Bayesian parameter estimation of Euler-Bernoulli beams
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Authors
Ardekani, Iman
Kaipio, J.
Sharifzadeh, Hamid
Kaipio, J.
Sharifzadeh, Hamid
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2018-11
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Conference Contribution - Paper in Published Proceedings
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
statistical signal processing
Euler-Bernoulli beams
Bayesian approximation error
system identification
Euler-Bernoulli beams
Bayesian approximation error
system identification
ANZSRC Field of Research Code (2020)
Citation
Ardekani, I., Kaipio, J., & Sharifzadeh, H. (2018). Bayesian parameter estimation of Euler-Bernoulli beams.10th International Conference on Signal Processing Systems (ICSPS 2018) Retrieved from http://www.icsps.org/
Abstract
This paper develops a statistical signal processing algorithm for parameter estimation of Euler-Bernoulli beams from limited and noisy measurement. The original problem is split into two reduced-order sub-problems coupled by a linear equation. The first sub-problem is cast as an inverse problem and solved by using Bayesian approximation error analysis. The second sub-problem is cast as a forward problem and solved by using the finite element technique. An optimal solution to the original problem is then obtained by coupling the solutions to the two sub-problems. Finally, a statistical signal processing algorithm for adaptive estimation of the optimal solution is developed. Computer simulation shows the effectiveness of the proposed algorithm.
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