Tailing pond safety monitoring index comprehensive early warning method, terminal equipment and storage medium

Abstract

The invention discloses a tailing pond safety monitoring index comprehensive early warning method, terminal equipment and a storage medium, a tailing pond safety early warning system is explored through an evaluation index set, so that the evaluation index has a clear physical significance, and a main factor set influencing tailing pond safety factors is selected; and the influence of the weight of the influence factor on the early warning model is considered, and multiple factors and safety early warning are closely associated for collaborative analysis. A membership function is used for analyzing tailing pond monitoring evaluation indexes, and a fuzzy synthesis operator for comprehensive and accurate early warning is finally obtained by constructing influence factor evaluation sets, analyzing monitoring index risk indexes, possibility coefficients, influence degrees and boundary condition influence coefficients to determine weight coefficients, so that tailing pond safety features can be well reflected. And the prediction precision is improved.

Description

Technical Field

[0001] The present invention relates to the field of tailings pond safety monitoring, and in particular to a comprehensive early warning method for tailings pond safety monitoring indicators, terminal equipment and storage medium. Background Art

[0002] Tailings dam safety monitoring provides safety status data for tailings dams. If the tailings dam safety monitoring and early warning system cannot effectively predict and warn, and cannot obtain the internal and external interactions and effect parameters of the tailings dam, it will be impossible to understand the actual safety status of the tailings dam, and there will be no way to obtain key sign information before the dam breaks so as to take effective measures. How to achieve accurate tailings dam monitoring and early warning: Reasonable setting of safety monitoring indicators and improving monitoring accuracy are prerequisites, and establishing a sound early warning mechanism is the key.

[0003] Different monitoring methods have different early warning methods, which mainly include indicator early warning method: ① Setting corresponding indicator values ​​for early warning is the most intuitive method; ② Statistical early warning method: an early warning method suitable for the buried depth of the infiltration line and the displacement of the dam body; ③ Model early warning method: describing the correlation between the warning situation and the qualitative change of the warning, so as to give early warning for different warning situations; ④ Comprehensive early warning method: a relatively comprehensive early warning method, combining multiple models to unify and integrate various warning indicators to complete the early warning.

[0004] The tailings pond monitoring and early warning criterion system refers to an organic whole composed of several relatively independent, interactive and mutually influential indicator factors that reflect certain characteristics of the research object. The existing statistical early warning methods cannot effectively predict and warn, and the existing fuzzy early warning methods and comprehensive early warning methods have complex calculation processes, and the accuracy of early warnings needs to be improved. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a comprehensive early warning method for tailings pond safety monitoring indicators, terminal equipment and storage medium in response to the shortcomings of the existing technology, so as to improve the accuracy of tailings pond safety monitoring and early warning.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is: a comprehensive early warning method for tailings pond safety monitoring indicators, comprising the following steps:

[0007] S1. Construct the evaluation index set U: U={u1,u2,…,u n}; where u i represents the i-th influencing factor index, i = 1, 2, ... n, n is the number of influencing factor indicators;

[0008] Construct the evaluation set V of each influencing factor: V = {v1, v2, v3, v4}; v1 is the fourth-level warning, v2 is the third-level warning, v3 is the second-level warning, and v4 is the first-level warning;

[0009] S2. Calculate the total fuzzy evaluation result B using the following formula: B = D·R; where D = {d1, d2, ... d n}, d i ≥0, 0≤r ij ≤1, 1≤i≤n, 1≤j≤m, r ij represents the membership degree, a, b, c, d are the first-level warning, second-level warning, third-level warning, and fourth-level warning alarm values ​​of each evaluation indicator respectively, x is the monitoring value of each evaluation indicator, d i for u i The weight of

[0010] S3, using the fuzzy evaluation total result B to calculate the fuzzy synthesis operator b i :

[0011] S4, according to the fuzzy synthesis operator b i and the evaluation set of influencing factors to determine the warning level.

[0012] The present invention uses the uncertainty analysis method to solve the fuzzy problem of early warning. By studying the monitoring indicators and early warning mechanism of the tailings pond, a comprehensive safety early warning system of the tailings pond is established, which effectively solves the relationship between the effect quantity and the monitoring cause quantity (or between several effect quantities) and the degree of correlation. The fuzzy synthesis operator b of the present invention is i The fuzzy comprehensive evaluation takes into account the relationship between the combination of various indicator criteria and risks, realizes the comprehensive early warning of multiple indicators, and improves the reliability and accuracy of tailings pond safety monitoring and early warning.

[0013] Membership degree r ij The calculation formula is:

[0014]

[0015] In the present invention, the membership function represents the degree of membership of the elements in U relative to the elements in the set V, which is designed as a fuzzy mapping f from U to V. For each factor u i , a separate judgment f(u i ), take the single factor evaluation set as the row to form the matrix: f(u i )=(r i1 ,r i2 …r ij ).

[0016] In the present invention, d i =a i1 ×a i2 ×a i3 ×a i4 ; Among them, 0<aij <1, a i1 for u i The risk index, a i2 for u i The probability coefficient, a i3 for u i The degree of influence, a i4 for u i The present invention comprehensively considers the risk index, possibility coefficient, impact degree and boundary condition impact coefficient of each influencing factor indicator, further improving the calculation accuracy and objectivity of the influencing factor indicator weight, thereby further improving the accuracy of the early warning result.

[0017] In the present invention, the boundary conditions include: production information, topographic and geological conditions, material divisions of each layer of the dam body and physical and mechanical indicators, and inspection conditions.

[0018] The specific implementation process of step S4 of the present invention includes:

[0019] If 0.8<b i ≤1, it is judged as a level 4 warning;

[0020] If 0.5<b i ≤0.8, it is judged as a level 3 warning;

[0021] If 0.2<b i ≤0.5, it is judged as a Level 2 warning;

[0022] If 0≤b i If ≤0.2, it is judged as a level one warning.

[0023] The influencing factor indicators include the tailings pond dam seepage, accumulation dam slope ratio, rainfall intensity, dry beach, reservoir water level, and dam displacement.

[0024] As an inventive concept, the present invention also provides a terminal device, including a memory, a processor, and a computer program stored in the memory; the processor executes the computer program to implement the steps of the above method.

[0025] As an inventive concept, the present invention also provides a computer-readable storage medium having a computer program / instruction stored thereon; the computer program / instruction implements the steps of the above method when executed by a processor.

[0026] As an inventive concept, the present invention also provides a computer program product, comprising a computer program / instruction; when the computer program / instruction is executed by a processor, the steps of the above method are implemented.

[0027] Compared with the existing technology, the present invention has the following beneficial effects: the present invention explores the tailings pond safety early warning system through an evaluation index set, makes the evaluation index have a clear physical meaning, selects the main factor set that affects the safety of the tailings pond, and takes into account the influence of the weight of the influencing factors on the early warning model, closely links multiple factors with the safety early warning for collaborative analysis. The tailings pond monitoring evaluation index is analyzed using a membership function, and the weight coefficient is determined by constructing a judgment set of each influencing factor, analyzing the monitoring indicator risk index, possibility coefficient, influence degree, and boundary condition influence coefficient, and finally obtaining a fuzzy synthesis operator for comprehensive and accurate early warning, which can better reflect the safety characteristics of the tailings pond and improve the accuracy of the prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0030] Example 1

[0031] This embodiment provides a comprehensive early warning method for tailings pond safety monitoring indicators, constructs a cloud model of indicator criteria to achieve comprehensive and accurate early warning. The indicator criteria determined in this embodiment, namely the monitoring indicators, are as follows: displacement monitoring, infiltration line monitoring, reservoir water level monitoring, dry beach monitoring, seepage flow monitoring and other system monitoring indicators.

[0032] This embodiment determines the reference value and boundary conditions by comprehensively considering factors such as the measurement object, measurement method and instrument, and measurement environment and conditions:

[0033] Indicator baseline value: the initial value of each monitoring indicator, that is, the baseline value of each monitoring point;

[0034] Boundary conditions: production information (dam construction technology, tailings discharge data), topographic and geological conditions, material divisions and physical and mechanical indicators of each layer of the dam body, and inspection status.

[0035] This embodiment takes the tailings pond as the monitoring object, and through the feasibility analysis of online monitoring, monitors the structural response, assists in monitoring the natural environment, and determines the indicator criteria for changes in working conditions: dam seepage, accumulation dam slope ratio, rainfall intensity, dry beach, reservoir water level, and dam displacement.

[0036] This embodiment analyzes and studies the basic geological environment conditions of the tailings pond and the production information of the tailings pond (dam) as input boundary conditions.

[0037] The geological environment that affects monitoring and early warning mainly includes topographic and geological conditions and the load of stability calculation:

[0038] (1) Topographic and geological factors:

[0039] Fractures, wrinkles, etc.

[0040] Reservoir surface water and reservoir groundwater factors

[0041] Geological environmental disasters such as debris flow, landslide, collapse, etc. in the reservoir area and surrounding areas

[0042] The above geological environment is expressed structurally and input as boundary conditions:

[0043] The event "exists" is expressed by "1" and "does not exist" is expressed by "0";

[0044] (2) Boundary conditions involved in tailings dam slope stability calculation:

[0045] The load for dam stability calculation is composed of the seepage force generated by the normal high water level of the tailings pond and the dam's own weight during normal operation; it is composed of the dam's own weight and the stable seepage pressure that may be generated by the highest flood level during flood operation; and it is composed of the dam's own weight and the stable seepage pressure that may be generated by the normal water level and seismic load during special operation.

[0046] The calculated loads are directly expressed using the corresponding numerical values ​​or their mathematical expressions.

[0047] (3) Tailings pond (dam) production information

[0048] Reservoir capacity, dam height, dam construction process parameters, and tailings discharge data.

[0049] The specific implementation process of this embodiment is as follows:

[0050] (1) Based on the corresponding monitoring indicators of the dam body seepage, accumulation dam slope ratio, rainfall intensity, dry beach, reservoir water level, and dam body displacement monitoring items determined above, an evaluation index set is constructed and represented by U: U = {u1, u2, ..., u n}

[0051] u i ,{i=1,2,…n} represents the indicators of each influencing factor.

[0052] (2) Construct the evaluation set V of each influencing factor: V = {v1, v2, ..., v m}

[0053] v i,{i=1,2,…m} represents various possible evaluation results.

[0054] In this embodiment, m=4. According to the safety regulations for tailings dams, tailings dam safety monitoring and early warning should be divided into four levels from low to high: blue warning, yellow warning, orange warning, and red warning:

[0055] v1: Red alert;

[0056] v2: Orange warning;

[0057] v3: Yellow warning;

[0058] v4: blue warning;

[0059] (3) Construct membership function.

[0060] The membership function represents the degree of membership of the elements in U relative to the elements in the set V. It is designed as a fuzzy mapping f from U to V. For each factor u i , a separate judgment f(u i ), take the single factor evaluation set as the row to form the matrix: f(u i )=(r i1 ,r i2 …r ij )

[0061] where 0≤r ij ≤1, 1≤i≤n, 1≤j≤m, r ij Indicates the degree of membership.

[0062] This embodiment uses an assignment method and a trapezoidal membership function to obtain the membership of the evaluation index.

[0063]

[0064] x is the monitoring value of each evaluation index.

[0065] a, b, c, and d are the blue warning, yellow warning, orange warning, and red warning alarm values ​​of each evaluation indicator, respectively.

[0066] (4) Construct the fuzzy evaluation matrix R

[0067]

[0068] (5) Constructing weight set

[0069] D={d1,d2,…d n}

[0070] d i , {i=1,2,…,n} satisfies:

[0071] d i ≥0

[0072] d i for u i Weight:

[0073] d i =a i1 ×a i2 ×a i3 ×a i4 ;

[0074] Where: 0<a ij <1;

[0075] a i1 :u i Risk index;

[0076] a i2 :u i Likelihood coefficient;

[0077] a i3 :u i Degree of impact;

[0078] a i4 :u i Boundary condition influence coefficient = probability of occurrence × degree of correlation.

[0079] (6) Combine D with the evaluation object R using the synthesis operator to obtain the fuzzy evaluation result B. It can be expressed as:

[0080] B=D·R

[0081] (7) Fuzzy synthesis operator: Use the maximum product and prominent main factor type to perform fuzzy comprehensive evaluation. That is:

[0082]

[0083] Warning level 4 coefficient:

[0084] Red alert (level 4): 0.8 < b i ≤1;

[0085] Orange alert (level 3): 0.5 < b i ≤0.8;

[0086] Yellow warning (level 2): ​​0.2 < b i ≤0.5;

[0087] Blue warning (level 1): 0≤b i ≤0.2.

[0088] Fuzzy synthesis operator b iThe fuzzy comprehensive overall evaluation takes into account the relationship between the combination of various indicator criteria and the risk. Compared with the conventional indicator criterion method, it has made great improvements. It effectively solves the complex problem of solving the relationship and correlation degree between the effect size and the monitored cause size (or between several effect sizes), and realizes the comprehensive early warning of multiple indicators.

[0089] This embodiment uses a programming language to develop programs and deploy an application system, including a data perception and transmission layer, a data management, analysis, and publishing layer, a pre-alarm management layer, and a contingency plan management and emergency decision-making support layer. The data perception and transmission layer automatically acquires data. The data management, analysis, and publishing layer analyzes and publishes data, accurately assessing the safety status of the tailings pond. The pre-alarm management layer issues warnings based on the results of the data management, analysis, and publishing layer. The contingency plan management and emergency decision-making support layer uses pre-defined contingency plan rules to provide decision makers with convenient information tools.

[0090] Example 2

[0091] Embodiment 2 of the present invention provides a terminal device corresponding to the above-mentioned embodiment 1. The terminal device can be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of the above-mentioned embodiment.

[0092] The terminal device of this embodiment includes a memory, a processor, and a computer program stored in the memory; the processor executes the computer program in the memory to implement the steps of the method in the above-mentioned embodiment 1.

[0093] In some implementations, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage.

[0094] In other implementations, the processor may be a central processing unit (CPU), a digital signal processor (DSP), or other general-purpose processors, which are not limited here.

[0095] Example 3

[0096] Embodiment 3 of the present invention provides a computer-readable storage medium corresponding to the above-mentioned embodiment 1, on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the steps of the method of the above-mentioned embodiment 1 are implemented.

[0097] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0098] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0099] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0100] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0101] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0102] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A comprehensive early warning method for tailings pond safety monitoring indicators, characterized in that: The following steps are involved: S1. Construct the evaluation index set U: U = {u1,u2,…,u n }; where u i represents the i-th influencing factor index, i=1,2,…n, n is the number of influencing factor indicators; Construct the evaluation set V of each influencing factor: V = {v1, v2, v3, v4}; v1 is the fourth-level warning, v2 is the third-level warning, v3 is the second-level warning, and v4 is the first-level warning; S2. Calculate the total fuzzy evaluation result B using the following formula: B = D·R; where D = {d1, d2, ... d n }, r ij represents the degree of membership, a, b, c, d are the first-level warning, second-level warning, third-level warning, and fourth-level warning alarm values ​​of each evaluation indicator, x is the monitoring value of each evaluation indicator, d i for u i The weight of S3, using the fuzzy evaluation total result B to calculate the fuzzy synthesis operator b i : S4, according to the fuzzy synthesis operator b i The warning level is determined based on the evaluation set of influencing factors.

2. The tailings dam safety monitoring index comprehensive early warning method according to claim 1 is characterized in that: Membership degree r ij The calculation formula is:

3. The comprehensive early warning method for tailings dam safety monitoring indicators according to claim 1 is characterized in that: d i =a i1 ×a i2 ×a i3 ×a i4 ; Among them, 0<a ij <1, a i1 for u i The risk index, a i2 for u i The probability coefficient, a i3 for u i The degree of influence, a i4 for u i The boundary condition influence coefficient.

4. The comprehensive early warning method for tailings dam safety monitoring indicators according to claim 3 is characterized in that: The boundary conditions include: production information, topographic and geological conditions, material divisions of each layer of the dam body and physical and mechanical indicators, and inspection conditions.

5. The comprehensive early warning method for tailings dam safety monitoring indicators according to claim 1 is characterized in that: The specific implementation process of step S4 includes: If 0.8<b i ≤1, it is judged as a level 4 warning; If 0.5<b i ≤0.8, it is judged as level 3 warning; If 0.2<b i ≤0.5, it is judged as a second-level warning; If 0≤b i ≤0.2, it is judged as a level one warning.

6. The comprehensive early warning method for tailings dam safety monitoring indicators according to claim 1 is characterized in that: The influencing factor indicators include the dam body seepage of the tailings pond, the slope ratio of the accumulation dam, the rainfall intensity, the dry beach, the reservoir water level, and the dam body displacement.

7. A terminal device comprising a memory, a processor and a computer program stored in the memory; characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program / instruction stored thereon; characterized in that: When the computer program / instructions are executed by a processor, the steps of the method described in any one of claims 1 to 6 are implemented.

9. A computer program product comprising a computer program / instructions; characterized in that: When the computer program / instructions are executed by a processor, the steps of the method of any one of claims 1 to 6 are implemented.

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