杨天鸿, 王赫, 董鑫, 等. 露天矿边坡稳定性智能评价研究现状、存在问题及对策[J]. 煤炭学报, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.NZ20.0347
引用本文: 杨天鸿, 王赫, 董鑫, 等. 露天矿边坡稳定性智能评价研究现状、存在问题及对策[J]. 煤炭学报, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.NZ20.0347
YANG Tianhong, WANG He, DONG Xin, et al. Current situation,problems and countermeasures of intelligent evaluation of slope stability in open pit[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.NZ20.0347
Citation: YANG Tianhong, WANG He, DONG Xin, et al. Current situation,problems and countermeasures of intelligent evaluation of slope stability in open pit[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.NZ20.0347

露天矿边坡稳定性智能评价研究现状、存在问题及对策

Current situation,problems and countermeasures of intelligent evaluation of slope stability in open pit

  • 摘要: 在收集整理国内外相关资料的基础上,从露天矿边坡稳定性智能感知手段、智能评价预测方法、智能决策技术等方面总结了露天矿边坡稳定性智能评价研究现状,分析露天矿边坡工程的特点,指出当前露天矿边坡稳定性智能评价研究存在的问题,提出“位移时间序列阈值、力学机理分析、案例分析及专家系统诊断”三位一体的边坡稳定性智能评价的学术思路,认为露天矿边坡稳定性智能评价研究发展趋势为: 首先,建立边坡灾害案例和多因素多模式智能识别数学模型,采用深度学习和大数据分析方法进行案例类型聚类、要素识别和模式匹配;其次,通过力学机理计算评价,识别隐患区确定滑坡隐患触发因素和条件; 然后,基于案例模式匹配结果建立监测预警指标体系和预警阈值,构建案例库知识库和专家系统并实现智能决策; 最后以大孤山铁矿西北帮滑坡为例,基于力学计算给出边坡安全系数变化规律,同时结合滑坡案例库的匹配结果,确定现场数据时序曲线指标阈值(位移累积量、位移速率),从而科学合理的给出预警警情判别结果,通过云平台实现数据分析、现场模型可视化和预警发布及滑坡诊断。 该案例初步验证了三位一体边坡稳性智能评价学术思路,为实现露天矿边坡稳定性智能评价提供了有效手段。

     

    Abstract: In this paper,the current research status of intelligent evaluation of open pit slope stability is summarized from the aspects of intelligent sensing means,intelligent evaluation and prediction methods,and intelligent decision- making technology,etc. ,the characteristics of open pit slope engineering are analyzed,and the existing problems in the current research of intelligent evaluation of open pit slope stability are presented. The academic idea of the three-in- one slope stability intelligent evaluation,including displacement time series threshold,mechanical mechanism analysis, case analysis and expert system diagnosis,is the development trend of open-pit mine slope stability intelligent evalua- tion research. Firstly,a slope disaster case library and multi-factor multi-modal intelligent recognition mathematical model are established,the deep learning and big data analysis methods to cluster case types are used,and the features as well as pattern matching are identified. Secondly,via the mechanical mechanism calculation and evaluation,the in- gesting hidden danger stoic triggers and conditions are identified. Thirdly,a monitoring warning index system and warn- ing threshold based on the case pattern matching results are established,the case library knowledge base and expert system are constructed,and intelligent decision-making is realized. Finally,taking the northwest slope landslide of Da- gushan Iron Mine as an example,the change rule of slope safety factor is given based on mechanical calculation. At the same time,combined with the matching result of landslide case database,the index threshold (displacement accumula- tion and displacement rate) of site data time series curve is determined,so as to scientifically and reasonably give the judgment result of early warning situation. Data analysis,site model visualization,early warning release and landslide diagnosis are realized through cloud platform. The case preliminarily verifies the academic thinking of the three-in-one slope stability intelligent evaluation,and provides an effective mean to realize the intelligent evaluation of open pit slope stability.

     

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