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Development of method for in-service crack detection based on distributed fiber optic sensors
Abstract
Many bridges worldwide are approaching the end of their lifespan and it is necessary to assess their health condition in order to mitigate risks, prevent disasters, and plan maintenance activities in an optimized manner. Fracture critical bridges are of particular interest since they have only little or no load path redundancy. Structural health monitoring (SHM) has recently emerged as a branch of engineering, which aim is to improve the assessment of structural condition. Distributed optical fiber sensing technology has opened new possibilities in SHM. A distributed deformation sensor (sensing cable) is sensitive at each point of its length to strain changes and cracks. Such a sensor practically monitors a one-dimensional strain field and can be installed over all the length of the monitored structural members, thereby providing with integrity monitoring, i.e. direct detection and characterization (including recognition, localization, and quantification or rating) of local strain changes generated by damage. Integrity monitoring principles are developed and presented in this article. A large scale laboratory test and a real on-site application are briefly presented.
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Citations
Cited by
Reynders, E., Wursten, G., & De Roeck, G. (2014) · Structural Health Monitoring · doi:10.1177/1475921713502836 · Cited by 237
Metadata
- Authors
- Glisic, B., & Inaudi, D.
- Venue
- Structural Health Monitoring
- Publisher
- SAGE Publications
- Published
- 2011-08-09
- Volume
- 11
- Issue
- 2
- Pages
- 161-171
- ISSN
- 1475-9217 (ISSN-L)
- 1741-3168
- OpenAlex
- W2108917711
- Cited by
- 161
- References
- 0
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- Glisic, B., & Inaudi, D. (2012). Development of method for in-service crack detection based on distributed fiber optic sensors. Structural Health Monitoring. https://doi.org/10.1177/1475921711414233
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.