Abstract: In response to safety hazards such as wind-induced excessive vibration, localized stress concentration, and failure of wind uplift resistance in enclosure structures that are prone to occur in large-span steel structures of large-scale terminal buildings under complex coastal super typhoon conditions, this paper takes the Zhuhai Airport T2 Terminal as an engineering case study. A structural health monitoring system covering the entire life cycle from construction to operation and maintenance was designed and implemented. Tailored to the large-span steel structural system of the T2 terminal and the unique high-salt, high-humidity, and high-temperature marine climate characteristics, the system integrates 13 types of sensing devices, including fiber Bragg gratings, vibrating wire strain gauges, wind pressure sensors, and accelerometers, to establish a multi-parameter collaborative monitoring network. Through the comprehensive design of subsystems such as sensors, data acquisition and transmission, data storage and management, and condition identification and evaluation, real-time perception of key indicators—including structural deformation, stress and strain, wind load, and dynamic characteristics—has been achieved. During the direct impact of Typhoon "Whipha," the system successfully acquired high-resolution data throughout the entire process, confirming a strong correlation between structural responses and wind load excitation, thereby enabling more accurate diagnosis of structural conditions. The research results indicate that the system operates stably under extreme weather conditions such as strong typhoons, accurately capturing dynamic responses and stress variations in the structure, with a sustained data availability rate of over 95%. The specialized measures implemented for corrosion prevention and lightning protection have effectively ensured its long-term durability in the high-temperature, high-humidity, and highly corrosive coastal environment. Ultimately, the system demonstrates comprehensive monitoring capabilities integrating intelligent warning, multi-terminal interaction, and big data analysis. The research findings also provide valuable references for structural health monitoring and safety maintenance of similar large-scale public buildings.