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Study On Stability Model Of Slope Dangerous Rock Mass Based On Dynamic Characteristics

Posted on:2019-02-03Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y C JiaFull Text:PDF
GTID:1312330542451713Subject:Civil engineering
Abstract/Summary:PDF Full Text Request
During the process of slope engineering construction and maintenance,Slope dangerous rock block on the side slope of the rock slope is unstable,which brings great safety hazard to the project.The failure of the Slope dangerous rock block depends on the condition of the main control surface of the rock mass.With the cracking of the main structural plane,the shear strength of the main structural plane decreases and the slope of the rock Collapse.The instability of the Slope dangerous rock block is characterized by sudden collapse,no obvious displacement characteristics,and the existing displacement,stress and strain monitoring methods are difficult to meet the purpose of monitoring and monitoring the slope rock.The degree of bond between the Slope dangerous rock block and the parent rock is closely related to the stability of the Slope dangerous rock block.The dynamic characteristic parameters of the slope rock block will change with the change of the degree of adhesion of the Slope dangerous rock block and the parent rock.Therefore,the relationship between the dynamic characteristics of Slope dangerous rock block and the stability of Slope dangerous rock block provides a new method for rapid identification,stability evaluation and safety monitoring and early warning of Slope dangerous rock block.In this paper,the relationship between stability and dynamic characteristics of Slope dangerous rock block is established by theory,laboratory experiment and field application.Based on this model,the rapid identification,stability evaluation and real-time monitoring and monitoring of slope dangerous rock are realized.The following is the main content of this paper.(1)Based on the dynamic characteristics and typical failure modes of Slope dangerous rock block,the dynamic characteristics of Slope dangerous rock block are realized.Based on this classification,the dynamic model of slope rock mass is established by theoretical derivation.(2)In order to verify the correctness of the dynamic model of Slope dangerous rock block,laboratory tests are carried out on rock masses with different cohesive areas and masses.(3)through laboratory experiments,the relationship between dynamic parameters of Slope dangerous rock block and bond area of Slope dangerous rock block is further studied.(4)Based on the relationship between the dynamic characteristics of the rock mass and the area of the rock mass,the quantitative relationship model between the safety factor and the natural vibration frequency of the Slope dangerous rock block is established.At the same time,the relationship between the safety factor of dangerous rock block and other dynamic characteristics of Slope dangerous rock block is established.(5)Based on the relationship between safety factor and its dynamic characteristics,the rapid identification system of Slope dangerous rock block based on laser vibration method is established,and the real-time on-line monitoring system of Slope dangerous rock block based on wireless vibration measurement is established.The method realizes the rapid identification and real-time on-line monitoring and warning of Slope dangerous rock block.(6)Taking the dangerous rock blocks on both sides of the Baihepu reservoir as the test object,the potential Slope dangerous rock block is identified by the laser vibrometer noncontact.Real-time Monitoring of Potential Dangerous Rock Blocks Based on Wireless Vibration Sensor and Internet of Things Platform.This technology realizes the real-time online stability evaluation and safety warning of Slope dangerous rock block,verifies the feasibility of rapid identification technology and real-time online monitoring and monitoring technology.
Keywords/Search Tags:Slope dangerous rock mass, dynamic characteristics, stability evaluation, rapid identification, early warning monitoring
PDF Full Text Request
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