马宏伟, 王鹏, 王世斌, 毛清华, 石增武, 夏晶, 杨征, 薛旭升, 王川伟. 煤矿掘进机器人系统智能并行协同控制方法[J]. 煤炭学报, 2021, 46(7): 2057-2067.
引用本文: 马宏伟, 王鹏, 王世斌, 毛清华, 石增武, 夏晶, 杨征, 薛旭升, 王川伟. 煤矿掘进机器人系统智能并行协同控制方法[J]. 煤炭学报, 2021, 46(7): 2057-2067.
MA Hongwei, WANG Peng, WANG Shibin, MAO Qinghua, SHI Zengwu, XIA Jing, YANG Zheng, XUE Xusheng, WANG Chuanwei. Intelligent parallel cooperative control method of coal mine excavation robot system[J]. Journal of China Coal Society, 2021, 46(7): 2057-2067.
Citation: MA Hongwei, WANG Peng, WANG Shibin, MAO Qinghua, SHI Zengwu, XIA Jing, YANG Zheng, XUE Xusheng, WANG Chuanwei. Intelligent parallel cooperative control method of coal mine excavation robot system[J]. Journal of China Coal Society, 2021, 46(7): 2057-2067.

煤矿掘进机器人系统智能并行协同控制方法

Intelligent parallel cooperative control method of coal mine excavation robot system

  • 摘要: 煤矿巷道掘进长期存在的“采快掘慢”“掘快支慢”顽症,尤其是掘进工作面装备成套化、自动化、智能化程度偏低、顺序作业工艺技术落后等问题,严重影响生产接续和安全高效开采。对此,研发了护盾推移式煤矿巷道掘进机器人系统成套装备,提出了一种煤矿巷道掘进机器人系统智能并行协同控制方法。首先,结合掘进机器人系统与巷道的耦合关系,分析了掘进机器人系统中各个子系统之间的相关性以及多任务之间的相互影响机理,得出了决定掘进效率的关键因素在于截割机器人和钻锚机器人的并行协同控制;其次,针对钻锚机器人各钻机之间的时空关系,构建了多钻机多任务协同钻锚作业数学模型,获得了钻机布置排距、排数及其各排钻锚任务数,同时使用优化组合的方法进行求解,并对计算结果通过安全距离最大原则进行优化,获得了钻锚机器人各排钻机最佳时空匹配策略;最后,通过钻锚机器人系统并行协同控制仿真和实验,证明了该方法的有效性;通过对掘进机器人工作时截割机器人与钻锚机器人的时序分析,得出优化后的钻锚机器人工作时间能够与截割机器人工作时间有效匹配,2者能够并行协同的完成截割和钻锚任务。该方法已经应用在团队研发的煤矿智能掘进机器人系统上,实现了多机器人系统的智能并行协同控制。具有智能并行协同控制的掘进机器人系统已经在大断面(6.50 m×4.25 m)、夹矸与片帮共存的巷道运行近10个月,经受了夹矸厚度达2.1 m、硬度f=5~7的严酷考验,日进尺突破50 m。

     

    Abstract: The persistent problems of “mining fast and heading slow” and “heading fast and supporting slow” in coal mine roadway drivage still exist currently,especially the problems of low degree of equipment complete set,automation,and intelligence,and backward sequential operation technology,which seriously affect the production continuity,and safe and efficient mining.To overcome the problems,this study had developed a complete set of shield pushing robot system for coal mine roadway drivage,and puts forward an intelligent parallel cooperative control method for coal mine roadway drivage robot system.Firstly,the correlation between the subsystems of the drivage robot system and the interaction mechanism between multiple tasks were analyzed based on the coupling relationship between the drivage robot system and the roadway.It was concluded that the key factor to determine the drivage efficiency is the parallel cooperative control of the cutting robot and the anchor drilling robot.Secondly,according to the space-time relationship between each drilling rig,a mathematical model of multi-rig and multi-task cooperative drilling and anchoring operation was built to obtain the row spacing,row number and the number of each row's drilling and anchoring tasks.At the same time,the optimal combination method was used to solve the problem,and the calculation results were optimized according to the maximum safety distance principle so as to obtain the optimal space-time matching strategy of each row of drilling rigs.Finally,the effectiveness of the proposed method was proved by the simulation and experiment of parallel cooperative control of drilling and anchoring robot system.The timing analysis of cutting robot and drilling and anchoring robot when drivage robot works shows that the working time of optimized drilling and anchoring robot can effectively match the working time of cutting robot,and they can complete the cutting and drilling and anchoring tasks in parallel and cooperation.The method has been applied to the intelligent drivage robot system developed by the team,and the intelligent parallel cooperative control of multi-robot system has been realized.The drivage robot system with intelligent parallel cooperative control has been operating for nearly 10 months in the roadway with large section (6.5 m×4.25 m),dirt band and rib spalling co-existing,and has withstood the severe test of 2.1 m thick dirt band and f=5-7 hardness,and the drill footage per day has exceeded 50 meters.

     

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