Abstract: To effectively improve tunnel management and maintenance efficiency, the internal and apparent tunnel diseases are summarized and a tunnel structure health management big data platform is established using Spring Boot with MyBatisPlus architecture and Redis and MySQL distributed deployment. Additionally, the field application is conducted through equipment management, disease management, and big data analysis. Consequently, the results reveal that (1) the big data platform for tunnel structural health management can meet the functional requirements of common disease data management and display, and the interface is simple and friendly, realizing the scientific decisionmaking of tunnel diseases; (2) based on the neural network model, the platform achieves the intelligent recognition of apparent tunnel disease and reduces the dependence on manual disease recognition; and (3) the platform supports multidimensional queries of disease information via personal computers and mobile terminals, thereby solving the problem of delayed and inconvenient access to tunnel disease information. 〖ＢＰ（〗Thus, this platform, which has a friendly interface and convenient operation, can provide realtime data support for professional personnel to evaluate the health status of tunnels, thereby making it worth popularizing.

Key words: railway tunnel, disease detection, big data platform; disease forecast