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主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
天-空-地协同的露天矿边坡智能监测技术及典型应用
  • Title

    Spaceborne-airborne-ground collaborated intelligent monitoring on open-pit slope and its typical applications

  • 作者

    刘善军吴立新毛亚纯贺黎明王植许志华魏恋欢杨泽发

  • Author

    LIU Shanjun1 ,WU Lixin2 ,MAO Yachun1 ,HE Liming1 ,WANG Zhi1 ,XU Zhihua3 ,WEI Lianhuan1 ,YANG Zefa2

  • 单位

    东北大学 资源与土木工程学院中南大学 地球科学与信息物理学院中国矿业大学(北京)地球科学与测绘工程学院

  • Organization
    1. School of Resource and Civil Engineering,Northeastern University,Shenyang  110819,China; 2. School Geosciences & Infor-physics,Central South Univer-sity,Changsha  410083,China; 3. College of Geoscience and Surveying Engineering,China University of Mining & Technology (Beijing),Beijing  100083, China
  • 摘要

    露天开采是我国矿产资源开采的主要形式之一,长期高强度、大规模开采形成了众多高陡边坡,由此带来的边坡失稳及灾害现象十分严重,对其进行有效监测和灾害预警,是边坡治理、安全保障和绿色矿山的关键。 

    由于大型露天矿山地形复杂、观测条件困难、影响因素众多,传统的、单一的监测手段均难以奏效。 

    在讨论智能监测相关概念的基础上,介绍了露天矿边坡智能监测的思想、内容和内涵;指出大型露天矿边坡智能监测的核心是天-空-地多平台多模式协同观测,包括时间协同、空间协同、参数协同和智能分析;介绍了目前大型露天矿边坡智能监测的 7 项关键技术,即导航卫星 GNSS 在线监测技术、雷达卫星InSAR 监测技术、光学卫星高分影像监测技术、无人机与TLS 联合监测技术、地基红外热像监测技术、顾及大气折光的测量机器人监测技术、基于 WiFi 的监测信息多终端显示技术。 

    这些手段不仅要强调监测仪器的先进性、鲁棒性和精度,更要发挥多手段的时空互补性和过程协同性,而稳定可靠的通讯网络、快速自动的数据处理和智能综合的分析模块,是实现矿山滑坡智能监测和智能应急的关键。 

    最后,以辽宁抚顺西露天煤矿特大滑坡、鞍钢鞍千铁矿大型排土场和鞍钢弓长岭铁矿滑坡的天-空-地协同观测为典型案例,介绍了适合不同矿山特点和任务需求的露天矿边坡智能监测技术方案及其取得的实效。


  • Abstract

    Surface mining is one of the major methods of mineral resource development in China. The long-term and high intensity development of surface mine has brought with a lot of slopes with high angle and great depth,which leads to serious instability issues and large landslides. To monitor the surface mine slopes effectively and to forecast the landslides are the keys of slope treatment,safe production and green mine development. However,the large surface mines usually have complex terrain,difficult observation conditions and multiple impacting factors,which make the tra- ditional and single observation method to be less effective. Based on discussing some conceptions related with intelli- gent monitoring,this paper introduces the idea, contents and connotation of intelligent monitoring on surface mine slope. The core of intelligent monitoring on surface mine slope is spaceborne-airborne-ground collaborated observations with multiple platforms and multiple modes,which include temporal coordination,spatial coordination,parametric coor- dination and intelligent analysis. Seven key technologies for the intelligent monitoring on surface mine slope are intro- duced,which are GNSS online monitoring,D-InSAR of radar satellite,high-resolution imaging of optical satellite,joint observation of unmanned aerial vehicle and terrestrial laser scanner,ground-based thermal imaging,surveying robot re- ferring to atmospheric refraction,and the WiFi-based multi-end display of monitoring information. These means not on- ly emphasize the advancement,robustness and accuracy of monitoring instruments,but also play the complementary and process coordination of multiple means. The stable and reliable communication network,fast and automatic data processing and intelligent integrated analysis module are the keys to realize the intelligent monitoring and intelligent e- mergency management of mine slope landslide. Finally,three typical application cases in Liaoning Province are intro- duced,which are the large-scale landslide in Fushun West Surface Mine,the large waste rock pile of the Anqian Iron Mine of AnSteel Group,and the landslide of the Gongchangling Iron Mine of AnSteel Group. The particular monitoring measures referring to the mine’s features and special demands. Following that,the practical effect reached are also in- terpreted.

  • 关键词

    露天矿山边坡智能监测协同观测数字矿山智能矿山

  • KeyWords

    open-pit slope;intelligent monitoring;collaborated observation;digital mine;intelligent mine

  • DOI
  • Citation
    LIU Shanjun,WU Lixin,MAO Yachun,et al. Spaceborne-airborne-ground collaborated intelligent monitoring on open- pit slope and its typical applications[J]. Journal of China Coal Society,2020,45(6):2265 -2276.
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主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

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