王海军,曹云,王洪磊. 煤矿智能化关键技术研究与实践[J]. 煤田地质与勘探,2023,51(1):44−54. DOI: 10.12363/issn.1001-1986.22.12.0992
引用本文: 王海军,曹云,王洪磊. 煤矿智能化关键技术研究与实践[J]. 煤田地质与勘探,2023,51(1):44−54. DOI: 10.12363/issn.1001-1986.22.12.0992
WANG Haijun,CAO Yun,WANG Honglei. Research and practice on key technologies for intelligentization of coal mine[J]. Coal Geology & Exploration,2023,51(1):44−54. DOI: 10.12363/issn.1001-1986.22.12.0992
Citation: WANG Haijun,CAO Yun,WANG Honglei. Research and practice on key technologies for intelligentization of coal mine[J]. Coal Geology & Exploration,2023,51(1):44−54. DOI: 10.12363/issn.1001-1986.22.12.0992

煤矿智能化关键技术研究与实践

Research and practice on key technologies for intelligentization of coal mine

  • 摘要: 煤矿智能化是煤炭行业实现可持续发展的重要途径,为煤矿企业减人增效、安全生产提供有效保障,大数据、机器人、人工智能等新一代信息技术有力支撑了煤矿智能化建设。首先阐述了智慧矿山的设计思路,提出了智能化建设总体技术体系。然后,分析了通用异构型控制和数据处理平台、矿用巡检机器人技术、人工智能技术、故障诊断技术和智能穿戴等煤矿智能化关键技术的发展现状与趋势,梳理了智能化建设应用过程中存在的关键难题,并针对瓶颈问题提出了解决方法与未来发展趋势。研究基于模块化开发的通用异构型控制和数据处理平台,实现了底层终端的可重构和底层通信协议的统一,解决了数据孤岛问题;研究巡检机器人驱动模块监测、运动控制与精确定位等关键技术,基于多传感器融合技术实现机器人精确定位;研究人工智能技术在煤矿场景应用中缺少典型数据和与场景知识结合的问题,提出小样本学习技术有望推动人工智能技术在煤矿智能化领域的进一步落地应用;研究煤矿设备故障诊断技术,提出构建基于数据和知识混合驱动的设备故障诊断模型将有效解决过度维修和欠维修的问题;智能穿戴技术是解决井下关键岗位作业人员防护问题的关键,提出了由呼吸系统、传感监测系统、人机交互系统、语音显示系统组成的智能穿戴系统设计方案。最后,阐述了内蒙古神东天隆集团霍洛湾煤矿与内蒙古神东天隆集团武家塔露天煤矿智能化建设实践经验与阶段成果,为不同类型煤矿的智能化建设提供参考。

     

    Abstract: Intelligentization of coal mine is an important way for coal industry to achieve sustainable development. It provides effective guarantee for coal mine enterprises to reduce workers, increase efficiency and improve the production safety. The new generation of information technologies, such as big data, robotics and artificial intelligence, strongly support the intelligent construction of coal mines. Firstly, the design ideas of intelligent mines are introduced in this paper, and the overall technical system of intelligent construction are developed. Secondly, the development status and trend of key technologies for the intelligentization of coal mine are analyzed, including the general heterogeneous control and data processing platform, mining inspection robot technology, artificial intelligence technology, fault diagnosis technology and intelligent wearable technology. Meanwhile, problems in the process of intelligent construction and application were combed through. In addition, solutions for the bottleneck problems and future development trend are pointed out. Besides, general heterogeneous control and data processing platform based on modular are developed, realizing the reconfigurability of underlying terminals and the unification of basic communication protocols. Thus, the problem of data islands is solved. Key technologies of the monitoring, motion control and precise positioning of inspection robot drive module are also studied to realize the precise positioning of robot based on the multi-sensor fusion technology. Problems in the application of artificial intelligence technologies in coal mine scenarios, such as lack of typical data and combination with scene knowledge, are also studied. It is shown that the few-shot learning technology is expected to promote further implementation and application of artificial intelligence technologies in the intelligent field of coal mine. The fault diagnosis technology of coal mine equipment is studied, and it is proposed that construction of equipment fault diagnosis model based on data and knowledge hybrid drive can effectively solve the problem of over-maintenance and under-maintenance. Moreover, intelligent wearable technology is the key to solve the problem of protecting workers in key underground positions, and the design scheme is also provided for the intelligent wearable system composed of respiratory system, sensor monitoring system, human-computer interaction system and voice display system. Finally, practical experience and phased achievements of intelligent construction of Huoluowan Coal Mine and Wujiata Open-pit Coal Mine of Shendong Tianlong Group are introduced, providing reference for intelligent construction of different types of coal mines.

     

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