CN111445057B - Displacement gradient method for predicting landslide slip direction and moment - Google Patents
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Abstract
The invention discloses a displacement gradient method for predicting landslide slip direction and moment, which comprises the following steps of 1, checking displacement monitoring data and a displacement cloud picture of monitoring equipment, and selecting a specific landslide body to be predicted; 2. the geological data of the landslide body is consulted, and the landslide scale, landslide inclination angle and rock mechanical parameters of the landslide body are obtained; 3. selecting displacement data of each point on the landslide body, and making a displacement contour map; 4. calculating displacement gradient and determining landslide direction; and judging landslide alarming according to the displacement gradient alpha. Compared with the prior art, the method can predict landslide time of different sizes and different geological conditions, and the landslide time is accurately predicted.
Description
Technical Field
The invention belongs to the technical field of geological disaster prevention and control, and particularly relates to a method for predicting a sliding direction of a side slope and a sliding time.
Background
At present, a common landslide time prediction method is mainly an analysis method based on displacement and speed, such as a speed reciprocal method, but the cloud image information of the displacement, the speed and the like displayed by radar data is more, and the method generally only uses partial displacement values and speed values, cannot completely describe the evolution characteristics of a landslide, can only be used for progressive landslide, and cannot be widely used for predicting the time of landslide instability.
Disclosure of Invention
Aiming at the problems existing in the prior art, the technical problem to be solved by the invention is to provide a displacement gradient method for predicting the sliding direction and time of a landslide, which can predict the landslide time of different sizes and different geological conditions and is accurate in landslide time prediction.
The technical problem to be solved by the invention is realized by the technical proposal that the invention comprises
Step 1, checking displacement monitoring data and a displacement cloud picture of monitoring equipment, and selecting a specific landslide body to be predicted;
step 2, referring to geological data of the landslide body to obtain landslide scale, landslide inclination angle and rock mechanical parameters of the landslide body;
step 3, selecting displacement data of each point on the landslide body, and making a displacement contour map;
and step 4, calculating a displacement gradient, wherein a displacement gradient calculation formula is as follows:
wherein alpha is displacement gradient, deltaS is displacement difference of two points in the landslide body, deltaL is distance of two points with minimum distance between two equivalent lines, S i And S is j Respectively the displacement values of two points;
and judging landslide alarming according to the displacement gradient alpha.
Compared with the prior art, the invention has the advantages that:
1. the operation is convenient, the data processing is simple, and only two parameters of displacement and distance are provided;
2. the prediction is accurate, and the method can be used for landslide in various different movement forms;
3. is not affected by the landslide scale;
4. the method can be used as a generalized criterion and is suitable for different landslide types;
5. the sliding direction and the sliding time of the side slope can be accurately predicted, so that the safety of lives and properties of people is protected.
Drawings
The drawings of the present invention are described as follows:
FIG. 1 is a schematic diagram of the location of a ground scanning radar and a landslide mass;
FIG. 2 is a displacement cloud of the selected area obtained by the ground-based radar of FIG. 1;
FIG. 3 is a displacement contour plot depicted on FIG. 2;
fig. 4 is a schematic diagram of the processing analysis performed on fig. 3.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
the invention comprises the following steps:
step 1, checking displacement monitoring data and a displacement cloud picture of monitoring equipment, and selecting a specific landslide body to be predicted;
FIG. 1 is a schematic diagram of the location of a ground scanning radar and a landslide mass; the displacement cloud picture of the selected area (landslide body) shown in fig. 2 is obtained from the scanning radar, the picture uses different colors to represent the pixel point displacement, a color picture is formed, and the displacement value of the corresponding point in the landslide body can be checked. In fig. 2, black and white is shown, and the darker the color is, the larger the displacement value is.
Step 2, referring to geological data of the landslide body to obtain landslide scale, landslide inclination angle and rock mechanical parameters of the landslide body;
step 3, selecting displacement data of each point on the landslide body, and making a displacement contour map;
in fig. 2, displacement contours are formed by connecting monitoring points with the same displacement value, and displacement contours of the landslide body are formed, so that the displacement contours shown in fig. 3 are obtained. Since the pixel points in fig. 2 are actually areas with a certain area, the center position of each pixel point is taken here, and the centers of the pixel points with the same displacement value are connected. The displacement contour lines are formed by connecting all points with the same displacement value by using a smooth curve, and the displacement of the points on each contour line is the same. In fig. 3, there are five curves, which are all displacement contours, and the displacement of the points on each line is the same.
In general, the area where landslide may occur and the area where landslide has occurred have boundaries, and the displacements of the two types of areas are significantly different, only that the overall landslide occurs under the condition of an earthquake or explosion.
And step 4, calculating a displacement gradient, wherein a displacement gradient calculation formula is as follows:
wherein alpha is displacement gradient, and delta S is landslideThe displacement difference of two points in the body, delta L is the distance between two points with the minimum distance between two equivalent lines, S i And S is j Respectively, are displacement values of two points.
The two points in the landslide body are selected based on the maximum displacement gradient.
As shown in FIG. 4, two moving contour lines with the largest displacement difference and the smallest distance are found in FIG. 3, two points are selected as tangent lines of a curve on the two moving contour lines, (if the two tangent lines are not parallel, two points with the smallest distance between the two contour lines are selected, the distance between the two points is delta L), the distance delta L of the two parallel tangent lines is 909.1mm, and the two points are calculated
As can be seen from fig. 4, there are two displacement contours: the displacement value of the last strip is +10mm, the displacement value of the next strip is +20mm, and the delta S is the displacement difference of the two displacement contours, namely the selected two-point displacement difference is 10.0mm. Δl is the distance between the selected two points, as measured by the radar monitoring system.
Determining landslide direction: the landslide direction refers to the direction in which the direction of sliding is projected on the landslide surface.
The direction of the displacement gradient is the direction between the two points of the existing displacement difference. The greater the displacement gradient change, the greater the possibility of slippage, and in the case of a real landslide, the main direction of slippage is the direction of greatest displacement gradient, i.e., the direction of greatest displacement gradient, and the arrow direction in fig. 4 is the landslide direction. As seen from this example, the direction of the landslide is almost the same as the direction in which the displacement gradient is greatest. In theory, the displacement gradient is caused by the movement of the earlier-stage slope rock mass, and the common landslide is caused by the movement of the accumulated slope rock mass, so that the larger the displacement gradient is, the more the earlier-stage accumulated movement is, and finally the landslide body moves along the direction with the maximum displacement gradient.
And 5, analyzing and processing the landslide cases through the steps 1 to 4 to obtain data, and establishing a historical database.
The landslide body is processed by the steps 1 to 1After the treatment in step 4, the landslide inclination angle and critical displacement gradient alpha cr And the rock parameters are stored in a historical database, and the historical database provides the distinguishing data of landslide accidents for future landslide bodies with similar landslide inclination angles and rock parameters.
The landslide inclination angle refers to the included angle between the landslide surface and the horizontal plane, and the landslide inclination angle can be obtained by using total station measurement and geological data after sliding. The landslide direction refers to the projection direction of the sliding direction on the landslide surface, the landslide direction is a plane direction, and the landslide direction comprises the main direction beta of the prediction landslide y And the actual landslide direction beta s . The maximum displacement gradient at the beginning of the slip is called the critical displacement gradient alpha cr In the displacement contour map, the denser the displacement contour map is, the larger the displacement gradient is, and the displacement gradient of the denser position is calculated, so that alpha is obtained cr 。
In this step 9 landslide were analyzed and the results obtained are shown in tables 1 and 2.
TABLE 1 analysis results of landslide of Mashan copper mine
TABLE 2 analysis results of smooth West mine landslide
From tables 1 and 2, it can be seen that: the predicted landslide main direction error is very small, and the average error is 4 degrees within the range of 1-9 degrees; for a slope with similar landslide inclination angle and rock parameters, the critical displacement gradient alpha of the slope cr Substantially the same, all are close to 0.01, the average value is 0.0105, the variance is 0.000143, and the error is small. Also verifies that the method can accurately predict the landslide direction and critical displacement gradient alpha cr As a prediction of the reliability of landslide occurrence.
The data in tables 1 and 2 may be stored in a historical database as criteria for predicting landslide occurrence.
Step 6,Analyzing and processing the existing landslide body through the steps 1 to 4 to obtain data, and comparing the data with critical displacement gradient alpha in the historical database of the step 5 cr And comparing, determining landslide alarming and finding out the landslide direction.
The invention uses the displacement gradient parameter of the landslide body to predict the slip direction and the occurrence time of the slip by comparing with the historical database, thereby realizing the accurate prediction of the landslide direction and the landslide time.
The invention is simple to operate and can reflect more information. The adopted displacement gradient alpha has no dimension and is not influenced by landslide area, rock mechanical parameters and the like. The displacement gradient is used as a dimensionless parameter, has a reference value compared with the dimensionless parameters such as displacement, speed, acceleration parameters and the like, and can be used as a generalized criterion for predicting landslide moments of different sizes and different geological conditions.
Claims (5)
1. A displacement gradient method for predicting landslide slip direction and moment is characterized by comprising the following steps:
step 1, checking displacement monitoring data and a displacement cloud picture of monitoring equipment, and selecting a specific landslide body to be predicted;
step 2, referring to geological data of the landslide body to obtain landslide scale, landslide inclination angle and rock mechanical parameters of the landslide body;
step 3, selecting displacement data of each point on the landslide body, and making a displacement contour map;
and step 4, calculating a displacement gradient, wherein a displacement gradient calculation formula is as follows:
wherein alpha is displacement gradient, deltaS is displacement difference of two points in the landslide body, deltaL is distance of two points with minimum distance between two equivalent lines, S i And S is j Respectively the displacement values of two points;
and judging landslide alarming according to the displacement gradient alpha.
2. The method of predicting slip direction and moment of a landslide of claim 1 further comprising determining a landslide direction in step 4, the landslide direction selecting a direction in which the displacement gradient is greatest.
3. The displacement gradient method for predicting landslide slip direction and moment according to claim 1 or 2, further comprising: and 5, analyzing and processing the landslide cases through the steps 1 to 4 to obtain data, and establishing a historical database.
4. A displacement gradient method for predicting landslide slip direction and time as defined in claim 3 wherein in step 5, the maximum displacement gradient at the beginning of slip is defined as critical displacement gradient α cr 。
5. The displacement gradient method for predicting landslide slip direction and moment of claim 4 further comprising: step 6, analyzing and processing the existing landslide body through the steps 1 to 4 to obtain data, and comparing the data with the critical displacement gradient alpha in the history database of the step 5 cr And comparing, determining landslide alarming and finding out the landslide direction.
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| CN102306233A (en) * | 2011-06-15 | 2012-01-04 | 浙江大学 | River basin landslide space-time predicting method under rainfall effect |
| CN104182646A (en) * | 2014-09-01 | 2014-12-03 | 重庆大学 | Three dimensional earthquake side slope landslide occurring time forecasting method based on slide displacement analysis |
| CN107341586A (en) * | 2017-05-12 | 2017-11-10 | 成都理工大学 | A kind of computational methods of the geological disaster occurrence frequency based on rainfall |
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| KR101608464B1 (en) * | 2014-06-17 | 2016-04-04 | 명지대학교 산학협력단 | System for predicting landslide using rainfall infiltration characteristics and method therefor |
| CN104700399A (en) * | 2015-01-08 | 2015-06-10 | 东北大学 | Method for demarcating large-deformation landslide displacement field based on high-resolution remote sensing image |
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| CN106339528B (en) * | 2016-08-09 | 2019-06-25 | 鞍钢集团矿业有限公司 | A kind of outdoors iron ore end side underground mining induces surface movement horizon prediction method |
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| CN102306233A (en) * | 2011-06-15 | 2012-01-04 | 浙江大学 | River basin landslide space-time predicting method under rainfall effect |
| CN104182646A (en) * | 2014-09-01 | 2014-12-03 | 重庆大学 | Three dimensional earthquake side slope landslide occurring time forecasting method based on slide displacement analysis |
| CN107341586A (en) * | 2017-05-12 | 2017-11-10 | 成都理工大学 | A kind of computational methods of the geological disaster occurrence frequency based on rainfall |
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