Tangent angle slip band depth identification method and system based on scale factor

Abstract

The invention provides a scale factor-based tangent angle slip band depth identification method and system, and the method comprises the steps: importing deep displacement monitoring data into a database, setting a threshold value and a rule, and removing abnormal data; according to the accumulated displacement increment of different depths in each inclinometry hole in each day, the tangent angle alpha at each depth from shallow to deep in each inclinometry hole is calculated in sequence, if the alpha at the jth depth in each inclinometry hole is larger than 80 degrees, the jth depth is selected as the suspected slip band depth, a third point judgment mechanism is introduced, the points meeting the judgment standard are verified again, and if the alpha at the jth depth in each inclinometry hole is larger than 80 degrees, the point meeting the judgment standard is verified again. And the tangent angle is judged by taking the next point, so that the influence of abnormal points is effectively reduced. The method has the advantages that the scaling ratio can be automatically calculated, the problem that the tangent angle is too large or too small is solved through self-adaptive adjustment, and the situation that the depths of other slip bands are ignored is avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of soil deformation monitoring, and particularly relates to a method and system for identifying the depth of a tangent angle slip zone based on a scale factor. Background Art

[0002] Landslide disasters occur frequently and have a great impact, often posing a huge threat to people's lives and property. Traditional landslide slip surface identification methods rely on manual experience and simple calculation models, and usually face problems such as low identification accuracy and insufficient efficiency. Although the traditional tangent angle algorithm has a certain basis in identifying the depth of the slip surface, its accuracy and adaptability still need to be improved. The tangent angle identification method emits electromagnetic waves to a slope target and receives the echo, measures the distance according to the time difference between transmission and reception, continuously scans without interruption, calculates the phase difference of the electromagnetic waves at two scanning times of the same minimum monitoring unit, obtains the displacement history curve of the target point, and pays attention to the change of the tangent angle of the landslide displacement history curve. When the landslide deforms, the tangent angle of the displacement history curve will change significantly, and these changes can be used to identify the position of the slip surface. This method mainly focuses on the depth where the maximum tangent angle is located, believing that this is the most likely position of the slip surface. This method ignores other possible slip surfaces because their tangent angle changes may not be so significant. This method does not design a multi-point identification mechanism and cannot identify multiple suspected slip zones simultaneously. This results in the neglect of other potential slip surfaces during the identification process, only focusing on the most significant one. This method also does not have an effective mechanism to identify and exclude abnormal points. These abnormal points may mislead the judgment of the slip zone depth and lead to incorrect identification results. For example, factors such as equipment errors, environmental changes, and human misoperations may cause abnormal values to appear in the monitoring data, and these abnormal values will affect the calculation of the tangent angle, thereby affecting the identification of the slip surface. Using an adaptive adjustment mechanism to automatically adjust the scaling ratio according to the actual situation limits the applicability and accuracy of the algorithm in different situations. Summary of the Invention

[0003] In view of the drawbacks existing in the monitoring data method of the above tangent angle identification method, the present invention proposes an optimized processing method for monitoring data during the surrounding rock excavation process. The aims are to solve the following problems:

[0004] (1) When determining the tangent angle of the slip zone depth, since the displacement ordinate in the displacement history curve output by different sensors is stretched, the tangent angle may be too large, or since the time abscissa in the displacement history curve output by different sensors is stretched, the tangent angle may be too small. When the slope target is located in a shallow slip zone, but the displacement ordinate in the displacement history curve is stretched, this may lead to an underestimated slip zone depth and may miss the actual slip surface.

[0005] (2) It may be affected by abnormal points, resulting in inaccurate judgment of the slip zone depth.

[0006] To solve the above technical problems, the present invention provides a tangent angle slip zone depth recognition algorithm based on a scale factor, comprising the following steps:

[0007] A tangent angle slip zone depth recognition method based on a scale factor, the method comprising the following steps:

[0008] Step 1: Deposit the displacement monitoring data at different depths at the same location into the database according to the date; repeatedly collect the displacements at different depths at other locations and deposit them into the database according to the date; screen the imported data by setting thresholds and rules to eliminate abnormal monitoring data; the displacement monitoring data includes the measurement depth D in the inclinometer borehole i and the cumulative displacement increment d corresponding to the measurement depth i , where i represents the serial number of a measurement depth sorted from shallow to deep in the inclinometer borehole;

[0009] Among them, the monitoring data is classified according to the data of different sensors, and each sensor is a class; when eliminating abnormal monitoring data, compare the data at different depths, and filter the historical monitoring data at the same depth of the same sensor through 3 times the standard deviation. If the data at a certain point deviates from the mean by more than 3 times the standard deviation, it is determined as abnormal.

[0010] Step 2: According to the cumulative displacement increment at different depths in each inclinometer borehole every day, calculate the tangent angle α at each depth from shallow to deep in the inclinometer borehole in turn i , if the α at the i-th depth in the inclinometer borehole is greater than 80°, then select the i-th depth as the suspected slip zone depth;

[0011]

[0012] In the formula, γ is a standard value obtained according to experience, γ = 85°, tanθ max is the tangent angle when the cumulative absolute displacement difference is the largest, tanθ max is tanθ i the maximum value of, D i+1 and D i are the depths at the i + 1 and i positions in the inclinometer borehole respectively, d i+1 and d i are the cumulative displacement increments at the i + 1 and i positions in the inclinometer borehole respectively;

[0013] Step 4: Adopt the depth D i+2 and the cumulative displacement increment d i+2 at the i + 2-th depth and the depth D i and the cumulative displacement increment d iSubstitute into Equation (1) to verify the tangent angle α' of the suspected slip zone depth. If α' is greater than 80°, then select the i-th depth as the slip zone depth. Otherwise, the i-th depth is no longer marked as the suspected slip zone depth. Repeat Steps 3-4 to traverse deeper depths in the inclinometer borehole and find the slip zone depth;

[0014]

[0015] The displacement monitoring data is collected by the following steps:

[0016] After arranging multiple dedicated inclinometer boreholes in the monitoring area, bury inclinometer pipes in the inclinometer boreholes. The inclinometer probe is connected to the data acquisition device through a cable. The inclinometer probe slides down along the pipe to the set depth for point-by-point measurement, and records the depth D at equal-length intervals; i and the inclination data. The inclinometer measures the inclination of the sensor in two horizontal orthogonal directions through a high-precision acceleration sensor;

[0017] For consecutive days, repeat the measurement of the inclination at the same position in the inclinometer borehole, and compare it with the data measured on the first day to calculate the cumulative displacement increment at the same position in the inclinometer borehole to obtain d i .

[0018] A tangent angle slip zone depth identification system based on a scale factor, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the tangent angle slip zone depth identification method based on the scale factor.

[0019] The beneficial effects of the present invention are as follows: It can obtain the tangent angle, solve the problem of too large or too small tangent angle, and avoid the situation of ignoring other slip zone depths. In addition, a scale factor r is introduced, which is the comparison result between the standard value obtained according to experience and the tangent angle when the cumulative absolute displacement difference is the largest, as a correction factor, so that the slip zone depth can be more accurately identified through the tangent angle in the end; by introducing a third-point judgment mechanism, the points that reach the judgment standard are verified again, and the tangent angle judgment is carried out by taking the next point, effectively reducing the influence of abnormal points; the tangent angle identification slip zone depth method based on the scale factor significantly improves the accuracy and reliability of landslide monitoring through the algorithm improvement of the adaptive scaling ratio and the abnormal point elimination and verification mechanism, and provides more effective technical support for landslide early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram for eliminating abnormal slip zone depths by the tangent angle identification algorithm based on the scale factor;

[0021] Figure 2 is Figure 1 a partial enlarged view of... DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0023] Example 1

[0024] A tangent angle sliding belt depth identification algorithm based on a proportional factor comprises the following steps:

[0025] Step 1: Use an inclinometer to measure the inclination angles at different positions and depths in the monitoring area, including: after laying out multiple dedicated inclinometer holes in the monitoring area, burying inclinometer conduits in the inclinometer holes, connecting the inclinometer probe to the data acquisition device through a cable, and sliding the inclinometer probe down the conduit to the set depth for point-by-point measurement, and recording the depth D every fixed depth (such as 0.5m or 1m). i And inclination data. The inclinometer measures the inclination of the sensor in two orthogonal directions (X and Y directions) through a high-precision acceleration sensor;

[0026] Repeat the measurement of the inclination angle at the same position of the inclinometer hole for several consecutive days, and compare it with the data measured on the first day to calculate the cumulative displacement increment at the same position in the inclinometer hole, and obtain d i .

[0027] Step 2: Import the deep displacement monitoring data into the database, and set thresholds and rules to eliminate abnormal data, including: storing the displacement monitoring data of different depths at the same location into the database by date; repeatedly collecting displacements of different depths at other locations and storing them in the database by date; and filtering the imported data by setting thresholds and rules to eliminate abnormal monitoring data to ensure the accuracy and reliability of subsequent analysis.

[0028] Among them, the monitoring data is classified according to the data of different sensors, and each sensor is a category; when eliminating abnormal monitoring data, the data at different depths are compared, and the historical monitoring data of the same sensor at the same depth are filtered through 3σ. If the data at a certain point deviates from the mean by more than 3 times the standard deviation, it is judged as abnormal.

[0029] Step 3: According to the daily cumulative displacement increments at different depths in each inclinometer hole, calculate the tangent angle α at each depth from shallow to deep in the inclinometer hole. i , if α at the i-th depth in the inclinometer hole is greater than 80°, the i-th depth is selected as the suspected sliding zone depth;

[0030]

[0031] Wherein, γ is a standard value obtained based on experience, γ = 85°, tanθ max is the tangent angle when the cumulative absolute displacement difference is the largest, tanθ max is the maximum value of tanθ i ; D i+1 and D i are respectively the depths at the (i + 1)-th and i-th positions in the inclinometer hole, d i+1 and d i are respectively the cumulative displacement increments at the (i + 1)-th and i-th positions in the inclinometer hole;

[0032] Step 4: Substitute the depth D i+2 and the cumulative displacement increment d i+2 at the (i + 2)-th depth into the depth D i and the cumulative displacement increment d i at the i-th depth into Equation (1) to verify the tangent angle α' of the suspected slip zone depth. If α′ is greater than 80°, then select the i-th depth as the slip zone depth; otherwise, the i-th depth is no longer marked as the suspected slip zone depth. Repeat Steps 3 - 4 to traverse deeper depths in the inclinometer hole and find the slip zone depth;

[0033]

[0034] In this Step 4, for example Figure 2 as shown Figure 2 is Figure 1 a partial enlarged view of, Figure 2 in which the red line is the true cumulative displacement increment - depth data curve. It can be seen that the tangent angles at the depths of 78m and 79m are both relatively large. However, when verifying the tangent angles at the depths of 78m and 80m using the third point at the depth of 80m according to Step 4, connecting the green line at 78m and 80m, it can be seen that the tangent angle is less than 80°. Adding the third point to calculate the tangent angle can effectively reduce the misjudgment of the slip zone depth identification caused by the mutation of the monitoring data at a certain point. As Figure 1 shown, the point at 79m is the suspected slip zone surface, but by judging the tangent angle of the next point, it can be determined that this point may be an abnormal point rather than the slip zone surface. For the point at a depth of 95m, even if the next point is used for verification, it can still be determined that this point is the slip zone depth.

[0035] In Steps 3 - 4, γ is a standard value obtained based on experience;

[0036] The geological conditions, topographic features, and deformation laws of landslides vary from place to place, and the threshold value of the tangent angle may differ in different landslide scenarios. Therefore, in the absence of a unified industry standard, it is a common practice to use empirical values as the criteria. When using the method of the present invention for 12 deep displacement monitors of the landslide body of the lower Gualiao mountain in Jinshui Village, Zhenbu Township, Qingtian County, the values of γ are taken as γ = 45°, γ = 60°, γ = 70°, γ = 85°, and γ = 89° respectively, obtaining 5×12 groups of depth - cumulative displacement increment data. It is found that when γ = 85°, there is a significant difference between the tangent angle of the slip zone depth and the tangent angle at the non - slip zone depth. By statistically analyzing the tangent angles at 12 depths, while the tangent angles at the slip zone depth are all greater than 80°, the tangent angles at the non - slip zone depth have a large gap with 80°. Therefore, when γ = 85° and the threshold is set to 80°, the slip zone depth can be better identified without omission in the case of multiple suspected slip zone depths.

[0037] Table 1 Identification accuracy of slip zone depth when γ takes different values

[0038]

[0039] A tangent - angle slip - zone depth identification system based on a scale factor, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the tangent - angle slip - zone depth identification method based on the scale factor are implemented.

[0040] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tangent angle sliding belt depth identification method based on proportional factor, characterized in that: The method comprises the following steps: Step 1: Store the displacement monitoring data of different depths at the same location in the database by date; Repeat the displacement collection of different depths at other locations and store them in the database by date; Filter the imported data by setting thresholds and rules to remove abnormal monitoring data; The displacement monitoring data includes the measured depth D in the inclinometer hole. i The cumulative displacement increment d corresponding to the measured depth i , i represents the serial number of a measurement depth in the inclinometer hole from shallow to deep; Step 2: According to the daily cumulative displacement increments at different depths in each inclinometer hole, calculate the tangent angle α at each depth from shallow to deep in the inclinometer hole. i , if α at the i-th depth in the inclinometer hole is greater than 80°, the i-th depth is selected as the suspected sliding zone depth; Where, γ is a standard value obtained based on experience, γ = 85°, tanθ max is the tangent angle when the cumulative absolute displacement difference is the largest, tanθ max is tanθ i The maximum value of D i+1 and D i are the depths of the i+1th and ith positions in the inclinometer hole, d i+1 and d i are the cumulative displacement increments of the i+1th and ith positions in the inclinometer hole, respectively; Step 4: Use the depth D at the i+2th depth i+2 and the cumulative displacement increment d i+2 and the depth D at the i-th depth i and the cumulative displacement increment d i Substitute into formula (1) and verify the tangent angle α' of the suspected sliding belt depth. If α' is greater than 80°, the i-th depth is selected as the sliding belt depth. If not, the i-th depth is no longer marked as the suspected sliding belt depth. Repeat steps 3 to 4 to traverse deeper depths in the inclinometer hole and find the sliding belt depth.

2. The method according to claim 1, characterized in that: In step 1, the monitoring data is filtered through 3σ to obtain historical monitoring data. If the data at a certain point deviates from the mean by more than 3 times the standard deviation, it is judged to be abnormal.

3. The method according to claim 1, characterized in that: The displacement monitoring data is collected by the following steps: After laying out multiple dedicated inclinometer holes in the monitoring area, an inclinometer conduit is buried in the inclinometer hole. The inclinometer probe is connected to the data acquisition device through a cable. The inclinometer probe slides down the conduit to the set depth for point-by-point measurement. The depth D is recorded every equal depth. i And inclination data, the inclinometer measures the inclination of the sensor in two horizontal orthogonal directions through a high-precision acceleration sensor; Repeat the measurement of the inclination angle at the same position of the inclinometer hole for several consecutive days, and compare it with the data measured on the first day to calculate the cumulative displacement increment at the same position in the inclinometer hole, and obtain d i .

4. The method according to claim 1, characterized in that: in, In step 1, the monitoring data is classified according to the data of different sensors, with each sensor as one category; when eliminating abnormal monitoring data, the data at different depths are compared, and the historical monitoring data of the same sensor at the same depth is filtered by 3 times the standard deviation. If the data at a certain point deviates from the mean by more than 3 times the standard deviation, it is judged as abnormal.

5. The method according to claim 1, characterized in that: The displacement monitoring data is collected by the following steps: After laying out multiple dedicated inclinometer holes in the monitoring area, an inclinometer conduit is buried in the inclinometer hole. The inclinometer probe is connected to the data acquisition device through a cable. The inclinometer probe slides down the conduit to the set depth for point-by-point measurement. The depth D is recorded every equal depth. i And inclination data, the inclinometer measures the inclination of the sensor in two horizontal orthogonal directions through a high-precision acceleration sensor; Repeat the measurement of the inclination angle at the same position of the inclinometer hole for several consecutive days, and compare it with the data measured on the first day to calculate the cumulative displacement increment at the same position in the inclinometer hole, and obtain d i .

6. A tangent angle slide belt depth identification system based on a proportional factor, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

Images