Tension force prediction method for mine-used belt conveyor

In view of problem that existing tension force detection device of belt conveyor could not realize real-time prediction of tension force according to load, a tension force prediction method based on BP neural network was proposed. Firstly, the relationships among the tension force, running resistance and load of the belt conveyor were analyzed, and the relationship between the load and motor current of the belt conveyor was explored. Then BP neural network was established to predict the load. According to the functional relationship between load and tension force, load variation trend in the running process of the belt conveyor was obtained, and the tension force was real-timely predicted by the load. The belt conveyor was adjusted adaptively according to the predicted tension force. The experimental results show that the prediction accuracy of the method is 92.1%, which can meet demand of real-time prediction of tension force of belt conveyor.