Tsialiamanis, G.P., Wagg, D.J., Antoniadou, I. et al. (1 more author) (2020) An ontological approach to structural health monitoring. In: Dilworth, B. and Mains, M., (eds.) Topics in Modal Analysis & Testing, Volume 8 : Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020. 38th IMAC, A Conference and Exposition on Structural Dynamics 2020, 10-13 Feb 2020, Houston, TX, USA. Springer International Publishing , pp. 51-59. ISBN 9783030477165
Abstract
In the current work, an ontological framework for structural health monitoring (SHM) is discussed. Ontologies are used in disciplines like knowledge engineering and natural language processing, but their structure and goals also fit the purposes of SHM. In SHM projects – as in all projects – many problems arise during knowledge sharing and application. Ontologies can deal with these problems and at the same time have more benefits for SHM processes, as their modularity may assist in extending and transferring knowledge. An SHM-specific ontology is constructed here and described; It contains many objects that can be used in the procedure of monitoring structures. The ontology can also be used as a database to store data acquired, but also serves as a knowledge-base for the current discipline’s algorithms and methods. Further, having close connections to object-oriented programming, ontologies straightforwardly facilitate software development and reusability of their components. Certainly, the ontology can be used to save time during the application of SHM, but also can be applied to improve performance of existing methods, by finding within the ontology the best algorithm to fit the purpose of each method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2021 The Society for Experimental Mechanics, Inc. This is an author-produced version of a paper subsequently published in Proceedings of the 38th IMAC. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Structural health monitoring (SHM); ontologies; database; knowledge-base; knowledge engineering |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/K003836/2 European Commission - Horizon 2020 764547 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Jan 2021 08:09 |
Last Modified: | 23 Oct 2021 00:38 |
Status: | Published |
Publisher: | Springer International Publishing |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-030-47717-2_6 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169410 |