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金属矿山 ›› 2024, Vol. 53 ›› Issue (01): 20-44.

• “智能矿山建设与实践”专题 • 上一篇    下一篇

金属矿山地质灾害风险智能监测预警技术现状与展望

朱万成 徐晓冬 李 磊 牟文强 宋清蔚 李 荟
  

  1. 东北大学岩石破裂与失稳研究所,辽宁 沈阳 110819
  • 出版日期:2024-01-15 发布日期:2024-04-19
  • 基金资助:
    “十四五”国家重点研发计划项目(编号:2022YFC2903903);国家自然科学基金联合基金重点支持项目(编号:U1906208);中央高校基本科研业务费专项(编号:N2301020);黑龙江揭榜挂帅项目(2021ZXJ02A04-03,2021ZXJ02A03-02)。

Status and Prospect of Intelligent Monitoring and Early-warning Technology of Geological Disaster Risk at Metal Mines

ZHU Wancheng XU Xiaodong LI Lei MU Wenqiang SONG Qingwei LI Hui   

  1. Center for Rock Instability and Seismicity Research,Northeastern University,Shenyang 110819,China
  • Online:2024-01-15 Published:2024-04-19

摘要: 金属矿山地质灾害风险智能监测预警技术是保障矿山安全生产的关键技术之一,是岩石力学应用于矿 山安全领域研究的热点问题。 从地质灾害风险定义、类型、监测方式、预警技术等方面出发,简述了金属矿山地质灾害 风险监测预警技术的发展现状,指出在灾害风险定义方面,金属矿山地质灾害风险易发性、易损性和危险性量化分析 理论体系尚不完善;在灾害风险监测与数据融合方面,多感知设备协同监测与数据融合理论仍不完善,尚未实现基于 风险条件的感知设备布设方案智能调整,难以保障采动岩体力学响应的时空完整性与连续性;在灾害风险预警方法 方面,监测与模拟相结合已成为矿山灾害预警发展趋势,应进一步与云计算、人工智能等技术相融合,建立完善的理 论体系,实现实时动态、精准高效、智能的灾害风险预警。 在此基础上,围绕“现场监测和数值模拟相结合灾害预测预 警”的学术思想,提出了“地质灾害案例匹配、多源数据挖掘、力学机理分析、专家系统诊断”四位一体的灾害风险智能 预测预警方法,进一步以弓长岭露天矿浅层隐伏空区垮塌与地表塌陷风险监测预警工作为背景,实现了上述方法的 应用与推广。 最后指出了金属矿山灾害风险智能监测预警技术存在着多源力学响应数据难以高精度连续协同感知、 灾害预测预警模型参数难以精准选取、灾害监测预警系统尚不完善等问题,多灾种高性能、专用特种智能感知技术与 装备,标准化数据通信协议与架构,监测—模拟相结合的灾害智能预警模型,地质灾害监测预警平台与数字孪生技术 是解决上述问题的关键技术,是未来的主要发展趋势。

关键词: 金属矿山, 地质灾害, 监测, 预警

Abstract: Intelligent monitoring and early-warning of mining-induced geological disaster in metal mines is an essential technology ensuring mine safety and production. This paper provides a concise overview on the current state of this technology, focusing on the definition of geological disaster risks,types,monitoring methods,and early warning techniques specifically used in metal mining. It is pointed out that the quantitative analytical framework for assessing the susceptibility,vulnerability and risk of geological disasters in metal mines is still not comprehensive in terms of disaster risk definition. In terms of disaster risk monitoring and data fusion,the theories of collaborative monitoring with multi-sensing devices and data fusion are still not comprehensive. The intelligent adjustment of sensing device deployment plans based on risk conditions has not been achieved yet, which makes it difficult to ensure the spatiotemporal integrity and continuity of mechanical responses of disturbed rock masses. In terms of disaster risk early warning methodology,the combination of monitoring and simulation has become a trend for early warning of mining disasters. It should be further integrated with cloud computing,artificial intelligence and other technologies to establish a comprehensive theoretical system,so as to achieve real-time,dynamic,accurate and intelligent risk early warning for disasters. On this basis,based on the academic concept of " combining on-site monitoring and numerical simulation for early warning" ,this study puts forward an integrated disaster risk intelligent prediction and early warning method consisting of " geological disaster case matching,multi-source data mining,mechanical mechanism analysis,and expert system diagnosis" . Taking the monitoring and early warning of shallow buried cavity collapse and surface subsidence risks in Gongchangling Open-pit Mine as a background,the application and promotion of the proposed method are realized. Finally,it is pointed out that disaster risk intelligent monitoring and early warning technologies in metal mines face challenges in multi-source data fusion,disaster prediction model parameter selection,and completeness of early warning systems. High-performance dedicated intelligent sensing technologies and equipment for multiple disaster types,standardized data communication protocols and architectures,disaster intelligent early warning models combining monitoring and simulation,geological disaster monitoring and warning platforms and digital twin technologies are key the technologies to solve the above issues and will be major future development trends.