SELF-LEARNING ENERGY-SAVING SPEED REGULATION STRATEGY OF BELT CONVEYOR

Abstract

At present, most belt conveyors operate at a constant speed, which causes very high energy consumption. In order to intelligently adjust the belt speed during the operation of the belt conveyor, reduce energy consumption. This paper presents a self-learning energy- saving speed regulation strategy for belt conveyor. In order to verify the strategy, this paper takes a belt conveyor as an example, and establishes the belt speed-carrying energy consumption model of belt conveyor. Secondly, this strategy combines the piecewise fuzzy PID control method with the self-learning optimisation method. The piecewise fuzzy PID control method is applied to effectively ensure the safety, reliability and accuracy of the belt conveyor speed regulation process, and the self-learning optimisation method is applied to make the belt conveyor automatically modify the carriage-belt speed energy consumption model according to the change of running power. Finally, Simulink toolbox is used to build a simulation model to verify the strategy. The results show that the strategy can effectively adjust the belt speed in the whole life cycle of the belt conveyor, so as to solve the problem of energy consumption caused by the fluctuation of carrying capacity in different running stages. The research results have important guiding significance for realising the energy saving and emission reduction operation of belt conveyor.