Abstract: ［Objective］ In response to issues such as periodic wind pressure caused by high-speed train operations in metro tunnels and fastener loosening due to equipment self-excitation, traditional manual maintenance suffers from delayed responses and insufficient predictive capabilities. It is urgently necessary to develop an intelligent early-warning system to achieve equipment status real-time monitoring and risk alerting, thereby improving the efficiency of operation and maintenance management. ［Method］ Based on the tunnel equipment loosening mechanism, a metro tunnel equipment safety early-warning system is constructed using static-dynamic analysis. The system collects vibration data through distributed sensors, extracts vibration features, and adopts a centralized management model for real-time monitoring and intelligent early-warning of equipment vibration status. Taking a specific metro station tunnel as an example, a comparative analysis for laboratory simulation and in-situ tunnel test is conducted. ［Result & Conclusion］ The safety early-warning system for metro tunnel equipment based on static-dynamic analysis could meet the design requirements in terms of early warning accuracy. The system enables a transition from passive response to proactive prevention in equipment maintenance, and establishes a comprehensive technical framework encompassing data acquisition, intelligent analysis, and decision support. It achieves timely identification of abnormal equipment vibration and risk forecasting, forming a unified and efficient operation and maintenance management mechanism, and effectively reduces the risk of equipment failure.