December 10, 2024
Prof. Dr. Hüseyin Bilgin, along with collaborators Varun Patrikar, G. Malathi, and M. Helen Santhi, has published a research article titled "Thermal Imaging for Void Detection and Quantification in Precast Grouted Structures Using Computer Vision" in the Alexandria Engineering Journal (Volume 114, February 2025).
The study introduces a novel approach to enhancing the detection and quantification of voids in precast grout-filled structures. By leveraging thermal imaging and advanced computer vision algorithms, the research addresses the critical issue of insufficient grout penetration, which can compromise the structural integrity of precast elements. A mathematical framework was developed to estimate unfilled grout volumes, and pre-trained image segmentation models were employed for precise anomaly detection.
Key findings demonstrate the effectiveness of machine learning techniques in detecting voids and assessing grout integrity, providing a promising solution for non-destructive testing in the construction industry.
The article is available at: doi.org/10.1016/j.aej.2024.11.080.
