Thermal imaging for void detection and quantification in precast grouted structures using computer vision
Grout penetration plays a pivotal role in ensuring the structural integrity and longevity of precast structural elements in construction industry. Insufficient grout penetration can lead to weak points in the structure, posing risks of leaks, collapses, and other forms of damage. This study analyzes...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824015527 |
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| author | Varun Patrikar G. Malathi M.Helen Santhi Huseyin Bilgin |
| author_facet | Varun Patrikar G. Malathi M.Helen Santhi Huseyin Bilgin |
| author_sort | Varun Patrikar |
| collection | DOAJ |
| description | Grout penetration plays a pivotal role in ensuring the structural integrity and longevity of precast structural elements in construction industry. Insufficient grout penetration can lead to weak points in the structure, posing risks of leaks, collapses, and other forms of damage. This study analyzes the thermal images of grout-filled pipes to identify the areas of insufficient grout penetration using computer vision algorithms. A mathematical framework is developed to estimate unfilled grout volumes. The research compares the performance of pre-trained segmentation models and traditional image segmentation techniques, highlighting their effectiveness and limitations in detecting voids. Results demonstrate the superior accuracy of pre-trained models for anomaly detection, offering a promising approach for assessing the grout integrity in precast construction. |
| format | Article |
| id | doaj-art-3d6cf37ff4b44e0a8ceec1e9a9eff4cf |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-3d6cf37ff4b44e0a8ceec1e9a9eff4cf2024-12-11T05:54:58ZengElsevierAlexandria Engineering Journal1110-01682025-02-01114608620Thermal imaging for void detection and quantification in precast grouted structures using computer visionVarun Patrikar0G. Malathi1M.Helen Santhi2Huseyin Bilgin3School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, IndiaSchool of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India; Corresponding author.School of Civil Engineering, Vellore Institute of Technology, Chennai, IndiaDepartment of Civil Engineering, Epoka University, Tirana, AlbaniaGrout penetration plays a pivotal role in ensuring the structural integrity and longevity of precast structural elements in construction industry. Insufficient grout penetration can lead to weak points in the structure, posing risks of leaks, collapses, and other forms of damage. This study analyzes the thermal images of grout-filled pipes to identify the areas of insufficient grout penetration using computer vision algorithms. A mathematical framework is developed to estimate unfilled grout volumes. The research compares the performance of pre-trained segmentation models and traditional image segmentation techniques, highlighting their effectiveness and limitations in detecting voids. Results demonstrate the superior accuracy of pre-trained models for anomaly detection, offering a promising approach for assessing the grout integrity in precast construction.http://www.sciencedirect.com/science/article/pii/S1110016824015527Thermal imagingPrecast grout-filled pipesComputer visionMachine learningImage segmentation |
| spellingShingle | Varun Patrikar G. Malathi M.Helen Santhi Huseyin Bilgin Thermal imaging for void detection and quantification in precast grouted structures using computer vision Alexandria Engineering Journal Thermal imaging Precast grout-filled pipes Computer vision Machine learning Image segmentation |
| title | Thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| title_full | Thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| title_fullStr | Thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| title_full_unstemmed | Thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| title_short | Thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| title_sort | thermal imaging for void detection and quantification in precast grouted structures using computer vision |
| topic | Thermal imaging Precast grout-filled pipes Computer vision Machine learning Image segmentation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824015527 |
| work_keys_str_mv | AT varunpatrikar thermalimagingforvoiddetectionandquantificationinprecastgroutedstructuresusingcomputervision AT gmalathi thermalimagingforvoiddetectionandquantificationinprecastgroutedstructuresusingcomputervision AT mhelensanthi thermalimagingforvoiddetectionandquantificationinprecastgroutedstructuresusingcomputervision AT huseyinbilgin thermalimagingforvoiddetectionandquantificationinprecastgroutedstructuresusingcomputervision |