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A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring

Author(s): ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Infrastructures, , n. 10, v. 7
Page(s): 141
DOI: 10.3390/infrastructures7100141
Abstract:

This research provides a practical guideline for Digital Image Correlation (DIC) data variations minimization in structural engineering through simple image processing techniques. The main objective of this research is to investigate the Pixel Averaging (P.A.) effect on the differential strain Diff(εx) variations. Three concrete arches were tested with three-point bending using the DIC technique for strain measurements. The measured strains are obtained through two virtual horizontal extensometers in the middle of each arch. The Diff(εx) was selected to avoid other 2D-DIC issues, such as the sample-camera out-of-plane movement. Three image cases, namely, one, ten, and twenty averaged images, were used for DIC analysis of each arch. The conditions of each image case are assessed by computing the Diff(εx) variance and the linear least square criterion (R2) between the two extensometers. The second objective is to examine the speckles’ dilation effects on the speckle pattern density and surface component quality utilizing the Image Erode (I.E.) technique. The (P.A.) technique provided consistent differential strain Diff(εx) values with a variance reduction of up to (90%) when averaged images were used. The (R2) has considerably increased (from 0.46, 0.66, 0.91 to 0.90, 0.96, 0.99), respectively, for the three samples. Moreover, the (I.E.) technique provided qualitatively denser speckles with a highly consistent DIC surface component.

Copyright: © 2022 the Authors. Licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10722806
  • Published on:
    22/04/2023
  • Last updated on:
    10/05/2023
 
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