Abstract: Due to single-unit upsizing and increased quantity, the failure rate of vibrating screens in large coal preparation plants has risen. Maintenance work primarily focuses on emergency repairs, while existing research is predominantly experimental, with monitoring points mainly concentrated on damping springs. In response to the aforementioned issues, and using the Xiaobao Dang Coal Preparation Plant as the application scenario, a smart monitoring and diagnostic system for vibrating screens was developed based on an analysis of the screen′s structure and motion characteristics. The system is designed for practical industrial environments and consists of three layers: data acquisition, analytical diagnosis, and application. Key measurement points were selected at four critical locations on the exciter and screen side plates. Hardware such as uniaxial/triaxial IEPE accelerometers and temperature sensors were deployed to collect vibration and temperature signals. By analyzing trends in data patterns such as acceleration, temperature, and motion trajectory, the system provides feedback on the operational status of the vibrating screen, classifying it into different health and degradation levels. The results show that after the system was put into use, it successfully gave early warnings of the failure of the shock-absorbing spring at the rear end of the non-driving end and a universal shaft fault of the 2214^# raw coal classifying screen, and the equipment returned to normal after maintenance. The number of unplanned shutdowns decreased from 2 times before the system was put into use to 0, the fault duration was reduced by 120 minutes, the daily maintenance workload decreased by 33.33%, and the operating duration increased by 0.65%. The system has effectively realized real-time monitoring and fault early warning of vibrating screens, promoted the transformation of maintenance work from passive emergency repair to active prevention, improved the equipment management level of coal preparation plant, and provided a useful reference for intelligent transformation of the industry.