摘要
煤矿巷道掘进智能化相关理论与技术研究是当前解决“采掘失衡”难题的基石。远程智能掘进是实现少人甚至无人化掘进作业的根本目标和远景,面临单一掘进装备定位与控制、设备群协同、人-机-环感知与呈现,以及远程智能决策等瓶颈问题。聚焦巷道近程或地面远程智能掘进场景控制需求,提出了数字孪生驱动掘进装备远程智能控制技术构架,通过构建掘进工作面数字孪生体,将井下人员、设备、环境相关信息呈现到数字空间,虚实融合,共智互驱,达到数字掘进与物理掘进智能协同的目标,破解掘进施工中人-机-环共生安全难题;针对掘-支-运并行作业要求,提出以掘进为智能化核心,自动钻锚和高效转运辅助的远程控制构架,介绍了远程虚拟呈现、精确位姿感知、孪生数据共享、虚实同步驱动、工艺记忆截割、设备群碰撞预警等方面的研究进展,以“DT+VR”远程决策、“视觉+”位姿测量、“人工示教”记忆截割,以及“虚拟设备”碰撞预警等四大核心技术,解决智能决策、精确定位(定向导航和成形质量的基础)、轨迹规划和设备群碰撞预警难题,总结了平面防爆玻璃以及光学球罩折射建模与矫正、振动工况下成像模糊机理、掘进机机身位姿精准测量、定向导航与纠偏、轨迹示教记忆截割,设备群协同与数字孪生驱动等基础理论和技术,以视觉感知的成像折射校正和去模糊入手,系统介绍视觉技术在定位、定向、定形截割方面的进展,并分析了数字孪生驱动技术是实现智能远程掘进工作常态化生产的有效途径。上述核心技术在实验室测试及陕煤小保当、榆林大海则等煤矿井下掘进工作面进行了初步验证,为解决煤矿远程智能掘进提供了新的实现路径。
The theoretical and technical study on intelligent roadway development is very important to solve its low efficiency problems in coal mines.The remote intelligent controlling is the fundamental goal and strategic vision of using less people or unmanned operation,facing the bottleneck technical problems such as single driving-gear positioning and control,equipment group coordination,man-machine-surrounding perception and rendering,and remote intelligence decision.Aimed at the requirements on the remote intelligent controlling,this paper proposes a technical framework for remote intelligent control based on DT(Digital Twins).The DT models of intelligent remote driving is built,and the underground personnel,equipment and environmental information are presented in the digital space,realizing the fusion and the mutual intelligent driving of virtual and reality,achieving the intelligent collaborative control of digital driving and the physical driving.So the safety problems in roadway excavation are solved.Aiming at the requirements of the parallel operation of the mining and transport,the remote control framework of automatic drilling anchor and efficient transport is proposed,and the research progress of remote virtual rendering,accurate position perception,DT data sharing,false synchronous drive,process memory cutting and equipment group collision alert are introduced.The paper introduces four technologies such as"DT+VR"remote control decision,"visual+"position estimation,"artificial teaching"memory cutting,and"virtual equipment"collision warning,to overcome the problems in intelligent decision-making,the accurate positioning,the trajectory planning and the equipment group collision warning in underground coal mines.The basic theories and technologies,such as the refraction imaging mechanism modeling and modification of plane flameproof glass and optical ball cover,imaging blur mechanism under vibration condition,the accurate body pose estimation of roadheader,directional navigation and deviation correction,manual teaching cutting track and memory cutting based on visual measurement,devices cooperative control and digital twin driven remote control,are summarized.Based on the imaging refraction correction and de-blurring of visual perception,this paper systematically overviews the progress of vision technology in positioning,orientation and shape cutting,and also analyzes that digital twin drive technology is an effective way to realize the normal production of intelligent remote roadway development.The core technologies mentioned above have been tested in the laboratory and preliminary verified underground,for instance,at the Xiaobadang Coal Mine and the Dahaize Coal Mine in Shaanxi province,China.The researches provide a new realization path for achieving remote intelligent controlling in coal mines.
作者
张旭辉
杨文娟
薛旭升
张超
万继成
毛清华
雷孟宇
杜昱阳
马宏伟
赵友军
李晓鹏
胡成军
田胜利
ZHANG Xuhui;YANG Wenjuan;XUE Xusheng;ZHANG Chao;WAN Jicheng;MAO Qinghua;LEI Mengyu;DU Yuyang;MA Hongwei;ZHAO Youjun;LI Xiaopeng;HU Chengjun;TIAN Shengli(College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an 710054,China;Xi’an coal mining machinery Co.,Ltd.,Xi’an 710032,China;Shaanxi MINST Technology Co.,Ltd.,Xi’an 710054,China;China Coal(Tianjin) Underground Engineering Intelligent Research Institute Co.,Ltd.,Tianjin 300120,China;Shandong Tianhe Technology Co.,Ltd.,Jining 273500,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2022年第1期579-597,共19页
Journal of China Coal Society
基金
国家自然科学基金资助项目(51974228,52104166)
陕煤联合基金资助项目(2021JLM-03)。
关键词
远程智能掘进
掘进数字孪生
“视觉+”位姿测量
掘进记忆截割
虚拟碰撞
intelligent remote driving
DT-driven roadheader
visual position estimation
memory cutting of roadheader
virtual collision warning
