CN107480840A - Come down applying forecasting procedure - Google Patents
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Abstract
The invention discloses a kind of Prediction Or Forecast of Landslides, mainly for the landslide applying forecast disposably slided.For the present invention by landslide displacement monitoring, displacement and unstability time to landslide are predicted forecast.The Prediction and Forecast of Landslide model being fitted by Monitoring Data, is the direct embodiment to Landslide Stability and tendency toward sliding；The model is easy to operation, and forecast result is reasonable；Pass through the comparative analysis of different type displacement, it may be determined that most rational fitting result, the model is the process of a performance matching, and with the increase of landslide monitoring data, model can realize self-checking and optimization；The pattern not only can determine that whether landslide stablizes, and more accurate can must predict that acute sliding time point occurs for landslide；Model provides matched curve simultaneously, intuitively shows the change curve of displacement, speed and acceleration to come down, can be by the change of the abnormal point analysis stress of data, and then it is modified using the mode of man-computer cooperation.
Description
Technical field
It is pre- mainly for the landslide applying disposably slided the present invention relates to a kind of Prediction Or Forecast of Landslides
Report, the present invention are more applicable for the small-sized side slope of soft rock or the soil body.
Background technology
Prediction and Forecast of Landslide is to prevent landslide from bringing one of effective means of disaster, due to special geological conditions and
Complicated risk factor, causes Prediction and Forecast of Landslide very difficult, but also it is significant therefore to seem.
Prediction and Forecast of Landslide, from broadly, including Time Forecast, Space Forecast and hazard forecasting.Involved by the present invention
And, the applying forecast being contained within Time Forecast.
The method of Prediction and Forecast of Landslide can be generally divided into following four classes：
First, by Monitoring Data, corresponding analytic formula, and then it is expected that the time that landslide occurs are fitted；
Second, by field test or laboratory test, the mechanics parameter on landslide is obtained, with reference to the practical significance on landslide, is selected
Suitable theoretical method is selected, calculates the stability on landslide, and then overall merit is carried out to landslide；
Third, modeling, will come down scaled, similar physical model is established；
Fourth, the computational methods such as finite element, discrete element, this kind of method, more precisely for should be an overall merit
Method, it is not used to independent prediction landslide, such as corresponding parameter acquiring method, it is necessary to laboratory test or field test
It is combined.
From the point of view of time development course, landslide can substantially be divided into three phases：
Six the seventies, Prediction and Forecast of Landslide mainly utilize phenomenon and empirical equation forecast stage.This stage is main
With the qualitative judgement of some explicitly signs before landslide failure, while also have using curve extrapolation method, as satio utilizes experience
Formula (Satio M.1965, Forcasting the time to occurrence of a slope failure,
Proc.6th Int.Conf.S.M.F.E,Montreal,2:537-541), success prediction Japanese meal mountain High-Field mountain tunnel is slided
Slope.
The eighties, Prediction and Forecast of Landslide introduce some modern mathematical theories, such as (Wang Sijing；Wang Xiaoning, 1989, greatly
The energy spectrometer and its hazard prediction of type HIGH-SPEED LANDSLIDE, come down selected papers, 117-124) by gray system theory GM (1,
1) model introduces the fitting extrapolation of landslide displacement-time graph；With the introducing of these methods, Prediction and Forecast of Landslide, from before
Empirical rules, enter stage of accurate prediction.
After the nineties, with nonlinear theory and GIS development, people also begin to pay attention to the phenomenon and physics on landslide
Meaning is combined.Such as：(Wang Junling；Sun Huaijun, 2005, Prediction and Forecast of Landslide system development and research, Zhe Jiangshui based on GIS
Sharp science and technology, 32 (3):6-8) Prediction and Forecast of Landslide system is developed with reference to GIS；(You Hui；Qin Siqing；Zhu Shiping；Wan Zhiqing, close
In the discussion 2001 of the Nonlinear Dynamical Characteristics of Landslide Evolution, engineering geology journal, 9 (3):331-335) then with non-linear reason
By, with reference to landslide physical significance, analyze its mechanical characteristics.
The present invention is mainly based on Monitoring Data, there is provided landslide applying forecasting procedure, this method is to face institute
For having general come down, it is adapted to the middle or short term temporal prediction on all landslides.
The content of the invention
It is an object of the invention to provide one kind landslide applying forecasting procedure, the present invention is supervised by landslide displacement
Survey, forecast is predicted to landslide displacement and unstability time using the prediction model.
The first development trend according to landslide monitoring data of the invention, set the citation form of Prediction and Forecast of Landslide model.Again
With reference to Monitoring Data, model parameter is determined.The model is finally utilized, whether prediction landslide is stable and acute sliding tool may occur
The body time.
The present invention comprises the following steps：
1. establish Prediction and Forecast of Landslide model：The form of model is：Wherein, p0、p1、p2To be undetermined
Parameter, calculating is iterated using Levenberg-Marquardt algorithms, seeks undetermined parameter；p1、p2It is the body of landslide displacement amount
Existing, its value is bigger, and explanation landslide displacement is bigger, and vice versa；p0It is that landslide displacement speed tends to infinite reaction, p0It is bigger, say
The time of the possible unstability in bright landslide is more long；
2. when acute sliding moment occurs for landslide, landslide displacement tends to be rapidly just infinite, and this illustrates that be fitted curve will be deposited
In the asymptote parallel with y-axis；The model is by increasing by one before exponential termCome what is realized；
3. the acquisition of land slide data：Monitoring Data be the model master data basis, Monitoring Data include horizontal displacement,
Vertical displacement and corresponding time；Three groups of data are classified as three row respectively, horizontal displacement with glide direction is consistent on landslide is
Just, vertical displacement is downwards for just, to be made a text, facilitate the later stage to call；
4. data inputting and selection：Above-mentioned text is imported into Prediction and Forecast of Landslide model, displacement data can be single
One selection horizontal displacement or vertical displacement, can also select resultant displacement；The selection of different pieces of information, can be simply according to number
According to being contrasted, the actual configuration on landslide can also be combined, analysis produces the difference of horizontal displacement and vertical displacement, and then
Analysed in depth with reference to physical significance；
5. select data uses item：Total data can be directly selected, n item datas before can also selecting；Landslide Prediction
Forecasting model is the process of a performance matching, and with the increase of landslide monitoring data, Prediction and Forecast of Landslide model can be realized certainly
I examines and optimization；
6. the preservation of result of calculation：Corresponding result of calculation is stored in the file where Monitoring Data；Check this article
Part presss from both sides, it can be seen that displacement, speed, acceleration and the graph of relation of time for the different time that comes down, the curve map can enter
One step demonstrate,proves the reasonability of Prediction and Forecast of Landslide；Corresponding text result of calculation is in corresponding folder.
Beneficial effects of the present invention：
The Prediction and Forecast of Landslide model being fitted by Monitoring Data, is the direct body to Landslide Stability and tendency toward sliding
It is existing；The model is easy to operation, and forecast result is reasonable；Pass through the comparative analysis of different type displacement, it may be determined that most rational to intend
Result is closed, the model is the process of a performance matching, and with the increase of landslide monitoring data, model can realize self-checking
And optimization；The pattern not only can determine that whether landslide stablizes, and more accurate can must predict that acute sliding time point occurs for landslide；
Model provides matched curve simultaneously, intuitively shows the change curve of displacement, speed and acceleration to come down, can pass through number
According to abnormal point analysis stress change, and then it is modified using the mode of man-computer cooperation.
Brief description of the drawings
Prediction and Forecast of Landslide model flow figures of the Fig. 1 based on Monitoring Data exponential fitting.
Fig. 2 landslide exponential forecasting forecasting model softwares and its associated data files.
The arrangement of Fig. 3 Monitoring Datas.
Fig. 4 landslides applying forecasting model software interface.
Fig. 5 imports Monitoring Data.
Fig. 6 result of calculations, displacement-time curve figure, speed-time curve figure and acceleration-time plot.
Fig. 7 the model calculation files.
File corresponding to Fig. 8 result of calculations and curve map.
The selection of Fig. 9 software parameter.
Figure 10 chooses different time, and the fitting result of different parameters stores side by side.
Figure 11 single fitting result files.
Figure 12 displacement-time curves (by taking resultant displacement as an example).
Figure 13 speed-time curves (by taking resultant displacement as an example).
Figure 14 acceleration-time graph (by taking resultant displacement as an example).
The corresponding data of Figure 15 result of calculation curves.
Figure 16 the model calculation word descriptions.
Figure 17 uses the result of total data item.
Figure 18 selects x displacement the Fitting Calculation result.
Embodiment
The present invention comprises the following steps：
1. establish Prediction and Forecast of Landslide model：The form of model is：Wherein, p0、p1、p2To be undetermined
Parameter, calculating is iterated using Levenberg-Marquardt algorithms, seeks undetermined parameter；p1、p2It is the body of landslide displacement amount
Existing, its value is bigger, and explanation landslide displacement is bigger, and vice versa；p0It is that landslide displacement speed tends to infinite reaction, p0It is bigger, say
The time of the possible unstability in bright landslide is more long；
2. when acute sliding moment occurs for landslide, landslide displacement tends to be rapidly just infinite, and this illustrates that be fitted curve will be deposited
In the asymptote parallel with y-axis；The model is by increasing by one before exponential termCome what is realized；
3. the acquisition of land slide data：Monitoring Data be the model master data basis, Monitoring Data include horizontal displacement,
Vertical displacement and corresponding time；Three groups of data are classified as three row respectively, horizontal displacement with glide direction is consistent on landslide is
Just, vertical displacement is downwards for just, to be made a text, facilitate the later stage to call；
4. data inputting and selection：Above-mentioned text is imported into Prediction and Forecast of Landslide model, displacement data can be single
One selection horizontal displacement or vertical displacement, can also select resultant displacement；The selection of different pieces of information, can be simply according to number
According to being contrasted, the actual configuration on landslide can also be combined, analysis produces the difference of horizontal displacement and vertical displacement, and then
Analysed in depth with reference to physical significance；
5. select data uses item：Total data can be directly selected, n item datas before can also selecting；Landslide Prediction
Forecasting model is the process of a performance matching, and with the increase of landslide monitoring data, Prediction and Forecast of Landslide model can be realized certainly
I examines and optimization；
6. the preservation of result of calculation：Corresponding result of calculation is stored in the file where Monitoring Data；Check this article
Part presss from both sides, it can be seen that displacement, speed, acceleration and the graph of relation of time for the different time that comes down, the curve map can enter
One step demonstrate,proves the reasonability of Prediction and Forecast of Landslide；Corresponding text result of calculation is in corresponding folder.
It is numerous to influence the factor on landslide, the morphological feature of slip mass in itself should be considered, while also to consider earthquake rainfall
Etc. many inducements.These conditions are coupled and then predict the play sliding time on landslide, are the mistakes that a comparison is difficult to
Journey.The actual displacement Monitoring Data of the present invention, a comprehensive embodiment of the form that actually comes down and Rock And Soil parameter.It is bent
The flex point and catastrophe point of line, result caused by the embodiment that stress changes of exactly coming down, that is, various inducements synthesis.
The displacement curve on utilization index method fitting landslide, by the method for extrapolation, the movement tendency on landslide can be carried out
Prediction.Foundation for the model is, it is necessary to consider the practical significance to come down, when acute sliding moment, landslide position occur for landslide
Shifting tends to be just infinite rapidly, and this illustrates that be fitted curve will have the asymptote parallel with y-axis.It can increase before exponential term
OneTo realize.When in addition with t=0, the displacement for setting landslide determines the constant term of model as 0, and then determines model
Form be：Wherein, p0、p1、p2For undetermined parameter, carried out using Levenberg-Marquardt algorithms
Iterative calculation, seeks undetermined parameter.p1、p2It is the embodiment of landslide displacement amount, its value is bigger, and explanation landslide displacement is bigger, and vice versa.
p0It is that landslide displacement speed tends to infinite reaction, p0It is bigger, illustrate that the time of the possible unstability in landslide is more long.
Concrete operation step is：
1. data preparation：Landslide detection data are organized into text.First is classified as the time, and second is classified as corresponding water
Prosposition moves, and the 3rd is classified as vertical displacement, as shown in Figure 2.
Runs software is opened 2. clicking on：Software position is found, as shown in figure 3, double-clicking ui.exe, opens software.It is soft
Part interface is as shown in Figure 4.
3. import data：Click browses, and finds the landslide monitoring data place path obtained by step 1, double-clicks and import, such as
Shown in Fig. 5.
4. displacement selects：It is single selection to select x displacement, y displacement or resultant displacement, resultant displacement according to actual conditions.
5. selection data use item：For the result of lasting observation, it can directly select and use total data, then
Renewal Monitoring Data every time, can obtain a slightly differentiated prediction result, this result is also closest in theory
Actual.If for one group of Monitoring Data, it is eager to obtain an evaluation result, then n items are further added by as prediction before selecting
Several Monitoring Datas are verified afterwards, and then obtain a complete forecast model.
6. the selection of model：Preference pattern：
7. start to calculate：Click starts to calculate, and system oneself is calculated automatically and ejects result, as shown in Figure 6.
8. check result：It can be evaluated whether to come down by asymptote and the acute sliding time may occur, while position can also be passed through
Move or speed is predicted.The result that can directly open preservation accordingly checks that prediction result is stored in where Monitoring Data
File, named with the time, as shown in fig. 7, each file includes the relation of displacement, speed and acceleration and time
Curve, and corresponding result of calculation, such as scheme, shown in 8.
Specific embodiment：
1. so that Fushun Western Surface Mine south nation comes down one group of Monitoring Data as an example.By landslide monitoring data preparation into shown in Fig. 2
Result.
2. double-clicking running software, resultant displacement is selected first here.Mainly belong to rock mass slope, main edge in view of landslide
The soft stratum bedding slip of slip mass.And the result of 45 before use, models fitting first is carried out to landslide, as shown in Figure 9.
3. click starts to calculate, after calculating terminates, result of calculation and curve map are ejected.Directly analysis can be carried out to it to sentence
It is disconnected, after window, result can be checked again in corresponding save location, save location, as shown in Figure 10.
A 4. open file folder, it can be seen that calculate each time, there is 5 corresponding document results.Wherein, three curve maps
It is displacement-time curve, speed-time curve and acceleration time graph respectively, as shown in Figure 12, Figure 13 and Figure 14.Especially
It is displacement time curve, the curve has prediction curve and monitoring result simultaneously, may also be used for judging fitting effect.Three curves
Specific data are shown in file outputdata.txt corresponding to figure, as shown in figure 15.The entitled output.txt of another file text
Part, then some relevant parameters of fit procedure are have recorded, as shown in figure 16.The hits of model, selection including selection,
Model parameter and the coefficient correlation of fitting.Except by curve intuitive judgment fitting effect, coefficient correlation is also one quantitative
The parameter of fitting effect is described.It can be seen that the coefficient correlation of this fitting is 0.99608, illustrate that fitting effect is fine.Finally
Obtained asymptote, then it is a supposition for landslide occurring the acute sliding time.
5. as Monitoring Data is constantly updated, model is increased using data volume.Also dynamic is occurring for corresponding fitting result
Change.Selection uses total data item, obtained fitting result, as shown in figure 17.
Come down 6. because monitoring site is in the trailing edge on landslide, at this and mainly mainly showed by tensile stress, this result
To move horizontally, accordingly it is also possible to be directly fitted with horizontal displacement.Fitting result is as shown in figure 18.
Claims (1)
1. one kind landslide applying forecasting procedure, it comprises the following steps：
1) establishes Prediction and Forecast of Landslide model：The form of model is：Wherein, p0、p1、p2For undetermined parameter,
Calculating is iterated using Levenberg-Marquardt algorithms, seeks undetermined parameter；p1、p2It is the embodiment of landslide displacement amount, its
Value is bigger, and explanation landslide displacement is bigger, and vice versa；p0It is that landslide displacement speed tends to infinite reaction, p0It is bigger, illustrate landslide
The time of possible unstability is more long；
2) for when acute sliding moment occurs for landslide, landslide displacement tends to be rapidly just infinite, this illustrate be fitted curve to exist with
The parallel asymptote of y-axis；The model is by increasing by one before exponential termCome what is realized；
3) acquisition of land slide datas：Monitoring Data is the master data basis of the model, and Monitoring Data includes horizontal displacement, erected
To displacement and corresponding time；Three groups of data are classified as three row respectively, horizontal displacement with it is consistent with landslide glide direction be just,
Vertical displacement is downwards for just, to be made a text, facilitate the later stage to call；
4) data inputtings and selection：Above-mentioned text is imported into Prediction and Forecast of Landslide model, displacement data can be with single
Horizontal displacement or vertical displacement are selected, resultant displacement can also be selected；The selection of different pieces of information, simply it can be entered according to data
Row contrast, the actual configuration on landslide can also be combined, analysis produces the difference of horizontal displacement and vertical displacement, and then combines
Physical significance is analysed in depth；
5) selects the use item of data：Total data can be directly selected, n item datas before can also selecting；Prediction and Forecast of Landslide
Model is the process of a performance matching, and with the increase of landslide monitoring data, Prediction and Forecast of Landslide model can realize that self is examined
Test and optimize；
6) preservation of result of calculations：Corresponding result of calculation is stored in the file where Monitoring Data；Check this document
Folder, it can be seen that displacement, speed, acceleration and the graph of relation of time for the different time that comes down, the curve map can be further
Verify the reasonability of Prediction and Forecast of Landslide；Corresponding text result of calculation is in corresponding folder.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108010280A (en) * | 2017-12-26 | 2018-05-08 | 成都理工大学 | A kind of sudden Loess Landslide method for early warning and its application |
| CN109543341A (en) * | 2018-12-11 | 2019-03-29 | 重庆大学 | A kind of prediction side slope faces the power function speed counting backward technique of sliding time |
| CN110400000A (en) * | 2019-05-31 | 2019-11-01 | 西安工程大学 | Prediction of Displacement in Landslide method based on singular value decomposition and UPF |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030078901A1 (en) * | 2001-10-22 | 2003-04-24 | Coppola Emery J. | Neural network based predication and optimization for groundwater / surface water system |
| CN103605903A (en) * | 2013-12-03 | 2014-02-26 | 吉林大学 | Middle or short term forecasting method for landslide time |
| CN104699995A (en) * | 2015-04-03 | 2015-06-10 | 吉林大学 | Prediction and forecast method of landslide monitoring data logarithm fitting |
-
2017
- 2017-10-17 CN CN201710964822.5A patent/CN107480840A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030078901A1 (en) * | 2001-10-22 | 2003-04-24 | Coppola Emery J. | Neural network based predication and optimization for groundwater / surface water system |
| CN103605903A (en) * | 2013-12-03 | 2014-02-26 | 吉林大学 | Middle or short term forecasting method for landslide time |
| CN104699995A (en) * | 2015-04-03 | 2015-06-10 | 吉林大学 | Prediction and forecast method of landslide monitoring data logarithm fitting |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108010280A (en) * | 2017-12-26 | 2018-05-08 | 成都理工大学 | A kind of sudden Loess Landslide method for early warning and its application |
| CN109543341A (en) * | 2018-12-11 | 2019-03-29 | 重庆大学 | A kind of prediction side slope faces the power function speed counting backward technique of sliding time |
| CN109543341B (en) * | 2018-12-11 | 2023-06-27 | 重庆大学 | Power function speed reciprocal method for predicting side slope critical slip time |
| CN110400000A (en) * | 2019-05-31 | 2019-11-01 | 西安工程大学 | Prediction of Displacement in Landslide method based on singular value decomposition and UPF |
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Application publication date: 20171215 |