Effectively monitoring and controlling the material’s level in ball mills

are the key for optimizing operation

energysaving

and consumptionreducing of the coal pulverizing system. Directing against operation features of ball mills

a BP neural network model has been established to classify a variety of parameters under various working conditions in operation

and the adaptive monitoring of material’s level being realized. The results of emulation show that the said neural network has good effectiveness

laying a foundation for optimized operation and automatic control of the coal pulverizing system.