PublicationBayesian Inverse Problems
PublisherCRC Press
Pages1-21
AbstractThis chapter illustrates the suitability of advanced Bayesian techniques to extract the modal properties of vibrating structures and stochastic model updating. A technique for variable separation is presented so that the interaction between spectrum variables (e.g. frequency, damping ratio as well as the amplitude of modal excitation and prediction error) and spatial variables (e.g. mode shape components) can be decoupled completely. Based on the uncertainties of the modal properties, a novel Bayesian methodology is developed for structural stochastic model updating by incorporating the local mode shape components identified from different clusters automatically without prior assembling. The suitability and potential of the presented methodology is illustrated using a numerical example and an experimental case study.
KeywordBayesian analysis Model updating Uncertainties
Language英語English
ISBN9781315232973
The Source to ArticlePB_Publication
PUB ID58781
Document TypeBook chapter
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorYan, W.
Recommended Citation
GB/T 7714
Yan, W.,Katafygiotis, L.,Papadimitriou, C.. Fast Bayesian Approach for Stochastic Model Updating using Modal Information from Multiple Setups[M]. Bayesian Inverse Problems:CRC Press, 2021, 1-21.
APA Yan, W.., Katafygiotis, L.., & Papadimitriou, C. (2021). Fast Bayesian Approach for Stochastic Model Updating using Modal Information from Multiple Setups. Bayesian Inverse Problems, 1-21.
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