Research and application practice of digital intelligent technology and complete set of equipment for efficient coalmining

WANG Guofa; ZHANG Jinhu; REN Huaiwei; DU Yibo; ZHANG Desheng; YAN Ruyu; YU Xiang

doi:10.13225/j.cnki.jccs.2024.1402

Abstract：Summarizing the current development status of intelligent and digital technologies in the coal industry,analyz-ing the new situations and requirements for research and application of intelligent technologies and complete sets of equip-ment for efficient coal mining.Addressing challenges such as comprehensive perception of the state of high-strength min-ing surrounding rock and equipment under different coal seam conditions and integrated coordinated advancement and linked control of equipment groups,the paper explores the deep integration of advanced information technologies such as the Internet of Things,cloud computing,big data analytics,and high-precision inertial navigation with coal mining techno-logies.This integration has enabled condition monitoring and data integrated management of coal mining equipment,im-proving monitoring,management,and decision-making efficiency in the coal mining process through precise perception,real-time data analysis,and intelligent control.It has also enhanced the adaptability of complete mining equipment sets to different coal seam conditions.To address the challenges of integrated advancement and coordinated control of equipment groups in ultra-long workfaces for medium-thick coal seams,the paper introduces synchronous mapping of geological in-formation ahead of the mining face through dynamic perception of geographical information and real-time model updat-ing technology.High-power rapid advancement equipment suitable for ultra-long workfaces has been developed,and a multi-area synchronous advancement process system covering all aspects of support,mining,and transportation has been established.This forms a linked mechanism for support equipment groups in ultra-long workfaces and achieves coordin-ated control among equipment groups,significantly improving mining efficiency and resource recovery rates for medium-thick coal seams.For complex geological conditions in deep thick coal seams,refined control of supports and intelligent coordinated control technologies for equipment groups have been developed,enabling perceptual coordination and adapt-ive precise control between equipment,thus improving system reliability and efficiency.Addressing challenges such as coal wall protection in ultra-large mining spaces,intense dynamic loads on surrounding rock in the workface,and signific-ant variations in coal flow loads in 8-10 m ultra-high mining height workfaces,the paper proposes adaptive control tech-nology for coupling hydraulic supports with surrounding rock,enhancing the adaptability of equipment to ultra-high min-ing height workface environments.Key technologies such as a guard plate monitoring system,adaptive cutting technology for shearer stability,coal flow load balancing,and dynamic chain tensioning control have been developed,enabling effi-cient mining under conditions of significant coal seam thickness variations and strong mining pressure.In the overseas promotion of intelligent and digital complete sets of equipment for efficient coal mining,the paper addresses challenges such as differences in coal mine conditions,safety requirements,and technical standards through customized adjustments to technical equipment.An integrated monitoring and big data analytics system has been developed,improving the re-sponse to abnormal situations and enabling autonomous perception,high-reliability data transmission,intelligent analysis and decision-making,precise control and execution among equipment groups within the workface.A technical system for intelligent and digital complete sets of equipment for efficient coal mining adaptable to different working conditions has been established and has achieved good results in engineering practice.This provides support for the high-quality develop-ment of coal mine intelligence and solutions to key technical challenges in coal mine intelligent construction.