Research On Precise And Fast Moving Control Of Hydraulic Powered Support In Intelligent Fully Mechanized Mining Face

With the rapid development of fully mechanized mining technology,the main direction of equipment development is towards large-scale and intelligent equipment,which requires high automation level,fast speed,and high precision in equipment operation.Currently,there are problems with inaccurate position control and slow speed during automatic tracking of hydraulic supports,which seriously affects the continuous and stable advancement of intelligent fully mechanized mining faces.This paper conducts researches from three aspects: influencing factors and control of hydraulic cylinder precise moving,influencing factors and control of hydraulic support rapid moving and field test application of hydraulic support accurate and rapid moving.This paper investigates the impact of various factors on the position control accuracy of displacement hydraulic cylinders and the speed of support tracking using modeling &simulation,mathematical models,and laboratory experiments.The precise moving control algorithm and automatic following strategy are proposed and tested in the field.The specific results are as follows:(1)The overshoot of the valve-controlled cylinder system is the main factor affecting the displacement control accuracy.Predicting the advance amount and controlling the cylinder action is one of the effective ways to improve accuracy.Using modeling & simulation and mathematical models,a simulation model of the valvecontrolled cylinder position control system and a mathematical model of the overshoot stage of the system were established.The impact of eight variables such as pump flow rate and friction coefficient on overshoot was studied.Based on this,the main control factors were determined to be pump pressure and load.The valve-controlled cylinder position control test bench was built to conduct push-pull tests of hydraulic cylinders with the main control factors as independent variables.The BP neural network algorithm was used to predict the advance amount based on pump pressure and speed,and the cylinder action was controlled based on this.(2)When different hydraulic cylinders act simultaneously,it will cause fluctuations in the hydraulic system of the working face,which is a key factor affecting the tracking speed.Using modeling & simulation and laboratory experiments,a working face hydraulic system model was established,and a three-machine model test bench was built.By using the control variable method,the impact of factors such as push-pull distance,working face inclination,and shifting process on tracking speed were explored.Based on this,an automatic tracking strategy was proposed.It was suggested that installing an accumulator at the inlet end of the support can weaken the degree of influence of various factors,provide liquid for stabilizing the support,and improve the tracking speed.(3)On the S1204 working face of the Ningtiaota coal mine,a data acquisition and control system was built on the No.69 hydraulic support to collect the hydraulic system state of the support and control the hydraulic cylinder.The control accuracy of the cylinder was improved from 40-80 mm to within 20 mm using the BP neural network predicted advance control algorithm,which was validated the effectiveness of the algorithm.The hydraulic system state curves of the support during the shifting process was obtained by on-site measurement.The curves were divided into four intervals:lowering the leg,pulling the support,switching,and raising the leg.The method of predicting the pulling action time based on the inlet hydraulic pressure was used with the 95% prediction interval upper limit.By installing an accumulator at the inlet end of the support to compensate for the pressure and flow loss of the support caused by various factors,the pulling time was shortened by 1.15 s,and the speed was increased by 20%,which verified the effectiveness of the fast tracking control method.