摘要
针对薄煤层综采工作面存在的受限空间作业难、多机协同工作能力差等问题,构建了智能化系统。提出了红外、射频、轴编码器多信号融合的采煤机定位方法,建立了以惯性导航为主、视频信号为辅的工作面找直技术。搭建了乳化液泵站智能控制系统、喷雾降尘智能系统、三机和带式输送机故障诊断系统等智能化保障系统;在工作巷搭建集成控制平台,通过多种数据接口接入各保障系统,采用工业总线网络为通道,实现井下集控和地面远控。工业运行表明,系统可实现采煤全流程自动化生产,采煤队生产班减少5人,人员减少30%,每天平均多推进6刀,生产效率提升102%。
Aiming at the problems of difficult operation in confined space and poor cooperative working ability of multiple machines in thin coal seam fully mechanized mining face, an intelligent system is built.A shearer positioning method is proposed based on multi-signal fusion of infrared, radio frequency and shaft encoder.The working face straightening technology based on inertial navigation and supplemented by video signal is established.Intelligent support systems such as emulsion pump station intelligent system, spraying dust control intelligent system, three machines and belt conveyor fault diagnosis system are built.An integrated control platform is set up in the crossheading centralized control center, based on advanced and reliable electro-hydraulic control system access to each subsystem through multiple data interfaces, using industrial BUS network as the channel, to realize underground centralized control and ground remote control.The industrial operation shows that the system can automatize the whole production process of coal mining in the working face, production squad of the coal mining team was downsized by 30%(5 personnel), while the average daily advance increased 6 cuts, enhancing the production efficiency by 102%.
作者
孙晋璐
高贵军
琚林涛
时三波
SUN Jin-lu;GAO Gui-jun;JU Lin-tao;SHI San-bo(School of Intelligent Manufacturing Engineering,Shanxi University of Science and Technology,Jincheng 048006,China;School of Mechanical and Transportation Engineering,Taiyuan University of Technology,Taiyuan 030024,China;Sihe No.2 Coal Mine,Jinneng Holding Equipment Manufacturing Group Co.,Ltd.,Jincheng 048006,China)
出处
《煤炭工程》
北大核心
2022年第10期17-21,共5页
Coal Engineering
关键词
薄煤层
综采工作面
智能化
采煤机定位
三机故障诊断
thin coal seam
fully-mechanized working face
intellectualization
shearer positioning
three machine fault diagnosis