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Dataset to track concrete cracking using DIC with fixed and moving camera
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Concrete Structures.ORCID iD: 0000-0001-8375-581X
Sapienza University of Rome. (Divison of Geoinformatics)ORCID iD: 0000-0003-4765-0281
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.ORCID iD: 0000-0001-9692-8636
2022 (English)Data set
Abstract [en]

Today, Digital Image Correlation (DIC) has become a standardized method to track displacements and crack-propagation of civil engineering structures in a laboratory environment. The benefit of using DIC over other standard methods is that it is contact-free and only requires a standard DSLR camera. Moreover, the displacement can be tracked over the entire image, which is a great advantage compared to the limitations of standard sensors that only measure the deformation at a specific point. In standard DIC, the displacements are directly extracted from the images. Hence, the position of the camera must be fixed during the entire test. Therefore, DIC is commonly used in a laboratory environment to measure displacement during short-term testing, e.g. testing of the structural capacity of a reinforced concrete beam. The data presented in this paper was used to verify a newly developed and innovative photogrammetric algorithm, Deformation from Motion (DfM). This algorithm overcomes the standard limitation of traditional DIC and enables high-accuracy measurements to be performed using a camera with no fixed position. As a reference, the crack propagation was on one side monitored with a LVDT and on the other side with a camera with a fixed position. During testing, a moving camera also captured imagery on both sides.

Place, publisher, year
2022.
Version
1.0
Keywords [en]
Digital Image Correlation, Crack Monitoring from Motion, Cracked concrete
National Category
Infrastructure Engineering
Research subject
Civil and Architectural Engineering, Concrete Structures; Geodesy and Geoinformatics, Geoinformatics
Identifiers
URN: urn:nbn:se:kth:diva-336505DOI: 10.17632/dns97tfdjn.1OAI: oai:DiVA.org:kth-336505DiVA, id: diva2:1796295
Projects
TACK -Tunnel Automatic CracK Detection
Funder
Vinnova, InfraSweden2030EU, Horizon 2020, 101012456
Note

QC 20230913

Available from: 2023-09-12 Created: 2023-09-12 Last updated: 2023-09-13Bibliographically approved

Open Access in DiVA

bilaga(1970 kB)43 downloadsDescription of content
File information
File name ATTACHMENT01.pdfFile size 1970 kBChecksum SHA-512Description Description on how to use the dataset. All data is available at Mendeley Data
381653ee0043de784977558019c51af4bc56f0f8de2828f8bd52c07139124455aa5c43fb134c6b75d64cf3195601cda36dbfad9d8b184bec185ff4fca85fb592
Type attachmentMimetype application/pdf

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Sjölander, AndreasNascetti, Andrea

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Sjölander, AndreasBelloni, ValeriaNascetti, Andrea
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Citation style
  • apa
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Output format
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  • text
  • asciidoc
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