CN104881583A - Multi-means, dynamic and whole-process landslide prewarning method - Google Patents
Multi-means, dynamic and whole-process landslide prewarning method Download PDFInfo
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Abstract
The invention provides a multi-means, dynamic and whole-process landslide prewarning method. The method includes: performing macroscopic observation, engineering exploration data monitoring and displacement monitoring on landslide; performing macro damage phenomenon analysis and influence factor analysis according to a result of macro observation; building a numerical value model and performing parameter indicator determination according to a result of engineering exploration data monitoring; performing displacement back analysis and displacement tendency analysis according to a result of displacement monitoring; building a correcting numerical value model according to influence factor analysis and the built numerical value model; determining calculating parameters through parameter indicator determination and displacement back analysis; performing numerical value analog calculation analysis according to the correcting numerical value calculating model and the calculating parameters; calculating a displacement-time curve under a series of different stability safe coefficients according to numerical value analog calculation analysis; drawing a monitoring displacement-time curve according to displacement tendency analysis; comparing the above two curves to determine stability state of the landslide. By the method, landslide disaster recognition, prewarning and control level can be improved effectively.
Description
Technical field
The invention belongs to early warning technology field, landslide, be specifically related to a kind of many means, dynamic, overall process landslide method for early warning.
Background technology
Landslide Prediction early warning is a global difficult problem, and for the landslide engineering under complex engineering geologic condition, as reservoir landslide, Earthquake-landslide etc., its prediction and warning is more complicated, has the advantages that multidisciplinary high integrity intersects.
In theoretical research, vegetarian rattan enlightening filial piety (1965), by a large amount of tests, proposes landslide creep and destroys three-stage theory, establish the differential equation accelerating creep; Yan Tongzhen (1998,1988,1985), Chen Changyan etc. (2001) adopt multiple method to be studied slope failure regularity and spatio-temporal prediction prediction theory thereof.In Forecasting Methodology, Shi Bin etc. (2004,2005) Distributed Optical Fiber Sensing Techniques is adopted to carry out monitoring and warning to landslide, the forecast of system synthesis that real-time follow-up forecast, Liu Handong etc. (1998) that nonlinear prediction, Li Tianbin etc. (2003) that Ling You Qin cleaning politics, economics, organization, and ideology etc. (1993) propose propose propose, and the Forecasting Methodology such as the holography forecast that proposes of Huang Runqiu etc. (1997).
In forecast model research, Hu Xinli (2002), Tang Huiming (2005) propose the predictive model of landslide based on GIS method; Qin Siqing etc. (1993), Li Xiuzhen etc. (2007) propose Cusp Catastrophe and grey Cusp Catastrophe Model; Zhang Guirong etc. (2005) establish the rain-induced landslide early-warning and predicting system based on WEBGIS; Li Tianbin etc. (1999) propose dynamically point dimension track prediction model; Huang Runqiu and Xu Qiang (1997) proposes the multiple forecast models such as collaborative forecasting model.Can say, since nineteen sixty-eight Japanese scholars vegetarian rattan enlightening filial piety proposes creep rupture three-stage theory, over more than 40 year, the prediction on landslide experienced by by experimental forecast → empirical equation forecast → mathematical model forecast → Simulation Prediction; By the evolution of qualitative forecast → quantitative forecast → comprehensive forecasting.Forecast foundation is also by engineering experience, the empirical mathematical formula of macroscopic failure phenomenon, expert, develop into Corpus--based Method, recurrence, intelligent Theory set up calculation model targetedly, the analysis result arrived again based on numerical simulation forecasts, achieves significant progress.
Analyze existing prediction methods, its deficiency is mainly reflected in following three aspects: one be landslide criterion in, at present mostly using come down day displacement deformation amount as come down criterion.But for rock-soil material of different nature, landslide day displacement is widely different, there is the phenomenon of mass mutation, breakpoint, negative value, easily cause and misrepresent deliberately and fail to report, simple dependence monitoring result carries out mathematics deduction, by rate of displacement, acceleration etc. relatively change forecast the development trend on landslide, after all or being familiar with again displacement time curve geometric shape, be difficult to the effect reaching accurate forecast.Two is in calculating and artificial intelligence forecast, does not take into full account the dynamic process of Landslide Deformation, the change of Affecting Factors of Landslide Stability, and comes down intensive parameter over time etc.These influence factors are in the different phase of slide prediction, the effect played is also different, develop into different phase to affect the principal element of its stability also different on landslide, and conventional numerical analysis method does not mostly reflect the real process that Landslide Deformation is destroyed and inside and outside many risk factors completely.Three is in the Stability Judgement on landslide, lacks unified standard at present.The evaluation criterion of macroscopic appearance, Monitoring Data, numerical analysis three aspect is difficult to mutual correspondence, and discrimination standard is single, and insufficient.Do not have to consider the different phase on landslide, the difference of the feature, criterion, time limit etc. of slide prediction.Therefore, need now the feature for Landslide Deformation different phase badly, set up a set of comprehensive landslide stability evaluation system.
Summary of the invention
One of the object of the invention be to provide a kind of can improve landslide disaster identification, early warning and level of control many means, dynamically, overall process comes down method for early warning.
The many means of one provided by the invention, dynamic, overall process landslide method for early warning, comprise the steps:
Macroscopic observation, Geotechnical Engineering Investigation Data monitoring and displacement monitoring are carried out to the landslide surveyed;
Macroscopic failure phenomenon analysis and analysis of Influential Factors is carried out according to described macroscopic observation result;
Numerical model and parameter index mensuration is set up according to described Geotechnical Engineering Investigation Data monitoring result;
Backanalysis on displacements and displacement trend analysis is carried out according to described displacement monitoring result;
According to described analysis of Influential Factors result, described numerical model is corrected;
According to described parameter index measurement result and described backanalysis on displacements result determination calculating parameter;
Numerical simulation calculation analysis is carried out according to the numerical model after described correction and described calculating parameter;
According to described numerical simulation calculation analysis result, and combination carries out comprehensive evaluation analysis to the stability analysis of described macroscopic failure phenomenon analysis result, calculates the displacement-time curve under a series of different buckling safety factor;
Displacement monitoring-time curve is drawn according to described displacement trend analysis result;
By contrasting described displacement-time curve and described displacement monitoring-time curve, determining each moment real-time stabilization safety coefficient, finally quantitatively determining with safety coefficient to be the landslide form mechanism state of index.
Further, judged by described macroscopic observation, landslide is divided into stable, weak distortion, severe deformation and faces sliding four-stage.
Further, judged by described displacement monitoring, landslide can be divided into zero distortion, constant speed distortion, accelerate distortion and play speed distortion four-stage.
Further, judged by described different buckling safety factor index, when safety coefficient is greater than 1.1, landslide, without distortion, is in steady state (SS); When safety coefficient is 1.1-1.04, rate of deformation, close to constant speed, is in basicly stable state or weak distortion and comparatively severe deformation stage; When safety coefficient is 1.04-1.01, rate of deformation is tending towards accelerating, and be in tertiary creep transition section, side slope is in the severe deformation stage; When safety coefficient is 1.01-1.00, displacement and speed increase severely, and displacement increases two orders of magnitude, calculated distortion, and landslide enters acute speed distortion and faces the sliding stage.
Beneficial effect of the present invention is, the present invention is by the analysis to the on-the-spot displacement monitoring data of landslide engineering and macroscopic appearance, the deformation behaviour of the sliding mass obtained in conjunction with numerical analysis and Evolution, adopt buckling safety factor, quantitative evaluation and prediction forecast is carried out to the stability in landslide each stage residing, be convenient to engineering technical personnel understand and operation, contribute to improving the level of landslide disaster identification, early warning and control.
Accompanying drawing explanation
Figure 1 shows that the many means of the present invention, dynamic, overall process landslide method for early warning process flow diagram.
Embodiment
Hereafter will describe the present invention in detail in conjunction with specific embodiments.It should be noted that the combination of technical characteristic or the technical characteristic described in following embodiment should not be considered to isolated, they can mutually be combined thus be reached better technique effect.
As shown in Figure 1, the many means of one provided by the invention, dynamic, overall process landslide method for early warning, comprise the steps:
Step S1: macroscopic observation, Geotechnical Engineering Investigation Data monitoring and displacement monitoring are carried out to the landslide surveyed;
Step S2: carry out macroscopic failure phenomenon analysis and analysis of Influential Factors according to macroscopic observation result;
Step S3: set up numerical model and parameter index mensuration according to Geotechnical Engineering Investigation Data monitoring result;
Step S4: carry out backanalysis on displacements and displacement trend analysis according to displacement monitoring result;
Step S5: correct according to analysis of Influential Factors result logarithm value model;
Step S6: according to parameter index measurement result and backanalysis on displacements result determination calculating parameter;
Step S7: carry out numerical simulation calculation analysis according to the numerical model after correction and calculating parameter;
Step S8: according to numerical simulation calculation analysis result, and combination carries out comprehensive evaluation analysis to the stability analysis of macroscopic failure phenomenon analysis result, calculates the displacement-time curve under a series of different buckling safety factor;
Step S9: draw displacement monitoring-time curve according to displacement trend analysis result;
Step S10: by contrast displacement-time curve and displacement monitoring-time curve, determine each moment real-time stabilization safety coefficient, finally quantitatively determines with safety coefficient to be the landslide form mechanism state of index.
Come down early-warning and predicting accurately, must set up corresponding judgment criteria.Concerning many means, forecast system stage by stage, the macroscopic observation data should destroyed from Landslide Deformation, displacement monitoring data, Geotechnical Engineering Investigation Data three aspects set up corresponding judging quota respectively.The landslide of different stabilization sub stage, there is significant difference in deformation-failure character.
Judged by macroscopic observation data, landslide is divided into stable, weak distortion, severe deformation and faces sliding four-stage.
Judged by displacement monitoring data, landslide can be divided into zero distortion, constant speed distortion, accelerate distortion and play speed distortion four-stage.Little time large during the actual displacement of constant speed deformation stage, be tending towards constant speed, but deformation velocity also slightly can change, in the trend increased gradually; Accelerate deformation stage displacement and increase quickening, turn to acceleration gradually by constant speed, speed goes is large; Displacement, the speed of the most measuring point of acute fast deformation stage increase severely, and grow continuously and fast and no longer occur obviously declining, until landslide occurs.
Judged by different buckling safety factor index, when safety coefficient is greater than 1.1, landslide, without distortion, is in steady state (SS); When safety coefficient is 1.1-1.04, rate of deformation, close to constant speed, is in basicly stable state or weak distortion and comparatively severe deformation stage; When safety coefficient is 1.04-1.01, rate of deformation is tending towards accelerating, and be in tertiary creep transition section, side slope is in the severe deformation stage; When safety coefficient is 1.01-1.00, displacement and speed increase severely, and displacement increases two orders of magnitude, calculated distortion, and landslide enters acute speed distortion and faces the sliding stage.
Many means refer to adopt the multiple means such as macroscopic observation, displacement monitoring, Geotechnical Engineering Investigation Data monitoring analysis, and these means are organically combined, accomplish from determining trend, qualitative, quantitative angle carries out comprehensive descision to displacement Monitoring Data, macroscopic observation data and Geotechnical Engineering Investigation Data monitoring analysis result;
Dynamically refer in research process, dynamic consideration come down inside and outside risk factor change impact, analysis of landslide displacement increases the concrete reason of change, this process that landslide intrinsic strength and stability reduce gradually can be reflected, locomotory mechanism, analysis and prediction is carried out to the distortion on landslide and slip.For determining the real-time stabilization state come down, namely the landslide form mechanism safety coefficient of each period is determined, need to calculate the displacement-time curve under a series of different buckling safety factor, then by comparing with the displacement-time curve of monitoring, finally determine each moment real-time stabilization safety coefficient.
Overall process refers to from constant rate creeep stage, tertiary creep transition section to the play fast creep stage; From weak distortion, severe deformation to facing the sliding stage, omnidistance Landslide Deformation of grasping destroys situation, quantitatively determines to take safety coefficient as the landslide form mechanism state of index, and can make accurate forecast facing the sliding stage to landslide sliding time;
This prediction thought based on complete survey data, to preconditions such as the accurate understanding of Geological And Geomorphological Features on landslide, the test of the physical and mechanical parameter of slope body or inverting, detailed landslide macroscopic deformation breakoff phenomenon and displacement deformation Monitoring Data.Logarithm value model and numerical evaluation have higher requirements simultaneously, need to select suitable viscoelastic to mould the method for theoretical model and backanalysis on displacements mechanics parameter.
The present invention is by the analysis to the on-the-spot displacement monitoring data of landslide engineering and macroscopic appearance, the deformation behaviour of the sliding mass obtained in conjunction with numerical analysis and Evolution, adopt buckling safety factor, quantitative evaluation and prediction forecast is carried out to the stability in landslide each stage residing, be convenient to engineering technical personnel understand and operation, contribute to improving the level of landslide disaster identification, early warning and control.
Although give some embodiments of the present invention, it will be understood by those of skill in the art that without departing from the spirit of the invention herein, can change embodiment herein.Above-described embodiment is exemplary, should using embodiment herein as the restriction of interest field of the present invention.
Claims (4)
1. means more than, dynamic, an overall process landslide method for early warning, is characterized in that, comprise the steps:
Macroscopic observation, Geotechnical Engineering Investigation Data monitoring and displacement monitoring are carried out to the landslide surveyed;
Macroscopic failure phenomenon analysis and analysis of Influential Factors is carried out according to described macroscopic observation result;
Numerical model and parameter index mensuration is set up according to described Geotechnical Engineering Investigation Data monitoring result;
Backanalysis on displacements and displacement trend analysis is carried out according to described displacement monitoring result;
According to described analysis of Influential Factors result, described numerical model is corrected;
According to described parameter index measurement result and described backanalysis on displacements result determination calculating parameter;
Numerical simulation calculation analysis is carried out according to the numerical model after described correction and described calculating parameter;
According to described numerical simulation calculation analysis result, and combination carries out comprehensive evaluation analysis to the stability analysis of described macroscopic failure phenomenon analysis result, calculates the displacement-time curve under a series of different buckling safety factor;
Displacement monitoring-time curve is drawn according to described displacement trend analysis result;
By contrasting described displacement-time curve and described displacement monitoring-time curve, determining each moment real-time stabilization safety coefficient, finally quantitatively determining with safety coefficient to be the landslide form mechanism state of index.
2. a kind of many means as claimed in claim 1, dynamic, overall process landslide method for early warning, it is characterized in that, judged by described macroscopic observation, landslide is divided into stable, weak distortion, severe deformation and faces sliding four-stage.
3. a kind of many means as claimed in claim 1, dynamic, overall process landslide method for early warning, be is characterized in that, judged by described displacement monitoring, and landslide can be divided into zero distortion, constant speed distortion, accelerate distortion and play fast distortion four-stage.
4. a kind of many means as claimed in claim 1, dynamic, overall process landslide method for early warning, it is characterized in that, judged by described different buckling safety factor index, when safety coefficient is greater than 1.1, landslide, without being out of shape, is in steady state (SS); When safety coefficient is 1.1-1.04, rate of deformation, close to constant speed, is in basicly stable state or weak distortion and comparatively severe deformation stage; When safety coefficient is 1.04-1.01, rate of deformation is tending towards accelerating, and be in tertiary creep transition section, side slope is in the severe deformation stage; When safety coefficient is 1.01-1.00, displacement and speed increase severely, and displacement increases two orders of magnitude, calculated distortion, and landslide enters acute speed distortion and faces the sliding stage.
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Cited By (14)
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| CN105488582A (en) * | 2015-11-13 | 2016-04-13 | 辽宁工程技术大学 | Mountain talus landslide prediction method and device |
| CN106202908A (en) * | 2016-07-05 | 2016-12-07 | 西安交通大学 | A kind of high slope relaxes the decision method in district |
| CN106295040A (en) * | 2016-08-17 | 2017-01-04 | 中国科学院、水利部成都山地灾害与环境研究所 | Landslide disaster monitoring and warning earth's surface inclinometer threshold determination method |
| CN106405675A (en) * | 2016-08-25 | 2017-02-15 | 山东科技大学 | Dynamic monitoring system and method for early warning against slope slide of tailing pond of strip mining pit |
| CN108414573A (en) * | 2018-01-11 | 2018-08-17 | 山东大学 | A kind of Stability Analysis Methods for Evaluating Landslide based on electrical method and numerical simulation |
| CN108961688A (en) * | 2018-07-13 | 2018-12-07 | 福建特力惠信息科技股份有限公司 | A kind of big data support under Geological Hazards Monitoring and method for early warning |
| CN110261573A (en) * | 2019-05-16 | 2019-09-20 | 同济大学 | A kind of high position rock landslip stability dynamic value evaluation method |
| CN111209528A (en) * | 2020-01-06 | 2020-05-29 | 武汉理工大学 | Slope accumulated displacement grading early warning threshold value determination method |
| CN112504624A (en) * | 2020-11-11 | 2021-03-16 | 华能澜沧江水电股份有限公司 | Hydrodynamic landslide multi-information multi-source fusion early warning method |
| CN112597689A (en) * | 2020-12-11 | 2021-04-02 | 清华大学 | Landslide process analysis method, process numerical value reconstruction method and application |
| CN114186312A (en) * | 2021-12-03 | 2022-03-15 | 石家庄铁道大学 | Tunnel-related landslide type identification method based on tunnel deformation characteristics |
| CN115376283A (en) * | 2022-08-23 | 2022-11-22 | 江西理工大学 | Monitoring and early warning method and system based on multivariate data fusion |
| CN117493832A (en) * | 2023-12-29 | 2024-02-02 | 江西飞尚科技有限公司 | Landslide hazard curve identification method, landslide hazard curve identification system, storage medium and computer |
| CN117809433A (en) * | 2023-08-31 | 2024-04-02 | 应急管理部大数据中心 | Internet of things equipment-closing processing method and system supporting accurate fusion early warning |
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Cited By (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105488582A (en) * | 2015-11-13 | 2016-04-13 | 辽宁工程技术大学 | Mountain talus landslide prediction method and device |
| CN106202908A (en) * | 2016-07-05 | 2016-12-07 | 西安交通大学 | A kind of high slope relaxes the decision method in district |
| CN106202908B (en) * | 2016-07-05 | 2018-10-19 | 西安交通大学 | A kind of determination method in high slope relaxation area |
| CN106295040B (en) * | 2016-08-17 | 2019-04-30 | 中国科学院、水利部成都山地灾害与环境研究所 | Landslide disaster monitoring and warning earth's surface inclinometer threshold determination method |
| CN106295040A (en) * | 2016-08-17 | 2017-01-04 | 中国科学院、水利部成都山地灾害与环境研究所 | Landslide disaster monitoring and warning earth's surface inclinometer threshold determination method |
| CN106405675A (en) * | 2016-08-25 | 2017-02-15 | 山东科技大学 | Dynamic monitoring system and method for early warning against slope slide of tailing pond of strip mining pit |
| CN108414573A (en) * | 2018-01-11 | 2018-08-17 | 山东大学 | A kind of Stability Analysis Methods for Evaluating Landslide based on electrical method and numerical simulation |
| CN108961688A (en) * | 2018-07-13 | 2018-12-07 | 福建特力惠信息科技股份有限公司 | A kind of big data support under Geological Hazards Monitoring and method for early warning |
| CN108961688B (en) * | 2018-07-13 | 2020-11-03 | 特力惠信息科技股份有限公司 | Geological disaster monitoring and early warning method under support of big data |
| CN110261573A (en) * | 2019-05-16 | 2019-09-20 | 同济大学 | A kind of high position rock landslip stability dynamic value evaluation method |
| CN110261573B (en) * | 2019-05-16 | 2021-09-03 | 同济大学 | Dynamic evaluation method for stability of high-position rocky landslide |
| CN111209528A (en) * | 2020-01-06 | 2020-05-29 | 武汉理工大学 | Slope accumulated displacement grading early warning threshold value determination method |
| CN111209528B (en) * | 2020-01-06 | 2021-08-03 | 武汉理工大学 | Slope accumulated displacement grading early warning threshold value determination method |
| CN112504624A (en) * | 2020-11-11 | 2021-03-16 | 华能澜沧江水电股份有限公司 | Hydrodynamic landslide multi-information multi-source fusion early warning method |
| CN112597689A (en) * | 2020-12-11 | 2021-04-02 | 清华大学 | Landslide process analysis method, process numerical value reconstruction method and application |
| CN112597689B (en) * | 2020-12-11 | 2022-07-05 | 清华大学 | Landslide process analysis method, process numerical value reconstruction method and application |
| CN114186312A (en) * | 2021-12-03 | 2022-03-15 | 石家庄铁道大学 | Tunnel-related landslide type identification method based on tunnel deformation characteristics |
| CN114186312B (en) * | 2021-12-03 | 2022-07-19 | 石家庄铁道大学 | Tunnel-related landslide type identification method based on tunnel deformation characteristics |
| CN115376283A (en) * | 2022-08-23 | 2022-11-22 | 江西理工大学 | Monitoring and early warning method and system based on multivariate data fusion |
| CN115376283B (en) * | 2022-08-23 | 2023-11-28 | 江西理工大学 | Monitoring and early warning method and system based on multivariate data fusion |
| CN117809433A (en) * | 2023-08-31 | 2024-04-02 | 应急管理部大数据中心 | Internet of things equipment-closing processing method and system supporting accurate fusion early warning |
| CN117809433B (en) * | 2023-08-31 | 2024-05-28 | 应急管理部大数据中心 | Internet of things equipment-closing processing method and system supporting accurate fusion early warning |
| CN117493832A (en) * | 2023-12-29 | 2024-02-02 | 江西飞尚科技有限公司 | Landslide hazard curve identification method, landslide hazard curve identification system, storage medium and computer |
| CN117493832B (en) * | 2023-12-29 | 2024-04-09 | 江西飞尚科技有限公司 | Landslide hazard curve identification method, landslide hazard curve identification system, storage medium and computer |
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Application publication date: 20150902 |