The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Structural health monitoring: Closing the gap between research and industrial deployment
Open accessAbstract
There has been a large volume of research on structural health monitoring since the 1970s but this research effort has yielded relatively few routine industrial applications. Structural health monitoring can include applications on very different structures with very different requirements; this article splits the subject into four broad categories: rotating machine condition monitoring, global monitoring of large structures (structural identification), large area monitoring where the area covered is part of a larger structure, and local monitoring. The capabilities and potential applications of techniques in each category are discussed. Condition monitoring of rotating machine components is very different to the other categories since it is not strictly concerned with structural health. However, it is often linked with structural health monitoring and is a relatively mature field with many routine applications, so useful lessons can be read across to mainstream structural health monitoring where there are many fewer industrial applications. Reasons for the slow transfer from research to practical application of structural health monitoring include lack of attention to the business case for monitoring, insufficient attention to how the large data flows will be handled and the lack of performance validation on real structures in industrial environments. These issues are discussed and ways forward proposed; it is concluded that given better focused research and development considering the key factors identified here, structural health monitoring has the potential to follow the path of rotating machine condition monitoring and become a widely deployed technology.
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Cites
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Cited by
Structural Health Monitoring for Advanced Composite Structures: A Review
Güemes, A., Fernandez-Lopez, A., Pozo, A. R., & Sierra-Pérez, J. (2020) · Journal of Composites Science · doi:10.3390/jcs4010013 · Cited by 298
Miao, H., & Li, F. (2021) · Ultrasonics · doi:10.1016/j.ultras.2021.106355 · Cited by 268
Vibration-based multiclass damage detection and localization using long short-term memory networks
Sony, S., Gamage, S., Sadhu, A., & Samarabandu, J. (2022) · Structures · doi:10.1016/j.istruc.2021.10.088 · Cited by 140
Structural Health Monitoring Damage Detection Systems for Aerospace
(2021) · Springer Aerospace Technology · doi:10.1007/978-3-030-72192-3 · Cited by 92
Mariani, S., Rendu, Q., Urbani, M., & Sbarufatti, C. (2021) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.107748 · Cited by 86
Metadata
- Authors
- Cawley, P.
- Venue
- Structural Health Monitoring
- Publisher
- SAGE Publications
- Published
- 2018-01-29
- Volume
- 17
- Issue
- 5
- Pages
- 1225-1244
- ISSN
- 1475-9217 (ISSN-L)
- 1741-3168
- OpenAlex
- W2792679127
- Cited by
- 423
- References
- 28
- FWCI
- 33.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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