Abstract: To improve the operation and maintenance management level of coal mine electromechanical equipment, research and development of a coal mine electromechanical equipment supervision platform based on Internet of Things technology will be carried out. Discuss from the aspects of overall system architecture, fault diagnosis, hardware and software structure, etc. Propose a fault diagnosis method based on BP neural network model, construct a system architecture that integrates multiple technologies, and implement a hierarchical hardware system. After deploying 315 sensors on 126 key electromechanical equipment in a large coal mine for testing, it was found that the wireless communication signal had excellent fluctuations, the equipment status perception was accurate, and abnormal detection was timely, achieving the effect of ensuring stable equipment operation, improving coal mine production efficiency and safety management level, and solving problems such as untimely equipment monitoring and difficult fault warning in traditional management.