Fast Bayesian Approach for Stochastic Model Updating using Modal Information from Multiple Setups

UM > THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)

Status	已發表Published
	Fast Bayesian Approach for Stochastic Model Updating using Modal Information from Multiple Setups
	Yan, W.; Katafygiotis, L.; Papadimitriou, C.
	2021-11-01
Source Publication	Bayesian Inverse Problems
Publisher	CRC Press
Pages	1-21
Abstract	This 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.
Keyword	Bayesian analysis Model updating Uncertainties
Language	英語English
ISBN	9781315232973
The Source to Article	PB_Publication
PUB ID	58781
Document Type	Book chapter
Collection	THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding Author	Yan, 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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