金属结构和设备在使用过程中的腐蚀不仅会导致巨大经济损失，还可能引发环境污染和安全隐患。因此，采取快速的腐蚀检测与分析技术显得尤为重要。随着人工智能算法的不断进步，其在腐蚀图像检测与分析领域展现出巨大潜力。文章综述了人工智能，特别是计算机视觉技术和深度学习的发展，探讨了其如何改变传统检测技术的格局，并通过自动化、数据分析和特征提取等方法，有效解决腐蚀图像检测与分析的效率和准确性。最后，总结了人工智能在该领域中需要解决的一些关键问题，旨在探讨人工智能在腐蚀研究领域的应用潜力，为未来检测与评估技术的研究提供新视角，促进人工智能广泛应用。

The corrosion of metal structures and equipment in use not only lead tosignificant economic losses，but also may cause environmental pollution and potential safety hazards. Therefore，it is particularly important to adopt rapid corrosion detection and analysistechniques. With the continuous progress of technology，artificial intelligence（AI）algorithmsshowed great potential in the fields of corrosion image detection and analysis. In this paper，the development of AI，especially computer vision technology and deep learning was reviewed，and how they could change the pattern of traditional detection methods was discussed. Through themethods of automation，data analysis and feature extraction，many challenges in corrosion image detection and analysis could be solved. In short，the integration of AI with deep learningcould facilitate automated feature extraction and classification，substantially enhance the detection precision and efficiency. Additionally，some key challenges to solve in this field werealso summarized. The purpose was to explore the potential applications of AI in corrosionresearch，provide a new perspective for the future research of detection and evaluationtechnologies，and promote the wider adoption of AI.