Coal pillar dam body stability evaluation method, electronic equipment, storage medium and computer program product

Abstract

The invention discloses a coal pillar dam body stability evaluation method, electronic equipment, a storage medium and a computer program product. The method comprises the steps that a fuzzy relation evaluation matrix of a coal pillar dam body established through an expert scoring method is acquired, a membership function matrix of the fuzzy relation evaluation matrix is calculated, and the fuzzy relation evaluation matrix comprises evaluation scores of stability categories of evaluation indexes; calculating a comprehensive weight of each evaluation index, and performing weighted calculation on the membership matrix based on the comprehensive weights to obtain a weighted matrix; setting an ideal point according to the weighting matrix, calculating the closeness between the stability category and the ideal point, and judging the stability of the coal pillar dam body according to the closeness. According to the method, the influence of various factors is comprehensively considered, and the authenticity and reliability of the evaluation result are relatively high. According to the method, the stability of the coal pillar dam body is effectively and accurately evaluated, the simplification of complex problems is realized, the practicability is good, and a certain basis and reference are provided for the reinforcing and supporting design of the coal pillar dam body and the like.

Description

Technical Field

[0001] This invention relates to the field of coal-related technologies, and in particular to a method for evaluating the stability of coal pillar dams, electronic equipment, storage media, and computer program products. Background Technology

[0002] The stability of coal pillar dams provides a basis and reference for the design of their reinforcement and support. Existing technologies have proposed methods for detecting coal pillar dams, using sensors to monitor and determine dam stability. For example, Chinese patent document CN201310195414.X proposes a displacement monitoring method for determining dam stability. This method monitors the entire dam body and uses statistical methods to evaluate overall dam stability and provide early warnings of instability risks. This method can provide graded early warnings of dam instability, providing a basis for dam protection and management. Another monitoring method, such as Chinese patent document CN201610554076.8, proposes a device and method for testing the stability of a simulated goaf reservoir dam. This method uses stress sensors and water pressure sensors to monitor the stress and water pressure changes in the goaf reservoir dam body, and calculates the dam body's stability under the weight of the overlying rock and dynamic and static water pressure, providing a monitoring method for the stability of coal pillar dams.

[0003] However, existing methods for monitoring the stability of coal pillar dams generally only determine whether the dam is unstable from the perspective of displacement, without comprehensively considering the influence of multiple factors on dam stability. For example, the displacement monitoring method for judging dam stability disclosed in Chinese patent document CN201310195414.X has a certain impact on the evaluation results due to the selection of the monitoring line position. For large dams, the layout of the monitoring line is difficult and has poor operability. At the same time, dam instability is the result of the combined effect of multiple factors, and judging dam instability solely from the perspective of displacement is somewhat one-sided, resulting in low accuracy of the evaluation results. Furthermore, the stability testing device and method for a simulated goaf reservoir dam disclosed in Chinese patent document CN201610554076.8 does not provide classification and grading standards for the stability of coal pillar dams, nor does it provide specific calculation methods. Moreover, this method does not consider the influence of surrounding rock lithology, reservoir water quality, and mining disturbance on the coal pillar dam, and the testing device cannot take these factors into account. Therefore, the evaluation criteria are not comprehensive enough, and the evaluation results are not accurate enough. Summary of the Invention

[0004] Therefore, it is necessary to address the technical problems of insufficient comprehensiveness and inaccuracy of existing dam stability evaluation standards by providing a method, electronic equipment, storage medium, and computer program product for evaluating the stability of coal pillar dams.

[0005] This invention provides a method for evaluating the stability of coal pillar dams, comprising:

[0006] Obtain the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method, and calculate the membership function matrix of the fuzzy relation evaluation matrix. The fuzzy relation evaluation matrix includes the evaluation score of each stability category of each evaluation index.

[0007] Calculate the comprehensive weight of each evaluation indicator, and perform a weighted calculation on the membership matrix based on the comprehensive weight to obtain a weighted matrix;

[0008] Ideal points are set according to the weighted matrix, the closeness between the stability category and the ideal points is calculated, and the stability of the coal pillar dam is judged based on the closeness.

[0009] Further, the step of obtaining the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method, and calculating the membership function matrix of the fuzzy relation evaluation matrix, includes:

[0010] Obtain the fuzzy relation evaluation matrix established by the expert scoring method, wherein the fuzzy relation evaluation matrix is: Where A is the fuzzy relation evaluation matrix, a ij The evaluation score for the j-th stability category of the i-th evaluation indicator;

[0011] The membership function matrix of the fuzzy relation evaluation matrix is ​​calculated as follows: Among them, s ij Let be the membership degree of the j-th stability category of the i-th evaluation index, and Where max(a) j ) represents the maximum value of the j-th stability category among all evaluation indicators, min(a j ) is the minimum value of the j-th stability category among all evaluation indicators.

[0012] Furthermore, the calculation of the comprehensive weight of each evaluation indicator includes:

[0013] The fuzzy entropy of the i-th evaluation index is calculated as follows: Among them, D i Let be the fuzzy entropy of the i-th evaluation index, k be a preset constant, R be the number of stability categories, and s be the fuzzy entropy of the i-th evaluation index. ij Let be the membership degree of the j-th stability category of the i-th evaluation index;

[0014] The entropy weight of the i-th evaluation index is calculated as follows: in, Let Q be the entropy weight of the i-th evaluation indicator, and Q be the number of evaluation indicators.

[0015] The comprehensive weight of the i-th evaluation indicator is calculated as follows: Where, d i Let be the comprehensive weight of the i-th evaluation indicator, and wi be the weight of the i-th evaluation indicator.

[0016] Further, the step of performing a weighted calculation on the membership matrix based on the comprehensive weights to obtain a weighted matrix includes:

[0017] The weighting matrix is ​​calculated as follows: Where M is the weighting matrix, d i Let s be the comprehensive weight of the i-th evaluation indicator. ij Let m be the membership degree of the j-th stability category of the i-th evaluation index. ij is the weighted membership degree of the j-th stability category of the i-th evaluation index.

[0018] Further, setting the ideal point according to the weighting matrix includes:

[0019] Calculate the ideal point n of the i-th evaluation index i The maximum value among all stability categories of the i-th evaluation index;

[0020] Establish the ideal point vector as: N = (n1, n2, ..., n i ,...,n Q ) T , where N is the ideal point vector and Q is the number of evaluation indicators.

[0021] Furthermore, the degree of closeness between the calculated stability category and the ideal point includes:

[0022] Calculate the closeness of the stability category of the j-th item as follows: Where, P j For the closeness of the j-th stability category, a ij Let be the evaluation score for the j-th stability category of the i-th evaluation indicator.

[0023] Furthermore, the step of determining the stability of the coal pillar dam based on the proximity includes:

[0024] If there is only one stability category with the lowest proximity, then the stability of the coal pillar dam is determined to be the stability category with the lowest proximity.

[0025] If there is more than one stability category with the smallest proximity, the distance from the stability category to the ideal point is calculated, and the stability of the coal pillar dam is determined to be the stability category with the smallest distance.

[0026] This invention provides an electronic device, comprising:

[0027] At least one processor; and,

[0028] A memory communicatively connected to at least one of the processors; wherein,

[0029] The memory stores instructions that can be executed by at least one of the processors to enable at least one of the processors to perform the coal pillar dam stability evaluation method as described above.

[0030] The present invention provides a storage medium that stores computer instructions, which, when executed by a computer, are used to perform all the steps of the coal pillar dam stability evaluation method as described above.

[0031] This invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the coal pillar dam stability evaluation method as described above.

[0032] This invention establishes a fuzzy relation evaluation matrix for coal pillar dams using an expert scoring method. It obtains evaluation scores for multiple stability categories across various evaluation indicators, calculates the membership function matrix, and uses the entropy weight method to calculate a comprehensive weight. The membership matrix is ​​then weighted to obtain a weighted matrix. Ideal points are set based on this weighted matrix, and the closeness between the evaluated object and the ideal point is calculated to determine the stability of the coal pillar dam. This invention comprehensively considers the influence of multiple factors and selects multi-level evaluation indicators, resulting in high authenticity and reliability of the evaluation results. Based on the fundamental principles of the entropy weight method and ideal points, this invention effectively and accurately evaluates the stability of coal pillar dams, simplifying complex problems and effectively avoiding the fuzziness and complexity of previous evaluation methods. It has good practicality, with simple and clear calculation results and high evaluation accuracy, providing a basis and reference for the design of coal pillar dam reinforcement and support. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the process of a method for evaluating the stability of a coal pillar dam according to an embodiment of the present invention.

[0034] Figure 2 This is a flowchart illustrating the process of a method for evaluating the stability of a coal pillar dam, according to another embodiment of the present invention.

[0035] Figure 3 A schematic diagram of an evaluation index system for a coal pillar dam in a concentrated brine reservoir, representing the preferred embodiment of the present invention;

[0036] Figure 4 A flowchart illustrating the workflow of a method for evaluating the stability of a coal pillar dam in a concentrated brine reservoir, representing the preferred embodiment of the present invention.

[0037] Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to the present invention. Detailed Implementation

[0038] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. Identical components are indicated by the same reference numerals. It should be noted that the terms "front," "rear," "left," "right," "up," and "down" used in the following description refer to directions in the accompanying drawings, while the terms "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0039] like Figure 1 The diagram shown is a flowchart of a method for evaluating the stability of a coal pillar dam according to an embodiment of the present invention, including:

[0040] Step S101: Obtain the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method, and calculate the membership function matrix of the fuzzy relation evaluation matrix. The fuzzy relation evaluation matrix includes the evaluation score of each stability category of each evaluation index.

[0041] Step S102: Calculate the comprehensive weight of each evaluation indicator, and perform a weighted calculation on the membership matrix based on the comprehensive weight to obtain a weighted matrix;

[0042] Step S103: Set ideal points according to the weighted matrix, calculate the closeness between the stability category and the ideal points, and determine the stability of the coal pillar dam body based on the closeness.

[0043] Specifically, the present invention can be applied to electronic devices with processing capabilities, such as computers.

[0044] The present invention preferably evaluates the stability of the coal pillar dam body of a concentrated brine reservoir.

[0045] First, step S101 is executed to obtain the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method, and to calculate the membership function matrix of the fuzzy relation evaluation matrix. The fuzzy relation evaluation matrix includes the evaluation score of each stability category of each evaluation index.

[0046] Specifically, taking into account the influence of factors such as actual geological conditions, dam structure dimensions, and concentrated brine concentration in the reservoir, evaluation indicators were selected, an evaluation indicator system was established, and the stability of coal pillar dams in concentrated brine reservoirs was classified.

[0047] Among them, such as Figure 3The diagram illustrates a preferred embodiment of the present invention's evaluation index system for a coal pillar dam in a concentrated brine reservoir. Taking into account the influence of actual geological conditions, dam structural dimensions, and reservoir water quality, the system selects stress environment, surrounding rock lithology, mining disturbance, reservoir water quality, and dam dimensions as criterion layers. Specifically, in-situ stress (burial depth) and reservoir water pressure are criterion layers under stress environment; uniaxial compressive strength and surrounding rock integrity coefficient are criterion layers under surrounding rock lithology; mining speed and mining height are criterion layers under mining disturbance; brine concentration and suspended solids concentration are criterion layers under reservoir water quality; and dam length, width, and dip angle are criterion layers under dam dimensions. Figure 3 As shown, there are 11 evaluation indicators from left to right, and they are defined as evaluation indicators numbered 1, 2, ..., 11. Meanwhile, the stability of the coal pillar dam body in the concentrated brine reservoir is divided into five categories: very stable, stable, moderately stable, unstable, and extremely unstable.

[0048] Then, several industry experts scored the various evaluation indicators of the stability of the coal pillar dam of the concentrated brine reservoir on-site, constructed a fuzzy relation evaluation matrix, and calculated the membership function matrix.

[0049] Then, step S102 is executed to calculate the comprehensive weight of each evaluation index, and the membership matrix is ​​weighted based on the comprehensive weight to obtain a weighted matrix.

[0050] Specifically, the comprehensive weights are calculated using the entropy weight method, and the membership matrix is ​​weighted to obtain the weighted matrix.

[0051] Finally, step S103 is executed, an ideal point is set according to the weighted matrix, the closeness between the stability category and the ideal point is calculated, and the stability of the coal pillar dam is judged based on the closeness.

[0052] Specifically, ideal points are set according to the weighted matrix, and the degree of closeness between the evaluation object and the ideal points is calculated to determine the stability of the coal pillar dam body of the concentrated brine reservoir.

[0053] This invention establishes a fuzzy relation evaluation matrix for coal pillar dams using an expert scoring method. It obtains evaluation scores for multiple stability categories across various evaluation indicators, calculates the membership function matrix, and uses the entropy weight method to calculate a comprehensive weight. The membership matrix is ​​then weighted to obtain a weighted matrix. Ideal points are set based on this weighted matrix, and the closeness between the evaluated object and the ideal point is calculated to determine the stability of the coal pillar dam. This invention comprehensively considers the influence of multiple factors and selects multi-level evaluation indicators, resulting in high authenticity and reliability of the evaluation results. Based on the fundamental principles of the entropy weight method and ideal points, this invention effectively and accurately evaluates the stability of coal pillar dams, simplifying complex problems and effectively avoiding the fuzziness and complexity of previous evaluation methods. It has good practicality, with simple and clear calculation results and high evaluation accuracy, providing a basis and reference for the design of coal pillar dam reinforcement and support.

[0054] like Figure 2 The diagram shown is a flowchart of a method for evaluating the stability of a coal pillar dam according to another embodiment of the present invention, including:

[0055] Step S201: Obtain the fuzzy relation evaluation matrix established by the expert scoring method, wherein the fuzzy relation evaluation matrix is... Where A is the fuzzy relation evaluation matrix, a ij The evaluation score for the j-th stability category of the i-th evaluation indicator;

[0056] Step S202, calculate the membership function matrix of the fuzzy relation evaluation matrix as follows: Among them, s ij Let be the membership degree of the j-th stability category of the i-th evaluation index, and Where max(a) j ) represents the maximum value of the j-th stability category among all evaluation indicators, min(a j ) is the minimum value of the j-th stability category among all evaluation indicators;

[0057] Step S203, calculate the fuzzy entropy of the i-th evaluation index as follows: Among them, D i Let be the fuzzy entropy of the i-th evaluation index, k be a preset constant, R be the number of stability categories, and s be the fuzzy entropy of the i-th evaluation index. ij Let be the membership degree of the j-th stability category of the i-th evaluation index;

[0058] Step S204, calculate the entropy weight of the i-th evaluation index as follows: in, Let Q be the entropy weight of the i-th evaluation indicator, and Q be the number of evaluation indicators.

[0059] Step S205, calculate the comprehensive weight of the i-th evaluation index as follows: Where, d i w is the comprehensive weight of the i-th evaluation indicator. i Let be the weight of the i-th evaluation indicator;

[0060] Step S206, calculate the weighting matrix as follows: Where M is the weighting matrix, d i Let s be the comprehensive weight of the i-th evaluation indicator. ij Let m be the membership degree of the j-th stability category of the i-th evaluation index. ij The weighted membership degree of the j-th stability category of the i-th evaluation index;

[0061] Step S207: Calculate the ideal point n of the i-th evaluation index. i The maximum value among all stability categories of the i-th evaluation index;

[0062] Step S208, establish the ideal point vector as: N = (n1, n2, ..., n i ,...,n Q ) T Where N is the ideal point vector, and Q is the number of evaluation indicators;

[0063] Step S209, calculate the proximity of the j-th stability category as follows: Where, P j For the closeness of the j-th stability category, a ij The evaluation score for the j-th stability category of the i-th evaluation indicator;

[0064] Step S210: If there is only one stability category with the smallest proximity, then the stability of the coal pillar dam is determined to be the stability category with the smallest proximity.

[0065] Step S211: If there is more than one stability category with the smallest proximity, calculate the distance from the stability category to the ideal point and determine the stability of the coal pillar dam body as the stability category with the smallest distance.

[0066] Specifically, step S201 is executed first, where multiple industry experts score the various evaluation indicators of the coal pillar dam's stability on-site, constructing a fuzzy relation evaluation matrix A:

[0067] Where A is the fuzzy relation evaluation matrix, a ij The evaluation score for the j-th stability category of the i-th evaluation indicator.

[0068] Then, step S202 is executed to calculate the membership function of each evaluation index and transform the fuzzy relation evaluation matrix A into the membership function matrix S:

[0069] Among them, s ij Let be the membership degree of the j-th stability category of the i-th evaluation index, and Where max(a) j ) represents the maximum value of the j-th stability category among all evaluation indicators, min(a j ) is the minimum value of the j-th stability category among all evaluation indicators.

[0070] Then, step S203 is executed. Combining the calculation method of entropy weight, when there are i evaluation indicators and j coal pillar dam stability categories, the fuzzy entropy D of the i-th evaluation indicator is... i for: Among them, D i Let be the fuzzy entropy of the i-th evaluation index, k be a preset constant, R be the number of stability categories, and s be the fuzzy entropy of the i-th evaluation index. ij Let k be the membership degree of the j-th stability category of the i-th evaluation index, and k is preferably -0.29.

[0071] Then, step S204 is executed to calculate the entropy weight of the i-th evaluation index: in, Let be the entropy weight of the i-th evaluation indicator, and Q be the number of evaluation indicators.

[0072] Considering that for coal pillar dams with different stability levels, similar scores for a certain indicator might lead to inaccurate stability classification, an indicator weight is introduced to adjust the entropy weight. Step S205 is executed to calculate the comprehensive weight of the i-th evaluation indicator: Where, d i w is the comprehensive weight of the i-th evaluation indicator. i w represents the weight of the i-th evaluation indicator. i The value can be calculated using the 1-9 scale method.

[0073] Then, step S206 is executed, using the comprehensive weights of the evaluation indicators to perform a weighted calculation on the membership function matrix S, resulting in the weighted matrix M:

[0074] Where M is the weighting matrix, d i Let s be the comprehensive weight of the i-th evaluation indicator. ij Let m be the membership degree of the j-th stability category of the i-th evaluation index. ij is the weighted membership degree of the j-th stability category of the i-th evaluation index.

[0075] Then, step S207 is executed to calculate the ideal point of the i-th evaluation index as the maximum value among all stability categories of the i-th evaluation index.

[0076] Specifically, calculate the ideal point of the i-th evaluation index. That is, the value with the highest stability type among the same evaluation index is selected as the ideal point of that evaluation index, where n i Let R be the ideal point of the i-th evaluation index, R be the number of stability categories, and Q be the number of evaluation indexes.

[0077] Then, execute step S208 to establish the ideal point vector as: N = (n1, n2, ..., nn2) i ,...,n Q ) T , where N is the ideal point vector and Q is the number of evaluation indicators.

[0078] Then, step S209 is executed, which calculates the closeness P between various evaluation indicators of the coal pillar dam body and the ideal point. j To determine the stability of the coal pillar dam body in a concentrated brine reservoir, P j The expression is: Right now Where, P j For the closeness of the j-th stability category, a ij Let be the evaluation score for the j-th stability category of the i-th evaluation indicator.

[0079] The evaluation index of the j-th stability category of the coal pillar dam body Substitute into the above formula and calculate all P respectively. j The size of P. j The smaller the value, the more the stability category of the coal pillar dam body leans towards category j.

[0080] Therefore, if there is only one stability category with the lowest proximity, proceed to step S210 to determine that the stability of the coal pillar dam is the stability category with the lowest proximity.

[0081] When multiple proximity values ​​Pj are equal and all are the minimum proximity values, the distance L from the stability category to the ideal point can be calculated. j Further assessment is needed. j The smaller the value, the more the stability category of the coal pillar dam body is biased towards category j. Therefore, if there is more than one stability category with the smallest proximity, step S211 is executed to calculate the distance from the stability category to the ideal point, and the stability of the coal pillar dam body is determined to be the stability category with the smallest distance.

[0082] Among them, L j The expression is: Where L j Let be the distance from the j-th stability category to the ideal point.

[0083] This embodiment comprehensively considers the influence of factors such as actual geological conditions, dam structure dimensions, and reservoir water quality, and selects representative multi-level evaluation indicators. The selected indicators are representative, comprehensive, complete, and operable, resulting in high authenticity and reliability of the evaluation results. This embodiment comprehensively considers the influence of factors such as actual geological conditions, dam structure dimensions, and concentrated brine concentration in the reservoir, selects evaluation indicators, and establishes an evaluation indicator system; classifies the stability of coal pillar dams; establishes a fuzzy relation evaluation matrix using expert scoring, and calculates the membership function matrix; calculates the comprehensive weight using the entropy weight method, and performs weighted calculations on the membership matrix to obtain a weighted matrix; sets ideal points based on the weighted matrix, and calculates the closeness between the evaluation object and the ideal points, thereby judging the stability of the coal pillar dam. The coal pillar dam stability evaluation method of this invention is highly practical and operable, with high accuracy in evaluation results, and can provide a certain basis and reference for the design of coal pillar dam reinforcement and support.

[0084] like Figure 4 The diagram shown is a flowchart of a method for evaluating the stability of a coal pillar dam in a concentrated brine reservoir, according to the preferred embodiment of the present invention. The method includes:

[0085] Step S401: Taking into account the influence of factors such as actual geological conditions, dam structure dimensions and concentrated brine concentration in the reservoir, select evaluation indicators and establish an evaluation indicator system.

[0086] Step S402: Classify the stability of the coal pillar dam body of the concentrated brine reservoir;

[0087] Step S403: Establish a fuzzy relation evaluation matrix using the expert scoring method and calculate the membership function matrix;

[0088] Step S404: Calculate the comprehensive weights using the entropy weight method, and perform weighted calculations on the membership matrix to obtain the weighted matrix;

[0089] Step S405: Set ideal points according to the weighted matrix, calculate the closeness between the evaluation object and the ideal points, and thus determine the stability of the coal pillar dam body of the concentrated brine reservoir.

[0090] Preferably, step S401 specifically includes:

[0091] Taking into account the influence of actual geological conditions, dam structure dimensions, and reservoir water quality, stress environment, surrounding rock lithology, mining disturbance, reservoir water quality, and dam dimensions were selected as the criterion layers. Among them, in-situ stress (burial depth) and reservoir water pressure are the index layers under stress environment; uniaxial compressive strength and surrounding rock integrity coefficient are the index layers under surrounding rock lithology; mining speed and mining height are the index layers under mining disturbance; brine concentration and suspended solids concentration are the index layers under reservoir water quality; and dam length, width, and dip angle are the index layers under dam dimensions.

[0092] Preferably, step S402 specifically includes:

[0093] The stability of coal pillar dams in concentrated brine reservoirs is classified into five categories: very stable, stable, moderately stable, unstable, and extremely unstable.

[0094] Preferably, step S403 specifically comprises:

[0095] Ten industry experts conducted on-site scoring of various evaluation indicators of the stability of the coal pillar dam of the concentrated brine reservoir, and constructed a fuzzy relation evaluation matrix A, as shown in Equation (Ⅰ).

[0096]

[0097] Where aij represents the evaluation score of the i-th evaluation index of the j-th type of stability of the coal pillar dam body (i = 1, 2, ..., 11; j = 1, ..., 5).

[0098] Calculate the membership function of each evaluation index and transform the fuzzy relation evaluation matrix A into the membership function matrix S, as shown in Equation (II).

[0099]

[0100] Where sij represents the membership function of the evaluation index. The calculation method is shown in equation (Ⅲ).

[0101]

[0102] Preferably, step 4 specifically includes:

[0103] Combining the calculation method of entropy weight, when there are i evaluation indicators and j stability categories of the coal pillar dam body in the concentrated brine reservoir, the fuzzy entropy D of the i-th evaluation indicator is... i As shown in equation (Ⅳ).

[0104]

[0105] Therefore, the entropy weight of the i-th evaluation index is shown in equation (V).

[0106]

[0107] Considering that for coal pillar dams with different stability levels, similar scores for a certain indicator may lead to inaccurate stability classification, an indicator weight is introduced to adjust the entropy weight, as shown in equation (VI).

[0108]

[0109] Where, d i w is the comprehensive weight of the i-th evaluation indicator.i Let be the weight of the i-th evaluation index. Its value can be calculated using the 1-9 scale method, which will not be elaborated here.

[0110] Using the comprehensive weight d of the evaluation indicators i The membership function matrix S is weighted to obtain the weighted matrix M, as shown in equation (Ⅶ).

[0111]

[0112] Preferably, step 5 specifically comprises:

[0113] The ideal point is set according to the weighting matrix, that is, a set of optimal index data is selected as the ideal point in this method. The expression of the ideal point N is shown in equation (VIII).

[0114] N = (n1, n2, ..., nn) i ,…,n 11 ) T (VIII)

[0115] in,

[0116] By calculating the closeness P between various evaluation indicators of the coal pillar dam body and the ideal point, j To determine the stability of the coal pillar dam body in a concentrated brine reservoir, P j The expression is shown in equation (IX).

[0117]

[0118] Stability evaluation indicators for coal pillar dams in concentrated brine reservoirs Substitute into equation (IX) and calculate the values ​​of P1, P2, ..., P5 respectively. When P j The smaller the value, the more the stability category of the coal pillar dam in the concentrated brine reservoir leans towards category j. Specifically, when P... j When the values ​​are equal, the distance L from the stability category to the ideal point can be calculated. j Further assessment is needed. j The smaller the value, the more the stability category of the coal pillar dam in the concentrated brine reservoir leans towards category j. j The expression is shown in equation (X).

[0119]

[0120] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0121] like Figure 5The diagram shown is a hardware structure schematic of an electronic device according to the present invention, comprising:

[0122] At least one processor 501; and,

[0123] A memory 502 is communicatively connected to at least one of the processors 501; wherein,

[0124] The memory 502 stores instructions that can be executed by at least one of the processors to enable the at least one of the processors to perform the coal pillar dam stability evaluation method as described above.

[0125] Figure 5 Take a processor 501 as an example.

[0126] The electronic device may also include an input device 503 and a display device 504.

[0127] The processor 501, memory 502, input device 503 and display device 504 can be connected by a bus or other means. The figure shows an example of connection by bus.

[0128] The memory 502, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the coal pillar dam stability evaluation method in the embodiments of this application, for example, Figure 1 , Figure 2 The method flow is shown. The processor 501 executes various functional applications and data processing by running non-volatile software programs, instructions, and modules stored in the memory 502, thereby realizing the coal pillar dam stability evaluation method in the above embodiment.

[0129] The memory 502 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the coal pillar dam stability evaluation method. Furthermore, the memory 502 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 502 may optionally include memory remotely located relative to the processor 501, and these remote memories may be connected via a network to the apparatus performing the coal pillar dam stability evaluation method. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0130] The input device 503 can receive user clicks and generate signal inputs related to user settings and function control for the coal pillar dam stability evaluation method. The display device 504 may include display screens or other display devices.

[0131] When one or more modules are stored in the memory 502, and are run by one or more processors 501, the coal pillar dam stability evaluation method in any of the above method embodiments is executed.

[0132] This invention establishes a fuzzy relation evaluation matrix for coal pillar dams using an expert scoring method. It obtains evaluation scores for multiple stability categories across various evaluation indicators, calculates a membership function matrix, and uses the entropy weight method to calculate a comprehensive weight. The membership matrix is ​​then weighted to obtain a weighted matrix. Ideal points are set based on this weighted matrix, and the closeness between the evaluated object and the ideal point is calculated to determine the stability of the coal pillar dam. This invention comprehensively considers the influence of multiple factors and selects multi-level evaluation indicators, resulting in high authenticity and reliability of the evaluation results. Based on the fundamental principles of the entropy weight method and ideal points, this invention effectively and accurately evaluates the stability of coal pillar dams, simplifying complex problems and effectively avoiding the fuzziness and complexity of previous evaluation methods. It has good practicality, with simple and clear calculation results and high evaluation accuracy, providing a basis and reference for the design of coal pillar dam reinforcement and support.

[0133] One embodiment of the present invention provides a storage medium that stores computer instructions, which, when executed by a computer, are used to perform all the steps of the coal pillar dam stability evaluation method as described above.

[0134] In the context of this disclosure, a storage medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. The storage medium can be a machine-readable signal medium or a machine-readable storage medium. Optionally, the storage medium can be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), compact disc ROM (CD-ROM), magnetic tape, floppy disk, and optical data storage device.

[0135] One embodiment of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the coal pillar dam stability evaluation method as described above.

[0136] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for evaluating the stability of a coal pillar dam, characterized in that, include: Obtain the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method, and calculate the membership function matrix of the fuzzy relation evaluation matrix. The fuzzy relation evaluation matrix includes the evaluation score of each stability category of each evaluation index. Calculate the comprehensive weight of each evaluation indicator, and perform a weighted calculation on the membership matrix based on the comprehensive weight to obtain a weighted matrix; Ideal points are set according to the weighted matrix, the closeness between the stability category and the ideal points is calculated, and the stability of the coal pillar dam is judged based on the closeness.

2. The method for evaluating the stability of coal pillar dams according to claim 1, characterized in that, The process of obtaining the fuzzy relation evaluation matrix of the coal pillar dam body established by the expert scoring method and calculating the membership function matrix of the fuzzy relation evaluation matrix includes: Obtain the fuzzy relation evaluation matrix established by the expert scoring method, wherein the fuzzy relation evaluation matrix is: Where A is the fuzzy relation evaluation matrix, a ij The evaluation score for the j-th stability category of the i-th evaluation indicator; The membership function matrix of the fuzzy relation evaluation matrix is ​​calculated as follows: Among them, s ij Let be the membership degree of the j-th stability category of the i-th evaluation index, and Where max(a) j ) represents the maximum value of the j-th stability category among all evaluation indicators, min(a j ) is the minimum value of the j-th stability category among all evaluation indicators.

3. The method for evaluating the stability of coal pillar dams according to claim 1, characterized in that, The calculation of the comprehensive weight for each evaluation indicator includes: The fuzzy entropy of the i-th evaluation index is calculated as follows: Among them, D i Let be the fuzzy entropy of the i-th evaluation index, k be a preset constant, R be the number of stability categories, and s be the fuzzy entropy of the i-th evaluation index. ij Let be the membership degree of the j-th stability category of the i-th evaluation index; The entropy weight of the i-th evaluation index is calculated as follows: in, Let Q be the entropy weight of the i-th evaluation indicator, and Q be the number of evaluation indicators. The comprehensive weight of the i-th evaluation indicator is calculated as follows: Where, d i Let be the comprehensive weight of the i-th evaluation indicator, and wi be the weight of the i-th evaluation indicator.

4. The method for evaluating the stability of coal pillar dams according to claim 1, characterized in that, The step of calculating a weighted matrix by weighting the membership matrix based on the comprehensive weights includes: The weighting matrix is ​​calculated as follows: Where M is the weighting matrix, d i Let s be the comprehensive weight of the i-th evaluation indicator. ij Let m be the membership degree of the j-th stability category of the i-th evaluation index. ij is the weighted membership degree of the j-th stability category of the i-th evaluation index.

5. The method for evaluating the stability of coal pillar dams according to claim 1, characterized in that, Setting the ideal point according to the weighting matrix includes: Calculate the ideal point n of the i-th evaluation index i The maximum value among all stability categories of the i-th evaluation index; Establish the ideal point vector as: N = (n1, n2, ..., n i ,...,n Q ) T , where N is the ideal point vector and Q is the number of evaluation indicators.

6. The method for evaluating the stability of coal pillar dams according to claim 5, characterized in that, The degree of closeness between the calculated stability category and the ideal point includes: Calculate the closeness of the stability category of the j-th item as follows: Where, P j For the closeness of the j-th stability category, a ij Let be the evaluation score for the j-th stability category of the i-th evaluation indicator.

7. The method for evaluating the stability of coal pillar dams according to claim 6, characterized in that, The determination of the stability of the coal pillar dam based on the proximity includes: If there is only one stability category with the lowest proximity, then the stability of the coal pillar dam is determined to be the stability category with the lowest proximity. If there is more than one stability category with the smallest proximity, the distance from the stability category to the ideal point is calculated, and the stability of the coal pillar dam is determined to be the stability category with the smallest distance.

8. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by at least one of the processors to enable at least one of the processors to perform the coal pillar dam stability evaluation method as described in any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium stores computer instructions, which, when executed by the computer, are used to perform all the steps of the coal pillar dam stability evaluation method as described in any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the stability evaluation method for coal pillar dams as described in any one of claims 1 to 7.

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