Abstract: Aiming at the existing problems of incomplete parameter monitoring, inflexible control mode, and unfriendly human-machine interface in the monitoring system of the main ventilation fan in Huayang No.1 Mine, the intelligent management and control system of the mine main ventilation fan is studied. Based on controller and sensor theories, an intelligent management and control scheme is proposed with PLC controller as the core, integrating improved particle swarm optimization fuzzy PID adjustment algorithm and LSTM fault prediction model. The sensor data of the main ventilation fan is periodically collected by utilizing the acquisition module, and after analysis and calculation by the PLC controller, control instructions are issued to the lower computer; It receive operational data from the lower computer and transmit them uniformly to the upper computer and remote terminal equipment to achieve parameter monitoring, intelligent adjustment, fault early warning, and dynamic optimization of the main ventilation fan. After completing the experimental analysis, the results show that the designed intelligent management and control system for the mine used main ventilation fan has a complete parameter monitoring function, which can flexibly and accurately control the main ventilation fan. It is beneficial for maintenance personnel to carry out their work and improve the safety and economy of mine ventilation.