Bayesian parameter estimation of Euler-Bernoulli beams
Loading...
Other Title
Authors
Ardekani, Iman
Kaipio, J.
Sharifzadeh, Hamid
Kaipio, J.
Sharifzadeh, Hamid
Author ORCID Profiles (clickable)
Degree
Grantor
Date
2018-11
Supervisors
Type
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.
Publisher
Permanent link
Link to ePress publication
DOI
Copyright holder
Copyright notice
All rights reserved