CN115563802A - Landslide and critical-sliding-time forecasting method based on self-adaptive time window and multiple criteria - Google Patents
Landslide and critical-sliding-time forecasting method based on self-adaptive time window and multiple criteria Download PDFInfo
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Abstract
The invention discloses a landslide impending slip time forecasting method based on a self-adaptive time window and multiple criteria. According to the method, a plurality of time windows are set, and the optimal time window is selected based on the tangent angle time curve, so that the tangent angle calculation error is avoided, and the intelligence and the accuracy of landslide time prediction are improved; and then, the Pearson correlation coefficient is used as a second criterion for identifying the critical slip stage, namely, when the tangent angle value is large enough, the landslide time is predicted by adopting a speed inverse method, and when the Pearson correlation coefficient reaches a certain range, a landslide time prediction result is input. The method adaptively determines the optimal time window, and simultaneously adopts double criteria to ensure the accuracy of the identification in the critical slip stage, thereby improving the reliability of the forecast.
Description
Technical Field
The invention relates to the technical field of alarms responding to disaster events, in particular to a landslide impending landslide time forecasting method based on an adaptive time window and multiple criteria.
Background
Based on the landslide three-stage deformation theory of M.Saito, T.A.Fukuzono proves that the reciprocal speed of the landslide time-to-slip has a linear relation with time through analytical experiments. When the landslide deformation speed is increased, the expected landslide occurrence time can be calculated according to a speed reciprocal method, but the time forecast has reliability only when the landslide is in a near-slip stage. At present, the mainstream forecasting method is as follows: and judging the critical sliding stage of the landslide by adopting the tangent angle value, and forecasting the time by utilizing a speed reciprocal method. This method has several drawbacks: 1) The time window for calculating the tangent angle and the tangent speed is not definite, some researchers adopt the sampling time interval of monitoring data points, some researchers adopt a fixed time window (such as 3h,7 h), the tangent angle value has higher sensitivity to the time window, and an improper time window easily causes the calculation error of the tangent angle; 2) Only depending on a criterion of the tangent angle value, the accuracy of the identification in the critical sliding stage is not enough.
Disclosure of Invention
In view of this, the invention provides a landslide imminent-slip time forecasting method based on a self-adaptive time window and multiple criteria, which can effectively improve the reliability of landslide time forecasting.
The invention discloses a landslide impending slide time forecasting method based on a self-adaptive time window and multiple criteria, which comprises the following steps:
s1, monitoring a scene to acquire a deformation time curve; self-adaptively obtaining an optimal time window; the method for acquiring the optimal time window specifically comprises the following steps:
s11, continuously monitoring a scene in real time to obtain a deformation time curve; setting a plurality of fixed time windows, respectively calculating tangent angles of the deformation time curves under the fixed time windows, and moving the fixed time windows to obtain tangent angle curves corresponding to the fixed time windows;
s12, sequencing the fixed time windows from small to large, and sequentially calculating the coincidence rate of tangent angle curves under the adjacent fixed time windows; when the coincidence rate exceeds a set threshold value B for the first time, the corresponding fixed time window is the optimal time window;
s2, calculating tangent angles of all moments based on the optimal time window obtained in the step S1;
s3, calculating the reciprocal of the speed at each moment based on the optimal time window obtained in the step S1, and further obtaining the Pearson correlation coefficient at each moment;
and S4, extracting the moments when the tangent angle is larger than the threshold theta and the Pearson correlation coefficient is smaller than the threshold beta, and outputting the landslide critical slip time predicted by adopting an inverse speed method at the moments.
Preferably, the tangent angle under the fixed time window Δ t is calculated as follows:
first, the accumulated deformation S is calculated i Average rate of (B) i ：
Wherein S is 1 、S i Respectively, t in the deformation time curve 1 Time t and i accumulated deformation corresponding to the moment;
then, using the accumulated deformation S i Divided by the average rate B i Obtaining T consistent with the dimension of time T i ：
Then t is i Time of day, deformation time curve at fixed time window Δ t (Δ t = t) i -t i-n ) Lower tangent angle alpha i Comprises the following steps:
preferably, in step S12, the method for calculating the overlapping ratio of the tangent angle curves in the adjacent fixed time windows is as follows:
calculating tangent angle difference values on tangent angle curves corresponding to adjacent time windows at the same moment, and when the difference value is less than or equal to a set threshold value A, considering that the information of the two tangent angle curves at the moment is overlapped; and the ratio of the information coincidence duration of the two tangent angle curves to the total duration is the coincidence rate of the two curves.
Preferably, in S3, the pearson correlation coefficient calculation method is as follows:
calculating the inverse velocity IV in a fixed time window deltat i ：
In the formula (7), Δ t is the optimal time window obtained by S1; s i 、S i-n Respectively, t in the deformation time curve i Time t and i-n accumulated deformation corresponding to the moment;
then t i Pearson's correlation coefficient r at time i Comprises the following steps:
wherein IV i-n ～IV i Are each t i-n ～t i The inverse of the velocity at that moment.
Preferably, in S3, the speed reciprocal at each time is filtered to remove the maximum value and the negative value.
Preferably, the threshold θ depends on the type of landslide, θ ∈ [60 °,85 ° ].
Preferably, the threshold β depends on the type of landslide, β ∈ [ -0.90, -0.70].
Preferably, in S1, a deformation time curve is obtained by using a ground GNSS device or a ground-based interferometric radar.
Preferably, in the step S1, a ground-based interference radar is used to obtain an accumulated deformation amount of a surface of the monitoring scene; determining a tangent angle based on the surface accumulated deformation, specifically comprising:
s101, designing a plurality of deformation thresholds according to the maximum value in the surface accumulated deformation quantity;
s102, acquiring an area-time curve corresponding to each deformation threshold:
aiming at each deformation threshold, calculating the total area of the pixel points of which the accumulated deformation exceeds the deformation threshold at the current moment in real time; each moment corresponds to a total area value of the pixel points exceeding the deformation threshold, and an area-time curve is formed along with the lapse of time;
and S103, calculating tangent angles of the area-time curves corresponding to the deformation thresholds at the current moment aiming at the fixed time windows based on the self-adaptive time window method, wherein the largest tangent angle of the area-time curves corresponding to the deformation thresholds is the tangent angle at the current moment corresponding to the fixed time window.
Preferably, in S101, the N deformation thresholds are designed in the following manner:
maximum accumulated deformation value S in monitoring scene of current measurement period max When the thickness is less than or equal to 100mm,
deformation threshold S k ＝10·k，k＝1～N，
Represents rounding down;
maximum accumulated deformation value S in monitoring scene of current measurement period max When the thickness is larger than 100mm,
deformation threshold
Has the beneficial effects that:
(1) According to the method, a plurality of time windows are set, the optimal time window is selected based on the tangent angle time curve, the tangent angle calculation error is avoided, and the intelligence and the accuracy of landslide time prediction are improved; and then, the Pearson correlation coefficient is used as a second criterion for identifying the critical slip stage, namely, when the tangent angle value is large enough, the landslide time is predicted by adopting an inverse speed method, and when the Pearson correlation coefficient reaches a certain range, a landslide time prediction result is input. The method adaptively determines the optimal time window, and simultaneously adopts double criteria to ensure the identification accuracy of the critical slip stage, thereby improving the reliability of forecasting.
(2) And the different tangent angle curves judge whether the tangent angles are overlapped or not according to the distances of the corresponding tangent angles at the same moment, so that the method is simple and the operability is strong.
(3) When the ground interference radar is adopted to obtain the surface accumulated deformation amount of the monitoring scene, the tangent angle can be determined based on the surface accumulated deformation amount, compared with the traditional early warning method based on single-point deformation information, the method adopting the area time sequence curve can identify the whole deformation trend of the landslide surface, the early warning information is more comprehensive and accurate, and the accuracy of judgment in the landslide early warning stage can be effectively improved.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a plot of tangent angle α for multiple time windows.
Fig. 3 shows the coincidence of the tangent angle alpha curves for multiple time windows.
Fig. 4 is a plot of tangent angle α under an adaptive time window.
Fig. 5 shows the reciprocal velocity values at various times.
Fig. 6 shows the reciprocal velocity values (after filtering) at each time.
Fig. 7 shows the pearson correlation coefficient at each time.
FIG. 8 is t i Time forecast at time instant =51.33 h.
FIG. 9 is a landslide time forecast based on an adaptive time window and multiple criteria.
FIG. 10 is a flow chart of adaptive time window acquisition,
Fig. 11 is a tangent angle acquisition method based on a plane time curve.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The invention provides a landslide impending slip time forecasting method based on a self-adaptive time window and multiple criteria, which comprises the following steps of:
1. adaptive time window acquisition
When the tangent angle is calculated based on the deformation time curve, the calculated value of the tangent angle has high sensitivity to the time window, if the undersize time window easily causes the jump of the tangent angle, the oversize time window can cause the delay of the early warning information, and the fixed time window suitable for all conditions does not exist for deformation measuring equipment with different monitoring frequencies and deformation characteristics of different types of disasters. Therefore, this step first adaptively selects an optimal time window from a plurality of time windows.
First, the accumulated deformation S is calculated i Average rate of (B) i 。
Wherein S is i 、S 1 Are each t i Time and t 1 The accumulated deformation amount corresponding to the moment.
Then, using the accumulated deformation S i Divided by the average rate B i Obtaining T consistent with the dimension of time T i 。
Calculating T i Angle of tangency (slope of the curve) alpha in time window deltat time on the time curve i ，α i Is a dimensionless natural number.
In the formula (3), Δ t is the tangent angle time window, α i Is t i Angle of tangency at time, S i 、t i Respectively corresponding accumulated deformation and time S of the ith monitoring data i-1 、t i-1 Respectively the accumulated deformation amount and the time corresponding to the i-1 th monitoring data.
Now, Δ t is set to a plurality of fixed values, and the tangent angle calculation method is changed from equation (3) to equation (4).
In equation (4), Δ t is a fixed value, and the value of n depends on Δ t.
Then m fixed time windows are selected:
Δt j ＝j,j＝1,2,3,…,m (5)
in the formula (5), Δ t j The unit is h, and m is set according to the deformation frequency of the monitored object.
Calculating a time window Δ t j Corresponding tangential angle alpha i,j And obtaining m tangent angle time curves.
The fixed time windows are sequenced from small to large, and each time t is calculated i Lower, tangent angle difference C corresponding to adjacent time window i,j ：
C i,j ＝|α i,j -α i,j+1 | (7)
C i,j When t is less than or equal to 3, t is considered to be i Time alpha i,j Curve and alpha i,j+1 Curve information is superposed, and the ratio of the information superposition time length to the total time length is alpha i,j Curve and alpha i,j+1 Coincidence ratio C of curves j (equation (8)). The curves with a coincidence rate of 80% have high similarity, so when C is j When the time is more than or equal to 80 percent of the first time, the model adaptively determines j hours as the optimal time window.
2. Preliminary determination of tangent angle
The optimum time window is substituted into equation (3) to calculate the tangent angle α value at each time. If the tangent angle alpha value is larger than or equal to the threshold theta, time forecasting calculation is needed, otherwise, time forecasting is not needed. The value of the threshold θ depends on the type of landslide, typically θ ∈ [60 °,85 ° ].
3. Pearson correlation coefficient quadratic decision
The inverse speed of the landslide is in linear relation with time, and the linear correlation between the inverse speed and the time is measured by calculating the Pearson correlation coefficient of the inverse speed, so that whether the landslide is in a temporary slip state or not can be judged.
Inverse speed IV i The same time window as the tangent angle is used for the calculation of (c).
In the above formula, Δ t is the optimal time window obtained by the previous calculation; s i 、S i-n Respectively, t in the deformation time curve i Time t and i-n and (4) accumulated deformation corresponding to the moment.
Then t i Pearson's correlation coefficient r at time i Comprises the following steps:
wherein IV i-n ～IV i Are each t i-n ～t i The inverse of the velocity at that moment.
If the Pearson correlation coefficient is less than or equal to the threshold value beta, time forecasting calculation is needed, otherwise, time forecasting is not needed. The value of the threshold value beta depends on the type of landslide, usually beta e-0.90, -0.70.
4. Output time forecast
When the tangent angle and the pearson correlation coefficient satisfy the above conditions at the same time, linear fitting is performed on the inverse velocity scatter (time on the abscissa and inverse velocity value on the ordinate) in the time window, and the intersection of the fitted straight line and the abscissa is the predicted disaster occurrence time. And finally, outputting the landslide forecast time.
The deformation time curve of the invention can be obtained by adopting ground GNSS equipment or ground-based interferometric radar (GB-InSAR).
Particularly, for a mode of monitoring by using GB-InSAR, considering the technical advantage that the GB-InSAR can realize surface scene deformation monitoring, the tangent angle calculation method based on the area-time curve is provided based on the characteristic that a deformation area can show regular expansion in the landslide development process. And by setting a plurality of deformation threshold values, fusing tangent angle calculation results of a plurality of deformation time curves to obtain an optimal tangent angle for judging the landslide early warning stage. Compared with the traditional early warning method based on single-point deformation information, the method of the area time sequence curve can identify the whole change trend of the deformation of the landslide surface, the early warning information is more comprehensive and accurate, and the accuracy of judgment in the landslide early warning stage can be effectively improved. The specific method flow is shown in fig. 6, and specifically includes the following steps:
s101, designing a deformation threshold value
And monitoring the scene by adopting GB-InSAR to obtain the accumulated deformation of the scene under the current time window delta t. According to the maximum value S of the accumulated deformation quantity of the scene under the current time window delta t max Designing N deformation thresholds:
the number and the numerical value of the deformation threshold can be determined by experience or numerical simulation. The design of this embodiment is as follows:
when S is max When the thickness is less than or equal to 100mm,
deformation threshold S k ＝10·k，k＝1～N，
Meaning rounding down.
When S is max When the thickness is larger than 100mm,
deformation threshold
S102, acquiring an area-time curve
The deformation time curve based on single-point monitoring can better identify the landslide danger state of the point in the side slope deformation process. However, after a significant slope failure, the deformation rate of the single point may be reduced, but the deformation region may continue to expand. The method of the area-time curve can be used for more accurately identifying the whole deformation trend of the sliding slope surface.
For each deformation threshold S for the accumulated amount of deformation over a time window Δ t period k Calculating each time t in the time window delta t i Lower accumulated deformation amount exceeding S k Total area A of pixel points k,i All A within the time window Δ t k,i The set of (A) is the area-time curve A k (t) of (d). During the development of landslide, A k (t) is an increasing curve, A k The acceleration rate of (t) is the expansion rate of the strain region.
S103, calculating the tangent angle of the area-time curve
For each deformation threshold S k Corresponding area time curve A k (t) calculating an area-time curve A k (t) initial time t 1 To each time t i Average speed B of k,i (equation (11)).
Dividing the area by the average speed to obtain the ordinate A of the area-time curve k,i Transformed into T in accordance with the dimension of the abscissa time T k,i (equation (12)).
Calculating t i Tangential angle (slope) alpha at time k,i (equation (13)), α k,i Is a dimensionless natural number.
S104, obtaining the tangent angle of the early warning judgment
t i At the moment, each deformation threshold S k Corresponding to a tangent angle alpha k,i N tangent angles can be obtained by N deformation thresholds, and the maximum tangent angle alpha is obtained i As the tangent angle of the time window (equation (14)).
Case(s)
Taking the earth surface deformation data of the mountain and west sharp mountain iron ore side slope monitored by the foundation interference radar as an example, the forecasting and calculating process of the landslide critical-sliding time under the self-adaptive time window and multiple criteria is as follows:
1) Adaptive time window calculation: the multiple time windows, Δ t =1h,2h,3h,4h,5h,6h, \8230, 10h, are set, and the tangent angle α curves under the multiple time windows are shown in fig. 2. The coincidence rate of the tangent angle alpha curves under multiple time windows is shown in figure 3, and the coincidence rate of the tangent angle alpha curves under 4h and 5h time windows reaches 80 percent first, so that the self-adaptive time window is 4h.
2) Criterion 1 tangent angle: substituting the 4h time window into equation (3) calculates the tangent angle value at each time, see fig. 4. The threshold value theta in criterion 1 is set to 65 deg., the red part in fig. 4 corresponding to the moment of the tangent angle > 65 deg..
3) Calculating the speed reciprocal: substituting the 4h time window into equation (9) calculates the inverse velocity value at each time, see fig. 5. The inverse velocities in fig. 5 are filtered to remove maxima and negative values. In this example, values greater than 2000h/m and negative values are rejected to obtain the inverse effective velocity (FIG. 6).
4) Criterion 2 Pearson correlation coefficient: substituting the 4h time window and the filtered inverse velocity into a formula (10) to obtain the Pearson correlation coefficient r at each moment i See fig. 7. The threshold value beta in criterion 2 is set to-0.75 and the red part in fig. 7 corresponds to the moment when the correlation coefficient is < -0.75.
5) And (3) time forecast calculation: with t i The time instant of 51.33h is taken as an example, the tangent angle and the correlation coefficient corresponding to the time instant are 67.79 degrees and 0.98 degrees respectively, and the two criteria of the critical sliding stage are met, so the time pre-prediction needs to be carried outReporting and calculating. Linear fitting is carried out on the reciprocal velocity under the 4h time window, and the intersection point of the fitted straight line and the horizontal axis is t i =53.41h (fig. 8). Namely: t is t i The time of =51.33h, t is calculated i When the deformation is large in the case of =53.41h, the prediction is sent 2.98h in advance.
6) Time forecasting under double criteria:
and when the tangent angle is more than or equal to 65 degrees and the correlation coefficient is less than or equal to-0.75, performing time prediction calculation and outputting a prediction result, otherwise, no prediction is performed. Fig. 9 shows the forecast at each time point during monitoring, where the horizontal axis is 51.33h, and the vertical axis is 2.98h.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A landslide critical-slip time forecasting method based on an adaptive time window and multiple criteria is characterized by comprising the following steps:
s1, monitoring a scene to obtain a deformation time curve; self-adaptively obtaining an optimal time window; the method for acquiring the optimal time window specifically comprises the following steps:
s11, continuously monitoring a scene in real time to obtain a deformation time curve; setting a plurality of fixed time windows, respectively calculating tangent angles of the deformation time curves under the fixed time windows, and moving the fixed time windows to obtain tangent angle curves corresponding to the fixed time windows;
s12, sequencing the fixed time windows from small to large, and sequentially calculating the coincidence rate of tangent angle curves under the adjacent fixed time windows; when the coincidence rate exceeds a set threshold value B for the first time, the corresponding fixed time window is the optimal time window;
s2, calculating tangent angles of all moments based on the optimal time window obtained in the step S1;
s3, calculating the reciprocal of the speed at each moment based on the optimal time window obtained in the step S1, and further obtaining the Pearson correlation coefficient at each moment;
and S4, extracting the moments when the tangent angle is larger than the threshold theta and the Pearson correlation coefficient is smaller than the threshold beta, and outputting the landslide critical slip time predicted by adopting an inverse speed method at the moments.
2. The adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, characterized in that the tangent angle at a fixed time window Δ t is calculated as follows:
first, the accumulated deformation S is calculated i Average rate of (B) i ：
Wherein S is 1 、S i Respectively, t in the deformation time curve 1 Time t and i accumulated deformation corresponding to the moment;
then, using the accumulated deformation S i Divided by the average rate B i Obtaining T consistent with the dimension of time T i ：
Then t i Time of day, deformation time curve at fixed time window Δ t (Δ t = t) i -t i-n ) Lower tangent angle alpha i Comprises the following steps:
3. the adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, wherein in step S12, the coincidence rate of tangent angle curves in adjacent fixed time windows is calculated as follows:
calculating tangent angle difference values on tangent angle curves corresponding to adjacent time windows at the same moment, and when the difference value is less than or equal to a set threshold value A, considering that the information of the two tangent angle curves at the moment is overlapped; and the ratio of the information coincidence duration of the two tangent angle curves to the total duration is the coincidence rate of the two curves.
4. The adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, 2 or 3, wherein in S3, the Pearson' S correlation coefficient is calculated as follows:
calculating the reciprocal velocity IV in a fixed time window delta t i ：
In the formula (7), Δ t is the optimal time window obtained by S1; s i 、S i-n Respectively, t in the deformation time curve i Time and t i-n Accumulated deformation corresponding to the moment;
then t i Pearson's correlation coefficient r at time i Comprises the following steps:
wherein IV i-n ～IV i Are each t i-n ～t i The inverse of the velocity at that moment.
5. The adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, wherein in S3, the inverse speed at each time is filtered to eliminate maximum values and negative values.
6. The adaptive time window and multi-criterion based landslide time-to-slide forecasting method according to claim 1, characterized in that the threshold value θ depends on the type of landslide, θ e [60 °,85 ° ].
7. The adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, wherein the threshold β depends on the type of landslide, β e [ -0.90, -0.70].
8. The adaptive time window and multi-criterion based landslide critical-slip time forecasting method according to claim 1, wherein in S1, a deformation time curve is obtained by using a ground GNSS device or a ground-based interferometric radar.
9. The method for forecasting the landslide impending landslide time based on adaptive time window and multi-criteria as claimed in claim 8, wherein in S1, ground based interferometric radar is used to obtain the surface accumulated deformation amount of the monitored scene; determining a tangent angle based on the surface accumulated deformation, specifically comprising:
s101, designing a plurality of deformation thresholds according to the maximum value in the surface accumulated deformation quantity;
s102, acquiring an area-time curve corresponding to each deformation threshold:
aiming at each deformation threshold, calculating the total area of the pixel points of which the accumulated deformation exceeds the deformation threshold at the current moment in real time; each moment corresponds to a pixel point total area value exceeding the deformation threshold, and an area time curve is formed along with the time;
and S103, calculating tangent angles of the area-time curves corresponding to the deformation thresholds at the current moment aiming at the fixed time windows based on the self-adaptive time window method, wherein the largest tangent angle of the area-time curves corresponding to the deformation thresholds is the tangent angle at the current moment corresponding to the fixed time window.
10. The adaptive time window and multi-criterion-based landslide critical-slip time forecasting method according to claim 9, wherein in S101, N deformation thresholds are designed as follows:
maximum accumulated deformation value S in monitoring scene of current measurement period max When the thickness is less than or equal to 100mm,
deformation threshold S k ＝10·k，k＝1～N，
Represents rounding down;
maximum accumulated deformation value S in monitoring scene of current measurement period max When the thickness is more than 100mm,
deformation threshold
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| CN117192582B (en) * | 2023-11-08 | 2024-01-30 | 航天宏图信息技术股份有限公司 | Improved tangent angle real-time monitoring method, device and equipment for GNSS displacement data |
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