Research On Monitoring And Management Platform Of IOT In Coal Mine Electromechanical Equipment

Electromechanical equipment is the basic guarantee of safety in production of coal mining enterprises, with closely related to the life operators, and also a key factor in the impact of enterprise efficiency. Therefore, scientific management methods can effectively improve the safety and efficiency of equipment operation.Aimed at the management of electromechanical equipment of the coal mining enterprises, based on the theoretical framework of IoT, this research developed an electromechanical equipment monitoring and management platform set by the sensing layer, the network layer and the application layer. The sensing layer including handheld terminals and embedded acquisition terminal. The handheld terminal read the IC card of device identification through RFID technology to achieve the data sheet of device parameters return back. The embedded acquisition terminal real-time acquires key operating parameters of equipment back to the database regularly. The network layer based on WLAN technology. The system placed with a wireless LAN. The application layer includes the monitoring platform software, the database and the web server. Those parts achieve the role of human-computer interaction systems, data storage, and interactive media of the database and the terminal respectively.This paper introduces the theory of systems which includes theory and key technology of things. Combined with the issue of demand, the electromechanical equipment management system of three layers is designed for coal mining; for the issue of electromechanical equipment failure classification, the theory of BP neural network is introduced for modeling.Based on the experimental base in Nanfeng work area, Wuyang coal mine, Luan Group, the overall structure of the system is designed. The implementation of hardware and software are expounded respectively. The aspect of hardware includes the implementation of the application layer, the network layer and the sensing layer. The aspect of software includes the implementation of four major modules which are the monitoring platform software, the web servers, the handheld terminals and the embedded Linux applications.Finally, the results for system commissioning and the simulation experiment of BP neural network for the fault diagnosis are introdused.The advancement of this system is that the advanced IoT technology is introduced to the field of electromechanical equipment management to ensure the normative of the management work of the electromechanical equipment and timeliness of the its data, and improve the level of information equipment management.