Monitoring System of Coal Electrical Haulage Shearer Based on Data Fusion Theory

The electrical haulage coal shearer is very important cutting equipment in underground digging coal working space and plays a vital role for the coal mining production. But the coal mining environments are very harsher than ground, the shearer is often broken and stopping work, so its working states must be monitored. In this paper, a novel coal real-time monitoring system for the electrical haulage coal shearer is proposed based on multi-sensor data fusion theory. The four different kinds of sensors are used to supervise temperature, smog thickness, motor voltage and current for the key parts of the shearer. Fuzzy logic characteristic fusion algorithm and the quantum neural network fusion algorithm are adopted for fault diagnosis. The ARM12 is used as the master chip to carry out the on-line monitoring running parameters, and the Lab VIEW software is used to real-time display the running state of the shearer via CAN bus. The theory analysis and simulation results show that the system has higher reliable and more practical.