Coal mine roof blasting scheme determination method, device, equipment, medium and product

Abstract

The invention discloses a coal mine roof blasting scheme determining method and device, equipment, a medium and a product, and relates to the technical field of coal mine thick and hard roof blasting pressure relief. According to the engineering geological conditions, a blasting scheme determination expert system is adopted, and a coal mine roof blasting scheme of the target blasting area is obtained; a knowledge base of the blasting scheme determination expert system comprises a typical case database and a blasting rule knowledge base. The expert system is applied to determination of the coal mine roof blasting scheme, the expert system knowledge base is constructed according to the typical case database and the blasting rule knowledge base, and a basis is provided for intelligent optimization of the coal mine roof blasting scheme.

Description

Technical Field

[0001] The present application relates to the technical field of blasting and decompression of thick and hard roofs in coal mines, and in particular to a method, device, equipment, medium and product for determining a coal mine roof blasting plan. Background Art

[0002] Roof collapse accidents are a major cause of casualties in coal production. In mining areas with hard roofs, large areas of suspended roof are prone to form during working face advancement. A collapse of the roof can seriously impact safe coal mining. Roof blasting is crucial for coal roadway safety, and optimally designed roof blasting parameters are crucial for both mine safety and economic efficiency.

[0003] The existing parameter design for thick hard roof blasting in coal mines mostly relies on the personal experience and knowledge level of technicians. The parameter design of blasting schemes has certain limitations and lacks scientific basis. It is obviously unable to meet the safety and economic efficiency requirements of coal mine production in the context of the big data era. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, equipment, medium and product for determining a coal mine roof blasting plan, apply an expert system to the determination of a coal mine roof blasting plan, construct an expert system knowledge base based on a typical case database and a blasting rule knowledge base, and provide a basis for the intelligent optimization of coal mine roof blasting plans.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for determining a coal mine roof blasting plan, comprising:

[0007] Obtain engineering geological conditions of the target blasting area;

[0008] According to the engineering geological conditions, a blasting plan determination expert system is used to obtain a coal mine roof blasting plan for the target blasting area; the knowledge base of the blasting plan determination expert system includes a typical case database and a blasting rule knowledge base.

[0009] In a second aspect, the present application provides a device for determining a coal mine roof blasting plan, comprising:

[0010] Data acquisition module, used to obtain engineering geological conditions of the target blasting area;

[0011] The blasting scheme determination module is used to obtain the coal mine roof blasting scheme of the target blasting area by using the blasting scheme determination expert system according to the engineering geological conditions; the knowledge base of the blasting scheme determination expert system includes a typical case database and a blasting rule knowledge base.

[0012] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for determining a coal mine roof blasting plan.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for determining a coal mine roof blasting plan.

[0014] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the above-mentioned method for determining a coal mine roof blasting plan when executed by a processor.

[0015] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0016] The present application provides a method, device, equipment, medium and product for determining a coal mine roof blasting plan, applies an expert system to the determination of a coal mine roof blasting plan, constructs an expert system knowledge base based on a typical case database and a blasting rule knowledge base, and provides a basis for the intelligent optimization of coal mine roof blasting plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is an application environment diagram of a method for determining a coal mine roof blasting plan in one embodiment of the present application;

[0019] Figure 2 A schematic flow chart of a method for determining a coal mine roof blasting plan provided in one embodiment of the present application;

[0020] Figure 3 A schematic diagram of a method for building an expert system for determining a blasting plan according to an embodiment of the present application;

[0021] Figure 4 A schematic diagram of the overall framework of the blasting plan determination expert system provided in one embodiment of the present application;

[0022] Figure 5 A schematic diagram of the functional modules of a device for determining a coal mine roof blasting plan provided in one embodiment of the present application;

[0023] Figure 6A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0025] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0026] The method for determining a coal mine roof blasting scheme provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the engineering geological conditions of the target blasting area to the server 104. After receiving the engineering geological conditions of the target blasting area, the server 104 uses the blasting plan determination expert system to obtain the coal mine roof blasting plan for the target blasting area. The server 104 can feedback the obtained coal mine roof blasting plan for the target blasting area to the terminal 102. In addition, in some embodiments, the coal mine roof blasting plan determination method can also be implemented separately by the server 104 or the terminal 102. For example, the terminal 102 can directly process the engineering geological conditions of the target blasting area to obtain the coal mine roof blasting plan for the target blasting area, or the server 104 can obtain the engineering geological conditions of the target blasting area from the data storage system and use the blasting plan determination expert system to obtain the coal mine roof blasting plan for the target blasting area.

[0027] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers, or may be a cloud server.

[0028] In an exemplary embodiment, Figure 2As shown, a method for determining a coal mine roof blasting plan is provided. The method is executed by a computer device, specifically, it can be executed by a computer device such as a terminal or a server alone, or it can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the process, including the following steps 201 and 202.

[0029] Step 201: Obtain the engineering geological conditions of the target blasting area.

[0030] Step 202: Based on the engineering geological conditions, a blasting plan determination expert system is used to obtain a coal mine roof blasting plan for the target blasting area. The knowledge base of the blasting plan determination expert system includes a typical case database and a blasting rule knowledge base.

[0031] In an exemplary embodiment, Figure 3 As shown, the method for building the blasting plan determination expert system includes the following steps 301 to 305. Among them:

[0032] Step 301 : Building the typical case database based on multiple groups of sample engineering geological conditions and sample coal mine roof blasting schemes corresponding to each group of sample engineering geological conditions.

[0033] Step 302: Building the blasting rule knowledge base based on prior knowledge, wherein the blasting rule knowledge base includes multiple sets of theoretical engineering geological conditions and theoretical coal mine roof blasting schemes corresponding to each set of theoretical engineering geological conditions.

[0034] Step 303: construct a case-based reasoning engine corresponding to the typical case database based on the typical case database.

[0035] Step 304: Based on the blasting rule knowledge base, a rule inference engine corresponding to the blasting rule knowledge base is constructed using production rules.

[0036] Step 305: Building the blasting scheme determination expert system based on the typical case database, the blasting rule knowledge base, the case-based reasoning engine, and the rule-based reasoning engine.

[0037] In an exemplary embodiment, by conducting in-depth investigation and analysis of the basic conditions of the roofs and tunnels of different mining areas and the blasting unloading conditions, sample coal mine roof blasting plans are collected and a typical case database is established. The typical case database is mainly collected through three means: on-site investigation, questionnaire survey and literature search. The typical case database contains four modules: data index, tunnel conditions, geological conditions, and coal mine roof blasting plans, with a total of 23 blasting indicators. Among them, the data index includes serial number, mining area, and working face. Tunnel conditions include burial depth, tunnel dimensions (tunnel height, tunnel width, cross-sectional area), and construction scope. Geological conditions include roof lithology, roof thickness, roof inclination, Proctor coefficient, vertical distance between key layer and tunnel, and degree of joint development. The coal mine roof blasting plan includes the number of blastholes in each group, row spacing, blasthole diameter, blasthole depth, blasthole inclination, charging length, single hole charging amount, plugging length, and explosive type.

[0038] In another exemplary embodiment, by collecting relevant information on roof blasting, blasting industry norms, blasting expertise, and research results in the field of roof blasting, a blasting rule knowledge base based on prior knowledge is established. The blasting rule knowledge base consists of an input layer and an output layer. Among them, the input layer parameters mainly include influencing factors such as geological conditions and tunnel conditions, such as basic tunnel dimensions, burial depth, roof thickness, roof inclination, Proctor coefficient, and degree of joint development. The output layer parameters are coal mine roof blasting plans, including hole bottom distance, number of blastholes, blasthole depth, etc. In this embodiment, establishing a blasting rule knowledge base involves two types of parameters, numerical parameters and non-numerical parameters. For numerical parameters, the corresponding research results data are analyzed to find their corresponding functional relationships for numerical calculation. For non-numerical parameters, by analyzing typical case data with good blasting effects, combined with expert experience and blasting safety regulations, the corresponding output parameters under different conditions are set.

[0039] The typical case database and blasting rule knowledge base together constitute the knowledge base of the blasting plan determination expert system. The expert system knowledge base is the core support part of the intelligent optimization operation of the coal mine roof blasting plan and plays a decisive role in the results of parameter reasoning.

[0040] In an exemplary embodiment, Figure 4As shown, the blasting plan determination expert system consists of an expert knowledge base, an inference engine, an explanation engine, and a user interface. The expert knowledge base stores the expert system's specialized knowledge in this field, including facts, feasible operations, and rules. The inference engine derives new conclusions based on known facts and rules. Its core concept is to simulate the thinking patterns of human experts and perform logical deductions from existing knowledge to support decision-making. The explanation engine can explain the expert system's behavior to the user, including the correctness of the inference conclusions and the reasons why the system outputs alternative solutions. Through the user interface, the user enters the engineering geological conditions of the target blasting area and the various raw parameters required for roof blasting plan determination. The expert system then extracts data and rules from the representative case database and blasting rule knowledge base in the expert knowledge base and performs corresponding inferences, enabling interaction between the user and the expert knowledge base. Furthermore, the blasting plan determination expert system includes a comprehensive database, which stores initial data for the field or problem and intermediate data (information) obtained during the inference process, namely, some current facts about the object being processed.

[0041] In an exemplary embodiment, each set of sample engineering geological conditions in the typical case database includes multiple engineering geological factors. Then the above step 303 can be replaced by the following steps 3031 and 3032. Among them:

[0042] Step 3031: Use the analytic hierarchy process to process all engineering geological factors to obtain key engineering geological factors.

[0043] Step 3032: Based on the key engineering geological factors, a similarity calculation method is used to construct a case-based reasoning engine corresponding to the typical case database.

[0044] In an exemplary embodiment, engineering geological factors for a coal mine roof blasting plan are selected based on the collected and analyzed data, and the analytic hierarchy process is used to determine the weight of each engineering geological factor. The key engineering geological factors, i.e., the key indicators of expert system reasoning, are determined based on the weight values ​​and expert and on-site empirical knowledge.

[0045] When constructing the hierarchical analysis model, the target layer is set as the key engineering geological factors for the coal mine roof blasting plan. The criterion layer includes the roadway conditions, coal seam conditions and roof conditions. The sub-criterion layer includes cross-sectional area, burial depth, coal seam thickness, roof thickness, roof inclination, lithology, Proctor coefficient, joint development degree, roof integrity, and the vertical distance between the key layer and the roadway. The expert scoring method is used for pairwise comparison. The comparison results are quantitatively expressed on a comparison scale of 1 to 9 to construct a comparison judgment matrix. The maximum eigenvalue of the comparison judgment matrix and its corresponding eigenvector are obtained. After normalizing the eigenvector, the weight value of the engineering geological factors of a certain layer to the engineering geological factors of the previous layer is obtained, and the square root method is used for calculation. The specific steps of the hierarchical analysis method are as follows:

[0046] ① Construct a judgment matrix: Compare each influencing factor pairwise according to the scale and construct the following judgment matrix:

[0047]

[0048] Among them, A is the judgment matrix, a ij is the importance score of engineering geological factor i relative to engineering geological factor j, i, j = 1, 2,…, n, n is the total number of engineering geological factors.

[0049] ②Calculate the product of each row of the judgment matrix:

[0050]

[0051] Among them, M i Represents the product of all elements in the i-th row of the judgment matrix, m ij is the element in the i-th row and j-th column of the judgment matrix.

[0052] ③Calculate M i The nth root of:

[0053]

[0054] in, M i The nth root of .

[0055] ④ Normalize the vector:

[0056]

[0057] Among them, W i for The normalized processing result.

[0058] ⑤Calculate the maximum eigenvalue:

[0059]

[0060] where λ max is the maximum eigenvalue, and W is the weight vector.

[0061] ⑥Perform consistency test:

[0062]

[0063] Among them, CI is the consistency index.

[0064] The random consistency index RI is the random mean of the consistency index of the same order matrix, and the consistency ratio CR is the ratio of the consistency index CI to the random consistency index RI of the same order, that is, When CR < 0.1, the judgment matrix is ​​said to have passed the consistency test. Otherwise, the judgment matrix should be adjusted. The comparative judgment can be reviewed and revised, or more experts can be invited to help revise the judgment matrix.

[0065] In an exemplary embodiment, a case reasoning engine corresponding to a typical case database is constructed, the core of which is that the engineering geological conditions of the target blasting area and a sample engineering geological condition in the typical case database have the highest similarity, and the sample coal mine roof blasting plan corresponding to this sample engineering geological condition is used as the coal mine roof blasting plan for the target blasting area.

[0066] In this embodiment, taking any set of sample engineering geological conditions as an example, there are two similarity calculation models. The numerical engineering geological factors are directly calculated using the Euclidean distance calculation formula, that is, in, is the i-th engineering geological factor in the engineering geological conditions of the target blasting area, x i is the i-th engineering geological factor in the sample engineering geological conditions, for and x i The Euclidean distance of non-numeric engineering geological factors only needs to compare whether the two are equal, that is, Convert the above distance formula into a similarity calculation formula:

[0067]

[0068] in, for and x i The similarity between them.

[0069] In this embodiment, for the obtained key engineering geological factors, the similarity corresponding to each key engineering geological factor is multiplied by its corresponding weight and accumulated to obtain the similarity between the engineering geological conditions of the target blasting area and the engineering geological conditions of the sample. The calculation formula is as follows:

[0070]

[0071] Among them, S is the similarity between the engineering geological conditions of the target blasting area and the engineering geological conditions of the sample, is the i-th key engineering geological factor in the engineering geological conditions of the target blasting area, y i is the i-th key engineering geological factor in the sample engineering geological conditions, for and y i The similarity between i y i The corresponding weight, k, is the total number of key engineering geological factors.

[0072] In an exemplary embodiment, the above step 202 can be replaced by the following steps 2021 to 2023. In which:

[0073] Step 2021: Receive the knowledge base type selected by the user.

[0074] Step 2022: If the knowledge base type is a typical case database, a coal mine roof blasting plan for the target blasting area is obtained based on the engineering geological conditions, the typical case database, and the case-based reasoning engine.

[0075] Step 2023: If the knowledge base type is a blasting rule knowledge base, a coal mine roof blasting plan for the target blasting area is obtained according to the engineering geological conditions, the blasting rule knowledge base, and the rule inference engine.

[0076] In an exemplary embodiment, the above step 2022 may be replaced by the following steps 221 and 222. In which:

[0077] Step 221 : for any set of sample engineering geological conditions, use the case-based reasoning engine to determine the similarity between the engineering geological conditions and the sample engineering geological conditions, and obtain the similarity value corresponding to the sample engineering geological conditions.

[0078] Step 222 , using the sample coal mine roof blasting plan corresponding to the maximum value of the similarity value as the coal mine roof blasting plan for the target blasting area.

[0079] In one exemplary embodiment, based on the engineering geological conditions of the target blasting area, the expert system first extracts the first sample engineering geological condition from the typical case database in the knowledge base and calculates its similarity. It then extracts the second sample engineering geological condition and calculates its similarity. This continues until the similarity calculations for all sample engineering geological conditions in the typical case database are complete. The sample coal mine roof blasting plan corresponding to the maximum similarity value is selected as the coal mine roof blasting plan for the target blasting area.

[0080] In an exemplary embodiment, the above step 2023 may be replaced by the following steps 231 and 232. In which:

[0081] Step 231: Based on the engineering geological conditions, the rule-based inference engine is used to obtain a theoretical engineering geological condition matching result corresponding to the engineering geological conditions.

[0082] Step 232: Obtain a coal mine roof blasting plan for the target blasting area based on the theoretical engineering geological condition matching result and the blasting rule knowledge base.

[0083] In an exemplary embodiment, when designing a rule-based inference engine based on a blasting rule knowledge base, the engineering geological conditions of the target blasting area are matched with the rules in the blasting rule knowledge base, analyzed, calculated, inferred, and judged, ultimately resulting in a reasonable coal mine roof blasting plan. The rule-based inference engine adopts the form of production rules (IF-THEN rules), namely: {IF condition 1 AND condition 2…THEN conclusion}. Based on the engineering geological conditions of the target blasting area, the expert system will sequentially search the rules in the blasting rule knowledge base and match them one by one. If the premise of a rule fails to match the engineering geological conditions of the target blasting area, the expert system will continue to match the next rule, and so on. When the condition part of a rule successfully matches the engineering geological conditions of the target blasting area, the inference chain is gradually expanded, and finally a complete coal mine roof blasting plan is obtained.

[0084] Based on the same inventive concept, embodiments of the present application further provide a device for determining a coal mine roof blasting plan, for implementing the aforementioned method for determining a coal mine roof blasting plan. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for determining a coal mine roof blasting plan provided below can be found in the aforementioned method for determining a coal mine roof blasting plan, and will not be further elaborated here.

[0085] In an exemplary embodiment, Figure 5 As shown, a device for determining a coal mine roof blasting plan is provided, comprising a data acquisition module 501 and a blasting plan determination module 502. The data acquisition module 501 is configured to obtain the engineering geological conditions of a target blasting area. The blasting plan determination module 502 is configured to determine a coal mine roof blasting plan for the target blasting area using a blasting plan determination expert system based on the engineering geological conditions. The knowledge base of the blasting plan determination expert system includes a typical case database and a blasting rule knowledge base.

[0086] In an exemplary embodiment, the device for determining a coal mine roof blasting plan also includes an interactive interface for realizing the visual integration of the expert system's knowledge base and the blasting plan output. The interactive interface includes a user login interface, a menu bar, an input interface, and an output interface. The user login interface requires the user to provide a username and password to log in, and can jump to the expert system menu bar. The menu bar will display two reasoning methods, namely, reasoning based on typical cases and reasoning based on blasting rules, which the user can choose. The input interface is equipped with three modules, namely geological conditions, tunnel conditions, and initial blasting parameters. Users can fill in or select according to the actual situation of the mining area and the expected range of blasting. The output interface displays the coal mine roof blasting plan, including the specific blasting parameter design, hole layout method, single hole charge, number of blast holes, etc.

[0087] The beneficial effects of this application are as follows:

[0088] 1. The combination of expert system and coal mine roof blasting scheme determination is more accurate and intelligent than traditional blasting scheme design, providing scheme support and expert guidance for actual engineering applications.

[0089] 2. By investigating and analyzing typical case data and summarizing blasting design rules, a comprehensive and accurate expert knowledge base was established, ensuring the practicality of the intelligent optimization design of coal mine roof blasting schemes.

[0090] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the engineering geological conditions of the target blasting area. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining a coal mine roof blasting plan is implemented.

[0091] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0092] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0093] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0094] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0095] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0096] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0097] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0098] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0099] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining a coal mine roof blasting plan, characterized in that: The method for determining a coal mine roof blasting plan includes: Obtain engineering geological conditions of the target blasting area; According to the engineering geological conditions, a blasting plan determination expert system is used to obtain a coal mine roof blasting plan for the target blasting area; the knowledge base of the blasting plan determination expert system includes a typical case database and a blasting rule knowledge base.

2. The method for determining a coal mine roof blasting plan according to claim 1, wherein: The method for building the blasting plan determination expert system includes: Building the typical case database according to multiple groups of sample engineering geological conditions and sample coal mine roof blasting plans corresponding to each group of sample engineering geological conditions; The blasting rule knowledge base is constructed based on prior knowledge; the blasting rule knowledge base includes multiple sets of theoretical engineering geological conditions and theoretical coal mine roof blasting schemes corresponding to each set of theoretical engineering geological conditions; According to the typical case database, construct a case reasoning engine corresponding to the typical case database; According to the blasting rule knowledge base, using production rules, constructing a rule inference engine corresponding to the blasting rule knowledge base; The blasting scheme determination expert system is constructed based on the typical case database, the blasting rule knowledge base, the case reasoning engine and the rule reasoning engine.

3. The method for determining a coal mine roof blasting plan according to claim 2, wherein: Each set of sample engineering geological conditions in the typical case database includes multiple engineering geological factors; Based on the typical case database, a case-based reasoning engine corresponding to the typical case database is constructed, specifically comprising: The analytic hierarchy process is used to process all engineering geological factors and obtain key engineering geological factors; According to the key engineering geological factors, a similarity calculation method is adopted to construct a case-based reasoning engine corresponding to the typical case database.

4. The method for determining a coal mine roof blasting plan according to claim 2, wherein: According to the engineering geological conditions, a blasting plan determination expert system is used to obtain a coal mine roof blasting plan for the target blasting area, specifically including: receiving a knowledge base type selected by a user; If the knowledge base type is a typical case database, then obtaining a coal mine roof blasting plan for the target blasting area according to the engineering geological conditions, the typical case database and the case-based reasoning engine; If the knowledge base type is a blasting rule knowledge base, a coal mine roof blasting plan for the target blasting area is obtained according to the engineering geological conditions, the blasting rule knowledge base and the rule inference engine.

5. The method for determining a coal mine roof blasting plan according to claim 4, wherein: According to the engineering geological conditions, the typical case database and the case-based reasoning engine, a coal mine roof blasting plan for the target blasting area is obtained, specifically including: For any set of sample engineering geological conditions, the case-based reasoning engine is used to determine the similarity between the engineering geological conditions and the sample engineering geological conditions, and obtain the similarity value corresponding to the sample engineering geological conditions; The sample coal mine roof blasting plan corresponding to the maximum value of the similarity value is used as the coal mine roof blasting plan of the target blasting area.

6. The method for determining a coal mine roof blasting plan according to claim 4, wherein: According to the engineering geological conditions, the blasting rule knowledge base and the rule inference engine, a coal mine roof blasting plan for the target blasting area is obtained, specifically including: According to the engineering geological conditions, using the rule inference engine, obtaining a theoretical engineering geological condition matching result corresponding to the engineering geological conditions; According to the matching results of the theoretical engineering geological conditions and the blasting rule knowledge base, a coal mine roof blasting plan for the target blasting area is obtained.

7. A device for determining a coal mine roof blasting plan, characterized in that: The coal mine roof blasting scheme determination device comprises: Data acquisition module, used to obtain engineering geological conditions of the target blasting area; The blasting scheme determination module is used to obtain the coal mine roof blasting scheme of the target blasting area by using the blasting scheme determination expert system according to the engineering geological conditions; the knowledge base of the blasting scheme determination expert system includes a typical case database and a blasting rule knowledge base.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining a coal mine roof blasting plan according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining a coal mine roof blasting plan according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining a coal mine roof blasting plan according to any one of claims 1 to 6 is implemented.

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