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    <citation>
      <titlStmt>
        <titl xml:lang="sv">Dataset to track concrete cracking using DIC with fixed and moving camera</titl>
        <parTitl xml:lang="en">Dataset to track concrete cracking using DIC with fixed and moving camera</parTitl>
        <IDNo agency="SND">2024-399-1</IDNo>
      </titlStmt>
      <prodStmt>
        <producer xml:lang="en" abbr="SND">Swedish National Data Service</producer>
        <producer xml:lang="sv" abbr="SND">Svensk nationell datatjänst</producer>
      </prodStmt>
      <holdings URI="https://doi.org/10.17632/dns97tfdjn.1">Landing page</holdings>
    </citation>
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  <stdyDscr>
    <citation>
      <titlStmt>
        <titl xml:lang="sv">Dataset to track concrete cracking using DIC with fixed and moving camera</titl>
        <parTitl xml:lang="en">Dataset to track concrete cracking using DIC with fixed and moving camera</parTitl>
        <IDNo agency="SND">2024-399-1</IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty xml:lang="en" affiliation="Royal Institute of Technology">Sjölander, Andreas</AuthEnty>
        <AuthEnty xml:lang="sv" affiliation="Skolan för arkitektur och samhällsbyggnad, Kungliga tekniska högskolan">Sjölander, Andreas</AuthEnty>
        <AuthEnty xml:lang="en" affiliation="Divison of Geoinformatics, Sapienza University of Rome">Belloni, Valeria</AuthEnty>
        <AuthEnty xml:lang="sv" affiliation="Divison of Geoinformatics, Sapienza University of Rome">Belloni, Valeria</AuthEnty>
        <AuthEnty xml:lang="en" affiliation="Royal Institute of Technology">Nascetti, Andrea</AuthEnty>
        <AuthEnty xml:lang="sv" affiliation="Kungliga tekniska högskolan">Nascetti, Andrea</AuthEnty>
      </rspStmt>
      <prodStmt>
        <grantNo xml:lang="en" agency="Vinnova">InfraSweden2030</grantNo>
      </prodStmt>
      <distStmt>
        <distrbtr xml:lang="en" abbr="SND" URI="https://snd.se">Swedish National Data Service</distrbtr>
        <distrbtr xml:lang="sv" abbr="SND" URI="https://snd.se">Svensk nationell datatjänst</distrbtr>
        <distDate xml:lang="en" date="2024-06-26" />
      </distStmt>
      <verStmt>
        <version elementVersion="1" elementVersionDate="2024-06-26" />
      </verStmt>
      <holdings URI="https://doi.org/10.17632/dns97tfdjn.1">Landing page</holdings>
    </citation>
    <stdyInfo>
      <subject />
      <abstract xml:lang="en" contentType="abstract">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.

QC 20230913

The dataset was originally published in DiVA and moved to SND in 2024.</abstract>
      <abstract xml:lang="sv" contentType="abstract">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.

QC 20230913

Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024.</abstract>
      <sumDscr>
        <dataKind xml:lang="en">Still image</dataKind>
        <dataKind xml:lang="en">Software</dataKind>
        <dataKind xml:lang="en">Other</dataKind>
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    <dataAccs>
      <useStmt>
        <restrctn xml:lang="en">Access to data through an external actor. Data are freely accessible.</restrctn>
        <restrctn xml:lang="sv">Åtkomst till data via extern aktör. Data är fritt tillgängliga.</restrctn>
        <conditions elementVersion="info:eu-repo-Access-Terms vocabulary">openAccess</conditions>
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    </dataAccs>
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