Neural Network Model of Information Fusion for Coal Storage and Kinetic Energy of Ball Mill

Abstract

Abstract: A dynamic mathematical model of coal pulverizing system was analyzed. Simulation experiments on mill operation process were conducted by PFC3D software platform based on discrete element method. The associated data between different coal quality, coal storage and balls' motion were obtained under certain quantitative optimized operating parameters configuration. Neural network model of information fusion for coal storage and kinetic energy of ball mill was established by using an adaptive combination learning algorithm. Coal storage in mill cylinder was predicted from the energy point of view. The results indicate that there is a close relationship between coal storage, pulverizing efficiency and balls' real-time kinetic energy. The neural network information fusion model has good predictive power to coal storage. The coal storage control method based on balls' kinetic energy is therefore feasible for optimized operation of the coal pulverizing system.

Key words: ball mill, coal storage, PFC3D, energy, information fusion, neural network

CLC Number:

TP391.9

Bai Yan, He Fang. Neural Network Model of Information Fusion for Coal Storage and Kinetic Energy of Ball Mill[J]. Journal of System Simulation, 2015, 27(4): 689-696.

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