基于改进PSO-BP神经网络的煤炭港口带式输送机节能算法模型

Energy Saving Algorithm Model of Coal Port Belt Conveyor Based on Improved PSO-BP Neural Network

带式输送机是煤炭港口的主要生产设备。目前大多数带式输送机都是匀速运行,带速不能随着负载的变化而实时调整。因此带式输送机大部分时间都处于低负荷或空载,降低了电能的利用率以及电机的工作效率,增加了企业的运行成本。针对这些问题,设计了一种带式输送机控制算法,根据输送带上煤流量的大小调整带速,以此提升带式输送机的工作效率,从而达到节能的目的。

Belt conveyor is the main production equipment of coal port. At present, most belt conveyors are working at a uniform speed, the belt speed can not be adjusted in real time with the change of load.Therefore, the belt conveyor often run under low load or no load, which reduces the utilization rate of electric energy and the working efficiency of the driving motor, and increases the operating cost of enterprises. In view of these problems, designed a kind of a belt conveyor control algorithm, which can adjust the belt speed according to the coal flow volume on the conveyor belt, in order to improve the working efficiency of belt conveyor, so as to achieve the purpose of energy saving.