Publications / 2024 Proceedings of the 41st ISARC, Lille, France
Regular inspections, effective management, and timely maintenance are critical issues to ensure bridge safety and quality. Currently, visual inspection remains the predominant method employed worldwide for bridge inspection. However, visual inspection heavily relies on the training, experience, and subjective judgment of inspectors, leading to inconsistent assessments. When applying deep learning techniques to assist in identifying bridge crack formations, challenges persist. Some images may not clearly display the crack's location. Infrared thermography, with its non-contact, non-destructive properties, effectively detects surface delamination in concrete bridges. However, most research employs higher-spec infrared thermography, which comes with higher instrument costs and less economic viability. Hence, this study aims to investigate the feasibility of using lower-spec infrared thermography to detect surface delamination in concrete bridges as well as analyze the potential of using lower-spec infrared thermography results to assist AI image recognition of bridge surface defects.