An underground mine stope blasting mining method based on interval approximation

Abstract

This application relates to the field of mining technology and provides a method for underground mine blasting mining based on interval approximation. This method normalizes and normalizes the interval optimization matrix of deep-hole blasting mining schemes in an established underground mine, obtaining an analysis matrix to calculate the measure value of each evaluation index in each mining scheme; determines the combined weight of each evaluation index in each mining scheme; and calculates the interval approximation comprehensive evaluation value of different mining schemes based on the combined weight and measure value of each evaluation index. This effectively overcomes the problem of existing methods lacking analytical processing capabilities for indicators that are interval numbers, enabling more accurate and realistic analysis and optimization of mine blasting schemes, ensuring the comprehensiveness and accuracy of index weights, and making the optimization of deep-hole blasting mining schemes in underground mines more accurate and reliable.

Description

Technical Field

[0001] This application relates to the field of mining technology, and in particular to a method for blasting mining in underground mines based on interval approximation. Background Technology

[0002] Blasting is an efficient and economical method for mining ore in underground non-coal mines, and medium-deep hole blasting has become the preferred mining method in underground mines due to its high blasting efficiency and low overall cost. However, for underground ore mining, different combinations of medium-deep hole blasting schemes have different impacts on the amount of blasted ore, the size of blasted ore blocks, and the cost of blasting. Summary of the Invention

[0003] The purpose of this application is to provide a blasting mining method for underground mines based on interval approximation, so as to solve or alleviate the problems existing in the prior art.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] This application provides a method for blasting mining in underground mines based on interval approximation, including: establishing... Interval optimization matrix for deep-hole blasting mining schemes in underground mines ;in, , For the first A dataset of evaluation indicators for deep-hole blasting mining schemes in underground mines. The threshold range for evaluation indicators of deep-hole blasting mining schemes in underground mines. , This represents the total number of deep-hole blasting mining schemes in underground mines.

[0006] Based on the interval optimization matrix The analysis matrix obtained by performing homogenization and normalization processes Calculate the measurement value of each evaluation index in each deep-hole blasting mining scheme in each underground mine;

[0007] Determine the combined weight of each evaluation index in each deep-hole blasting mining scheme in an underground mine, and calculate the interval approximation comprehensive evaluation value of different deep-hole blasting mining schemes based on the combined weight and measurement value of each evaluation index.

[0008] Preferably, the eigenvectors of the decomposition matrix of the judgment matrix of the relative relationship between the evaluation indicators of the deep-hole blasting mining scheme in the underground mine that has passed the consistency test are calculated, and the first weight of the evaluation indicator is determined based on the constructed first weight model.

[0009] as well as,

[0010] In turn Interval optimization matrix of evaluation indicators for deep-hole blasting mining schemes in underground mines The evaluation indicators are processed by homogenization, normalization, and fixed-value processing, and the second weight of the evaluation indicators is determined based on the entropy value of the obtained evaluation indicators and the constructed second weight model.

[0011] The first and second weights of the evaluation indicators are input into the constructed combined weight model of the evaluation indicators to generate the combined weights of the evaluation indicators.

[0012] Preferably, a judgment matrix is ​​constructed to determine the relative relationships among the evaluation indicators of deep-hole blasting mining schemes in underground mines. and the judgment matrix Perform consistency checks, if the judgment matrix If the consistency check fails, the judgment matrix needs to be reconstructed. Until the constructed judgment matrix Consistency check passed; among which, the judgment matrix The elements in the table represent the relative importance scale between the two evaluation indicators;

[0013] The judgment matrix that passes the consistency check Decomposed into upper bound matrix and lower bound matrix And determine the upper limit matrix respectively. eigenvectors eigenvectors of the lower bound matrix Among them, the feature vector The elements in the vector represent the upper limit eigenvectors of the evaluation index. The elements in the vector represent the lower bound eigenvectors of the evaluation index.

[0014] Calculate the upper and lower bound consistency of the relative importance scale between two evaluation indicators, and input the upper and lower bound eigenvectors of the evaluation indicators and the corresponding upper and lower bound consistency into the constructed first weight model to obtain the first weight of the evaluation indicators.

[0015] Preferably, according to the consistency verification model:

[0016]

[0017] In the formula, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, , All are positive integers. This represents the total number of evaluation indicators.

[0018] The preferred first weighting model is:

[0019]

[0020] In the formula, For the first The lower bound eigenvector of each evaluation index For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The upper limit eigenvector of each evaluation index For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, This represents the total number of evaluation indicators.

[0021] Preferably, according to the formula:

[0022]

[0023] Sure Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle Entropy value of each evaluation indicator In the formula, This represents the total number of deep-hole blasting mining schemes in underground mines. For the first The first deep-hole blasting mining scheme in underground mines The standardized values ​​of each evaluation indicator; among which...

[0024]

[0025] In the formula, For the first The first deep-hole blasting mining scheme in underground mines Lower limit values ​​of evaluation indicators after homogenization The lower bound after normalization. For the first The first deep-hole blasting mining scheme in underground mines Upper limit of each evaluation indicator after homogenization The upper limit value after normalization.

[0026] Preferably, the second weighting model is:

[0027]

[0028] In the formula, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The entropy value of each evaluation indicator The number of evaluation indicators, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator.

[0029] The preferred combined weight model is:

[0030]

[0031] In the formula, For the first The first deep-hole blasting mining scheme in underground mines The combined weights of the evaluation indicators The first deep-hole blasting mining scheme in underground mines The first weight of each evaluation indicator for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator This represents the total number of evaluation indicators.

[0032] Preferably, according to the formula:

[0033]

[0034] Determine the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation index In the formula, The first deep-hole blasting mining scheme in underground mines The lower limit threshold values ​​of each evaluation indicator after being normalized and aligned. The first deep-hole blasting mining scheme in underground mines The values ​​of the upper limit thresholds of each evaluation indicator after being normalized and aligned; For the first The first deep-hole blasting mining scheme in underground mines The upper limit values ​​of each evaluation indicator are the values ​​after normalization and homogenization. For the first The first deep-hole blasting mining scheme in underground mines The lower limit values ​​of each evaluation indicator are the values ​​after being normalized and aligned.

[0035] Preferably, according to the formula:

[0036]

[0037] Determine the first Comprehensive evaluation value of interval approximation for deep-hole blasting mining schemes in underground mines In the formula, For the first The first deep-hole blasting mining scheme in underground mines The combined weights of the evaluation indicators For the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation indicator.

[0038] Beneficial effects:

[0039] The underground mine blasting mining method based on interval approximation provided in this application embodiment, through the establishment of... Interval optimization matrix for deep-hole blasting mining schemes in underground mines After performing homogenization and normalization, the resulting analysis matrix This method calculates the measurement value of each evaluation index in each deep-hole blasting mining scheme for underground mines; determines the combined weight of each evaluation index in each deep-hole blasting mining scheme for underground mines; and calculates the interval approximation comprehensive evaluation value of different deep-hole blasting mining schemes based on the combined weight and measurement value of each evaluation index. This effectively overcomes the problem of existing methods lacking analytical processing capabilities for indicators that are interval numbers, enabling more objective and realistic analysis and optimization of mine blasting schemes, ensuring the comprehensiveness and accuracy of index weights, and making the optimization of deep-hole blasting mining schemes for underground mines more accurate and reliable. Attached Figure Description

[0040] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. Wherein:

[0041] Figure 1This is a schematic flowchart of a blasting mining method for underground mines based on interval approximation, according to some embodiments of this application. Detailed Implementation

[0042] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. In fact, those skilled in the art will understand that modifications and variations can be made to the present application without departing from the scope or spirit of the present application. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0043] For the selection of deep-hole blasting parameters in underground mines, commonly used methods include single theoretical methods such as fuzzy hierarchical analysis and unknown measure theory, or combining theories such as hierarchical analysis, approximation ideal solution ranking method, matter-element analysis, rough set theory and grey relational analysis to construct a mine blasting scheme evaluation or analysis optimization model, and applying or verifying the evaluation or optimization model based on examples.

[0044] However, current methods for optimizing blasting parameters do not adapt their analytical indices to the characteristics of deep-hole blasting (depth greater than 5 meters, diameter greater than 50 mm) in underground mines, failing to adequately represent and reflect the features of deep-hole blasting in underground mines. Furthermore, the calculation of index weights typically employs a single method, neglecting the impact of fluctuations in index data on the weight calculation. Index data is analyzed and processed at fixed points. However, for specific blasting schemes, the effects of each blast are not identical, with index values ​​fluctuating within a range. Therefore, existing mine blasting schemes or models lack the ability to analyze and process indexes that are range-bound, and current technologies cannot provide more realistic and objectively accurate analysis and optimization of mine blasting schemes.

[0045] Based on this, this embodiment provides a blasting mining method for underground mines based on interval approximation. Considering the characteristics of deep-hole blasting in underground mines, a blasting effect optimization evaluation system is designed and constructed to fully reflect the blasting scheme, ensuring the comprehensiveness and accuracy of the index weights. This improves the traditional hierarchical evaluation of the system into a multi-objective decision-making optimization method that can optimize scheme selection. This allows for multi-objective analysis and optimization of deep-hole blasting mining schemes in underground mines, with the index being interval numbers. For example... Figure 1 As shown, the method includes:

[0046] Step S101, Establish Interval optimization matrix for deep-hole blasting mining schemes in underground mines .

[0047] in, , For the first A dataset of evaluation indicators for deep-hole blasting mining schemes in underground mines. The threshold range for evaluation indicators of deep-hole blasting mining schemes in underground mines. , This represents the total number of deep-hole blasting mining schemes in underground mines.

[0048] In this embodiment, an optimal evaluation system for underground mine blasting schemes is constructed based on technical, economic, and safety aspects. The evaluation system includes assessment indicators to comprehensively evaluate the underground mine blasting schemes. Among these, technical indicators... Including mining efficiency Explosion shape Explosive block size Economic indicators Including blasting costs Explosive consumption per unit Safety indicators Including the effects of impact and vibration Abnormal blasting efficiency Environmental protection indicators Including the highest dust concentration Noise impact .

[0049] In a specific example, the statistical analysis of on-site blasting evaluation indicators for deep-hole blasting mining schemes in multiple underground mines is shown in Table 1 below:

[0050] Table 1 Evaluation Indicators for Deep-Hole Blasting Mining Schemes in Underground Mines

[0051]

[0052] Traditional interval approximation analysis is performed for evaluation results with multiple levels of hierarchy. However, for the optimal selection of blasting schemes, there are no multi-level standards. Therefore, in this embodiment, the traditional interval approximation analysis is improved into an interval approximation optimization method that can directly perform multi-objective decision optimization. Specifically, for the first... A dataset of data on the optimal blasting effect indicators (i.e., evaluation indicators for deep-hole blasting mining schemes in underground mines) for a certain deep-hole blasting mining scheme. for:

[0053]

[0054] In the formula, For the first The first deep-hole blasting mining scheme in underground mines The lower limit of each evaluation indicator, For the first The first deep-hole blasting mining scheme in underground mines The upper limit of each evaluation indicator, The total number of evaluation indicators. , All values ​​are positive integers. Here, by statistically collecting data on various evaluation indicators of deep-hole blasting mining schemes in multiple underground mines across different mining areas, the maximum value among all data for each evaluation indicator is determined as the upper limit of that indicator, and the corresponding minimum value is determined as the lower limit of that indicator.

[0055] Simultaneously, the threshold range of evaluation indicators for deep-hole blasting mining schemes in underground mines is defined. for:

[0056]

[0057] In the formula, The first deep-hole blasting mining scheme in underground mines The lower limit threshold of each evaluation indicator. The first deep-hole blasting mining scheme in underground mines The upper limit threshold of each evaluation indicator.

[0058] Furthermore, construct ( , The interval optimization matrix of the evaluation system for the optimal selection of deep-hole blasting mining schemes in underground mines (where (a is a positive integer)). ,have:

[0059]

[0060] Step S102: Based on the interval optimization matrix The analysis matrix obtained by performing homogenization and normalization processes Calculate the measurement value of each evaluation index in the deep-hole blasting mining scheme of each underground mine.

[0061] In the evaluation system for deep-hole blasting mining schemes in underground mines, for efficiency-related indicators (blasting efficiency, blast pile shape, blast block size), higher values ​​indicate better blasting effects. For cost-related indicators (blasting cost, explosive consumption per unit, impact and vibration effects, abnormal blasting rate, maximum dust concentration, noise effects), higher values ​​indicate worse blasting effects. Regarding the different relationships between these indicators and blasting effects, this embodiment uses an interval optimization matrix... A homogenization process is performed to ensure that different indicators and blasting effects have a commensurate relationship. Specifically, according to the formula:

[0062]

[0063] The cost-type indicators and benefit-type indicators are aligned; where, For the first The first deep-hole blasting mining scheme in underground mines Upper limit of each evaluation indicator The lower limit value after the homogenization process (homogenization lower limit value). For the first The first deep-hole blasting mining scheme in underground mines The lower limit of each evaluation indicator The upper limit value after the homogenization process (homogenization upper limit value).

[0064] Then, according to the formula:

[0065]

[0066] Then, the interval optimization matrix after the direction-simplification process is normalized; where, For the first The first deep-hole blasting mining scheme in underground mines The lower limit value of the evaluation indicator after normalization and homogenization, i.e., the value of the th evaluation indicator. The first deep-hole blasting mining scheme in underground mines Lower bound of homogenization for each evaluation indicator The lower bound after normalization (lower bound of same-direction normalization); For the first The first deep-hole blasting mining scheme in underground mines The upper limit value of the evaluation indicator after normalization and homogenization, i.e., the value of the th evaluation indicator. The first deep-hole blasting mining scheme in underground mines Upper limit of homogenization for each evaluation indicator The upper limit value after normalization (the upper limit value of same direction normalization).

[0067] Furthermore, by Interval optimization matrix of the evaluation system for deep-hole blasting mining schemes in underground mines. Analysis matrix after normalization and homogenization for:

[0068]

[0069] In the formula, The first deep-hole blasting mining scheme in underground mines The lower limit threshold of each evaluation indicator is the value after normalization and homogenization, which is the value of the deep-hole blasting mining scheme in underground mines. Lower threshold of each evaluation indicator The lower limit threshold after undergoing homogenization and normalization processing (homogenized normalized lower limit threshold). The first deep-hole blasting mining scheme in underground mines The upper limit threshold of each evaluation indicator is normalized and aligned, which is the value of the first evaluation indicator in the deep-hole blasting mining scheme in underground mines. Upper limit threshold of each evaluation indicator The upper limit threshold after normalization and homogenization (lower limit threshold after normalization).

[0070] For the evaluation index of deep-hole blasting mining schemes in underground mines, the smaller the upper limit value and its corresponding upper limit threshold, or the larger the lower limit value and its corresponding lower limit threshold, the better the blasting effect of the corresponding deep-hole blasting mining scheme. In this embodiment, the blasting effect of the blasting scheme is characterized by the measurement value of the evaluation index, specifically according to the formula:

[0071]

[0072] Determine the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation index In the formula, These are the first deep-hole blasting mining schemes in underground mines. The lower and upper limits of the same-direction normalization for each evaluation indicator. The first The first deep-hole blasting mining scheme in underground mines The lower limit and upper limit of the same direction normalization for each evaluation indicator.

[0073] Step S103: Determine the combined weight of each evaluation index in each deep-hole blasting mining scheme in an underground mine, and calculate the interval approximation comprehensive evaluation value of different deep-hole blasting mining schemes based on the combined weight and measurement value of each evaluation index.

[0074] In this embodiment, a judgment matrix of evaluation indicators for deep-hole blasting mining schemes in underground mines is constructed. This paper analyzes the correlation among evaluation indicators of deep-hole blasting mining schemes in underground mines. Specifically, firstly, it examines the judgment matrix of the evaluation indicators. Perform a consistency check; then, evaluate the judgment matrix that passes the consistency check. The system performs decomposition, calculates the eigenvectors of the decomposition matrix, and determines the first weight of the evaluation index based on the constructed first weight model.

[0075] Specifically, the judgment matrix for:

[0076]

[0077] In the formula, The first one determined by the analytic hierarchy process The evaluation index is relative to the first The relative importance scale of each evaluation indicator; The first The evaluation index is relative to the first The lower and upper limits of the relative importance scale for each evaluation indicator.

[0078] Then, the judgment matrix of evaluation indicators for deep-hole blasting mining schemes in underground mines. Perform a consistency check, specifically according to the formula:

[0079]

[0080] In the formula, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, , All are positive integers. This represents the total number of evaluation indicators.

[0081] when and At that time, the judgment matrix of the evaluation indicators If the consistency check passes, then the matrix is ​​judged. If the consistency check fails, the judgment matrix of the evaluation indicators needs to be reconstructed. Then perform consistency verification again until the constructed judgment matrix is ​​reached. Through consistency verification, the judgment matrix that passes the consistency verification will be used. Decomposed into upper bound matrix and lower bound matrix ,Right now ,in,

[0082]

[0083]

[0084] Determine the upper limit matrix respectively eigenvectors eigenvectors of the lower bound matrix Among them, the feature vector The elements in the vector represent the upper limit eigenvectors of the evaluation index. The elements in the vector represent the lower bound eigenvectors of the evaluation index. That is:

[0085]

[0086] In the formula, The first The lower limit eigenvector and upper limit eigenvector of each evaluation indicator.

[0087] Finally, the first Lower bound eigenvectors of each evaluation indicator Upper limit eigenvector and the corresponding first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit Lower bound consistency and the The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Upper limit consistency The first weight model constructed from the input is used to calculate the... The first weight of each evaluation indicator Specifically, the first weight model is as follows:

[0088]

[0089] In the formula, For the first The lower bound eigenvector of each evaluation index For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The upper limit eigenvector of each evaluation index For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, This represents the total number of evaluation indicators. It should be noted that in this embodiment, the number of indicators is... Each deep-hole blasting mining scheme in an underground mine is determined by constructing a corresponding judgment matrix. Based on the constructed first weight model, the first weight of each evaluation index in the deep-hole blasting mining scheme of each underground mine is determined.

[0090] In this embodiment, a first weight is used to characterize the relative importance of the evaluation indicators for deep-hole blasting mining schemes in underground mines, while a second weight is used to characterize the range fluctuation of the evaluation indicators for deep-hole blasting mining schemes in underground mines. Specifically, the weights are sequentially assigned to... The interval optimization matrix X of the evaluation index of deep hole blasting mining scheme in underground mines is subjected to the same direction, normalization and fixed value processing, and the second weight of the evaluation index is determined based on the entropy value of the obtained evaluation index and the constructed second weight model.

[0091] In this embodiment, by Interval optimization matrix of the evaluation system for deep-hole blasting mining schemes in underground mines. Analysis matrix after normalization and homogenization for:

[0092]

[0093] In the formula, The first deep-hole blasting mining scheme in underground mines Lower threshold of each evaluation indicator The lower limit threshold after undergoing homogenization and normalization processing (homogenized normalized lower limit threshold). The first deep-hole blasting mining scheme in underground mines Upper limit threshold of each evaluation indicator The upper limit threshold after normalization and homogenization (lower limit threshold after normalization). The first The first deep-hole blasting mining scheme in underground mines The lower limit and upper limit of the same direction normalization for each evaluation indicator.

[0094] Then, for the first The first deep-hole blasting mining scheme in underground mines The midpoint of the interval range (lower bound and upper bound of normalized values ​​in the same direction) of the evaluation index is used to evaluate the th evaluation index. The first deep-hole blasting mining scheme in underground mines Each evaluation indicator is given a fixed value. Specifically, according to the formula:

[0095]

[0096] For the first The first deep-hole blasting mining scheme in underground mines The evaluation index is set to a fixed value to obtain the first evaluation index. The first deep-hole blasting mining scheme in underground mines Fixed values ​​of each evaluation indicator .

[0097] Next, according to the formula:

[0098]

[0099] Sure Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle Entropy value of each evaluation indicator In the formula, This represents the total number of deep-hole blasting mining schemes in underground mines. For the first The first deep-hole blasting mining scheme in underground mines The fixed values ​​of each evaluation indicator.

[0100] Will Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle Entropy value of each evaluation indicator In the second weight model constructed from the input, the first weight is determined. The second weight of each evaluation indicator Specifically, the second weighting model is as follows:

[0101]

[0102] In the formula, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The entropy value of each evaluation indicator The number of evaluation indicators, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator.

[0103] Finally, according to Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator And the first deep-hole blasting mining scheme in each underground mine The first weight of each evaluation indicator Based on the constructed evaluation index combination weight model, the first deep-hole blasting mining scheme for each underground mine is generated. The combined weight of each evaluation indicator Specifically, according to the formula:

[0104]

[0105] Determine the first The first deep-hole blasting mining scheme in underground mines The combined weight of each evaluation indicator In the formula, The first deep-hole blasting mining scheme in underground mines The first weight of each evaluation indicator for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator This represents the total number of evaluation indicators.

[0106] Finally, according to the formula:

[0107]

[0108] Determine the first Comprehensive evaluation value of interval approximation for deep-hole blasting mining schemes in underground mines In the formula, For the first The first deep-hole blasting mining scheme in underground mines The combined weights of the evaluation indicators For the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation indicator.

[0109] right The interval approximation comprehensive evaluation values ​​of deep-hole blasting mining schemes in underground mines are compared. The larger the interval approximation comprehensive evaluation value, the better the blasting effect of the corresponding deep-hole blasting mining scheme in underground mines.

[0110] Therefore, by constructing an evaluation system that fully reflects the blasting effect of blasting schemes, ensuring the comprehensiveness and accuracy of indicator weights, the traditional hierarchical evaluation of the system is improved into a multi-objective decision-making optimization method for scheme selection. This method performs multi-objective analysis and optimization of deep-hole blasting mining schemes in underground mines, with indicators as interval numbers. It effectively overcomes the problem that existing methods lack the ability to analyze and process cases where indicators are interval numbers, and conducts more objective and realistic analysis and optimization of mine blasting schemes, ensuring the comprehensiveness and accuracy of indicator weights, and making the optimization of deep-hole blasting mining schemes in underground mines more accurate and reliable.

[0111] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0112] In this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0113] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An interval-approximation-based underground mine stope blasting mining method, characterized in that, include: Establishing Interval optimization matrix of medium-length hole blasting mining scheme in underground mine ; wherein, , is the data set of the evaluation index of the medium-length hole blasting mining scheme in the first underground mine, , is the total number of the medium-length hole blasting mining scheme in the underground mine; ； In the formula, is the lower limit value of the first evaluation index of the middle-deep hole blasting mining scheme in the nth underground mine, is the upper limit value of the first evaluation index of the middle-deep hole blasting mining scheme in the nth underground mine, is the upper limit value of the first evaluation index of the middle-deep hole blasting mining scheme in the nth underground mine, is the total number of evaluation indexes, , are positive integers.​​​ the threshold range of evaluation indexes for the medium-long hole blasting mining scheme in underground mines, ； In the formula, is the lower limit threshold of the first evaluation index of the medium-deep hole blasting mining scheme in the underground mine, is the upper limit threshold of the first evaluation index of the medium-deep hole blasting mining scheme in the underground mine, is the lower limit threshold of the first evaluation index of the medium-deep hole blasting mining scheme in the underground mine, is the upper limit threshold of the first evaluation index of the medium-deep hole blasting mining scheme in the underground mine. According to the interval optimization matrix The analysis matrix obtained by homogenization and normalization processing The measure value of each evaluation index in the medium-long hole blasting mining scheme of each underground mine is calculated. Determine the combined weight of each evaluation index in each deep-hole blasting mining scheme in an underground mine, and calculate the interval approximation comprehensive evaluation value of different deep-hole blasting mining schemes based on the combined weight and measurement value of each evaluation index.

2. The method according to claim 1, characterized in that, The eigenvectors of the decomposition matrix of the judgment matrix of the relative relationship between the evaluation indicators of deep-hole blasting mining schemes in underground mines that have passed the consistency test are calculated, and the first weight of the evaluation indicators is determined based on the constructed first weight model. as well as, sequentially to Interval optimization matrix of evaluation indexes of medium-deep hole blasting mining scheme in underground mine Perform homogenization, normalization, and constantization, and determine the second weight of the evaluation indexes based on the constructed second weight model according to the obtained entropy values of the evaluation indexes. The first and second weights of the evaluation indicators are input into the constructed combined weight model of the evaluation indicators to generate the combined weights of the evaluation indicators.

3. The method according to claim 2, characterized in that, Constructing a judgment matrix of relative relationships among evaluation indicators for deep-hole blasting mining schemes in underground mines. and the judgment matrix Perform consistency checks, if the judgment matrix If the consistency check fails, the judgment matrix needs to be reconstructed. Until the constructed judgment matrix Consistency check passed; among which, the judgment matrix The elements in the table represent the relative importance scale between the two evaluation indicators; The judgment matrix that passes the consistency check Decompose into upper bound matrix and lower bound matrix And determine the upper limit matrix respectively. eigenvectors eigenvectors of the lower bound matrix Among them, the feature vector The elements in the vector represent the upper limit eigenvectors of the evaluation index. The elements in the vector represent the lower bound eigenvectors of the evaluation index. Calculate the upper and lower bound consistency of the relative importance scale between two evaluation indicators, and input the upper and lower bound eigenvectors of the evaluation indicators and the corresponding upper and lower bound consistency into the constructed first weight model to obtain the first weight of the evaluation indicators.

4. The method according to claim 3, characterized in that, According to the consistency verification model: ； In the formula, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, , All are positive integers. This represents the total number of evaluation indicators.

5. The method according to claim 3, characterized in that, The first weighting model is: ； In the formula, For the first The lower bound eigenvector of each evaluation index For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator upper limit Consistency of upper limits, For the first The upper limit eigenvector of each evaluation indicator. For the first The evaluation index is relative to the first The relative importance scale of each evaluation indicator lower limit The lower bound consistency, This represents the total number of evaluation indicators.

6. The method according to claim 2, characterized in that, According to the formula: ； Sure Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle Entropy value of each evaluation indicator In the formula, This represents the total number of deep-hole blasting mining schemes in underground mines. For the first The first deep-hole blasting mining scheme in underground mines The standardized values ​​of each evaluation indicator; among them... ； In the formula, For the first The first deep-hole blasting mining scheme in underground mines Lower limit values ​​of evaluation indicators after homogenization The lower bound after normalization. For the first The first deep-hole blasting mining scheme in underground mines Upper limit of each evaluation indicator after homogenization The upper limit value after normalization.

7. The method according to claim 2, characterized in that, The second weighting model is: ； In the formula, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The entropy value of each evaluation indicator The number of evaluation indicators, for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator.

8. The method according to claim 2, characterized in that, The combined weight model is as follows: ； In the formula, For the first The first deep-hole blasting mining scheme in underground mines The combined weights of the evaluation indicators The first deep-hole blasting mining scheme in underground mines The first weight of each evaluation indicator for Interval optimization matrix for deep-hole blasting mining schemes in underground mines The Middle The second weight of each evaluation indicator This represents the total number of evaluation indicators.

9. The method according to claim 1, characterized in that, According to the formula: ； Determine the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation index In the formula, The first deep-hole blasting mining scheme in underground mines The lower limit threshold values ​​of each evaluation indicator after being normalized and aligned. The first deep-hole blasting mining scheme in underground mines The values ​​of the upper limit thresholds of each evaluation indicator after being normalized and aligned; For the first The first deep-hole blasting mining scheme in underground mines The upper limit values ​​of each evaluation indicator are the values ​​after normalization and homogenization. For the first The first deep-hole blasting mining scheme in underground mines The lower limit values ​​of each evaluation indicator are the values ​​after being normalized and aligned.

10. The method according to claim 1, characterized in that, According to the formula: ； Determine the first Comprehensive evaluation value of interval approximation for deep-hole blasting mining schemes in underground mines In the formula, For the first The first deep-hole blasting mining scheme in underground mines The combined weights of the evaluation indicators For the first The first deep-hole blasting mining scheme in underground mines The measurement value of each evaluation indicator.

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