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基于滑动力监测滑坡系统的预警模式研究
引用本文:陈孝刚,陶志刚,桂洋,张钊.基于滑动力监测滑坡系统的预警模式研究[J].金属矿山,2011,40(12):127-131.
作者姓名:陈孝刚  陶志刚  桂洋  张钊
作者单位:1.深部岩土力学与地下工程国家重点实验室;2.中国矿业大学岩土工程研究中心
基金项目:国家自然科学基金项目,长江学者和创新团队发展计划项目
摘    要:基于滑动力大于抗滑力是滑坡发生的充分必要条件的预警原则,研发出一套滑坡远程实时监测预报系统,其对滑坡地质灾害预报预警具有重要意义。以滑坡滑动力模拟试验和滑坡室内物理模型试验为基础,初步确定出滑坡的预警模式,然后以平庄露天煤矿、西气东输(延安段)管道工程、南芬露天铁矿、朔州露天井工联合开采煤矿为现场应用研究对象,开展了滑坡监测及预警预报的现场试验研究,对前面提出的滑坡预警模式进行了充分的验证。结果显示,现场滑坡滑动力监测曲线的预警模式与室内模拟试验推断出的结果是一致的,说明这种预警模式可以用来继续分析判断其他现场边坡体的稳定性,在滑坡发生前做出准确预警预报。

关 键 词:滑坡  滑动力  监测曲线  预警模式  

Research of Sliding Force Warning Model Based on Remote Real-Time Monitor Landslide System
Chen Xiaogang,Tao Zhigang,Gui Yang,Zhang Zhao.Research of Sliding Force Warning Model Based on Remote Real-Time Monitor Landslide System[J].Metal Mine,2011,40(12):127-131.
Authors:Chen Xiaogang  Tao Zhigang  Gui Yang  Zhang Zhao
Affiliation:1.State Key Laboratory for Geomechanics & Deep Underground Engineering;2.Research Center of Geotechnical Engineering,China University of Mining & Technology
Abstract:Sliding force greater than sliding resistance is sufficient and necessary condition of the landslide,based on this warning principle,a landslide remote real-time monitoring and prediction system is developed,and it has important meaning in forecasting and warning geological dirsasters of landslide。Based on the landslide dynamic simulation and indoor physical model experiment,the landslide warning model is preliminarily determined。And the system are applied and researched in Pingzhuang open coal mine,west-east gas transmitting pipeline project(Yan'an section),NaFen open iron mine and ShuoZhou open-underground coal mine,which has proved sufficiently the landslide warning model.Results show that the field warning model of landslide sliding force monitoring curves is consistent with the inferred model of indoor physical model experiment.Thus,this kind of warning model can be used to continue to analyze and judge the stability in the other slip mass,and make accurate warning and forecasting ahead of landslide.
Keywords:Slope  Sliding force  Monitoring curves  Warning model
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