Abstract
This study addresses the challenges of low accuracy and poor timeliness in feeding metallic foreign object detection during high-output continuous crushing operations in coal mines. Based on the PEC method and TREE method, the time-domain solution for coaxial excitation, receiving coils, and Hall sensors interacting with the truncated region reflection eddy current field of feeding metallic foreign objects is calculated. The effect of the lift-off effect on the characteristic classification and identification of feeding metallic foreign objects is analyzed in detail. The sensitivity of the lift-off distance to the peak value and time to peak in PEC signals is compared, and the relationship between the LOI coordinates and the characteristics of feeding metallic foreign objects is established. Simulation and experimental results show that the PEC signals from the metallic foreign object detection system, processed by the DWT-TLBO noise reduction algorithm, enable the classification and identification of the falling position, size, conductivity, and magnetic permeability of feeding metallic foreign objects based on the lift-off point, peak value, time to peak, and effective time range. Experimental results meet the practical requirements for metallic foreign object detection in coal mine sites.