Abstract
Effective structural health monitoring (SHM) requires large amounts of data representing the normal condition of a structure as well as any damage conditions. However, it is not always feasible to obtain these data; for example, it is not economical to obtain damage-state data for a new bridge. To address this problem, a new framework is being explored called population based structural health monitoring (PBSHM), which proposes that if two structures are sufficiently similar, then data can be shared between them. Tools which enable the sharing of data, such as the transfer of models and damage classifiers, have been explored in previous work; as have methods for assessing the similarity of structures. This paper will describe how it may be possible to link structures based on their physical similarity in such a way that creates a network, with communities of similar structures. Within these communities, data can be shared between structures. Forming these communities in a way that is computationally efficient while still avoiding missing possible links is not straightforward. This paper outlines some of the considerations that must be taken into account for solving this problem.
Original language | English |
---|---|
Title of host publication | Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-10) |
Editors | Álvaro Cunha, Elsa Caetano |
Publisher | International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII |
Pages | 1803-1808 |
Publication status | Published - 30 Jun 2021 |
Publication series
Name | International Conference on Structural Health Monitoring of Intelligent Infrastructure: Proceedings |
---|---|
ISSN (Electronic) | 2564-3738 |
Fingerprint
Dive into the research topics of 'Creating a network of structures based on physical similarity'. Together they form a unique fingerprint.Student theses
-
Sensing and information extraction towards a population based structural health monitoring (PBSHM) framework for bridges
Bunce, A. (Author), Hester, D. (Supervisor), Taylor, S. (Supervisor) & Woods, R. (Supervisor), Jul 2024Student thesis: Doctoral Thesis › Doctor of Philosophy