摘要
采煤机工作环境恶劣,对操作人员伤害大,实现截割自动化对保障煤矿开采安全具有重要意义。记录人工示教模式下的路径,通过判断煤岩状态设置采煤机状态参数跟踪示教路径。在截割过程中以采煤机状态参数为输入信号,采用BP神经网络实时调整采煤机工作参数来实现自适应调速。为了验证基于BP神经网络的采煤机截割自适应调速控制系统的性能,采用MATLAB进行仿真,仿真结果显示自动截割时滚筒的高度大致与示教时相同,说明此系统可以很好地实现自动截割。
The working environment of the shearer is bad,which causes great harm to the operators.The realization of cutting automation is of great significance to guarantee the safety of coal mining.The path in the manual teaching mode was record.The shearer status parameters were set to track the teaching path through judging the coal rock status.The shearer status parameters were used as input signals during the cutting process,and BP neural network was used to adjust the coal mining machine working parameters to achieve adaptive speed regulation in real time.In order to verify the performance of the shearer cutting adaptive speed regulation control system based on BP neural network,MATLAB was used for simulation.The simulation results show that the height of the drum during automatic cutting is roughly the same as that during teaching,indicating that this system can achieve automatic cutting.
作者
刘力涛
董淑棠
Liu Litao;Dong Shutang(Jinzhong Vocational and Technical College,Jinzhong 030601,China;Taiyuan Huite Information Technology Co.,Ltd.,Jinzhong 030601,China)
出处
《煤矿机械》
北大核心
2020年第8期197-199,共3页
Coal Mine Machinery
