Issue |
E3S Web Conf.
Volume 631, 2025
6th International Conference on Multidisciplinary Design Optimization and Applications (MDOA 2024)
|
|
---|---|---|
Article Number | 01001 | |
Number of page(s) | 8 | |
Section | Prediction and Optimization for Advance Proceeding and Health Monitoring | |
DOI | https://doi.org/10.1051/e3sconf/202563101001 | |
Published online | 26 May 2025 |
Crack Detection in Civil Infrastructure: A Method-Scenario Review
1 IRAMAT, UMR-7065, Université Technologique de Belfort-Montbéliard, 90010 Belfort Cedex, France.
2 Smart Structural Health Monitoring and Control Lab (SSHMC) Lab, DGUT-Cnam Institute, Dongguan University of Technology, D1, Daxue Rd., Songshan Lake, Dongguan, Guangdong Province, P.R. China
3 School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China
4 Jiaozuo Engineering Research Center of Road Traffic and Transportation, Henan Polytechnic University, Jiaozuo, Henan 454000, China
a) haochen.chang@utbm.fr
b) guweifan1@126.com
c) guobaohua@139.com
d) david.bassir@utbm.fr
Ensuring the structural safety of civil infrastructure is vital for public welfare and cost-effective maintenance. Crack detection, as a key indicator of structural health, has transitioned from traditional image processing to advanced deep learning methods. This paper presents a systematic review of crack detection technologies organized under a novel “method-scenario” framework that categorizes techniques based on their underlying algorithms and the specific application contexts (e.g., pavements, bridges, tunnels, and specialized materials). By comparing conventional image processing approaches with modern deep learning models and multi-modal fusion techniques, we highlight the strengths and limitations of each method in various real-world scenarios. Our analysis reveals critical challenges—including data scarcity, sensitivity to noise, and the gap between theoretical models and practical deployment—which must be addressed to enhance reliability and generalizability. We conclude by proposing future research directions focused on integrating physics-based constraints with lightweight computational models and establishing unified evaluation protocols to bridge the gap between laboratory precision to engineering implementation.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.