Design of collecting and computing platform used for predictive maintenance of coal mine electromechanical equipment

Abstract

Existing operation maintenance mode of coal mine electromechanical equipment is collecting data in underground and analyzing data by ground controller or cloud platform, which has poor real-time performance and flexibility, limited data collection amount, high cost, etc.While predictive maintenance solution scheme in general industry of edge computer plus data collection card is not applicable for operation maintenance of coal mine electromechanical equipment because of difficulty of mine-used intrinsically safe design, poor flexibility of field arrangement, too high cost, etc. For the above problems, a collecting and computing platform used for predictive maintenance of coal mine electromechanical equipment was designed, which was based on main controlling chip of STM32F4. The platform can parallel collect vibration, temperature, pressure and other data of coal mine electromechanical equipment with high speed and take out fast Fourier transform and envelope spectrum analysis real-timely, so as to obtain health status of the electromechanical equipment. The monitored data and diagnosis results can be displayed through man-machine interaction module on the spot, and be transferred to underground controller or cloud platform through Ethernet for large-scale data analysis. The test results show that the platform has measuring errors of less than 4% for vibration signals, and can correctly judge running status and faults of different components in the electromechanical equipment, which meets requirements of real-time calculation, analysis on the spot and flexible arrangement in coal mine field.

Keywords

• smart mine
• coal mine electromechanical equipment
• predictive maintenance
• edge computing
• vibration signal analysis
• fault diagnosis