The role of the Bhattacharyya distance in stochastic model updating
- authored by
- Sifeng Bi, Matteo Broggi, Michael Beer
- Abstract
The Bhattacharyya distance is a stochastic measurement between two samples and taking into account their probability distributions. The objective of this work is to further generalize the application of the Bhattacharyya distance as a novel uncertainty quantification metric by developing an approximate Bayesian computation model updating framework, in which the Bhattacharyya distance is fully embedded. The Bhattacharyya distance between sample sets is evaluated via a binning algorithm. And then the approximate likelihood function built upon the concept of the distance is developed in a two-step Bayesian updating framework, where the Euclidian and Bhattacharyya distances are utilized in the first and second steps, respectively. The performance of the proposed procedure is demonstrated with two exemplary applications, a simulated mass-spring example and a quite challenging benchmark problem for uncertainty treatment. These examples demonstrate a gain in quality of the stochastic updating by utilizing the superior features of the Bhattacharyya distance, representing a convenient, efficient, and capable metric for stochastic model updating and uncertainty characterization.
- Organisation(s)
-
Institute for Risk and Reliability
- External Organisation(s)
-
University of Liverpool
Tongji University
- Type
- Article
- Journal
- Mechanical Systems and Signal Processing
- Volume
- 117
- Pages
- 437-452
- No. of pages
- 16
- ISSN
- 0888-3270
- Publication date
- 15.02.2019
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Control and Systems Engineering, Signal Processing, Civil and Structural Engineering, Aerospace Engineering, Mechanical Engineering, Computer Science Applications
- Electronic version(s)
-
https://strathprints.strath.ac.uk/79525/1/Bi_etal_MSSP_2018_The_role_of_the_Bhattacharyya_distance_in_stochastic_model_updating.pdf" (Access:
Open)
https://doi.org/10.1016/j.ymssp.2018.08.017 (Access: Closed)
