A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring
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(...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Infrastructures |
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| Online Access: | https://www.mdpi.com/2412-3811/7/10/141 |
| _version_ | 1797472634474070016 |
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| author | Mohammed Abbas Mousa Mustafasanie M. Yussof Lateef N. Assi SeyedAli Ghahari |
| author_facet | Mohammed Abbas Mousa Mustafasanie M. Yussof Lateef N. Assi SeyedAli Ghahari |
| author_sort | Mohammed Abbas Mousa |
| collection | DOAJ |
| description | 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(ε<sub>x</sub>) 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(ε<sub>x</sub>) 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(ε<sub>x</sub>) variance and the linear least square criterion (R<sup>2</sup>) 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(ε<sub>x</sub>) values with a variance reduction of up to (90%) when averaged images were used. The (R<sup>2</sup>) 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. |
| first_indexed | 2024-03-09T20:04:10Z |
| format | Article |
| id | doaj.art-c4e02d6389ab4bb592afaa43390c46d3 |
| institution | Directory Open Access Journal |
| issn | 2412-3811 |
| language | English |
| last_indexed | 2024-03-09T20:04:10Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Infrastructures |
| spelling | doaj.art-c4e02d6389ab4bb592afaa43390c46d32023-11-24T00:36:41ZengMDPI AGInfrastructures2412-38112022-10-0171014110.3390/infrastructures7100141A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure MonitoringMohammed Abbas Mousa0Mustafasanie M. Yussof1Lateef N. Assi2SeyedAli Ghahari3School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal 14300, Pulau Pinang, MalaysiaSchool of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal 14300, Pulau Pinang, MalaysiaDepartment of Civil Engineering, Mazaya University College, Nasiriyah 64001, IraqDepartment of Civil and Environmental Engineering, Purdue University, West Lafayette, IN 47907, USAThis 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(ε<sub>x</sub>) 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(ε<sub>x</sub>) 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(ε<sub>x</sub>) variance and the linear least square criterion (R<sup>2</sup>) 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(ε<sub>x</sub>) values with a variance reduction of up to (90%) when averaged images were used. The (R<sup>2</sup>) 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.https://www.mdpi.com/2412-3811/7/10/141concrete archDICdigital image correlationpre-processstructurevision-based method |
| spellingShingle | Mohammed Abbas Mousa Mustafasanie M. Yussof Lateef N. Assi SeyedAli Ghahari A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring Infrastructures concrete arch DIC digital image correlation pre-process structure vision-based method |
| title | A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring |
| title_full | A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring |
| title_fullStr | A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring |
| title_full_unstemmed | A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring |
| title_short | A Pre-Process Enhanced Digital Image Correlation Approach for Smart Structure Monitoring |
| title_sort | pre process enhanced digital image correlation approach for smart structure monitoring |
| topic | concrete arch DIC digital image correlation pre-process structure vision-based method |
| url | https://www.mdpi.com/2412-3811/7/10/141 |
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