摘要
针对当前煤矿巷道综掘工作面的智能化程度较低,掘进效率低下的问题,分析了煤矿综掘工作面实现智能化快速掘进的关键技术--自主感知和调控技术。首先,探讨了智能化快掘创新方法与理论,以智能感知技术、自主控制技术、群组协同技术为核心,构建智能化快速掘进技术体系,以实现煤矿综合掘进机器人化装备的探-掘-护-锚一体化协同作业。其次,重点阐述了智能化掘进的自主感知技术,包括基于超宽带原理的位姿感知、基于双频激电法的超前探测、基于SLAM原理的环境感知、基于变迁记忆故障Petri网的故障感知等;自主调控技术,包括基于群体智能算法的智能截割、基于遗传变异粒子群算法的路径规划、基于BP神经网络PID算法的自主纠偏等。再次,详细论述了智能临时支护感知,包括围岩压力、顶底板状况、支架位姿等多维信息的感知,研究了非水平场景下掘支协同与多机组多缸联动的自适应控制方法;介绍了智能永久支护感知,包括围岩位移感知和支护装备受力变形感知,探讨了锚护网络结构优化方法,提出了基于粒子群优化算法的自适应钻进控制策略。最后,展望了煤矿巷道智能化掘进的自主感知及调控技术的发展方向。
In order to solve the problems of low intelligentization and low driving efficiency of current coal mine comprehensive heading face,the key to realizing intelligent rapid heading in coal mine comprehensive heading face is autonomous sensing and control technology.Firstly,the key technical features of intelligent heading are discussed.The robotic equipment for coal mine comprehensive heading is supported by intelligent perception technology,autonomous control decision-making technology,and group collaborative operation technology to form an intelligent rapid heading technology system framework to achieve exploration-heading-support-anchor inte-gration cooperation.Secondly,it focuses on the self-aware technology of intelligent excavation,including posture perception based on the principle of ultra-wideband,advanced detection based on the dual-frequency electric shock method,environmental perception based on the principle of SLAM,and fault perception based on the transition memory fault Petri net,etc.Autonomous control technology includes intelligent cutting based on swarm intelligence algorithm,path planning based on genetic mutation particle swarm optimization algorithm,autonomous correction based on PID algorithm of BP neural network and so on.Thirdly,it discusses in detail the perception of intelligent temporary support including multi-dimensional information such as surrounding rock pressure,roof and floor conditions,support posture,etc.,and studies the adaptive control method for the linkage of excavation support and multi-unit multi-cylinder under non-horizontal scenarios.Intelligent permanent support perception includes surrounding rock displacement perception and support equipment stress deformation perception,and discusses the optimization method of anchor network structure.In order to obtain the best propulsion control performance in adaptive drilling control,a particle swarm optimization parameter tuning strategy of the algorithm’s auto disturbance rejection controller is proposed.Finally,the direction of further development of autonomous perception and control technology for intelligent tunneling of coal mine roadways is discussed.
作者
杨健健
张强
吴淼
王超
常博深
王晓林
葛世荣
YANG Jianjian;ZHANG Qiang;WU Miao;WANG Chao;CHANG Boshen;WANG Xiaolin;GE Shirong(Department of Mechanical,Electrical and Information Engineering,China University of Mining and Technology (Beijing),Beijing 100083,China;Robotic Mining Equipment Institute,China University of Mining and Technology (Beijing),Beijing 100083,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2020年第6期2045-2055,共11页
Journal of China Coal Society
基金
国家自然科学基金面上资助项目(2018101060080)
国家自然科学基金青年基金资助项目(2018101030061)
2019山西省科技重大专项资助项目(20181102027)。
关键词
智能化掘进
自主感知
智能调控
无人掘进工作面
intelligent tunneling
autonomous perception
intelligent regulation
unmanned driving face
