Abstract
Due to the imbalance of coal mine production, belt conveyors fail to reach full load in most cases, which not only causes waste of electric energy, but also increases equipment loss. Aiming at the above problems, this paper uses BP neural network to establish an energy-saving optimization model of belt conveyor coal flow, belt running speed and system power. The particle swarm optimization algorithm is used to optimize the model parameters, and the optimal matching map of coal flow rate and belt speed is obtained. The fuzzy control theory was used to design the control system of the belt conveyor. The simulation was carried out with MATLAB and the energy saving effect was analyzed.
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