In this paper, for the frequent faults problems of the mine air compressor main motor, we use the BP neural network learning algorithms on the basis of the theory of multi-sensor data fusion. The collected characteristic signals were processed by the method of data fusion, and we could get the current motor fault state value. Compared to the experimental results, it can realize the fault diagnosis of mine equipment obviously.

In order to solve the air supply pressure instability problem in mine compressor, a fuzzy-PID controller is designed to be combined with conventional proportional-integral-derivative (PID) control and fuzzy control technology based on the programmable logic controller (PLC), where the compressor air supply system can achieve optimal control based on the system requirements and the actual usage, realizing air supply with constant pressure for compressor.