Multi-Sensor Data Fusion Technology Based on BP Neural Network Application in the Coal Mine Equipment Fault Diagnosis

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.