A data processing method and device for a coal mine intelligent system

Abstract

The application provides a data processing method and equipment for a coal mine intelligent system, which comprises the following steps: identifying the type of production equipment in a coal mine, and setting layers and levels according to the type of production equipment; based on the topological relationship between the production equipment in the coal mine, constructing a system topological graph of all the production equipment, reading and storing the topological relationship for restoring the conversion path of matter, energy and information from the drawing result of the system topological graph; based on the mapping relationship between matter, energy and information, determining the cooperative relationship between the topological data, and discovering new correlation and correcting the quantitative attribute in the mapping relationship through a self-learning algorithm. Through the application, various types of data can be organically integrated, and the rapid landing implementation of various functions of the intelligent system can be effectively supported.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety technology, and in particular to a data processing method, apparatus, equipment, and storage medium for an intelligent coal mine system. Background Technology

[0002] For the four key production factors in coal mining—people, machinery, methods, and environment—the following points require special attention:

[0003] First, ensure the safety of personnel during operations and standardize procedures as much as possible.

[0004] Secondly, ensure the safe operation of all types of machinery and equipment, and manage and maintain them in a unified manner as much as possible.

[0005] Furthermore, it ensures that hazardous factors such as water, fire, harmful gases, and dust are within a safe and controllable range, and has comprehensive control over the overall working environment, enabling early detection and handling of emergencies before they occur, and obtaining accurate first-hand information to support precise and effective rescue efforts when disasters happen.

[0006] Finally, based on the refined analysis of daily production data, digital means can be used to improve operational and management efficiency, enhance scientific decision-making, and ultimately improve the overall benefits of the coal mine.

[0007] To achieve these goals, coal mines have deployed an increasing number of monitoring systems, which have played a certain role in ensuring data security. However, several problems remain: multiple systems are not interconnected, resulting in severe data silos, making it difficult to obtain data where needed; even if data from some systems is integrated through customized development, its versatility is weak, and customized integration solutions for each mine are too complex, costly, and difficult to replicate; or the correlation between data from multiple systems has not been explored, thus failing to maximize the value of existing data.

[0008] Therefore, integrating various systems to maximize benefits has become an urgent problem to be solved in the process of intelligent construction of coal mines. A crucial step in integrating the capabilities of various systems is to build a unified and flexible data model so that data can flow easily between different systems and be organically integrated. Only when the organic integration of data is completed can all subsequent capabilities be possible.

[0009] Coal mines have a wide variety of existing equipment and monitoring systems, covering a relatively complete range of areas. Data from various equipment and systems can be collected, digitally transmitted, and stored.

[0010] Key material flows, energy flows, and information flows in the coal mining process, such as Figure 1As shown, in addition to their own static physical properties, they also have temporal order relationships, spatial position relationships, inherent logical relationships, or mutual transfer and transformation mapping relationships between different devices and systems.

[0011] The systems currently used in coal mines are mostly monitoring and support systems for single equipment or single subsystems (power supply system, ventilation system, etc.). For example, there are coal mining systems, transportation systems, tunneling systems, electromechanical systems, drainage systems, and ventilation systems used in the production process, as well as monitoring and surveillance, personnel positioning, emergency escape, compressed air self-rescue, water supply rescue, and communication systems used for safety assurance and emergency rescue.

[0012] Each subsystem is responsible for data collection, status detection, anomaly alarms, fault recovery, data aggregation and analysis within its own system.

[0013] Some integrated application platforms combine data from multiple subsystems through customized development to form monitoring and protection solutions for specific application scenarios.

[0014] The shortcomings of the existing system are as follows:

[0015] The problem of multiple systems not being able to communicate with each other and the serious problem of data silos makes it impossible to easily obtain data where it is needed.

[0016] While some data from the system were integrated through customized development, the system lacked versatility. The customized integration solution for each mine was too complex, costly, and difficult to replicate.

[0017] The failure to uncover the relationships between data across multiple systems resulted in a failure to maximize the value of existing data. Summary of the Invention

[0018] This invention provides a data processing method, apparatus, equipment, and storage medium for intelligent coal mine systems, aiming to conveniently and quickly integrate various types of data and effectively support the rapid implementation of various functions of the intelligent system.

[0019] Therefore, the first objective of this invention is to provide a data processing method for an intelligent coal mine system, comprising:

[0020] Identify the types of production equipment in underground coal mines and set up hierarchical classifications based on these types.

[0021] Based on the topological relationships between production equipment in underground coal mines, a system topology diagram of all production equipment is constructed. The topological relationships of the transformation paths of matter, energy, and information are read and stored from the drawing results of the system topology diagram.

[0022] Based on the mapping relationship between matter, energy, and information, the collaborative relationship between topological data is determined, and new correlations are discovered and quantitative attributes in the mapping relationship are corrected through self-learning algorithms.

[0023] The steps involved in identifying the types of production equipment in underground coal mines and setting up hierarchical classifications based on these equipment types include:

[0024] Identify the types of production equipment in underground coal mines; among which, the types of production equipment include at least coal mining machines, conveyors, crushers, transfer machines, support equipment, water supply and drainage equipment, ventilation equipment, and gas / dust monitoring equipment;

[0025] Draw hierarchical attribute diagrams for different types of production equipment;

[0026] The hierarchical configuration information of the hierarchical attribute diagram of different types of production equipment is pre-set, and an object hierarchical attribute storage model is constructed.

[0027] The steps involved in constructing a system topology diagram of all production equipment based on the topological relationships between production equipment in an underground coal mine, and then reading and storing the topological relationships from the system topology diagram to reconstruct the transformation paths of matter, energy, and information, include:

[0028] The ability to visualize and draw topology relationships allows for the creation of various subsystem topology diagrams, where a single device may involve multiple subsystems.

[0029] The tunnel is used as a container, and the equipment and pipelines of various subsystems are placed inside the container.

[0030] The topological relationships are read and stored from the topological graph to reconstruct the transformation paths of matter, energy, and information.

[0031] The steps involved in determining the collaborative relationships between topological data based on the mapping relationships between matter, energy, and information, discovering new correlations through self-learning algorithms, and correcting the quantitative attributes in the mapping relationships include:

[0032] Based on the mapping relationships that exist between common substances, energy, and information, the mapping relationships are pre-defined through expert experience, and default qualitative and quantitative relationships are given.

[0033] New associations are discovered and quantitative attributes in mapping relationships are corrected through self-learning algorithms.

[0034] In the steps of discovering new associations and correcting quantitative attributes in mapping relationships through self-learning algorithms, newly discovered associations are reviewed and confirmed by experts before use to ensure their effectiveness.

[0035] In the event of an abnormality in the collaborative relationship, an alarm will be generated and automatically pushed to relevant personnel. The alarm will automatically locate the root cause of the problem and provide handling suggestions based on the pre-set expert experience.

[0036] The system acquires operational data through vibration, temperature, sound, harmful gas concentration, wind speed sensors, and various digital instruments. Based on the various models built into the system, it automatically calibrates the upper and lower limits and provides graded early warnings and alarms.

[0037] A second objective of this invention is to provide a data processing device for an intelligent coal mine system, comprising:

[0038] The hierarchical module is used to identify the types of production equipment in underground coal mines and to set up hierarchical levels according to the types of production equipment.

[0039] The topology construction module is used to construct a system topology diagram of all production equipment based on the topological relationships between production equipment in underground coal mines. It reads and stores the topological relationships from the system topology diagram drawing results to reconstruct the transformation paths of matter, energy, and information.

[0040] The data processing module is used to determine the collaborative relationships between topological data based on the mapping relationship between matter, energy, and information, and to discover new correlations and correct quantitative attributes in the mapping relationship through self-learning algorithms.

[0041] A third objective of the present invention is to provide an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the method described above.

[0042] A fourth objective of this invention is to provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the steps of the method according to the foregoing technical solution.

[0043] Unlike existing technologies, this invention provides a data processing method for intelligent coal mine systems. It identifies the types of production equipment underground and sets up hierarchical levels based on these types. Based on the topological relationships between the production equipment, it constructs a system topology diagram of all production equipment. From the diagram, it reads and stores the topological relationships used to reconstruct the transformation paths of matter, energy, and information. Based on the mapping relationships between matter, energy, and information, it determines the collaborative relationships between topological data and uses a self-learning algorithm to discover new correlations and correct quantitative attributes in the mapping relationships. This invention enables the convenient and rapid integration of various types of data, effectively supporting the rapid implementation of various functions of the intelligent system. Attached Figure Description

[0044] The present invention and / or its additional aspects and advantages will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0045] Figure 1 This is a schematic diagram illustrating the transformation and transfer relationships of key material flows, energy flows, and information flows in the existing coal mining process.

[0046] Figure 2 This is a flowchart illustrating a data processing method for an intelligent coal mine system provided by the present invention.

[0047] Figure 3 This is a schematic diagram of the result of hierarchical setting of object attributes in a data processing method for an intelligent coal mine system provided by the present invention.

[0048] Figure 4 This is a schematic diagram of the interconnection configuration in a data processing method for an intelligent coal mine system provided by the present invention.

[0049] Figure 5 This is a schematic diagram of the structure of a data processing device for an intelligent coal mine system provided by the present invention.

[0050] Figure 6 This is a schematic diagram of the structure of a non-transitory computer-readable storage medium storing computer instructions provided by the present invention. Detailed Implementation

[0051] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0052] The purpose of this invention is to construct a unified and flexible data model method. Based on this method, various types of data can be easily and quickly integrated, effectively supporting the rapid implementation of various functions of intelligent systems. Supported functions include:

[0053] Quickly configure production workflows: Quickly instantiate production workflows by dragging and dropping to match the actual production process.

[0054] Early warning and alarm: The system acquires operating data through sensors such as vibration, temperature, sound, harmful gas concentration, and wind speed, as well as various digital instruments and meters. Based on the various models built into the system, the upper and lower limits are automatically calibrated, and graded early warning and alarm are issued.

[0055] One-click device control: remote start / stop, adjust operating load, restore device status, etc., to assist in remote operation or device recovery.

[0056] Supports production management, operational analysis, and business management: equipment lifecycle management; accident investigation reports and scheduling logs; integrated management of production, sales, and transportation, etc.

[0057] like Figure 2 As shown, an embodiment of the present invention provides a data processing method for an intelligent coal mine system, comprising:

[0058] S110: Identify the types of production equipment in underground coal mines and set up hierarchical classifications based on the types of production equipment.

[0059] The types of mining production equipment supported in this invention include at least coal mining machines, conveyors, crushers, transfer machines, support equipment, water supply and drainage equipment, ventilation equipment, and gas / dust monitoring equipment.

[0060] Based on the type of production equipment, draw hierarchical attribute diagrams for different types of production equipment; such as... Figure 3 As shown, Figure 3 Taking coal mining machines as an example, based on the type and function of mining production equipment, coal mining machines are classified into different levels and grades, resulting in a classification diagram.

[0061] The system pre-configures common device hierarchical configuration information, which can be used directly when it matches the actual scenario. If it does not match, it can be quickly configured by copying and modifying parts, or new device types can be quickly configured through visual orchestration capabilities. In this invention, the system pre-configures some commonly used device types, hierarchical structures, and components. If adjustments are needed, existing settings can be modified, or new settings can be copied and modified.

[0062] The hierarchical configuration information of the hierarchical attribute diagram of different types of production equipment is pre-set, and an object hierarchical attribute storage model is constructed.

[0063] Object configuration: This includes all the equipment to be monitored in each subsystem (coal mining system, coal transportation system, power system, ventilation system, water supply system, drainage system, etc.). It is a specific specification of a type of equipment. For example, there can be multiple coal mining machines of the same type, and multiple scraper conveyors of the same type.

[0064] Object topology configuration: Configure the interconnection relationships between various devices, including interconnections within subsystems and interconnections between subsystems. For devices whose location relationships need to be determined, their relative positions should be specified during configuration. It is recommended to configure with coal and electricity as the main lines, and wind and water as auxiliary lines.

[0065] The hierarchical attribute storage model for objects is shown in Table 1:

[0066]

[0067] Table 1 Object Hierarchical Attribute Storage Model

[0068] S120: Based on the topological relationships between production equipment in underground coal mines, construct a system topology diagram of all production equipment, and read and store the topological relationships of the transformation paths of matter, energy and information from the drawing results of the system topology diagram.

[0069] The ability to visualize and draw topology relationships allows for the creation of various subsystem topology diagrams, where a single device may involve multiple subsystems.

[0070] The tunnel is used as a container, housing the equipment and piping of various subsystems; for example... Figure 4 As shown.

[0071] A pre-defined, universal coal mining production workflow can be used directly when it matches the actual scenario. If it does not match, it can be quickly configured by copying and making partial modifications. Alternatively, a new interconnection model can be quickly configured through visual orchestration capabilities.

[0072] The topological relationships are read and stored from the topological diagram to reconstruct the transformation paths of matter, energy, and information. The transformation paths are shown in Table 2.

[0073]

[0074] Table 2. Transformation Pathways of Matter, Energy, and Information

[0075] S130: Based on the mapping relationship between matter, energy, and information, determine the collaborative relationship between topological data, discover new correlations and correct quantitative attributes in the mapping relationship through self-learning algorithms.

[0076] As shown in Table 3, there are common mapping relationships between matter, energy, and information. These mapping relationships can be preset through expert experience, and default qualitative and quantitative relationships can be given.

[0077]

[0078] Table 3. Mapping Relationships Among Matter, Energy, and Information

[0079] New associations are discovered and quantitative attributes in mapping relationships are corrected through self-learning algorithms.

[0080] For newly discovered relationships, they should be verified and confirmed by experts before use to ensure their effectiveness.

[0081] Specifically, examples of pre-defined data collaboration relationships are shown in Table 4:

[0082]

[0083] Table 4 shows examples of pre-defined data collaboration relationships. Table 5 shows examples of data collaboration relationships that may be obtained through self-learning.

[0084]

[0085] Table 5. Examples of data collaboration relationships obtained through self-learning

[0086] In practical use, system anomalies can be detected by the synergistic relationship between coal and electricity. For example, if the power consumption is stable but the coal output is significantly reduced, it may be due to coal blockage on the belt conveyor or an abnormality in the cutting section of the coal mining machine.

[0087] Abnormal situations will generate alarms in a timely manner and automatically push them to relevant personnel. The alarms will automatically locate the root cause of the problem and can automatically provide handling suggestions based on the pre-set expert experience.

[0088] The system graphically displays the connection information between devices in the same space and time, displays the attribute information of the devices themselves in layers and levels, and shows the transfer and transformation relationships of matter and energy on different devices, giving users an immersive control experience.

[0089] The present invention has the following beneficial effects:

[0090] 1. By providing flexible device tiered configuration and storage solutions, as well as flexible interconnection configuration and storage solutions, the adaptability of the data model can be greatly improved, reducing the cost pressure brought by custom development.

[0091] 2. By providing default configurations for object properties, device interconnection relationships, and data collaboration relationships, as well as a visual orchestration method, the complexity of operations is reduced, implementation efficiency is improved, and the schedule pressure brought by custom development is reduced.

[0092] 3. By uncovering the data collaboration relationships between different subsystems, we can effectively warn or discover risks and problems that are not easily found in single-system data, and provide strong evidence for locating the root cause of the problem.

[0093] 4. By providing convenient data integration solutions for multiple systems, and by filling in missing data and deriving richer data through the inherent logical relationships between data, the value of data can be maximized.

[0094] like Figure 5 As shown, the present invention provides a data processing device 300 for an intelligent coal mine system, comprising:

[0095] The hierarchical module 310 is used to identify the types of production equipment in underground coal mines and to set up hierarchical levels according to the types of production equipment.

[0096] The topology construction module 320 is used to construct a system topology diagram of all production equipment based on the topological relationships between production equipment in underground coal mines. It reads and stores the topological relationships from the system topology diagram drawing results to reconstruct the transformation paths of matter, energy, and information.

[0097] The data processing module 330 is used to determine the collaborative relationship between topological data based on the mapping relationship between matter, energy and information, and to discover new correlations and correct quantitative attributes in the mapping relationship through a self-learning algorithm.

[0098] To implement the embodiments, the present invention also proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the data processing method for an intelligent coal mine system described above.

[0099] like Figure 6 As shown, the non-transitory computer-readable storage medium 800 includes a memory 810 for instructions and an interface 830, the instructions of which can be executed by a data processing processor 820 for an intelligent coal mine system to complete the method. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0100] To implement the embodiments, the present invention also proposes a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs data processing for an intelligent coal mine system as described in the embodiments of the present invention.

[0101] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0102] Furthermore, 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 technical features indicated. 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.

[0103] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0105] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the described embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0106] Those skilled in the art will understand that all or part of the steps of the method described in the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0107] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned may be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the embodiments within the scope of the present invention.

Claims

1. A data processing method for an intelligent coal mine system, characterized in that, include: Identify the types of production equipment in underground coal mines and set up hierarchical classifications based on these types, including: Identify the types of production equipment in underground coal mines; wherein, the types of production equipment include at least coal mining machines, conveyors, crushers, transfer machines, support equipment, water supply and drainage equipment, ventilation equipment, and gas / dust monitoring equipment; Draw a hierarchical attribute diagram for different types of production equipment, wherein the hierarchical attribute diagram includes: the hierarchical structure and component settings of different types of production equipment; The hierarchical configuration information in the hierarchical attribute diagram of different types of production equipment is pre-set, and an object hierarchical attribute storage model table is constructed. The hierarchical configuration information includes: all the equipment to be monitored in each subsystem that needs to be monitored, as well as the interconnection of each equipment within the subsystem and the interconnection between subsystems. Based on the topological relationships between production equipment in underground coal mines, a system topology diagram of all production equipment is constructed. The topological relationships of the transformation paths of matter, energy, and information are read and stored from the drawing results of the system topology diagram. Based on the mapping relationship between matter, energy, and information, the collaborative relationship between topological data is determined. New correlations are discovered and quantitative attributes in the mapping relationship are corrected through a self-learning algorithm. The collaborative relationship represents the transfer and transformation relationship of matter and energy on different devices.

2. The data processing method for an intelligent coal mine system according to claim 1, characterized in that, Based on the topological relationships between production equipment in underground coal mines, a system topology diagram of all production equipment is constructed. The steps of reading and storing the topological relationships used to reconstruct the transformation paths of matter, energy, and information from the system topology diagram include: The ability to visualize and draw topological relationships allows for the creation of various subsystem topology diagrams, where a single device may involve multiple subsystems. The tunnel is used as a container, and the equipment and pipelines of various subsystems are placed inside the container. The topological relationships are read and stored from the topological graph to reconstruct the transformation paths of matter, energy, and information.

3. The data processing method for an intelligent coal mine system according to claim 1, characterized in that, Based on the mapping relationship between matter, energy, and information, the steps to determine the collaborative relationship between topological data, discover new correlations through self-learning algorithms, and correct the quantitative attributes in the mapping relationship include: Based on the mapping relationships that exist between common substances, energy, and information, the mapping relationships are pre-defined through expert experience, and default qualitative and quantitative relationships are given. New associations are discovered and quantitative attributes in mapping relationships are corrected through self-learning algorithms.

4. The data processing method for an intelligent coal mine system according to claim 3, characterized in that, In the steps of discovering new associations and correcting quantitative attributes in mapping relationships through self-learning algorithms, newly discovered associations are reviewed and confirmed by experts before use to ensure their effectiveness.

5. The data processing method for an intelligent coal mine system according to claim 3, characterized in that, If an abnormality occurs in the collaboration relationship, an alarm will be generated and automatically pushed to relevant personnel. The alarm will automatically locate the root cause of the problem and provide handling suggestions based on the preset expert experience.

6. The data processing method for an intelligent coal mine system according to claim 5, characterized in that, The system acquires operational data through vibration, temperature, sound, harmful gas concentration, wind speed sensors, and various digital instruments. Based on the various models built into the system, it automatically calibrates the upper and lower limits and provides graded early warnings and alarms.

7. A data processing device for an intelligent coal mine system, characterized in that, include: The hierarchical classification module is used to identify the types of production equipment in coal mines and to set hierarchical classifications according to the types of production equipment. This includes: identifying the types of production equipment in coal mines; wherein the types of production equipment include at least coal mining machines, conveyors, crushers, transfer machines, support equipment, water supply and drainage equipment, ventilation equipment, and gas / dust monitoring equipment. Draw a hierarchical attribute diagram for different types of production equipment, wherein the hierarchical attribute diagram includes: the hierarchical structure and component settings of different types of production equipment; The hierarchical configuration information in the hierarchical attribute diagram of different types of production equipment is pre-set, and an object hierarchical attribute storage model table is constructed. The hierarchical configuration information includes: all the equipment to be monitored in each subsystem that needs to be monitored, as well as the interconnection of each equipment within the subsystem and the interconnection between subsystems. The topology construction module is used to construct a system topology diagram of all production equipment based on the topological relationships between production equipment in underground coal mines. It reads and stores the topological relationships from the drawing results of the system topology diagram to reconstruct the transformation paths of matter, energy, and information. The data processing module is used to determine the collaborative relationships between topological data based on the mapping relationship between matter, energy, and information, and to discover new correlations and correct quantitative attributes in the mapping relationship through a self-learning algorithm. The collaborative relationship represents the transfer and transformation relationship of matter and energy on different devices.

8. An electronic device, comprising: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the method according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform each step of the method according to any one of claims 1-6.

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