摘要
Abstract
In view of the problems of low pushing and movement location control accuracy,slow machine following speed and others in the automatic machine following of the S1204 working face hydraulic support in Wangcun Coal Industry,a precise pushing and movement control algorithm based on BP neural network to predict advance action distance and a strategy of automatic machine following for installing energy accumulator are proposed by using ways of theoretical analysis,experimental research and so on.Collecting the status of the support hydraulic system and controlling the pushing and movement hydraulic cylinder,the control accuracy of the hydraulic cylinder is improved from 40-80 mm to within 20 mm,and the control accuracy is significantly improved,indicating the effectiveness of using the BP neural network predictive control algorithm.The bracket movement process of support is divided into four intervals:lowering column,pulling frame,switching between pulling frame and lifting column,and lifting column.Using 95%to predict the upper limit of the prediction interval method,according to the liquid inlet pressure to predict the pulling frame action time.After installing an energy accumulator at the liquid inlet end of the support,the pulling frame time is reduced from 6.54 s to 5.39 s,a decrease of 1.15 s;The average value of speed improves from 0.147 m/s to 0.177 m/s,with a speed increase of 20.9%,verifying the effectiveness of the rapid machine following control method.关键词
液压支架快速推移/自动跟机/基于BP网络预测Key words
hydraulic support rapid pushing and movement/automatic machine follow/prediction based on BP network分类
矿业与冶金
