Research on intelligent identification technology for cracks in railway tunnel linings
铁路隧道衬砌裂缝智能识别技术研究

摘要

铁路隧道衬砌裂缝的智能识别技术对于提高隧道建设与运营的安全性具有重要意义。传统的裂缝检测方法依赖人工检查或基础的自动化设备，存在检测效率低、误差大等问题。随着人工智能、计算机视觉及深度学习技术的快速发展，基于图像处理和机器学习的智能识别技术逐渐成为解决这一难题的有效手段。本文探讨了铁路隧道衬砌裂缝的智能识别技术的应用，重点分析了现有技术的优势与局限，并提出了适用于隧道衬砌裂缝识别的优化方案。通过数据集的构建和模型训练，提升裂缝检测的准确性和效率，为隧道衬砌的维护和管理提供有效的技术支持。

Abstract

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.