Fibre-optic sensor and deep learning-based structural health monitoring systems for civil structures: A review
Article
Article Title | Fibre-optic sensor and deep learning-based structural health monitoring systems for civil structures: A review |
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ERA Journal ID | 650 |
Article Category | Article |
Authors | Jayawickrema, U. M. N. (Author), Herath, H. M. C. M. (Author), Hettiarachchi, N. K. (Author), Sooriyaarachchi, H. P. (Author) and Epaarachchi, J. A. (Author) |
Journal Title | Measurement |
Journal Citation | 199, pp. 1-31 |
Article Number | 111543 |
Number of Pages | 31 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0263-2241 |
1873-412X | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.measurement.2022.111543 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0263224122007618 |
Abstract | Structural health monitoring (SHM) systems in civil engineering structures have been a growing focus of research and practice. Over the last few decades, optical fibre sensor (OFS) technology has advanced rapidly, and various types of OFS technologies have found practical uses in civil engineering. Due to recent advances in optical sensors and data-driven solutions, the SHM systems are gaining prominence. Because of its superior ability to detect damage and flaws in civil engineering structures, deep learning (DL) gradually gained substantial attention among researchers in recent years. The main goal of this paper is to review the most recent publications in SHM related to bridges, buildings, and pipelines using emerging OFS and DL-based applications, and to provide readers with an overall knowledge and understanding of various SHM applications. Finally, current research trends and future research needs have been identified. |
Keywords | Civil engineering structures; Deep learning; Distributed optical fibre sensors; Fibre Bragg grating sensors; Structural health monitoring |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400503. Complex civil systems |
400605. Optical fibre communication systems and technologies | |
400599. Civil engineering not elsewhere classified | |
409902. Engineering instrumentation | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | Centre for Future Materials |
Centre for Future Materials (Research) | |
Uva Wellassa University of Sri Lanka, Sri Lanka | |
University of Ruhuna, Sri Lanka |
https://research.usq.edu.au/item/q7vq8/fibre-optic-sensor-and-deep-learning-based-structural-health-monitoring-systems-for-civil-structures-a-review
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