Tailing pond infiltration line monitoring point arrangement method, device and equipment and storage medium

Abstract

The invention relates to the technical field of tailing pond data monitoring, and discloses a tailing pond infiltration line monitoring point arrangement method, device and equipment and a storage medium. The method comprises the following steps: calculating theoretical burial depths of a plurality of existing infiltration line monitoring points according to basic parameters of the tailings pond; calculating the deviation degree of each existing infiltration line monitoring point according to the theoretical burial depth and the actual monitoring value of each existing infiltration line monitoring point; calculating the sensitivity of each existing infiltration line monitoring point according to the time sequence change data of the reservoir water level; calculating the criticality of each existing infiltration line monitoring point according to the deviation degree and the sensitivity of each existing infiltration line monitoring point; predicting the criticality of a plurality of newly added infiltration line monitoring points according to the criticality of each existing infiltration line monitoring point; and according to the criticality of each newly-added infiltration line monitoring point, determining the arrangement positions of a plurality of newly-built infiltration line monitoring points. According to the method, a scientific decision-making basis is provided for the next-stage seepage line monitoring point layout which can be closer to a representative seepage cross section and the fine monitoring of the stability of the tailing dam.

Description

Technical Field

[0001] The present invention relates to the technical field of tailings pond data monitoring, and in particular to a method, device, equipment and storage medium for arranging monitoring points of a tailings pond infiltration line. Background Art

[0002] Tailings ponds are important facilities used to store mineral processing waste (tailings) during the mining process. In essence, they are special artificial dams formed by the accumulation of tailings. As the core link in mine safety production, the stability of tailings ponds is directly related to the safety of life and property of downstream residents and the ecological environment, and the dynamic changes of the seepage line (i.e., the dividing line of pore water pressure in the tailings dam body) are the key factors affecting the stability of the dam body. The seepage line is the core characterization indicator of the interaction between the seepage field and the stress field of the tailings pond. When the seepage line is too high, the effective stress of the tailings sand is reduced, resulting in a decrease in the shear strength of the dam body, which is very likely to induce seepage damage phenomena such as pipe bursts and soil flow; at the same time, the increase in pore water pressure will also increase the risk of displacement and deformation of the dam body. Therefore, accurately determining the monitoring section of the seepage line is of decisive significance for mastering the seepage law of the dam body.

[0003] Currently, the layout of tailings dam seepage monitoring points is primarily based on the "Technical Specifications for Tailings Dam Safety Monitoring," which specifically stipulates that monitoring cross-sections should be selected within representative sections of the dam body that can control the main seepage conditions, as well as sections where abnormal seepage is expected. However, there is currently no accurate method for determining representative seepage cross-sections and sections where abnormal seepage is likely to occur. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method, device, equipment and storage medium for arranging monitoring points on a tailings pond infiltration line.

[0005] The present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present disclosure provides a method for arranging monitoring points on a tailings pond infiltration line, the method comprising:

[0007] Obtaining basic parameters of the tailings pond, calculating theoretical burial depths of multiple existing infiltration line monitoring points based on the basic parameters, and obtaining actual monitoring values ​​of each of the existing infiltration line monitoring points, wherein the basic parameters include structural parameters and material mechanical parameters;

[0008] Calculating the deviation of each of the existing infiltration line monitoring points based on the theoretical buried depth and the actual monitoring value of each of the existing infiltration line monitoring points;

[0009] Acquiring time series variation data of the reservoir water level, and calculating the sensitivity of each of the existing infiltration line monitoring points based on the time series variation data;

[0010] Calculating the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points;

[0011] predicting the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points;

[0012] The layout positions of the multiple newly added infiltration line monitoring points are determined according to the criticality of each of the newly added infiltration line monitoring points.

[0013] In an optional embodiment, the calculating the theoretical burial depths of a plurality of existing infiltration line monitoring points according to the basic parameters includes:

[0014] Inputting the structural parameters and material mechanics parameters of the tailings pond into finite element calculation software to construct a three-dimensional physical model of the tailings pond;

[0015] Obtaining the current water level of the tailings pond, inputting the current water level into the finite element calculation software to obtain the water head boundary condition of the tailings pond;

[0016] Using the finite element calculation software and the three-dimensional physical model of the tailings pond and the water head boundary condition of the tailings pond, a three-dimensional seepage field inside the dam body of the tailings pond is obtained, and a surface with a seepage field pressure value of 0 in the three-dimensional seepage field inside the dam body is used as the infiltration surface of the tailings pond;

[0017] Obtain the layout position coordinates of each existing infiltration line monitoring point on the tailings pond, and determine the vertical distance from the point corresponding to the layout position coordinates of each existing infiltration line monitoring point on the infiltration surface to the outer surface of the dam, and obtain the theoretical burial depth of each existing infiltration line monitoring point.

[0018] In an optional embodiment, the calculating the deviation of each existing infiltration line monitoring point according to the theoretical buried depth and the actual monitoring value of each existing infiltration line monitoring point includes:

[0019] Calculating an average value of the actual monitoring values ​​of each of the existing infiltration line monitoring points based on the actual monitoring values ​​of each of the existing infiltration line monitoring points;

[0020] Calculating the average theoretical burial depth of each of the existing infiltration line monitoring points based on the theoretical burial depth of each of the existing infiltration line monitoring points;

[0021] Calculating the standard deviation of the actual monitoring values ​​of each of the existing infiltration line monitoring points based on the actual monitoring values ​​and the average value of the actual monitoring values;

[0022] Calculating the standard deviation of the theoretical burial depth of each of the existing infiltration line monitoring points based on the theoretical burial depth and the average theoretical burial depth of each of the existing infiltration line monitoring points;

[0023] Calculate the deviation of each of the existing infiltration line monitoring points using a preset deviation calculation formula based on the actual monitoring value, the standard deviation of the actual monitoring value, the theoretical burial depth, and the standard deviation of the theoretical burial depth of each of the existing infiltration line monitoring points;

[0024] The preset deviation calculation formula is:

[0025]

[0026] Where D ij is the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, is the actual monitoring value of the infiltration line monitoring point in the jth section of the i-th layer, is the theoretical buried depth of the existing infiltration line monitoring point in the jth section of the i-th layer, σ obs is the standard deviation of the actual monitoring value, σ sim is the standard deviation of the theoretical burial depth.

[0027] In an optional embodiment, the calculating the sensitivity of each of the existing infiltration line monitoring points according to the time series change data includes:

[0028] At the same time as acquiring the time series change data, collecting the monitoring value response change data of each of the existing infiltration line monitoring points;

[0029] Calculating the sensitivity of each of the existing infiltration line monitoring points using a preset sensitivity calculation formula based on the time series change data of the reservoir water level and the monitoring value response change data of each of the existing infiltration line monitoring points;

[0030] The preset sensitivity calculation formula is:

[0031]

[0032] Where S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t+1, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t, u t+1 is the time series variation data of the reservoir water level at time t+1, u t is the time series variation data of the reservoir water level at time t, and T is the number of existing infiltration line monitoring points.

[0033] In an optional embodiment, the calculating the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points includes:

[0034] Calculating the deviation weight value and sensitivity weight value of each of the existing infiltration line monitoring points using a preset weight calculation method and based on the deviation and sensitivity of each of the existing infiltration line monitoring points, wherein the preset weight calculation method includes an entropy weight method, an expert scoring method, a coefficient of variation method, or a hierarchical analysis method;

[0035] Calculate the criticality of each of the existing infiltration line monitoring points using a preset criticality calculation formula according to the deviation, deviation weight, sensitivity, and sensitivity weight of each of the existing infiltration line monitoring points;

[0036] The preset criticality calculation formula is:

[0037] I ij =D ij ×ω|D′ ij +S ij ×ω|S′ ij

[0038] Where, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, D ij is the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|D′ ij is the deviation weight value of the existing infiltration line monitoring point in the jth section of the i-th layer, S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|S′ ij is the sensitivity weight value of the existing infiltration line monitoring point in the j-th section of the i-th layer.

[0039] In an optional embodiment, predicting the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points includes:

[0040] Obtaining the operating time of each of the existing infiltration line monitoring points, and grouping the existing infiltration line monitoring points according to different monitoring sections;

[0041] According to the running time of each of the existing infiltration line monitoring points, a relative smoothing parameter between two adjacent existing infiltration line monitoring points in each group is calculated using a preset relative smoothing parameter calculation formula;

[0042] According to the criticality and relative smoothness parameters of each existing infiltration line monitoring point in each group, the criticality of each newly added infiltration line monitoring point is predicted using a preset criticality prediction formula;

[0043] The preset relative smoothing parameter calculation formula is:

[0044]

[0045] Where a i～i+1 is the relative smoothing parameter between the existing infiltration line monitoring points in the i-th group and the existing infiltration line monitoring points in the i+1-th group, Δt i is the operating time of the existing infiltration line monitoring points in group i, Δt i+1 is the operating time of the existing infiltration line monitoring points in the i+1th group;

[0046] The preset criticality prediction formula is:

[0047]

[0048] Where, I 1j is the criticality of the infiltration line monitoring point in the j-th section of the first layer, I 2j is the criticality of the infiltration line monitoring point in the j-th section of the second layer, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, a 1～2 is the relative smoothing parameter between the existing infiltration line monitoring points in the first group and the existing infiltration line monitoring points in the second group, a t～1-t is the relative smoothing parameter between the existing infiltration line monitoring points of the tth group and the existing infiltration line monitoring points of the 1-tth group, It is the predicted value of the criticality of the existing infiltration line monitoring point in the j-th section of the (i+1)-th layer.

[0049] In an optional embodiment, determining the layout positions of the plurality of newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point includes:

[0050] Sorting the criticality of each newly added infiltration line monitoring point in descending order;

[0051] The newly added infiltration line monitoring points with a preset number of points in the previous order are used as the newly added infiltration line monitoring points;

[0052] The remaining new infiltration line monitoring points will be used as infiltration line monitoring points to be built.

[0053] In a second aspect, an embodiment of the present disclosure provides a device for arranging monitoring points on a tailings pond infiltration line, the device comprising:

[0054] a first calculation module, configured to obtain basic parameters of the tailings pond, calculate theoretical burial depths of a plurality of existing infiltration line monitoring points based on the basic parameters, and obtain actual monitoring values ​​of each of the existing infiltration line monitoring points; wherein the basic parameters include structural parameters and material mechanical parameters;

[0055] A second calculation module is used to calculate the deviation of each of the existing infiltration line monitoring points according to the theoretical buried depth and the actual monitoring value of each of the existing infiltration line monitoring points;

[0056] a third calculation module, configured to obtain time series variation data of the reservoir water level and calculate the sensitivity of each of the existing infiltration line monitoring points based on the time series variation data;

[0057] a fourth calculation module, configured to calculate the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points;

[0058] A prediction module, configured to predict the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points;

[0059] The determination module is used to determine the layout positions of multiple newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point.

[0060] In a third aspect, a computer device is provided in an embodiment of the present disclosure, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for arranging monitoring points of the tailings pond infiltration line described in the first aspect are implemented.

[0061] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for arranging monitoring points of the tailings pond infiltration line described in the first aspect.

[0062] Beneficial effects of this application:

[0063] The method for arranging seepage line monitoring points of tailings ponds provided in the embodiment of the present application utilizes the characteristics of step-by-step dam construction of tailings ponds and step-by-step construction of seepage line monitoring points. By analyzing the change pattern of monitoring data of previously constructed seepage line monitoring points, the importance of these seepage line monitoring points is obtained, thereby determining the representative seepage cross-section of the tailings pond, so that the layout of the next level of seepage line monitoring points can be closer to the representative seepage cross-section, and a scientific decision-making basis is provided for realizing refined monitoring of tailings dam stability.

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. Similar components are numbered similarly in the various drawings.

[0066] Figure 1 A flow chart of a method for arranging monitoring points on a tailings pond infiltration line provided in an embodiment of the present application is shown;

[0067] Figure 2 An example diagram of an existing infiltration line monitoring point provided by an embodiment of the present application is shown;

[0068] Figure 3 A schematic structural diagram of a tailings pond infiltration line monitoring point arrangement device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0069] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used in the template description herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0071] Example 1

[0072] like Figure 1 FIG. 1 is a flow chart of a method for arranging monitoring points on a tailings pond infiltration line according to an embodiment of the present application. The method for arranging monitoring points on a tailings pond infiltration line according to an embodiment of the present application includes the following steps:

[0073] Step S110, obtaining basic parameters of the tailings pond, calculating the theoretical burial depths of multiple existing infiltration line monitoring points based on the basic parameters, and obtaining actual monitoring values ​​of each of the existing infiltration line monitoring points, wherein the basic parameters include structural parameters and material mechanics parameters.

[0074] In this example, a tailings dam in a certain area currently has four layers of immersion line monitoring points, with six immersion line monitoring points per layer, forming six monitoring cross-sections, for a total of 4 × 6 = 24 existing immersion line monitoring points. Currently, the tailings dam is about to construct a fifth layer of immersion line monitoring points. This application is used to optimize the layout of the fifth layer of immersion line monitoring points.

[0075] For the convenience of expression, the middle layer in this embodiment is based on R i Indicates that the four layers are R1 to R4, and the monitoring section is W j The six sections are W1 to W6. Each monitoring point is represented by its layer and section, that is, R i W j , see the schematic diagram Figure 2 .

[0076] Specifically, the basic parameters of the tailings pond are first obtained, mainly including the basic topography, the initial dam height of the tailings pond, the initial dam outer slope ratio, the initial dam top width, the accumulation sub-dam height, the accumulation sub-dam outer slope ratio, the accumulation dam top width and other structural parameters obtained by actual measurement, as well as the permeability coefficient of the initial dam, the permeability coefficient of the tailings and other material mechanics parameters obtained by laboratory testing.

[0077] Furthermore, the structural parameters and material mechanics parameters of the tailings pond are input into finite element calculation software to construct a three-dimensional physical model of the tailings pond. Next, the current water level of the tailings pond is obtained through actual measurement or reading monitoring data. This current water level is input into the finite element calculation software to obtain the tailings pond head boundary conditions.

[0078] In the finite element calculation software, the three-dimensional seepage field inside the tailings pond is calculated through the three-dimensional physical model of the tailings pond and the head boundary conditions of the tailings pond. The surface with a seepage field pressure value of 0 in the three-dimensional seepage field inside the dam body is obtained as the infiltration surface of the tailings pond.

[0079] Furthermore, the coordinates of the locations of the existing infiltration line monitoring points on the tailings pond are obtained, the corresponding points on the infiltration surface are determined, and the vertical distances from these points to the outer surface of the dam are read to obtain the theoretical burial depth of the existing infiltration line monitoring points. In this embodiment, the theoretical burial depths of 24 existing infiltration line monitoring points obtained by finite element calculation are shown in Table 1.

[0080] Table 1 Theoretical burial depths of 24 existing infiltration line monitoring points

[0081]

[0082] Then, the actual monitoring values ​​of each existing infiltration line monitoring point are obtained by actual manual measurement or reading the online monitoring point data. In this embodiment, the actual monitoring values ​​of the 24 existing infiltration line monitoring points are shown in Table 2.

[0083] Table 2 Actual values ​​of 24 existing infiltration line monitoring points

[0084]

[0085] The above method obtains the basic parameters of the tailings pond and calculates the theoretical burial depth of the existing infiltration line monitoring point, while obtaining the actual monitoring value, laying the foundation for the subsequent analysis of the accuracy and reliability of the monitoring point.

[0086] Step S120 , calculating the deviation of each existing infiltration line monitoring point according to the theoretical buried depth and the actual monitoring value of each existing infiltration line monitoring point.

[0087] Understandably, according to the actual monitoring values ​​of each existing infiltration line monitoring point Calculate the average value μ of the actual monitoring value of each existing infiltration line monitoring point obs :

[0088]

[0089] According to the theoretical burial depth of each existing infiltration line monitoring point Calculate the theoretical average depth μ of each existing infiltration line monitoring point sim :

[0090]

[0091] In this embodiment, the average value of the monitoring values ​​of the 24 existing infiltration line monitoring points μ obs =11.11, theoretical average burial depth μ sim =10.84.

[0092] Furthermore, according to the actual monitoring values ​​of each existing infiltration line monitoring point And the average value of actual monitoring value μ obs , calculate the standard deviation σ of the actual monitoring values ​​of each existing infiltration line monitoring point obs :

[0093]

[0094] According to the theoretical burial depth of each existing infiltration line monitoring point and the theoretical average depth μ sim , calculate the theoretical depth standard deviation σ of each existing infiltration line monitoring point sim :

[0095]

[0096] In this embodiment, the standard deviation of the monitoring values ​​of the 24 existing infiltration line monitoring points is σ obs =3.41, theoretical burial depth standard deviation σ sim =3.30.

[0097] Then, according to the actual monitoring values ​​of each existing infiltration line monitoring point Actual monitoring value standard deviation σ obs , theoretical burial depth and the theoretical burial depth standard deviation σ sim , use the preset deviation calculation formula to calculate the deviation D of each existing infiltration line monitoring point ij , the preset deviation calculation formula is:

[0098]

[0099] Where D ij is the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, is the actual monitoring value of the infiltration line monitoring point in the jth section of the i-th layer, is the theoretical buried depth of the existing infiltration line monitoring point in the jth section of the i-th layer, σ obs is the standard deviation of the actual monitoring value, σ sim is the standard deviation of the theoretical burial depth.

[0100] In this embodiment, taking point R1W1 as an example, its deviation D 11 for:

[0101]

[0102] Similarly, the deviations of the remaining existing infiltration line monitoring points are calculated and shown in Table 3.

[0103] Table 3 Deviation indexes of 24 existing infiltration line monitoring points

[0104] <![CDATA[D ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.0548 0.1286 0.1159 0.1750 0.0675 0.0485 <![CDATA[R2]]> 0.0970 0.0443 0.0822 0.1518 0.0358 0.2234 <![CDATA[R3]]> 0.0696 0.1391 0.0148 0.1286 0.0232 0.1223 <![CDATA[R4]]> 0.0949 0.0021 0.1792 0.1159 0.2171 0.0443

[0105] The above method proposes a method for calculating the deviation between the theoretical and monitored values ​​of the tailings pond's infiltration line. By calculating the deviation at each existing infiltration line monitoring point, the degree of difference between the actual monitored value and the theoretical burial depth can be quantified. This helps identify monitoring points with significant data deviations, thereby clarifying areas in the monitoring system that may contain anomalies or require special attention, providing a key reference indicator for subsequent optimization of the monitoring point layout.

[0106] Step S130 , obtaining time series variation data of the reservoir water level, and calculating the sensitivity of each of the existing infiltration line monitoring points based on the time series variation data.

[0107] Preferably, first, the time series variation data of the reservoir water level is obtained. Specifically, the method for obtaining the data can be performed manually at fixed time intervals or by reading the data from the online monitoring system under conditions such as rainfall that cause the reservoir water level to change. In this embodiment, the method for obtaining the time series variation data of the reservoir water level is to read the reservoir water level monitoring data from the online monitoring system every 15 minutes during a 6-hour rainfall process, and obtain a set of time series variation data including 24 reservoir water level indicators, which is recorded as {μ t |t=1,2,...,24}, as shown in Table 4.

[0108] Table 4 Time series change data of reservoir water level

[0109] Time series / t 1 2 3 4 5 6 <![CDATA[Reservoir water level / u t > 1008.320 1008.400 1008.450 1008.480 1008.500 1008.580 Time series / t 7 8 9 10 11 12 <![CDATA[Reservoir water level / u t > 1008.630 1008.690 1008.730 1008.800 1008.900 1008.930 Time series / t 13 14 15 16 17 18 <![CDATA[Reservoir water level / u t > 1008.990 1009.060 1009.070 1009.170 1009.210 1009.140 Time series / t 19 20 21 22 23 24 <![CDATA[Reservoir water level / u t > 1009.110 1009.020 1008.980 1008.880 1008.850 1008.770

[0110] Furthermore, at the same time as acquiring the time series change data, the monitoring value response change data of each existing infiltration line monitoring point is collected. Since multiple points collect data simultaneously, the monitoring value response change data of each existing infiltration line monitoring point should be read through the online monitoring system.

[0111] In this embodiment, while reading the reservoir water level time series change data, the monitoring value response change data of 24 existing infiltration line monitoring points are synchronously obtained through the online monitoring system, that is, the time series data containing 24 infiltration line monitoring indicators are obtained, totaling 24 groups, recorded as Taking point R1W1 as an example, the monitoring value response change data is shown in Table 5.

[0112] Table 5 R1W1 point monitoring value response change data table

[0113] Time series / t 1 2 3 4 5 6 <![CDATA[Measured phreatic line / h t 11 > 7.810 7.806 7.789 7.778 7.771 7.743 Time series / t 7 8 9 10 11 12 <![CDATA[Measured phreatic line / h t 11 > 7.729 7.728 7.720 7.703 7.681 7.679 Time series / t 13 14 15 16 17 18 <![CDATA[Measured phreatic line / h t 11 > 7.675 7.663 7.660 7.644 7.631 7.625 Time series / t 19 20 21 22 23 24 <![CDATA[Measured phreatic line / h t 11 > 7.623 7.617 7.610 7.598 7.597 7.571

[0114] Next, according to the time series change data u of the reservoir water level t and the monitoring value response change data of each existing infiltration line monitoring point Calculate the sensitivity S of each existing infiltration line monitoring point using the preset sensitivity calculation formula ij :

[0115]

[0116] Where S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t+1, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t, u t+1 is the time series variation data of the reservoir water level at time t+1, u t is the time series variation data of the reservoir water level at time t, and T is the number of existing infiltration line monitoring points.

[0117] With the sensitivity S of R1W1 point 11 For example:

[0118]

[0119] Similarly, the sensitivity of other existing infiltration line monitoring points can be calculated as shown in Table 6.

[0120] Table 6 Sensitivity indicators of 24 existing infiltration line monitoring points

[0121] <![CDATA[S ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.182 0.338 0.256 0.398 0.281 0.149 <![CDATA[R2]]> 0.2041 0.0784 0.0453 0.2148 0.1389 0.1733 <![CDATA[R3]]> 0.1522 0.5057 0.0330 0.1984 0.0822 0.0802 <![CDATA[R4]]> 0.0390 0.046 0.2257 0.1848 0.8513 0.2153

[0122] The above method proposes a sensitivity calculation method based on reservoir water level time-series data and the response of the seepage line. By obtaining the time-series change data of the reservoir water level and calculating the sensitivity of each existing seepage line monitoring point, the response degree of the monitoring point to reservoir water level changes can be clearly determined. This helps to gain a deeper understanding of the dynamic characteristics of the tailings pond seepage field as the water level changes, determine which monitoring points are most sensitive to seepage changes, and provide a dynamic basis for evaluating the safety and stability of the tailings pond.

[0123] Step S140 , calculating the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points.

[0124] Preferably, the deviation weight value and sensitivity weight value of each existing infiltration line monitoring point are calculated using a preset weight calculation method and based on the deviation and sensitivity of each existing infiltration line monitoring point. The preset weight calculation method includes but is not limited to the entropy weight method, expert scoring method, coefficient of variation method or hierarchical analysis method.

[0125] In this embodiment, the entropy weight method is used to calculate the weight, and the process is as follows:

[0126] (1) First, the deviation and sensitivity of the 24 existing infiltration line monitoring points are normalized to obtain the normalized deviation value D′ ij and sensitivity normalized value S′ ij Taking deviation as an example, the normalization method is:

[0127]

[0128] Where, min(D ij ) and max(D ij) represent the minimum and maximum deviations of the 24 existing infiltration line monitoring points, respectively. The normalized deviation values ​​of the 24 existing infiltration line monitoring points are calculated, as shown in Table 7;

[0129] Table 7 Normalized deviation values ​​of 24 existing infiltration line monitoring points

[0130] <![CDATA[D′ ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.240 0.572 0.515 0.781 0.297 0.211 <![CDATA[R2]]> 0.430 0.192 0.363 0.677 0.154 1.000 <![CDATA[R3]]> 0.306 0.620 0.059 0.572 0.097 0.544 <![CDATA[R4]]> 0.420 0.002 0.800 0.515 0.971 0.192

[0131] Similarly, the normalized sensitivity values ​​of the 24 existing infiltration line monitoring points were calculated, as shown in Table 8;

[0132] Table 8 Normalized sensitivity values ​​of 24 existing infiltration line monitoring points

[0133]

[0134]

[0135] (2) Then, calculate the deviation ratio P|D′ of the 24 existing infiltration line monitoring points respectively ij and sensitivity ratio P|S′ ij Taking the deviation as an example, the weight calculation method is:

[0136]

[0137] The deviation ratios of the 24 existing infiltration line monitoring points were calculated, as shown in Table 9;

[0138] Table 9 Deviation ratio of 24 existing infiltration line monitoring points

[0139] <![CDATA[P|D′ ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.023 0.054 0.049 0.074 0.028 0.020 <![CDATA[R2]]> 0.041 0.018 0.034 0.064 0.015 0.095 <![CDATA[R3]]> 0.029 0.059 0.006 0.054 0.009 0.052 <![CDATA[R4]]> 0.040 0.001 0.076 0.049 0.092 0.018

[0140] Similarly, the sensitivity ratios of the 24 existing infiltration line monitoring points were calculated, as shown in Table 10;

[0141] Table 10 Sensitivity ratios of 24 existing infiltration line monitoring points

[0142] <![CDATA[P|S′ ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.036 0.068 0.051 0.080 0.056 0.030 <![CDATA[R2]]> 0.041 0.015 0.009 0.043 0.027 0.034 <![CDATA[R3]]> 0.030 0.101 0.006 0.039 0.016 0.016 <![CDATA[R4]]> 0.007 0.000 0.045 0.037 0.171 0.043

[0143] (3) Then, calculate the deviation information entropy e|D′ respectively ij and sensitivity information entropy e|S′ ij , the calculation method of information entropy is:

[0144]

[0145] Taking deviation as an example, the calculation method of information entropy is:

[0146]

[0147] Similarly, we get the information entropy of sensitivity e|S′ ij =0.902;

[0148] (4) Then, calculate the deviation information entropy redundancy g|D′ respectively ij and sensitivity information entropy redundancy g|S′ ij , the calculation method of information entropy redundancy is:

[0149] g j =1-e j

[0150] Taking deviation as an example, the calculation method of information entropy redundancy is:

[0151] g|D′ ij =1-e|D′ ij =1-0.933=0.067

[0152] Similarly, the information entropy redundancy of sensitivity g|S′ is obtained ij =0.098;

[0153] (5) Finally, calculate the deviation weight ω|D′ ij and sensitivity weight ω|S′ ij , taking the deviation as an example, the weight of the deviation is:

[0154]

[0155] Similarly, the sensitivity weight ω|S′ is obtained ij =0.594.

[0156] It can be understood that after calculating the deviation weight value and sensitivity weight value of each existing infiltration line monitoring point, according to the deviation D of each existing infiltration line monitoring point ij , deviation weight value ω|D′ ij , Sensitivity S ij and sensitivity weight value ω|S′ ij , use the preset criticality calculation formula to calculate the criticality I of each existing infiltration line monitoring point ij , the preset criticality calculation formula is:

[0157] I ij =D ij ×ω|D′ ij +S ij ×ω|S′ ij

[0158] Where, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, D ijis the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|D′ ij is the deviation weight value of the existing infiltration line monitoring point in the jth section of the i-th layer, S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|S′ ij is the sensitivity weight value of the existing infiltration line monitoring point in the j-th section of the i-th layer.

[0159] In this embodiment, the criticality of 24 existing infiltration line monitoring points is shown in Table 11.

[0160] Table 11 Criticality of 24 existing infiltration line monitoring points

[0161] <![CDATA[I ij ]]> <![CDATA[W1]]> <![CDATA[W2]]> <![CDATA[W3]]> <![CDATA[W4]]> <![CDATA[W5]]> <![CDATA[W6]]> <![CDATA[R1]]> 0.223 0.467 0.386 0.594 0.315 0.188 <![CDATA[R2]]> 0.315 0.131 0.177 0.423 0.158 0.526 <![CDATA[R3]]> 0.229 0.604 0.045 0.369 0.095 0.275 <![CDATA[R4]]> 0.196 0.002 0.481 0.337 0.988 0.227

[0162] The above method proposes a method for calculating the criticality of tailings pond infiltration lines. By comprehensively considering deviation and sensitivity, the criticality of each existing infiltration line monitoring point is calculated, which can comprehensively assess the importance of each monitoring point. This helps to screen monitoring points that are critical to tailings pond safety monitoring, rationally allocate monitoring resources, improve monitoring efficiency and accuracy, and provide a reliable reference standard for subsequent prediction of the criticality of new monitoring points.

[0163] Step S150 : predicting the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points.

[0164] Specifically, the operating time of each existing infiltration line monitoring point is determined by taking the completion time of the theoretical burial depth calculation for each existing infiltration line monitoring point as the time node, combined with the construction completion time of each existing infiltration line monitoring point in the construction record. The operating time can be measured in days or months, which is not limited in this embodiment.

[0165] In this example, the operating time of each existing saturation line monitoring point is determined on a monthly basis. This tailings pond has four layers of saturation line monitoring points, with six monitoring points per layer. Each layer of monitoring points was constructed and commissioned simultaneously, so the operating time of each layer of saturation line monitoring points is consistent.

[0166] <![CDATA[R1]]> <![CDATA[R2]]> <![CDATA[R3]]> <![CDATA[R4]]> <![CDATA[Δt i ]]> 48 37 24 11

[0167] The operating time of the existing infiltration line monitoring points in the four different layers in this embodiment is shown in Table 12.

[0168] Table 12 Operating time of four different layer infiltration line monitoring points

[0169] The existing infiltration line monitoring points are grouped according to different monitoring sections. In this embodiment, 24 existing infiltration line monitoring points form 6 sections, namely W1 to W6, that is, 6 groups.

[0170] Then, according to the running time of each existing infiltration line monitoring point, the relative smoothing parameter a between two adjacent existing infiltration line monitoring points in each group is calculated using the preset relative smoothing parameter calculation formula. i～i+1 , the preset relative smoothing parameter calculation formula is:

[0171]

[0172] Where a i～i+1 is the relative smoothing parameter between the i-th group of existing infiltration line monitoring points and the i+1-th group of existing infiltration line monitoring points, Δt i is the operating time of the i-th group of existing infiltration line monitoring points, Δt i+1 is the operating time of the i+1th group of existing infiltration line monitoring points.

[0173] In this embodiment, there are 4 layers, that is, it is necessary to calculate the relative smoothing parameters of 3 groups of adjacent existing infiltration line monitoring points, which are the relative smoothing parameters a between R1 and R2. 1～2 , the relative smoothing parameter a between R2 and R3 2～3 , the relative smoothing parameter a between R3 and R4 3～4 , with the relative smoothing parameter a between R1 and R2 1～2 For example, the calculation result is:

[0174]

[0175] Similarly, we can calculate that a 2～3 =0.607, a 3～4 =0.686.

[0176] Furthermore, according to the criticality of each existing infiltration line monitoring point in each group and the relative smoothing parameters of each layer, the criticality of each newly added infiltration line monitoring point is predicted by grouping using the preset criticality prediction formula. The default criticality prediction formula is:

[0177]

[0178] Where, I 1j is the criticality of the infiltration line monitoring point in the j-th section of the first layer, I 2j is the criticality of the infiltration line monitoring point in the j-th section of the second layer, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, a 1～2 is the relative smoothing parameter between the first group of existing infiltration line monitoring points and the second group of existing infiltration line monitoring points, a t～1-t is the relative smoothing parameter between the infiltration line monitoring points of the tth group and the infiltration line monitoring points of the 1-t group, is the predicted value of the criticality of the existing infiltration line monitoring point in the j-th section of the (i+1)-th layer.

[0179] In this embodiment, the tailings pond is divided into 6 sections for monitoring, namely W1 to W6, that is, divided into 6 groups. Taking the W1 section as an example, the criticality of the newly added infiltration line monitoring point of the preset 5th layer on the W1 section is predicted. The calculation process is as follows:

[0180]

[0181] Similarly, the criticality of the newly added infiltration line monitoring point in the 5th layer of sections W2 to W6 is predicted and calculated, as shown in Table 13.

[0182] Table 13 Predicted criticality values ​​of the fifth layer preset monitoring points in the six infiltration line monitoring sections

[0183]

[0184] This method predicts the criticality of new seepage line monitoring points based on the criticality of existing monitoring points, allowing for the rational planning of the location and number of new monitoring points in advance. This helps ensure that the new monitoring points effectively cover critical areas, optimizes the monitoring network layout, and improves the monitoring system's ability to monitor the overall seepage conditions of the tailings pond, providing more comprehensive assurance for its safe operation.

[0185] Step S160: determining the layout positions of a plurality of newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point.

[0186] Finally, the criticality of each newly added infiltration line monitoring point is sorted from high to low. In this embodiment, based on the calculation results of the criticality prediction values ​​of the fifth layer preset monitoring points of the six infiltration line monitoring sections, the ranking is from high to low, and the ranking results are:

[0187]

[0188] The newly added infiltration line monitoring points that are ranked in the front of the preset number will be regarded as the newly added infiltration line monitoring points that must be newly built. Understandably, according to the industry specification "Technical Specifications for Safety Monitoring of Tailing Dams" (AQ2030-2010), the seepage monitoring section of the tailings dam should be selected in a representative dam section that can control the main seepage conditions, and generally not less than 3. In combination with the requirements of this specification, if the predicted criticality of the newly added infiltration line monitoring points is ranked in the top 3 from high to low, it proves that the monitoring section is a representative dam section that can control the main seepage conditions, that is, a critical section. According to the requirements of the specification, a new infiltration line monitoring point must be built at the preset position, and online or manual monitoring must be carried out by setting up piezometers, water level observation holes, etc. That is, the selected The corresponding monitoring points are the new infiltration line monitoring points that must be newly built.

[0189] The remaining new infiltration line monitoring points will be used as infiltration line monitoring points to be built. It is understandable that if the new infiltration line monitoring points are predicted to be ranked 4th or later in order of criticality from high to low, it proves that under the current conditions, the monitoring section does not constitute the top 3 critical sections. It can be determined whether to set up monitoring points at the preset positions based on the actual needs such as the construction cost of the monitoring points, the safety risk level of the tailings pond and the monitoring accuracy. It should be noted that if the tailings dam is short and there are only three monitoring sections, then according to the relevant specifications, new monitoring points should be built at the three preset positions. In the actual management process, differentiated management can be implemented according to the criticality ranking. For monitoring sections with higher criticality rankings, management can be strengthened by increasing the monitoring frequency and improving the monitoring accuracy.

[0190] This method determines the placement of new monitoring points based on their criticality, enabling precise deployment of monitoring resources. Prioritizing limited resources to critical sections not only meets regulatory requirements but also allows for flexible adjustments based on actual needs. This effectively improves the economic and practicality of tailings pond safety monitoring, while also enhancing monitoring efficiency and relevance through differentiated management.

[0191] This application is driven by monitoring data. Based on an analysis of the operating characteristics of the tailings dam infiltration line, it quantifies the differences between actual operating conditions and design expectations and the time-varying dynamic response characteristics of the infiltration line. It integrates three dimensional indicators: deviation, sensitivity, and criticality, to achieve adaptive adjustment of the infiltration line monitoring network as risk evolves. This method effectively solves the current technical problem of the lack of quantitative judgment criteria for key sections of tailings dam monitoring. Through risk-driven point placement, it can effectively predict high-risk sections of the tailings dam, improving monitoring efficiency while reducing monitoring costs.

[0192] The method for arranging seepage line monitoring points of tailings ponds provided in the embodiment of the present application utilizes the characteristics of step-by-step dam construction of tailings ponds and step-by-step construction of seepage line monitoring points. By analyzing the change pattern of monitoring data of previously constructed seepage line monitoring points, the importance of these seepage line monitoring points is obtained, thereby determining the representative seepage cross-section of the tailings pond, so that the layout of the next level of seepage line monitoring points can be closer to the representative seepage cross-section, and a scientific decision-making basis is provided for realizing refined monitoring of tailings dam stability.

[0193] Example 2

[0194] like Figure 3 FIG. 1 is a schematic diagram of a tailings pond infiltration line monitoring point arrangement device 300 according to an embodiment of the present application, wherein the device includes:

[0195] A first calculation module 310 is configured to obtain basic parameters of the tailings pond, calculate theoretical burial depths of a plurality of existing immersion line monitoring points based on the basic parameters, and obtain actual monitoring values ​​of each of the existing immersion line monitoring points, wherein the basic parameters include structural parameters and material mechanical parameters;

[0196] The second calculation module 320 is configured to calculate the deviation of each of the existing infiltration line monitoring points based on the theoretical buried depth and the actual monitoring value of each of the existing infiltration line monitoring points;

[0197] The third calculation module 330 is used to obtain the time series variation data of the reservoir water level and calculate the sensitivity of each of the existing infiltration line monitoring points according to the time series variation data;

[0198] A fourth calculation module 340 is configured to calculate the criticality of each of the existing infiltration line monitoring points based on the deviation and sensitivity of each of the existing infiltration line monitoring points;

[0199] A prediction module 350 is configured to predict the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points;

[0200] The determination module 360 ​​is configured to determine the layout positions of a plurality of newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point.

[0201] The tailings pond infiltration line monitoring point arrangement device provided in the embodiment of the present application can realize each process of the tailings pond infiltration line monitoring point arrangement method corresponding to Example 1, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0202] The tailings pond seepage line monitoring point arrangement device provided in the embodiment of the present application utilizes the characteristics of the tailings pond being built step by step and the seepage line monitoring points being constructed step by step. By analyzing the change pattern of the monitoring data of the previously constructed seepage line monitoring points, the importance of these seepage line monitoring points is obtained, thereby determining the representative seepage cross-section of the tailings pond, so that the layout of the next level of seepage line monitoring points can be closer to the representative seepage cross-section, and a scientific decision-making basis is provided for realizing refined monitoring of the tailings dam stability.

[0203] A computer device is also provided in an embodiment of the present disclosure. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the tailings pond infiltration line monitoring point arrangement method described in Example 1 are implemented.

[0204] A computer-readable storage medium is also provided in an embodiment of the present disclosure. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the method for arranging monitoring points of the tailings pond infiltration line described in Example 1 are implemented.

[0205] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or flowchart, and the combination of boxes in the structure diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0206] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A method for arranging monitoring points of a tailings pond infiltration line, characterized in that: The method comprises: Obtaining basic parameters of the tailings pond, calculating theoretical burial depths of multiple existing infiltration line monitoring points based on the basic parameters, and obtaining actual monitoring values ​​of each of the existing infiltration line monitoring points, wherein the basic parameters include structural parameters and material mechanical parameters; Calculating the deviation of each of the existing infiltration line monitoring points based on the theoretical buried depth and the actual monitoring value of each of the existing infiltration line monitoring points; Acquiring time series variation data of the reservoir water level, and calculating the sensitivity of each of the existing infiltration line monitoring points based on the time series variation data; Calculating the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points; predicting the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points; The layout positions of the multiple newly added infiltration line monitoring points are determined according to the criticality of each of the newly added infiltration line monitoring points.

2. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: The calculating of the theoretical burial depths of a plurality of existing infiltration line monitoring points according to the basic parameters includes: Inputting the structural parameters and material mechanics parameters of the tailings pond into finite element calculation software to construct a three-dimensional physical model of the tailings pond; Obtaining the current water level of the tailings pond, inputting the current water level into the finite element calculation software to obtain the water head boundary condition of the tailings pond; Using the finite element calculation software and the three-dimensional physical model of the tailings pond and the water head boundary condition of the tailings pond, a three-dimensional seepage field inside the dam body of the tailings pond is obtained, and a surface with a seepage field pressure value of 0 in the three-dimensional seepage field inside the dam body is used as the infiltration surface of the tailings pond; Obtain the layout position coordinates of each existing infiltration line monitoring point on the tailings pond, and determine the vertical distance from the point corresponding to the layout position coordinates of each existing infiltration line monitoring point on the infiltration surface to the outer surface of the dam, and obtain the theoretical burial depth of each existing infiltration line monitoring point.

3. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: Calculating the deviation of each existing infiltration line monitoring point based on the theoretical buried depth and the actual monitoring value of each existing infiltration line monitoring point includes: Calculating an average value of the actual monitoring values ​​of each of the existing infiltration line monitoring points based on the actual monitoring values ​​of each of the existing infiltration line monitoring points; Calculating the average theoretical burial depth of each of the existing infiltration line monitoring points based on the theoretical burial depth of each of the existing infiltration line monitoring points; Calculating the standard deviation of the actual monitoring values ​​of each of the existing infiltration line monitoring points based on the actual monitoring values ​​and the average value of the actual monitoring values; Calculating the standard deviation of the theoretical burial depth of each of the existing infiltration line monitoring points based on the theoretical burial depth and the average theoretical burial depth of each of the existing infiltration line monitoring points; Calculate the deviation of each of the existing infiltration line monitoring points using a preset deviation calculation formula based on the actual monitoring value, the standard deviation of the actual monitoring value, the theoretical burial depth, and the standard deviation of the theoretical burial depth of each of the existing infiltration line monitoring points; The preset deviation calculation formula is: Where D ij is the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, is the actual monitoring value of the infiltration line monitoring point in the jth section of the i-th layer, is the theoretical buried depth of the existing infiltration line monitoring point in the jth section of the i-th layer, σ obs is the standard deviation of the actual monitoring value, σ sim is the standard deviation of the theoretical burial depth.

4. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: Calculating the sensitivity of each of the existing infiltration line monitoring points according to the time series change data includes: At the same time as acquiring the time series change data, collecting the monitoring value response change data of each of the existing infiltration line monitoring points; Calculating the sensitivity of each of the existing infiltration line monitoring points using a preset sensitivity calculation formula based on the time series change data of the reservoir water level and the monitoring value response change data of each of the existing infiltration line monitoring points; The preset sensitivity calculation formula is: Where S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t+1, is the monitoring value response change data of the existing infiltration line monitoring point in the jth section of the i-th layer at time t, u t+1 is the time series variation data of the reservoir water level at time t+1, u t is the time series variation data of the reservoir water level at time t, and T is the number of existing infiltration line monitoring points.

5. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: Calculating the criticality of each of the existing infiltration line monitoring points based on the deviation and sensitivity of each of the existing infiltration line monitoring points includes: Calculating the deviation weight value and sensitivity weight value of each of the existing infiltration line monitoring points using a preset weight calculation method and based on the deviation and sensitivity of each of the existing infiltration line monitoring points, wherein the preset weight calculation method includes an entropy weight method, an expert scoring method, a coefficient of variation method, or a hierarchical analysis method; Calculate the criticality of each of the existing infiltration line monitoring points using a preset criticality calculation formula according to the deviation, deviation weight, sensitivity, and sensitivity weight of each of the existing infiltration line monitoring points; The preset criticality calculation formula is: I ij =D ij ×ω|D′ ij +S ij ×ω|S′ ij Where, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, D ij is the deviation of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|D′ ij is the deviation weight value of the existing infiltration line monitoring point in the jth section of the i-th layer, S ij is the sensitivity of the existing infiltration line monitoring point in the jth section of the i-th layer, ω|S′ ij is the sensitivity weight value of the existing infiltration line monitoring point in the j-th section of the i-th layer.

6. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: The step of predicting the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points includes: Obtaining the operating time of each of the existing infiltration line monitoring points, and grouping the existing infiltration line monitoring points according to different monitoring sections; According to the running time of each of the existing infiltration line monitoring points, a relative smoothing parameter between two adjacent existing infiltration line monitoring points in each group is calculated using a preset relative smoothing parameter calculation formula; According to the criticality and relative smoothness parameters of each existing infiltration line monitoring point in each group, the criticality of each newly added infiltration line monitoring point is predicted using a preset criticality prediction formula; The preset relative smoothing parameter calculation formula is: Where a i～i+1 is the relative smoothing parameter between the existing infiltration line monitoring points in the i-th group and the existing infiltration line monitoring points in the i+1-th group, Δt i is the operating time of the existing infiltration line monitoring points in group i, Δt i+1 is the operating time of the existing infiltration line monitoring points in the i+1th group; The preset criticality prediction formula is: Where, I 1j is the criticality of the infiltration line monitoring point in the j-th section of the first layer, I 2j is the criticality of the infiltration line monitoring point in the j-th section of the second layer, I ij is the criticality of the existing infiltration line monitoring point in the jth section of the i-th layer, a 1～2 is the relative smoothing parameter between the existing infiltration line monitoring points in the first group and the existing infiltration line monitoring points in the second group, a t～1-t is the relative smoothing parameter between the existing infiltration line monitoring points of the tth group and the existing infiltration line monitoring points of the 1-tth group, It is the predicted value of the criticality of the existing infiltration line monitoring point in the j-th section of the (i+1)-th layer.

7. The method for arranging monitoring points of the tailings pond infiltration line according to claim 1, characterized in that: The step of determining the layout positions of the plurality of newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point comprises: Sorting the criticality of each newly added infiltration line monitoring point in descending order; The newly added infiltration line monitoring points with a preset number of points in the previous order are used as the newly added infiltration line monitoring points; The remaining new infiltration line monitoring points will be used as infiltration line monitoring points to be built.

8. A device for arranging monitoring points on the tailings pond infiltration line, characterized in that: The device comprises: a first calculation module, configured to obtain basic parameters of the tailings pond, calculate theoretical burial depths of a plurality of existing infiltration line monitoring points based on the basic parameters, and obtain actual monitoring values ​​of each of the existing infiltration line monitoring points; wherein the basic parameters include structural parameters and material mechanical parameters; A second calculation module is used to calculate the deviation of each of the existing infiltration line monitoring points according to the theoretical buried depth and the actual monitoring value of each of the existing infiltration line monitoring points; a third calculation module, configured to obtain time series variation data of the reservoir water level and calculate the sensitivity of each of the existing infiltration line monitoring points based on the time series variation data; a fourth calculation module, configured to calculate the criticality of each of the existing infiltration line monitoring points according to the deviation and sensitivity of each of the existing infiltration line monitoring points; A prediction module, configured to predict the criticality of a plurality of newly added infiltration line monitoring points based on the criticality of each of the existing infiltration line monitoring points; The determination module is used to determine the layout positions of multiple newly added infiltration line monitoring points according to the criticality of each newly added infiltration line monitoring point.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for arranging monitoring points of the tailings pond infiltration line according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for arranging monitoring points of a tailings pond infiltration line according to any one of claims 1 to 7 are implemented.

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