AHP-TOPSIS model-based rapid optimization method for span of room-and-pillar stope

Abstract

The application relates to a kind of AHP-TOPSIS model-based room-and-pillar stope span rapid optimization method, belong to the technical field of mine stope design, comprising the following steps: S1: establishing stope span optimization multi-factor evaluation index system;S2: collecting stope basic data and carrying out quantitative score;S3: establishing weight distribution system;S4: using the sorting TOPSIS algorithm of approaching ideal solution to calculate comprehensive closeness;S5: parameter optimization decision based on closeness value output.

Description

Technical Field

[0001] This invention belongs to the field of mining stope design technology, and relates to a rapid optimization method for the span of room-and-pillar stopes based on the AHP-TOPSIS model. Background Technology

[0002] In room-and-pillar mining, the rationality of the stope span is crucial for ensuring mining safety, preventing roof collapse and pillar instability, and maximizing ore recovery rate while improving economic efficiency. However, current parameter design methods have significant limitations, leading to insufficient long-term stability of the goaf. Pillar design may be overly conservative, resulting in a loss of recovery rate, or overly risky, causing safety hazards.

[0003] Traditional design methods primarily rely on two technical paths: empirical formulas and numerical simulation. Both have inherent drawbacks: while empirical formulas are simple and easy to use, they are essentially highly simplified models, failing to comprehensively reflect the synergistic influence of multiple geological factors in the roof-pillar co-bearing mechanism of the room-pillar method. This results in highly subjective design results and a lack of unified quantitative standards. Numerical simulation, while capable of precisely analyzing the mechanical response of specific models, suffers from complex modeling processes, high computational costs, and heavy reliance on assumptions, leading to poor universality and difficulty in rapid application to various mining areas with varying geological conditions. More significantly, traditional methods typically use the same set of design parameters for the entire mining area, failing to achieve refined zoning. This can result in unnecessary strong support in geologically favorable sections, causing economic waste; while in geologically unfavorable sections, support may be insufficient, creating safety hazards. Therefore, the industry urgently needs a new method that can systematically integrate multi-source geological information, quantitatively analyze the influence weights of various factors, and provide rapid and targeted optimization solutions for different mining areas. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a rapid optimization method for the span of room-and-pillar stopes based on the AHP-TOPSIS model, so as to achieve rapid and accurate optimization of the stope span in different sections of the mining area, thereby maximizing the optimization of support costs and improving mining efficiency while ensuring safety. The core of this invention lies in "rapid" and "targeted" approaches. Its rapidity is reflected in the establishment of a standardized quantitative scoring system and fixed decision-making rules, transforming complex geological assessments into a repeatable calculation process, eliminating the cumbersome modeling process of numerical simulation. This enables "instant response and rapid reassessment" of subsequent mining areas or changed sections after mine production progresses and geological information is updated, gaining valuable time for dynamically adjusting support schemes and avoiding waste in the early design phase.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A rapid optimization method for the span of room-and-pillar mining areas based on the AHP-TOPSIS model includes the following steps: S1: Establish a multi-factor evaluation index system for optimizing the mining span; S2: Collect basic data from the mining area and perform quantitative scoring; S3: Establish a weight allocation system; S4: Use the TOPSIS algorithm, which approximates the ideal solution, to perform a comprehensive closeness calculation; S5: Optimize decision-making based on output parameters according to proximity value.

[0006] Furthermore, in step S1, based on the analysis of factors affecting the stability of room-pillar mining, an evaluation system containing four core factors is established: measured range of loosened zone L, RMR rock mass quality classification R, rationality of existing stope span S, and geostress environment σ. The measured range L of the loosened zone is used to quantify the severity of the actual damage range of the surrounding rock relative to the reference safety threshold based on the measured thickness of the loosened zone of the sidewalls and roof of the roadway or mining area. The RMR rock mass quality classification R considers the comprehensive rock mass quality evaluation results of multiple indicators, and integrates multiple geological information into a quantitative score; The rationality S of the existing mine span is used to quantify the safety margin of the current span; The geostress environment σ is used to quantify the relative relationship between the load on the rock mass and its strength.

[0007] Furthermore, the quantification formula for the measured range L of the loosening ring is as follows:

[0008] in, The thickness of the loose ring is obtained through on-site measurement using methods such as acoustic wave testing, borehole photography, or multi-point displacement gauges. This is a reference loosening zone threshold determined based on the lithology, burial depth, and RMR empirical values ​​of the mining area; This formula quantifies the severity of the actual damage range of the surrounding rock relative to a reference safety threshold; The larger the ratio, the more severe the loosening of the surrounding rock and the worse the stability. The lower.

[0009] Furthermore, the R quantification formula for the RMR rock mass quality classification is as follows:

[0010] The above formula is a linear standardization process, which maps the RMR range to a scoring interval of 0-1, making it easier to calculate comprehensively. The RMR value considers six indicators, including the strength of intact rock material, core quality, joint spacing, joint state, groundwater influence, and joint direction.

[0011] Furthermore, the formula for quantifying the rationality S of the existing mine span is as follows:

[0012] This formula is based on a simplified empirical relation of the Hoek-Brown strength criterion, where For the theoretical critical span, For the current mining area span, , The calculation is based on the rock mass proposed by Barton et al. Q Systems theory; For support ratio.

[0013] Furthermore, the formula for quantifying the geostress environment σ is as follows:

[0014] in For vertical stress, For rock mass strength, when / When ≥1, score σ A value of 1 indicates that the rock mass is already in its ultimate bearing capacity state, and the span should not be increased.

[0015] Furthermore, in step S2, the following data collection and quantification work is carried out for the target mining site: The thickness of the loosened zone is determined by using acoustic testing or borehole photography to probe around the roadway or mining area. Calculate the loosening zone range score ; RMR values ​​were obtained through borehole logging and field surveys, and then standardized. ; The span of the existing stope is measured, and the theoretical span is calculated using theoretical formulas applicable to the room-and-pillar method to obtain a rationality score for the current stope span. ; Based on the mining depth and rock mass strength parameters, the geostress environmental impact score is calculated. .

[0016] Furthermore, in step S3, the judgment matrix is ​​assigned values ​​based on the 1-9 scaling method of the Analytic Hierarchy Process (AHP), and the judgment matrix is ​​as follows:

[0017] The weight coefficients are calculated from the judgment matrix and then normalized to obtain the final weights of each factor. The measured range of the loose circle, as a comprehensive response index characterizing the immediate stability state of surrounding rock after excavation, together with the RMR rock mass quality classification, constitutes the two most core foundations for stability assessment; the in-situ stress environment, as the main external load, is of secondary importance; the rationality of the currently used stope span, as an optimizable design parameter, has the lowest weight.

[0018] Further, in step S4, the closeness is calculated based on the weighted normalization matrix: Construct a weighted decision matrix:

[0019] Determine the positive and negative ideal solutions: ,

[0020] Calculate the distance D of each scheme to the positive and negative ideal solutions + and D - :

[0021]

[0022] Calculate the comprehensive closeness: .

[0023] Further, in step S5, through retrospective verification of several stope cases of the room-and-pillar method with known stable states, it is determined that the following CSI decision threshold has the best discrimination and engineering safety, and specific parameter adjustment suggestions based on the CSI value are provided: CSI>0.7: increase the stope span by 30%-50%; 0.6<CSI≤0.7: increase the stope span by 10%-30%; 0.4≤CSI≤0.6: maintain the existing stope parameters; 0.3≤CSI<0.4: reduce the stope span by 10%-30%; CSI<0.3: reduce the stope span by 30%-50%.

[0024] The beneficial effects of the present invention are as follows: 1. Systematicness: By establishing a complete four-factor evaluation system, the key geological factors affecting stope stability are comprehensively considered, which overcomes the limitation of traditional single-index evaluation.

[0025] 2. Quantitative Analysis and Scientific Decision-Making: The AHP-TOPSIS integrated evaluation model combines qualitative analysis with quantitative calculation. AHP solves the problem of multi-factor weight allocation, while TOPSIS provides an objective ranking of merits. Its decision-making mechanism based on relative proximity, compared with single-weighted methods or fuzzy decision-making methods, can more effectively distinguish the subtle differences between various schemes. The two complement each other, realizing scientific decision-making for the optimization of mining parameters and significantly reducing subjective judgment bias.

[0026] 3. High practicality: The required data can all be obtained through conventional geological surveys, the calculation process is standardized and clear, which is easy for on-site technicians to master and apply, and has good engineering practicality.

[0027] 4. High Efficiency, Economy, and Dynamic Adaptability: Compared to numerical simulation methods, this method offers faster computation, enabling parameter optimization for multiple mining areas or different sections within the same mining area in a short time, significantly improving design efficiency. This "rapid evaluation-rapid decision-making" capability allows the method to keep pace with mining operations, achieving dynamic design with "evaluation as mining progresses." By conducting refined evaluation and optimization of mining areas by section, it avoids "over-support" in areas with good conditions and "precise reinforcement" in weak areas, thereby achieving optimal allocation of support resources and effectively saving costs. It avoids long-term economic losses or safety risks caused by conservative or risky parameters from the design stage.

[0028] 5. Highly targeted: Through comprehensive evaluation of multiple factors, it can provide personalized parameter optimization suggestions for mining areas or sections with different geological conditions, achieving truly targeted optimization.

[0029] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0030] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 Flowchart of a rapid and targeted optimization method for stope span in room-pillar stopes based on the AHP-TOPSIS model; Figure 2 This is a schematic diagram of the calculation process. Detailed Implementation

[0031] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0032] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0033] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0034] Example 1: like Figure 1-2As shown, this invention provides a rapid optimization method for the span of room-and-pillar stopes based on the AHP-TOPSIS model. This invention employs a comprehensive evaluation model combining AHP (Analytic Hierarchy Process) and TOPSIS (Topology for Approximating Ideal Solutions). Its advantages are: AHP can effectively quantify the subjective weights of various influencing factors, transforming engineering experience into a calculable judgment matrix, thus solving the problem of multi-factor weight allocation; while TOPSIS provides an intuitive and objective ranking basis by calculating the relative closeness between the evaluated scheme and the ideal scheme. In particular, compared to other multi-attribute decision-making methods (such as fuzzy comprehensive evaluation or grey relational analysis), the TOPSIS method has unique advantages in its intuitive principle, simple calculation, and easily interpretable results. It ranks the stopes by calculating the relative closeness (CSI) to the "ideal solution," the physical meaning of which is clear—the higher the CSI value, the closer the geological conditions of the stope are to the ideal state, and the greater its potential for increasing the span. This clear mathematical and physical meaning makes the decision result (such as "the current span should be increased by 30%-50%) not only a ranking, but also a quantitative confidence indicator with clear guiding significance. This greatly facilitates the understanding and application by on-site engineering personnel, ensuring the transparency and feasibility of the decision. The combination of these two aspects can accommodate expert experience while ensuring the mathematical rigor of the decision-making process and the comparability of the results, making it particularly suitable for rapid optimization decisions involving multiple factors and multiple options.

[0035] The technical solution of the present invention is as follows: S1. Establish a multi-factor evaluation index system for optimizing the mining area span.

[0036] Based on the analysis of factors affecting the stability of room-and-pillar mining and referencing mature evaluation systems established in relevant domestic and international research, an evaluation system comprising four core factors was developed: measured range of the loosened zone (L), RMR (Resolution Margin) rock mass quality classification (R), rationality of the existing stope span (S), and geostress environment (σ). This four-factor system eliminates redundant parameters and comprehensively covers all dimensions affecting stope stability from inherent rock mass properties, external mechanical environment, engineering disturbance response to current design state, fully considering the synergistic effects of geological conditions, external forces, engineering effects, and safety margins. Focusing on the core contradictions controlling the stability of room-and-pillar stopes, this system, while ensuring scientific rigor, minimizes the difficulty of data collection and computational complexity, perfectly aligning with the invention's objective of "rapid and targeted optimization."

[0037] Table 1

[0038] 1. Measured range of loosening ring (L) Evaluation index: Measured thickness of the loosened zone of the sidewalls and roof of the roadway or mining area; Quantification methods: ,in, The loosening ring thickness (unit: m) is obtained by on-site measurement using methods such as acoustic wave testing, borehole photography, or multi-point displacement gauge. The reference loosening zone threshold (unit: m) is determined based on the lithology, burial depth, and RMR empirical values ​​of the mining area and can be calculated based on engineering cases or theoretical formulas.

[0039] Quantification approach: This formula quantifies the severity of the actual damage range of the surrounding rock relative to the reference safety threshold. The larger the ratio, the more severe the loosening of the surrounding rock and the worse the stability. The lower.

[0040] 2. RMR Rock Mass Quality Classification (R) Evaluation metric: RMR score; Quantification methods: .

[0041] Quantification Approach: This formula employs linear standardization, mapping the common RMR range (20-80 points) to a scoring interval of 0-1, facilitating subsequent comprehensive calculations. The RMR value considers six core indicators, including rock strength, fracture development, and groundwater influence, and is an internationally recognized comprehensive evaluation system for rock mass quality. The table below shows the specific rules for determining the RMR value.

[0042] Table 2 (a) Classification parameters and their indices

[0043] (b) Joint direction index correction R6

[0044] (c) Determine rock mass classification based on overall indicators

[0045] (d) Guiding significance of RMR

[0046] 3. Rationality of the existing mining area dimensions (S) Evaluation index: The ratio of the current mine span to the theoretical critical span calculated based on Barton's empirical formula. This formula is based on the rock mass quality Q system theory proposed by Barton et al., and is a classic empirical formula that has been verified by a large number of engineering practices and is applicable to estimating the stable span of underground caverns.

[0047] Quantification methods: .

[0048] Quantification Approach: This ratio directly quantifies the safety margin of the current span. The formula is based on a simplified empirical relationship of the Hoek-Brown strength criterion, where... For the theoretical critical span, For the current mining area span, , The calculation is based on the rock mass proposed by Barton et al. Q Systems theory; For support ratio.

[0049] 4. Geostress Environment ( ) Evaluation index: stress-intensity ratio; Quantification methods: ,in (Vertical stress) (Rock mass strength).

[0050] Quantitative Approach: This formula quantifies the relative relationship between the load on the rock mass and its strength. When / When ≥1, score σ A value of 1 indicates that the rock mass is already in its ultimate bearing capacity state, and the span should not be increased.

[0051] S2. Collect basic data from the mining area and perform quantitative scoring. For the target mining area, the following data collection and quantification work was carried out: Methods such as acoustic testing or borehole photography are used to detect the thickness of the loosened zone in the surrounding area of ​​the roadway or mining area. Calculate the loosening zone range score .

[0052] RMR values ​​were obtained through borehole logging and field surveys, and then standardized. .

[0053] The span of the existing mine stop is measured, and the theoretical span is calculated using the theoretical formula applicable to metal mines mentioned above, thus obtaining a rationality score for the current mine stop span.

[0054] Based on the mining depth and rock mass strength parameters, the geostress environmental impact score is calculated. .

[0055] S3, Weight Allocation System The judgment matrix is ​​assigned values ​​based on the AHP 1-9 scale, primarily stemming from an in-depth analysis of the mechanical principles of the room-column method system and consensus reached in engineering practice. The table below details the basis for assigning values ​​to each pair of factor comparisons in the judgment matrix. These bases integrate industry standards, general understanding supported by relevant research, and the unique mechanical mechanisms of the room-column method system.

[0056] Table 3

[0057] Based on the above, the judgment matrix is ​​constructed as follows:

[0058] The weight coefficients are calculated from the judgment matrix and then normalized to obtain the final weights of each factor: =0.35 (multi-factor coupling analysis method), =0.35, =0.12, =0.18.

[0059] Quantitative Approach: The measured range of the loosened zone serves as a comprehensive response index characterizing the immediate stability state of the surrounding rock after excavation. Together with the RMR (Rock Mass Quality Rating), the most crucial long-term stability control factor, it forms the two core foundations of stability assessment. The geostress environment, as the primary external load, is of secondary importance. The rationality of the existing stope span, as an optimizable design parameter, has the lowest relative weight. This weighting system is a preferred embodiment; those skilled in the art can construct and fine-tune the judgment matrix based on the AHP (Advanced Hierarchical Method) method according to the specific characteristics of the mining area.

[0060] The consistency ratio (CR) of the judgment matrix was verified to be 0.005, which is much less than 0.1. The consistency test was passed, proving that the weight allocation is reasonable and reliable.

[0061] S4. Calculate the overall closeness using the TOPSIS method. Closeness calculation based on weighted normalization matrix: Construct a weighted decision matrix:

[0062] Determine the positive and negative ideal solutions: ,

[0063] Calculate the distance D from each solution to the positive and negative ideal solutions. + and D - :

[0064]

[0065] Calculate the overall similarity:

[0066] S5. Optimize decision-making based on proximity value output parameters Through retrospective verification of several known stable stope cases using the room-and-pillar method, it is determined that the following CSI decision thresholds have the best discrimination and engineering safety, and specific parameter adjustment suggestions based on the CSI value are provided: CSI>0.7: Stope span increases by 30%-50%; 0.6<CSI≤0.7: Stope span increases by 10%-30%; 0.4≤CSI≤0.6: Maintain the existing stope parameters; 0.3≤CSI<0.4: Stope span decreases by 10%-30%; CSI<0.3: Stope span decreases by 30%-50%.

[0067] As a preferred embodiment, this adjustment suggestion can be independently judged and finely adjusted by those skilled in the art according to the characteristics of the specific mining area based on the AHP method.

[0068] Embodiment 2: A rapid targeted optimization method for the span of ore rooms in room-and-pillar method stopes based on the AHP-TOPSIS model, which is basically as Figure 1 shown, includes the following steps: S1. Establish a multi-factor evaluation index system for optimizing the span of ore rooms in room-and-pillar method stopes Based on the analysis of factors affecting the stability of room-and-pillar mining stopes, an evaluation system including four core factors is established: the measured range of the loose zone, the RMR rock mass quality classification, the rationality of the current ore room span, and the in-situ stress environment.

[0069] S2. Collect basic stope data and conduct quantitative scoring Taking a stope of a room-and-pillar mining mine as the implementation object, collect basic data and calculate the score of each factor: S2.1. Adopt the borehole acoustic wave testing method, arrange measuring boreholes in the stope roof and two side walls, and obtain the average loose zone thickness through actual measurement = 1.8 m. According to the lithology (sandstone) and average burial depth conditions of this mining area, the reference threshold is determined = 2.5 m.

[0070] Loose zone range score: = 1-min(1, 1.8 / 2.5) = 0.28 S2.2. Based on borehole logging and on-site investigation, the RMR score of the roof is obtained as 64 points.

[0071] RMR rock mass quality score: = =0.733 S2.3. The ore room span currently used in this part

[0072] Q=27, ESR=3.5 (room-pillar method mining site), calculated as follows 14.8m Rationality rating of current dimensions: =1.48 S2.4. Based on the burial depth and geostress data, the rock mass unit weight γ = 0.027MN / m³ (skarn), the vertical stress σ_v = 0.027 × 400 = 10.8 MPa, the rock mass strength σ_c = 5 × 64 - 50 = 270 MPa, and the geostress environmental impact score is: burial depth of the mining area H = 400 m.

[0073] Geostress Environmental Impact Score: =0.96 S3, Weight Allocation System By calculating the eigenvectors of the judgment matrix and performing normalization, the final weights of each factor are obtained as follows: =0.35, =0.35, =0.12, =0.18.

[0074] The consistency ratio (CR) of the judgment matrix was verified to be 0.005, which is less than 0.1. This passed the consistency test and proved that the weight allocation was reasonable and reliable.

[0075] S4. Calculate the overall closeness using the TOPSIS method. Taking a room-and-pillar method mining operation as an example, the proximity is calculated based on a weighted standardized matrix: First, construct a weighted decision matrix based on the results of S1 and S3:

[0076]

[0077] Next, we calculate the distance D from each scheme to the positive and negative ideal solutions. + and D - :

[0078] =0.40 Finally, calculate the overall similarity:

[0079] S5. Optimize decision-making based on proximity value output parameters Based on CSI=0.20, the optimal solution is output according to the decision rule: CSI < 0.3, falling within the range of "reducing stope span by 30%-50%". Therefore, a specific optimization plan is derived: the current 10m stope span in a room-and-pillar method mine in Tibet can be appropriately reduced, with an increase of 6m to 8m.

[0080] The rapid and targeted optimization method for stope span based on the AHP-TOPSIS model has certain reference value and rationality. It can provide rapid and scientific decision support for stope span optimization under complex geological conditions, and significantly improve the economic benefits of mining while ensuring safety.

[0081] Example 3: An electronic device, comprising a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the method described in Embodiment 1 when executing the computer program.

[0082] Example 4: A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0083] Example 5: A computer program product includes a computer program that, when executed by a processor, implements the method described in Example 1.

[0084] In the above embodiments, the reference to "this embodiment" in the specification indicates that a specific feature, structure, or characteristic described in connection with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple appearances of "this embodiment" do not necessarily refer to the same embodiment.

[0085] In the above embodiments, although the invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed. The embodiments of the invention are intended to cover all such substitutions, modifications, and variations falling within the broad scope of the appended claims.

[0086] As will be understood by those skilled in the art, the computer-readable storage medium described in this embodiment allows for the implementation of all or part of the steps in the above method embodiments by computer program-related hardware. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0087] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication between them. The memory is used to store computer programs, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer programs, so that the electronic terminal performs the steps of the above method.

[0088] In this embodiment, the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0089] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0090] This invention can be used in a wide range of general-purpose or special-purpose computing system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0091] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A rapid optimization method for the span of room-and-column type stopes based on the AHP-TOPSIS model, characterized in that: comprising the following steps: S1: establishing a multi-factor evaluation index system for stope span optimization; S2: collecting basic stope data and performing quantitative scoring; S3: establishing a weight distribution system; S4: performing comprehensive closeness calculation using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) algorithm; S5: outputting a parameter optimization decision based on the closeness value.

2. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 1, characterized in that: In step S1, based on the analysis of factors affecting the stability of room-and-pillar mining, an evaluation system including four core factors is established: the measured range L of the loosening zone, the RMR rock mass quality classification R, the rationality S of the currently used stope span, and the in-situ stress environment σ; The measured range L of the loosening zone is used to quantify the severity of the actual damage range of surrounding rock relative to the reference safety threshold according to the measured thickness of the loosening zone at the side and roof of the roadway or stope; The RMR rock mass quality classification R considers the comprehensive rock mass quality evaluation results of multiple indexes, and integrates multiple geological information into a quantitative score; The rationality S of the currently used stope span is used to quantify the safety margin of the current span; The in-situ stress environment σ is used to quantify the relative relationship between the load on the rock mass and its strength.

3. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 2, characterized in that: The quantification formula for the measured range L of the loosening zone is as follows: in, The thickness of the loose ring is obtained through on-site measurement using methods such as acoustic wave testing, borehole photography, or multi-point displacement gauges. This is a reference loosening zone threshold determined based on the lithology, burial depth, and RMR empirical values ​​of the mining area; This formula quantifies the severity of the actual damage range of the surrounding rock relative to a reference safety threshold; The larger the ratio, the more severe the loosening of the surrounding rock and the worse the stability. The lower.

4. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 2, characterized in that: The quantification formula for the RMR rock mass quality classification R is as follows: The above formula is a linear normalization process, which maps the RMR range to a 0-1 scoring interval to facilitate comprehensive calculation; the RMR value takes into account six indexes including the strength of intact rock material, core quality, joint spacing, joint condition, groundwater influence and joint orientation.

5. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 2, characterized in that: The quantification formula for the rationality S of the currently used stope span is as follows: This formula is based on a simplified empirical relation of the Hoek-Brown strength criterion, where For the theoretical critical span, For the current mining area span, , The calculation is based on the rock mass proposed by Barton et al. Q Systems theory; For support ratio.

6. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 2, characterized in that: The quantification formula for the in-situ stress environment σ is: in For vertical stress, For rock mass strength, when / When ≥1, score σ A value of 1 indicates that the rock mass is already in its ultimate bearing capacity state, and the span should not be increased.

7. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 2, characterized in that: In step S2, the following data collection and quantification work is carried out for the target stope: The thickness of the loosened zone is determined by using acoustic testing or borehole photography to probe around the roadway or mining area. Calculate the loosening zone range score ; RMR values ​​were obtained through borehole logging and field surveys, and then standardized. ; The span of the existing stope is measured, and the theoretical span is calculated using theoretical formulas applicable to the room-and-pillar method to obtain a rationality score for the current stope span. ; Based on the mining depth and rock mass strength parameters, the geostress environmental impact score is calculated. .

8. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 7, characterized in that: In step S3, the assignment of the judgment matrix is based on the 1-9 scale method of Analytic Hierarchy Process (AHP), and the judgment matrix is as follows: The weight coefficients are calculated from the judgment matrix and normalized to obtain the final weight of each factor; As a comprehensive response index characterizing the immediate stability state of the surrounding rock after excavation, the measured range of the loosening zone and the RMR rock mass quality classification together constitute the two most critical foundations for stability evaluation; the in-situ stress environment, as the main external load, is of secondary importance; the rationality of the currently used stope span, as an optimizable design parameter, has the lowest weight.

9. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 8, characterized in that: In step S4, the closeness is calculated based on the weighted normalized matrix: Construct a weighted decision matrix: Determine the positive and negative ideal solutions: , Calculate the distance D from each solution to the positive and negative ideal solutions. + and D - : Calculate the overall similarity: .

10. The method for rapid optimization of the span of a room-column type mining area based on the AHP-TOPSIS model according to claim 9, characterized in that: In step S5, through retrospective verification of several room-and-pillar stope cases with known stable states, it is determined that the following CSI decision threshold has the best discrimination and engineering safety, and specific parameter adjustment suggestions based on the CSI value are provided: CSI>0.7: increase the stope span by 30%-50%; 0.6<CSI≤0.7: increase the stope span by 10%-30%; 0.4≤CSI≤0.6: keep the existing stope parameters; 0.3≤CSI<0.4: reduce the stope span by 10%-30%; CSI<0.3: reduce the stope span by 30%-50%.

11. An electronic device, characterized in that, comprising a memory and a processor; the memory is configured to store a computer program; The processor is configured to, when executing the computer program, implement the rapid optimization method for room-column type mining area span based on the AHP-TOPSIS model as described in any one of claims 1-10.

12. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the rapid optimization method for room-column type mining area span based on the AHP-TOPSIS model as described in any one of claims 1-10.

13. A computer program product, characterized in that: The invention includes a computer program that, when executed by a processor, implements the rapid optimization method for room-column type mining area span based on the AHP-TOPSIS model as described in any one of claims 1-10.

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