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基于矿鸿软总线的综采工作面三机联动控制方法

Three⁃machine linkage control method of fully mechanized mining face based on Mineral⁃hong soft bus
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摘要 为实现不同设备间的无缝连接,高效共享设备信息,研究基于矿鸿软总线的综采工作面三机联动控制方法。采集压力、位置、牵引速度、方向、电流等信息,利用Elman神经网络与PID控制算法,结合三机相关信息,输出三机联动控制指令,经由矿鸿软总线传输至支架、输送机与采煤机控制器内,执行对应动作,完成采煤机自动牵引割煤控制、液压支架自动化跟机控制,输送机加减速牵引控制;通过监测中心查看三机联动控制结果。实验结果表明,该方法可有效采集综采工作面三机相关信息;该方法的信息传输完整性较优,且传输速率较快;该方法可有效完成综采工作面三机联动控制,且控制精度较高。 To achieve seamless connection between different devices and efficiently share device information,a three machine linkage control method based on Mineral⁃hong soft bus for fully mechanized mining face is studied.Collect information such as pressure,position,traction speed,direction,and current,use Elman neural network and PID control algorithm,combined with relevant information of the three machines,output linkage control instructions of the three machines,and transmit them to the support,conveyor,and shearer controllers through the Mineral⁃hong soft bus.Execute corresponding actions to complete automatic traction and cutting control of the shearer,automatic follow⁃up control of the hydraulic support,and acceleration and deceleration traction control of the conveyor;View the results of the three machine linkage control through the monitoring center.Experimental results have shown that this method can effectively collect information related to the three machines in the fully mechanized mining face.This method has better information transmission integrity and faster transmission speed.This method can effectively achieve the linkage control of the three machines in the fully mechanized mining face,and the control accuracy is high.
作者 肖伟 马开德 刘钊 XIAO Wei;MA Kaide;LIU Zhao(Middling Coal Information Technology(Beijing)Co.,Ltd.,Beijing 100000,China;China Coal Mine Machinery Equipment Co.,Ltd.,Beijing 100000,China)
出处 《电子设计工程》 2024年第21期80-84,89,共6页 Electronic Design Engineering
基金 中国中煤能源集团有限公司重大科技专项(22-03)。
关键词 矿鸿软总线 综采工作面 三机联动控制 液压支架 采煤机 ELMAN神经网络 Mineral⁃hong soft bus fully mechanized mining face three machine linkage control hydraulic support shearer Elman neural network
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