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阶跃型滑坡综合变形预测及监测预警方法研究
引用本文:袁维,孙瑞峰,钟辉亚,焦海明,胡惠华,林杭.阶跃型滑坡综合变形预测及监测预警方法研究[J].水利学报,2023,54(4):461-473.
作者姓名:袁维  孙瑞峰  钟辉亚  焦海明  胡惠华  林杭
作者单位:中国电建集团中南勘测设计研究院有限公司, 湖南 长沙 410014;石家庄铁道大学 土木工程学院, 河北 石家庄 050043;中南大学 资源与安全工程学院, 湖南 长沙 410012;中铁十七局集团城市建设有限公司, 贵州 贵阳 550029;湖南省交通规划勘察设计院有限公司, 湖南 长沙 410200
基金项目:河北省重点研发计划项目(22375402D);河北省自然科学基金项目(E2021210041);国家自然科学基金项目(11902208);湖南省自然科学基金项目(2022JJ30641);湖南省交通运输科技进步与创新计划项目(202120)
摘    要:大型库岸滑坡的长期变形在汛期降雨作用下呈现明显的周期性“阶跃式”陡增特征。针对阶跃型滑坡的变形特征,本文提出了一种多源数据“融合-预测-预警”的三步式滑坡监测预警方法:(1)“融合”,即基于经验模态分解法将多点位移监测数据分别分解为趋势项和周期项,采用加权值法分别融合不同监测点的趋势项和周期项位移得到融合趋势项和融合周期项序列,并将两者叠加得到滑坡体的现状综合变形时间序列;(2)“预测”,即引入“一个预测周期”概念,采用滑动多项式拟合法和随机森林算法分别对融合趋势项和融合周期项进行预测并叠加得到滑坡体的预测综合变形时间序列;(3)“预警”,即基于斜率变点分析方法搜索综合变形曲线的“稳定点”和“跃迁点”,确定稳定变形和加速变形区间的斜率,建立阶跃型滑坡的四级递进式分级预警模型,基于该预警模型对滑坡现状进行预警。以向家坝水库某滑坡体自动化位移监测数据为研究对象,采用本文所提方法对该滑坡进行了综合变形预测和监测预警,结果表明:综合变形时间序列可以整体反映滑坡的变形演化规律,且预测结果可靠,根据分级预警模型判断此滑坡体当前处于稳定变形阶段(Ⅰ级预警)。

关 键 词:阶跃型滑坡  变形预测  监测预警  数据融合  经验模态分解  灰色关联理论  随机森林算法  变点分析方法
收稿时间:2022/4/29 0:00:00

Research on comprehensive deformation prediction and monitoring and early warning method for step-like landslide
YUAN Wei,SUN Ruifeng,ZHONG Huiy,JIAO Haiming,HU Huihu,LIN Hang.Research on comprehensive deformation prediction and monitoring and early warning method for step-like landslide[J].Journal of Hydraulic Engineering,2023,54(4):461-473.
Authors:YUAN Wei  SUN Ruifeng  ZHONG Huiy  JIAO Haiming  HU Huihu  LIN Hang
Affiliation:Power China Zhongnan Engineering Corporation Limited, Changsha 410014, China;School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China;School of Resources and Safety Engineering, Central South University, Changsha 410012, China;China Railway 17th Bureau Group Urban Construction Co., Ltd., Guiyang 550029, China;Hunan Provincial Communications Planning, Survey and Design Institute CO. LTD., Changsha 410200, China
Abstract:The long-term deformation of the bank slope of the large reservoir presents an obvious periodical "step-type" steep increase under the action of rainfall in flood season.Aiming at the deformation characteristics of step landslide, a three-step landslide monitoring and early warning method for multi-source data is proposed in this study:(1) "Fusion"-The multi-point monitoring data are decomposed into trend term and period term based on empirical mode decomposition method, the trend term and periodic term displacements of different monitoring points are fused by weighting method, and the obtained trend term and periodic term are superimposed to obtain the current status of the integrated landslide deformation.(2) "Prediction"-The concept of "one prediction period" is introduced, the sliding polynomial fitting method and the random forest algorithm are used to predict the fusion trend term and the fusion period term respectively and superimpose them to obtain the predicted comprehensive deformation of the landslide.(3) "Early warning"-Based on the slope change point theory, the "stable point" and "transition point" of the comprehensive deformation curve are searched, and the average slope of the stable deformation and accelerated deformation interval is determined.Then, a 4-stage progressive hierarchical warning model of step-like landslide is established, and the current safety of the bank slope is warned.Taking the slope automatic displacement monitoring data of a bank slope of Xiangjiaba Reservoir as an example, the comprehensive deformation prediction and safety warning of this bank slope are carried out by using the method proposed in this paper.The results show that the comprehensive deformation time series can reflect the deformation evolution law of the landslide as a whole, and the prediction results are reliable.According to the hierarchical warning model, this slope is currently in the stage of stable deformation (Grade I early-warning).
Keywords:step-like landslide  deformation prediction  monitoring and early warning  data fusion  empirical mode decomposition method  gray correlation theory  random forest algorithm  change point analysis method
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