Barthorpe, R.J. orcid.org/0000-0002-6645-8482 and Worden, K. orcid.org/0000-0002-1035-238X (2020) Emerging trends in optimal structural health monitoring system design: From sensor placement to system evaluation. Journal of Sensor and Actuator Networks, 9 (3). 31. ISSN 2224-2708
Abstract
This paper presents a review of advances in the field of Sensor Placement Optimisation (SPO) strategies for Structural Health Monitoring (SHM). This task has received a great deal of attention in the research literature, from initial foundations in the control engineering literature to adoption in a modal or system identification context in the structural dynamics community. Recent years have seen an increasing focus on methods that are specific to damage identification, with the maximisation of correct classification outcomes being prioritised. The objectives of this article are to present the SPO for SHM problem, to provide an overview of the current state of the art in this area, and to identify promising emergent trends within the literature. The key conclusions drawn are that there remains a great deal of scope for research in a number of key areas, including the development of methods that promote robustness to modelling uncertainty, benign effects within measured data, and failures within the sensor network. There also remains a paucity of studies that demonstrate practical, experimental evaluation of developed SHM system designs. Finally, it is argued that the pursuit of novel or highly efficient optimisation methods may be considered to be of secondary importance in an SPO context, given that the optimisation effort is expended at the design stage.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | sensor placement optimisation; structural health monitoring; damage identification; mutual information; evolutionary optimisation |
Dates: |
|
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/J013714/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/N010884/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/R003645/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jul 2020 15:22 |
Last Modified: | 17 Jul 2020 15:55 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/jsan9030031 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163407 |