Advances in Constructional Engineering

The intelligent identification technology for cracks in railway tunnel linings is of great significance for enhancing the safety of tunnel construction and operation. Traditional crack detection methods rely on manual inspection or basic automated equipment, which have problems such as low detection efficiency and large errors. With the rapid development of artificial intelligence, computer vision, and deep learning technologies, intelligent identification technology based on image processing and machine learning has gradually become an effective means to solve this problem. This paper discusses the application of intelligent identification technology for cracks in railway tunnel linings, focuses on analyzing the advantages and limitations of existing technologies, and proposes an optimization scheme suitable for crack identification in tunnel linings. Through the construction of datasets and model training, the accuracy and efficiency of crack detection are improved, providing effective technical support for the maintenance and management of tunnel linings.

Intelligent identification technology; Railway tunnels; Lining cracks; Deep learning; Image processing