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Research On The Monitoring And Early Warning System Of Single Landslide Disaster On Huang-Yan Highway

Posted on:2019-04-06Degree:MasterType:Thesis
Country:ChinaCandidate:B LiFull Text:PDF
GTID:2432330545491437Subject:Civil engineering
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The geological disasters in the loess area of Northwest China occur frequently,a great deal of traffic infrastructure damage and loss of life and property are caused by various geological disasters every year.A great number of practices show that the monitoring and early warning of geological disasters has become one of the key problems to be solved urgently in the work of disaster prevention and reduction in the road construction and operation of loess area.This paper is based on Huang-Yan expressway in Shanxi province,reference to the relevant technology of the automation and information science,establish an automatic remote monitoring system for geological disasters in the research area,the stability grading evaluation method and deformation prediction and warning model of single side slope are proposed.On this basis,a multi-objective and multi task information management and decision system for slope geological disasters has been developed,which integrates geological disaster monitoring information database,slope geological hazard prediction,widely deliver monitoring and forecasting information,applied to the slop of support project.The main research contents and conclusions of this paper are as follows:(1)According to the characteristics of the punctate distribution and numerous along the highway of Huang-Yan expressway slop,established the monitor principle of monitoring the deformation and rainfall,mainly.The main monitoring unit is deep displacement,rainfall and underground water level,and so on.Taking the GPRS module as the wireless transmission unit and the solar panel as the power supply system,we have carried out the overall construction of the remote monitoring system,realized the real-time data receiving,storage and multi-user networking communication,and established the remote monitoring center.(2)In view of the complex and varied characteristics of loess slope deformation and failure modes,nonlinear regression models,equal dimension and new interest grey models and their applicability are studied,and a prediction model base for slope deformation is established,which establishes a theoretical foundation for deformation tracking and prediction in the system.Based on the study of the regional rainfall early warning threshold and the instability criterion of the single slope in the loess region,a state early warning model suitable for the single slope is proposed.(3)Based on the framework of.Net and its development environment with the technology of Web Service and GSM network,Integrated development of multi–objective and multi-task automatic monitoring data integration and analysis system.,realizes the function of real-time information release,deformation tracking and forecast and geological disaster monitoring and early warning system information is released in real time.Provide efficient information management and decision support platform for the work of disaster prevention and reduction.(4)Taking Huang-Yan freeway slope engineering as an example,based on the method of fuzzy variable set and weight optimization evaluation,the stability of key slopes is evaluated and graded,efficiently,making monitoring and early warning work more accurate and eliminating a lot of redundant monitoring work.Select the typical slope to establish a remote monitoring system,real-time monitoring the deformation trend of slope,while using the single slope deformation prediction model to predict the deformation trend of the slope,and the use of early warning model to determine the warning level of slope,finally,use the network to issue early warning information,provide a strong support for disaster prevention and reduction.
Keywords/Search Tags:loess landslides, automated remote monitoring, deformation forecasting model, slide in the early warning, the system of data integration and analysis
PDF Full Text Request
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