Data · dataset · 2022
Distributed Optic Fibre Sensor data, Digital Image Correlation data and Actuator data.
Listed in Researchdata.se
The implementation of structural health monitoring systems in existing civil engineering structures could contribute to a safer and more resilient infrastructure as well as important savings.
Description
Due to their light weight, small size, and high resistance to the environment, distributed optical fibre sensors (DOFS) stand out as a very promising technology for damage detection and quantification in reinforced concrete structures.
This dataset includes information of DOFS featuring an external polymeric cladding with rough surface, deployed in a stainless-steel reinforced concrete beam subjected to four-point bending. Several sensor positions, both embedded in the concrete and attached to the surface, are included in a multilayer configuration. The data of the sensors includes two series of test, first cyclic loading under service loads and lastly cyclic loading to failure.
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Additionally, data from Digital Image Correlation and the actuator recordings are included for cross-validation purposes. The data included in this dataset basically consists in strain measurement of fibre optic sensor, i.e. BRUSens V9 cable, attached at different places on a Stainless-steel Reinforced Concrete Beam. The equipment to measure the strains of the sensor is an ODISI 6004 from Luna ink. which uses the Rayleight backscatter technology.
In addition, Digital Image Correlation data is included offering mid-span deflections of the beam. The equipment used for the acquisition of the images and the corresponding displacement fields is a ARAMIS from GOM technologies, that features two 12 MP cameras. The dataset is available in MatLab and GNU Octave/txt (gnu.org/software/octave/index) formats.
Links
Where it is published
- DOI doi.org/10.5878/rnn3-dy47 ↗
DOI / persistent id · from researchdata se
Catalogue records · 1
- OAI-PMH record api.researchdata.se/oai-pmh?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3A… ↗
metadata API · from researchdata se
Topics
- From keywords
- Earth & Environmental Science · Engineering
- Inferred from text
- Image 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Researchdata.se | oai:researchdata.se:2021-291-1/1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata se | connector:researchdata_se@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata se | connector:researchdata_se@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata se | connector:researchdata_se@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata se | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata se | connector:researchdata_se@1.0.0 | /metadata/dc/description |
| license_text | source · researchdata se | connector:researchdata_se@1.0.0 | |
| publication_date | source · researchdata se | connector:researchdata_se@1.0.0 | |
| title | source · researchdata se | connector:researchdata_se@1.0.0 | /metadata/dc/title |