Ball mill states classification using competitive neural networks

Abstract

A competitive neural network is proposed to be used to process a vibration acceleration signal from pilot ball mill pins in order to determine the filling level of its drum. It is experimentally proved that the neural network is able to detect the mill state characterized by its drum filling level under the condition of disturbances. Experimental results show the feasibility of the proposed method.