A three-dimensional comprehensive wiring method and system for a mine electrical cabinet cable network

Abstract

The present application relates to the technical field of mine electrical equipment wiring management, and particularly relates to a mine electrical cabinet cable network three-dimensional comprehensive wiring method and system. The method comprises the following steps: performing electrical cabinet packaging model design of structure and interface based on mine electrical cabinet physical structure heterogeneous data and mine electrical cabinet electrical element interface data, and generating a packaging electrical cabinet structure-interface model; performing beam management analysis and processing of cable connection topology requirements based on the packaging electrical cabinet structure-interface model, and generating cable connection topology requirement beam management data; performing three-dimensional cable wiring constraint field analysis on the packaging electrical cabinet structure-interface model, and generating three-dimensional cable wiring constraint field data; and performing spatial constraint cable three-dimensional wiring path analysis based on the cable connection topology requirement beam management data and the three-dimensional cable wiring constraint field data, and generating cable three-dimensional wiring path data. The present application realizes intelligent wiring of mine electrical cabinet ground cable network.

Description

Technical Field

[0001] This invention relates to the field of wiring management technology for electrical equipment in mines, and in particular to a three-dimensional integrated wiring method and system for cable networks in mine electrical cabinets. Background Technology

[0002] As the core hub of the electrical control system in mining operations, the mine electrical cabinet undertakes key functions such as power distribution, signal transmission, and equipment control. The quality of its internal cable network directly determines the operational stability, reliability, and ease of maintenance of the electrical system. With the development of intelligent and large-scale mining technology, the integration level of mine electrical cabinets is constantly increasing, the number of internal electrical components is surging, interface types are becoming more diverse, and cable connections are becoming increasingly complex. However, existing cable network wiring methods for mine electrical cabinets mainly rely on manual experience combined with two-dimensional drawings for planning and implementation. This easily leads to unreasonable wiring path planning, a lack of systematic bundle management of cable connection topology, increased difficulty in wiring construction management, and an inability to accurately identify different levels of spatial characteristics such as wiring areas and component installation areas. This results in planned wiring paths easily conflicting with the cabinet's load-bearing structure and internal components. Furthermore, in the wiring conflict optimization stage, the high requirements for cable wiring mechanical stability and anti-interference, coupled with the lack of a proactive optimization mechanism for cable conflicts, lead to problems such as low efficiency, poor accuracy, and insufficient reliability in wiring. Summary of the Invention

[0003] Based on this, the present invention provides a three-dimensional integrated cabling method and system for electrical cabinet cable networks in mines, in order to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a three-dimensional integrated cabling method for electrical cabinet cable networks in mines includes the following steps:

[0005] Step S1: Obtain heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet; design the electrical cabinet encapsulation model of structure and interface based on the heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet, and generate the encapsulated electrical cabinet structure-interface model.

[0006] Step S2: Based on the encapsulated electrical cabinet structure-interface model, perform bundle management analysis and processing of cable connection topology requirements to generate cable connection topology requirement bundle management data;

[0007] Step S3: Perform 3D cable routing constraint domain analysis on the encapsulated electrical cabinet structure-interface model to generate 3D cable routing constraint domain data;

[0008] Step S4: Map the cable connection topology requirement bundle management data to the three-dimensional cable routing constraint domain data to perform spatial constraint cable three-dimensional routing candidate path analysis and generate cable three-dimensional routing candidate path data;

[0009] Step S5: Perform cable conflict optimization processing on the candidate path data of the three-dimensional cable routing to generate the three-dimensional cable routing path data.

[0010] Furthermore, step S5 includes the following steps:

[0011] Step S51: Perform cable routing cooperative conflict feature analysis based on the cable 3D routing candidate path data to generate cable routing cooperative conflict feature data;

[0012] Step S52: Based on the cable routing coordination conflict characteristic data, perform cable conflict relationship assessment processing to generate cable conflict relationship assessment data;

[0013] Step S53: Use the cable conflict relationship assessment data to perform local replanning of the conflict paths in the cable 3D routing candidate path data, and generate replanned cable 3D routing candidate path data;

[0014] Step S54: Perform global optimization processing on the candidate paths of the replanned cable 3D routing to generate cable 3D routing path data.

[0015] This specification provides a three-dimensional integrated cabling system for mine electrical cabinet cable networks, used to implement the three-dimensional integrated cabling method for mine electrical cabinet cable networks as described above. The three-dimensional integrated cabling system for mine electrical cabinet cable networks includes:

[0016] The electrical cabinet structure-interface model building module is used to acquire heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets; based on the heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets, the module designs the electrical cabinet encapsulation model of structure and interface, and generates the encapsulated electrical cabinet structure-interface model.

[0017] The cable connection topology requirement analysis module is used to perform bundle management analysis and processing of cable connection topology requirements based on the encapsulated electrical cabinet structure-interface model, and generate cable connection topology requirement bundle management data.

[0018] The cable routing constraint domain analysis module is used to perform three-dimensional cable routing constraint domain analysis on the structure-interface model of the encapsulated electrical cabinet and generate three-dimensional cable routing constraint domain data.

[0019] The cabling candidate path analysis module is used to map cable connection topology requirement bundle management data to three-dimensional cable cabling constraint domain data for spatial constraint three-dimensional cable cabling candidate path analysis, and generate three-dimensional cable cabling candidate path data.

[0020] The cable 3D routing path analysis module is used to optimize the cable conflict of the candidate path data and generate cable 3D routing path data.

[0021] The beneficial effects of this application are as follows: This invention acquires heterogeneous physical structure data and electrical component interface data of mining electrical cabinets through a system, achieving comprehensive coverage of the core basic data of the electrical cabinets. Based on the heterogeneous physical structure data and electrical component interface data of the mining electrical cabinets, a structural and interface encapsulation model of the electrical cabinet is designed, transforming scattered heterogeneous data into structured geometric and functional data. On this basis, hierarchical 3D modeling, interface characteristic identification, and model attribute encapsulation are completed, generating an encapsulated electrical cabinet structure-interface model. This achieves the organic integration and precise mapping of the physical structure and electrical interface features of the electrical cabinet, solving the defect that traditional 2D drawings cannot intuitively present 3D spatial relationships. At the same time, the precise identification of the hierarchical entity structure makes key areas such as the load-bearing structure and the wiring area clearly identifiable, while the attribute identification of the electrical component interfaces ensures the accurate association of interface information, significantly reducing design deviations caused by missing data or insufficient spatial awareness in subsequent wiring planning, and improving the accuracy and efficiency of the overall wiring design. Based on the structure-interface model of the encapsulated electrical cabinet, this paper analyzes and processes the bundled management of cable connection topology requirements. First, electrical connection characteristics are screened and verified to ensure the compliance and accuracy of connection relationships. Then, the topological structural relationships are analyzed in depth to complete the bundled management of cable connection topology requirements. A systematic bundled management mechanism based on electrical control logic is established, which changes the problem of traditional cabling relying on manual experience for cable bundling, which is prone to disorder. This mechanism not only allows for the scientific classification of closely related cables, reducing the difficulty of organization and management during cabling construction, but also improves the standardization of cable cabling, reduces signal interference between cables with different functions, and provides clear and orderly topology guidance for subsequent cable cabling path planning, ensuring efficient progress and high-quality cabling. A three-dimensional cable cabling constraint domain analysis is performed on the structure-interface model of the encapsulated electrical cabinet, realizing a refined disassembly of the internal space of the electrical cabinet and precise mining of constraint features. Among these methods, spatial voxelization discretization transforms the continuous electrical cabinet space into precisely analyzable voxel units, improving the accuracy of constraint analysis. The classification of voxelized spatial wiring types and the analysis of constraint characteristics accurately identify different levels of spatial constraint features, such as wired areas, prohibited wiring areas, and component installation avoidance areas. The integrated 3D cable wiring constraint domain data clearly defines the feasible space and constraints for cable wiring. This effectively solves the problems of inaccurate identification of internal spatial features and conflicts between wiring paths and supporting structures or internal components, significantly reducing invalid searches in candidate path planning, improving path search efficiency, and avoiding wiring conflicts from the source. Mapping cable connection topology requirement bundle management data to 3D cable wiring constraint domain data for spatially constrained 3D cable wiring candidate path analysis achieves the fusion of topology requirements and spatial constraints, providing a comprehensive and accurate basis for candidate path analysis.First, cable connection path units are established based on topology bundle data to clarify the basic unit modules of cabling. Then, feasible search space analysis is used to lock in the search range that meets spatial constraints, reducing ineffective search costs. Subsequently, a comprehensive path evaluation system is constructed through multi-dimensional prior data analysis, including movement cost, occupancy cost, and turning impact. Based on this, targeted cabling path search strategies are designed to achieve intelligent search for candidate paths for 3D cable cabling under spatial constraints. This addresses the subjectivity and limitations of planned paths, not only quickly generating multiple candidate paths that meet topology requirements and spatial constraints, but also ensuring the rationality and feasibility of candidate paths through multi-dimensional cost analysis. Cable conflict optimization processing is performed on the candidate path data for 3D cable cabling. First, collaborative conflict feature analysis is performed on the candidate path data to accurately identify potential conflict points and conflict types between paths. Then, the conflict degree is quantified through conflict relationship evaluation to provide data support for optimization strategy formulation. Subsequently, local replanning is performed on conflicting paths to quickly eliminate local conflicts. Finally, global optimization processing is used to coordinate the spatial layout of all paths to ensure that the final generated 3D cable cabling path data is optimal overall. This process not only completely avoids conflicts between cables and between cables and electrical cabinet components, but also takes into account engineering requirements such as the mechanical stability and reasonable length of cable wiring during the optimization process. Ultimately, it outputs a high-quality wiring path solution, ensuring the operational reliability of the mine electrical cabinet cable network, reducing construction difficulty and later maintenance costs, and helping to achieve intelligent and refined design of mine electrical cabinet wiring.

[0022] Therefore, the three-dimensional integrated cabling method for cable networks in mine electrical cabinets of the present invention can effectively solve the above-mentioned problems in the prior art and has significant beneficial effects: By constructing an encapsulated electrical cabinet structure-interface model, the physical structure and electrical interface characteristics of the electrical cabinet are accurately integrated, replacing the planning mode of manual experience combined with two-dimensional drawings, presenting the internal three-dimensional spatial relationship, and avoiding the problem of unreasonable cabling path planning; through the bundle management analysis of cable connection topology requirements, a systematic bundle management mechanism based on electrical control logic is established, which greatly reduces the difficulty of cabling construction management and improves the standardization and anti-interference capability of cabling; targeted three-dimensional cable cabling constraint domain analysis can accurately identify different levels of spatial characteristics such as cabling areas and component installation areas, effectively avoiding spatial conflicts between cabling paths and the load-bearing structure and internal components of the electrical cabinet, and improving design and construction efficiency; through the cable conflict optimization processing of candidate paths, a cable conflict active optimization mechanism is constructed, which, combined with the high requirements of the harsh working conditions of mines for the mechanical stability and anti-interference of cables, realizes the global optimization of cabling paths, and ultimately significantly improves the efficiency, accuracy and reliability of cable cabling, providing strong technical support for improving the design quality of mine electrical cabinets and the intelligent upgrading of mine electrical systems. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the steps of an intelligent medication management method according to the present invention;

[0024] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S4.

[0025] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. Functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods. The term "and / or" as used herein includes any and all combinations of one or more of the associated items listed.

[0028] To achieve the above objectives, please refer to Figures 1 to 2 This invention provides a three-dimensional integrated cabling method and system for electrical cabinet cable networks in mines. In the embodiments of this invention, please refer to... Figure 1 The diagram shown is a flowchart illustrating the steps of a three-dimensional integrated cabling method for a mine electrical cabinet cable network according to the present invention. The three-dimensional integrated cabling method for a mine electrical cabinet cable network includes the following steps:

[0029] Step S1: Obtain heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet; design the electrical cabinet encapsulation model of structure and interface based on the heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet, and generate the encapsulated electrical cabinet structure-interface model.

[0030] In this embodiment of the invention, heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet are collected. The heterogeneous physical structure data includes the overall outline of the cabinet frame, the distribution of internal partitions, the installation orientation of guide rails, the structural form of fixed brackets and the connection method of each component, collected by different monitoring equipment (such as two-dimensional imaging equipment, three-dimensional imaging equipment, laser monitoring equipment, etc.). The electrical component interface data includes the interface type, pin arrangement, signal transmission type, rated voltage and current parameters and the installation position of the component where the interface is located for various electrical components. Based on the above two types of data, the design of the electrical cabinet encapsulation model for structure and interface is carried out. First, heterogeneous geometric analysis is performed on the heterogeneous physical structure data to extract the geometric feature parameters of each structural component and perform standardization processing. Then, based on a unified three-dimensional coordinate system, a three-dimensional spatial mapping of heterogeneous geometry is completed to establish the spatial positional relationship between each structural component. At the same time, functional component analysis is carried out on the heterogeneous physical structure data to distinguish the components corresponding to the load-bearing structure, wiring area, and component installation area. Subsequently, the heterogeneous geometric spatial mapping data and functional component data are integrated to construct a three-dimensional model of the electrical cabinet hierarchical structure, clarifying the spatial boundaries and functional attributes of each level of structure. Based on the interface data of electrical components, the core attributes and connection requirements of the interface are parsed. Combined with the analysis of the three-dimensional structural model, the spatial correspondence between the interface and the structural model is analyzed, and the interface parsing data is accurately mapped to the corresponding position in the three-dimensional model to complete the spatial interface characteristic identification. Finally, the structural features, interface characteristics, and functional attribute information of the three-dimensional model are integrated to complete the model attribute feature encapsulation, forming a complete encapsulated electrical cabinet structure-interface model, realizing the integrated integration of the electrical cabinet physical structure and electrical interface information.

[0031] Step S2: Based on the encapsulated electrical cabinet structure-interface model, perform bundle management analysis and processing of cable connection topology requirements to generate cable connection topology requirement bundle management data;

[0032] In this embodiment of the invention, the cable connection topology requirements are analyzed and managed based on the encapsulated electrical cabinet structure-interface model. The connection relationships of various electrical components and their corresponding electrical control logic rules are extracted from the encapsulation model, clarifying the electrical control logic associations of different circuits such as power circuits, signal circuits, and control circuits. Based on the extracted electrical control logic rules, electrical connection characteristics are analyzed, clarifying the connection paths, signal transmission directions, and necessity of connections between various electrical components, forming electrical connection characteristic data. The electrical connection characteristic data is then standardized and verified according to relevant specifications for mine electrical equipment wiring, eliminating non-compliant connections and correcting connection data with deviations in connection parameters, generating verified electrical connection characteristic data. Based on the verified electrical connection characteristic data, electrical connection topology relationships are analyzed, clarifying the hierarchical relationships of each component in the electrical circuit, and constructing a multi-level topology including main circuits and branch circuits. Based on electrical connection topology data, a bundle management analysis of cable connection topology requirements is conducted. First, basic cable connection information is extracted, including the starting and ending components and loop type. Then, the multi-level connection relationships of cables are analyzed to clarify the connection associations of cables in different loop levels. At the same time, the cable connection engineering attributes are analyzed, including the cable's function and transmission characteristic requirements. The above three types of data are integrated, and the cables are divided into different bundles according to the degree of functional association, loop type consistency, and signal interference avoidance requirements. The cable composition, connection range, and wiring priority of each bundle are clarified, generating bundle management data for cable connection topology requirements.

[0033] Step S3: Perform 3D cable routing constraint domain analysis on the encapsulated electrical cabinet structure-interface model to generate 3D cable routing constraint domain data;

[0034] In this embodiment of the invention, a three-dimensional cable routing constraint domain analysis is conducted based on the structure-interface model of the encapsulated electrical cabinet. First, the overall space available for cable routing within the electrical cabinet is defined, and the boundary conditions of the routing space are delineated, generating the electrical cabinet spatial computational domain data. The electrical cabinet spatial computational domain data undergoes spatial voxel discretization processing, dividing the overall routing space into several uniform voxel units. The morphological characteristics of the routing space are accurately represented through the combination of voxel units, generating the electrical cabinet spatial voxel discretized data. Based on the electrical cabinet spatial voxel discretized data, voxel spatial routing types are classified. According to the spatial location of the voxel unit and the surrounding structural characteristics, free routing voxel areas, restricted routing voxel areas, and prohibited routing voxel areas are distinguished. The prohibited routing voxel areas correspond to unoccupiable structural areas such as the cabinet frame and fixed supports, while the restricted routing voxel areas correspond to areas near heat-generating components and strong electromagnetic interference components. Cable routing constraint feature analysis is conducted for different types of voxelized spaces to extract routing restrictions for each type of region, including routing direction constraints in free routing voxel areas, routing distance and anti-interference constraints in restricted routing voxel areas, and absolute occupancy constraints in prohibited routing voxel areas, generating voxelized space cable routing constraint feature data. The routing constraint feature data of all voxelized spaces are integrated to establish the correlation between various constraints, clarify the priority of routing constraints in different regions, complete the integrated processing of the 3D cable routing constraint domain, and generate 3D cable routing constraint domain data, achieving a comprehensive and accurate characterization of the routing space constraints within the electrical cabinet.

[0035] Step S4: Map the cable connection topology requirement bundle management data to the three-dimensional cable routing constraint domain data to perform spatial constraint cable three-dimensional routing candidate path analysis and generate cable three-dimensional routing candidate path data;

[0036] In this embodiment of the invention, cable connection topology requirement bundle management data is mapped to three-dimensional cable routing constraint domain data to conduct spatially constrained three-dimensional cable routing candidate path analysis. Based on the connection start point, connection end point, and routing priority of each bundle group in the cable connection topology requirement bundle management data, cable connection path units corresponding to each bundle group are established. Each path unit corresponds to the routing channel requirement of a single bundle group from the start element interface to the end element interface, generating cable connection path unit data. The cable connection path unit data is spatially correlated with the three-dimensional cable routing constraint domain data to clarify the routing space range corresponding to each path unit, exclude spaces corresponding to prohibited routing voxel areas, determine the spatial range in which routing searches can be conducted for each path unit, and generate feasible search space data for path units. Based on the feasible search space data of path units, prior data analysis of feasible cable connection paths is conducted to extract spatial topological features within the feasible search space, including connected voxel unit combinations, voxel unit densities in different regions, and feasible turning node positions, generating prior data for feasible cable connection paths. Based on prior data of feasible cable connection paths, spatial feasible path movement cost, occupancy cost, and turning impact analyses are conducted. Movement cost analysis assesses the ease of cabling based on spatial characteristics related to path length; occupancy cost analysis assesses the rationality of cabling's use of space resources based on the scarcity of spatial voxel units; and turning impact analysis assesses the degree of cabling's impact on signal transmission based on the number and angle of turning nodes, generating corresponding cost data for each. A search strategy for cable connection cabling paths is designed by integrating these three types of cost data, establishing a path search criterion based on cost priority, and prioritizing the path direction with the optimal comprehensive cost across the three types. Based on the designed cable connection cabling path search strategy, an intelligent search for candidate 3D cable cabling paths under spatial constraints is performed on the feasible search spatial data of path units. Feasible voxel unit combinations are traversed, generating multiple candidate paths that meet spatial constraints and bundling requirements. Each candidate path clearly defines its corresponding voxel unit sequence and cabling direction, generating candidate 3D cable cabling path data.

[0037] Step S5: Perform cable conflict optimization processing on the candidate path data of the three-dimensional cable routing to generate the three-dimensional cable routing path data.

[0038] In this embodiment of the invention, cable conflict optimization processing is performed on the candidate path data for three-dimensional cable routing to generate three-dimensional cable routing path data. First, the spatial location information of all candidate paths in the three-dimensional cable routing candidate path data is extracted, including the voxel unit occupancy range, routing direction, and spatial distribution characteristics of each path. Cable routing collaborative conflict characteristic analysis is then performed to identify the overlapping occupancy of different candidate paths in the same voxel unit area and the cross-interference of different path routing directions. The spatial location of the conflict, the path bundles involved, and the severity of the conflict are determined, generating cable routing collaborative conflict characteristic data. Based on the cable routing collaborative conflict characteristic data, cable conflict relationship evaluation processing is performed. Based on the path priority involved in the conflict, the spatial importance of the conflict area, and the degree of impact of the conflict on the routing function, conflict evaluation standards are established. Various types of conflicts are quantitatively evaluated, and the processing priority of the conflicts is determined, generating cable conflict relationship evaluation data. Based on cable conflict assessment data, local replanning of conflicting cable 3D routing candidate path data is performed. For path areas corresponding to high-priority conflicts, the voxel selection of conflicting paths is adjusted to avoid conflict areas, and the local routing is replanned to ensure that the adjusted paths still meet the requirements of the 3D cable routing constraint domain, generating replanned cable 3D routing candidate path data. Global optimization of the candidate paths is then performed on the replanned cable 3D routing candidate path data, coordinating the path distribution of all bundles, balancing the routing density in each area, ensuring uniform overall routing space distribution, and considering the rationality of routing length and signal transmission stability of each path. Paths with potential conflict risks and functional defects are eliminated, and the overall optimal path combination is selected to generate cable 3D routing path data, ensuring that the final routing path meets all spatial constraints, bundle requirements, and functional requirements.

[0039] Furthermore, step S1 includes the following steps:

[0040] Step S11: Obtain heterogeneous physical structure data of the mining electrical cabinet and interface data of electrical components of the mining electrical cabinet;

[0041] In this embodiment of the invention, a multi-device collaborative acquisition mechanism is employed to acquire heterogeneous physical structure data and electrical component interface data of the mining electrical cabinet. The heterogeneous physical structure data is acquired collaboratively using two-dimensional high-definition imaging equipment, three-dimensional laser scanning equipment, and high-precision infrared ranging equipment. This acquisition targets the electrical cabinet as a whole and its internal core components, covering the overall dimensions of the cabinet (length, width, and height), the material properties and cross-sectional shape of the cabinet frame, the thickness, installation height, and fixing hole distribution of the internal horizontal and vertical partitions, the model specifications, installation spacing, and extension length of the guide rails, the structural form, installation orientation, and load-bearing parameters of various fixing brackets, and the connection methods and assembly gaps of all structural components. For example, the acquisition covers the overall outline dimensions of the mining electrical cabinet frame (length 800mm × width 600mm × height 1200mm), the distribution positions of the internal horizontal partitions at 300mm, 600mm, and 900mm from the bottom surface of the cabinet, the installation orientation of the vertical guide rails arranged longitudinally along the inner walls of both sides of the cabinet, and the structural form of the L-shaped fixing bracket (thickness 8mm, hole diameter 12mm) and the connection method between the bracket and the cabinet frame via bolts. The electrical component interface data acquisition covers all electrical components in the electrical cabinet, including the interface types of various components such as circuit breakers, contactors, relays, and sensors; the number, spacing, and distribution of pins; the signal transmission type corresponding to the interface, including power signals, control signals, and detection signals; the rated voltage, rated current, and insulation level parameters of the interface; for example, the specific arrangement of pins using a 2×5 matrix; the signal transmission type of analog or digital signals; the rated voltage and current parameters of AC380V and 50A; and the installation position of each interface component in the 200mm×150mm area on the left side of the middle partition of the cabinet. At the same time, the specific installation position of each interface electrical component and its relative distance to surrounding structural components are recorded to ensure that both types of data completely cover the core characteristics of the electrical cabinet structure and electrical interfaces.

[0042] Step S12: Perform heterogeneous geometric analysis on the physical structure heterogeneous data of the mine electrical cabinet to generate heterogeneous geometric data of the electrical cabinet structure;

[0043] In this embodiment of the invention, heterogeneous geometric analysis of the physical structure of mining electrical cabinets is conducted. First, the structural data collected from different devices are standardized, converting pixel coordinate data from 2D imaging devices, point cloud data from 3D laser scanning devices, and distance data from infrared ranging devices into a unified 3D Cartesian coordinate data format. Next, the data is categorized and sorted to distinguish heterogeneous data corresponding to different types of structural components such as cabinet frames, partitions, guide rails, and supports. For each type of structural component, geometric feature parameters are extracted based on the converted coordinate data, including linear dimensions, cross-sectional shape parameters, surface curvature (if present), hole location coordinates and dimensions, and relative positional deviations between components. The extracted geometric feature parameters are then standardized, unifying the units of measurement and data format to eliminate errors caused by different acquisition methods. By using geometric feature matching and difference analysis, the geometric heterogeneity characteristics between different structural components are identified, such as the differences in cross-sectional shape between frames and partitions, and the differences in structural morphology between different supports, thus clarifying the geometric boundary conditions of various structural components. The processed geometric feature parameters are then systematically integrated to form heterogeneous geometric data of the electrical cabinet structure. This data accurately characterizes the geometric attributes and heterogeneous features of various structural components.

[0044] Step S13: Perform three-dimensional spatial mapping processing for heterogeneous geometry alignment based on the heterogeneous geometric data of the electrical cabinet structure to generate heterogeneous geometric spatial mapping data of the electrical cabinet;

[0045] In this embodiment of the invention, a three-dimensional spatial mapping process for heterogeneous geometric alignment is performed based on the heterogeneous geometric data of the electrical cabinet structure. A unified three-dimensional spatial coordinate system is established, with the lower left corner vertex of the bottom surface of the electrical cabinet as the origin, the depth direction of the cabinet as the X-axis, the height direction as the Y-axis, and the width direction as the Z-axis. The unit length and directional reference of the coordinate system are determined. For the geometric feature parameters of various structural components in the heterogeneous geometric data of the electrical cabinet structure, the coordinates of key feature points of each component are extracted, including the core positions such as the vertex, center point, and hole center of the component. Based on the unified coordinate system, the coordinates of key feature points of different structural components are transformed and aligned to eliminate the coordinate system differences between different components in the original acquired data, ensuring that the geometric data of all structural components are mapped to the same three-dimensional spatial coordinate system. Through spatial coordinate association, the spatial positional relationship between each structural component is established, clarifying the spatial constraints such as relative distance, parallelism, and perpendicularity between components. The aligned geometric data and spatial positional relationships of all structural components are integrated to generate heterogeneous geometric spatial mapping data of the electrical cabinet.

[0046] Step S14: Analyze the functional components of the electrical cabinet based on the heterogeneous physical structure data of the mine electrical cabinet, and generate functional component data of the electrical cabinet;

[0047] In this embodiment of the invention, functional component analysis of the heterogeneous physical structure data of mining electrical cabinets is conducted. First, based on the working principle and functional requirements of the mining electrical cabinets, the functional classification standards of the internal components are clarified, dividing them into four categories: load-bearing structural components, wiring area components, component installation area components, and auxiliary fixing components. Based on this classification standard, functional matching is performed on various structural components in the heterogeneous physical structure data to determine the functional attributes of each component. For load-bearing structural components, their load-bearing strength, support range, and impact on the overall cabinet structural stability are analyzed, including the cabinet frame and main support partitions. For wiring area components, their spatial range, wiring channel dimensions, and spacing with surrounding components are analyzed, including wiring channels, wire frames, and gaps between partitions. For component installation area components, their installation accuracy, load-bearing capacity, and component fixing methods are analyzed, including guide rails, component mounting plates, and fixing brackets. For auxiliary fixing components, their fixing objects, fixing strength, and assembly methods are analyzed. The functional attributes, functions, and related structural parameters of various components are integrated to generate functional component data for the electrical cabinet.

[0048] Step S15: Based on the heterogeneous geometric space mapping data of the electrical cabinet and the functional component data of the electrical cabinet, establish a three-dimensional model of the hierarchical structure of the electrical cabinet and generate a three-dimensional model of the electrical cabinet structure.

[0049] In this embodiment of the invention, a three-dimensional model of the hierarchical structure of the electrical cabinet is established based on heterogeneous geometric spatial mapping data and functional component data of the electrical cabinet. First, the two types of data are integrated. Using the three-dimensional spatial coordinates in the heterogeneous geometric spatial mapping data as a foundation, the geometric features and functional attributes of various components in the functional component data are associated with their corresponding spatial positions. Based on the functional attributes and spatial distribution of the components, a preliminary three-dimensional model of the electrical cabinet structure is constructed, which presents the three-dimensional spatial form and preliminary positional relationships of various components. Based on the functional component data of the electrical cabinet, a hierarchical solid structure feature analysis of the electrical cabinet is conducted, extracting the core features of the load-bearing structure layer, the wiring area layer, and the component mounting area layer. The features of the load-bearing structure layer include the three-dimensional shape of the overall support frame, the spatial distribution of key support points, and the load-bearing range. The features of the wiring area layer include the three-dimensional contours of various wiring channels, the channel cross-sectional dimensions, and connectivity. The features of the component mounting area layer include the three-dimensional distribution of guide rails, the spatial position of mounting plates, and the three-dimensional coordinates of fixing holes, forming the hierarchical solid structure feature data of the electrical cabinet. Using the hierarchical entity structure feature data, the preliminary three-dimensional model of the electrical cabinet structure is identified with hierarchical structure entities. The spatial boundaries of the load-bearing structure layer, the wiring area layer, and the component installation area layer are clearly defined in the model. The functional attributes and core feature parameters of each layer are labeled to generate the three-dimensional model of the electrical cabinet structure.

[0050] Step S16: Based on the interface data of the electrical components of the mine electrical cabinet, perform spatial interface characteristic identification processing on the three-dimensional model of the electrical cabinet structure to generate an interface-identified three-dimensional model of the electrical cabinet structure.

[0051] In this embodiment of the invention, spatial interface characteristic identification processing of the electrical cabinet structure's three-dimensional model is carried out based on the interface data of the electrical components in the mining electrical cabinet. First, the interface data of the electrical components in the mining electrical cabinet is parsed to extract the core attribute parameters of each interface, including interface type identifier, number and arrangement of pins, signal transmission type encoding, rated voltage and current parameter range, and physical dimensions and shape characteristics of the interface, forming electrical component interface parsing data. Using the three-dimensional model of the electrical cabinet structure as a reference, the precise three-dimensional position of each electrical component in the model is located. The relative positional relationship between each interface and its corresponding electrical component, as well as the spatial distance and spatial obstruction between the interface and surrounding structural components, are analyzed to clarify the spatial reachability of the interface, generating structural model-component interface spatial relationship data. Through the structural model-component interface spatial relationship data, various attribute parameters in the electrical component interface parsing data are accurately mapped to the corresponding three-dimensional positions of the interfaces in the three-dimensional model of the electrical cabinet structure. Each interface is visually identified in the model, and its attribute parameters and spatial characteristics are labeled to ensure that the identified interface characteristics and the structural characteristics of the model achieve precise spatial correspondence, generating an interface-identified three-dimensional model of the electrical cabinet structure.

[0052] Step S17: Perform model attribute feature encapsulation processing on the 3D model of the interface identifier electrical cabinet structure to generate an encapsulated electrical cabinet structure-interface model.

[0053] In this embodiment of the invention, the three-dimensional model of the interface-identified electrical cabinet structure undergoes model attribute feature encapsulation processing. First, the various attribute features contained in the model are identified, covering three main categories: structural attributes, interface attributes, and functional attributes. Structural attributes include core structural parameters such as the geometric dimensions, spatial location, material properties, and connection methods of various components; interface attributes include interface-related parameters such as the type, pin characteristics, signal type, and rated parameters of each interface; functional attributes include functional-related parameters such as the functional positioning, load-bearing capacity, wiring adaptability, and component installation adaptability of each structural level. An attribute feature association system is established, clarifying the spatial relationship between structural attributes and interface attributes, the correspondence between structural attributes and functional attributes, and the adaptation relationship between interface attributes and functional attributes, ensuring that various attribute features form a logical closed loop. A hierarchical attribute feature encapsulation mechanism is adopted to integrate structural attributes, interface attributes, and functional attributes into the model hierarchically, forming a unified set of attribute features. Simultaneously, an attribute feature retrieval and query mechanism is established to ensure that the encapsulated model can quickly retrieve various attribute data. Through the above encapsulation process, the three-dimensional model of the electrical cabinet structure with the integrated attribute feature set is integrated to generate an encapsulated electrical cabinet structure-interface model, realizing the comprehensive integration and precise association of the electrical cabinet structure, interface, and functional attributes.

[0054] Furthermore, step S15 includes the following steps:

[0055] Step S151: Establish a preliminary three-dimensional structural model of the electrical cabinet based on the heterogeneous geometric space mapping data and the functional component data of the electrical cabinet;

[0056] In this embodiment of the invention, a three-dimensional rectangular coordinate system in the heterogeneous geometric spatial mapping data of the electrical cabinet is used as the reference. This coordinate system has the center of the bottom surface of the electrical cabinet as the origin, with the X-axis extending along the length of the cabinet, the Y-axis extending along the width, and the Z-axis extending along the height, all in millimeters. The geometric feature parameters and functional attributes of various components in the functional component data of the electrical cabinet are accurately associated with the corresponding spatial positions in the heterogeneous geometric spatial mapping data through a coordinate association mapping mechanism. For the cabinet frame, which is a load-bearing structure, its geometric dimensions of 800mm in length × 600mm in width × 1200mm in height, the mechanical properties of the steel material, and the load-bearing functional attributes are associated. For the gap between the middle and upper partitions, which is a wiring area, its spatial dimensions of 280mm in height × 780mm in length × 580mm in width and the wiring channel functional attributes are associated. For the vertical guide rail, which is a component mounting component, its geometric parameters of T-shaped cross-section, 15mm in groove width, and 1180mm in length, and the component guiding and mounting functional attributes are associated. Based on the correlated data, a preliminary 3D model of the electrical cabinet structure is constructed using a geometric reconstruction method of 3D solid modeling. The model fully presents the three-dimensional outline of the cabinet frame, the distribution of the three-layer horizontal partitions, the installation form of the vertical guide rails on both sides, and the assembly position of various fixed brackets. It clarifies the preliminary spatial positional relationship between all components and ensures that the geometric dimensional accuracy of the model and the error of the heterogeneous geometric spatial mapping data are controlled within ±0.1mm, providing a basic 3D structural carrier for subsequent hierarchical feature analysis and identification.

[0057] Step S152: Perform hierarchical solid structure feature analysis of the electrical cabinet based on the functional component data of the electrical cabinet, and generate hierarchical solid structure feature data of the electrical cabinet. The hierarchical solid structure feature data of the electrical cabinet includes feature data of the electrical cabinet load-bearing structure layer, feature data of the electrical cabinet wiring area layer, and feature data of the electrical cabinet component installation area layer.

[0058] In this embodiment of the invention, the three core components—load-bearing structural components, wiring area components, and component installation area components—divided from the functional component data of the electrical cabinet are used as the basis for analysis. A combination of feature parameter quantification extraction and functional attribute matching is employed to conduct hierarchical physical structural feature analysis of the electrical cabinet. For the load-bearing structural layer, the three-dimensional morphological parameters of the cabinet frame are extracted, including the rectangular dimensions of the frame column cross-section (100mm × 80mm), the coordinates of the welding connection nodes between the beams and columns, and the corresponding coordinates of the key support points distributed at the four corners of the cabinet and the two ends of the middle partition (e.g., (400, 300, 0), (-400, 300, 0), etc.). The load-bearing range covers the entire internal space of the cabinet, 800mm × 600mm × 1200mm, forming the feature data of the load-bearing structural layer. For the wiring zone layer, the 3D contours of various wiring channels are extracted. The main vertical channel extends along the inner rear wall of the cabinet with a cross-sectional dimension of 150mm × 200mm, while the branch horizontal channels are distributed below each shelf with a cross-sectional dimension of 100mm × 80mm. The coordinates of the connecting nodes between the main and branch channels are also determined, forming the feature data for the wiring zone layer. For the component mounting zone layer, the 3D distribution coordinates of the vertical guide rails (e.g., the left guide rail extends along the X=-380mm, Z=0-1200mm area), the spatial position of the mounting plate (e.g., the 20mm × 300mm × 200mm area above the middle shelf), and the 3D coordinates of the fixing holes (e.g., (-350, 250, 320), (-300, 250, 320), etc., with a hole diameter of 12mm) are extracted, forming the feature data for the component mounting zone layer. These three types of data are integrated to form the complete hierarchical solid structure feature data of the electrical cabinet.

[0059] Step S153: Use the hierarchical entity feature data of the electrical cabinet to perform hierarchical structure entity identification processing on the preliminary three-dimensional model of the electrical cabinet structure, and generate a three-dimensional model of the electrical cabinet structure.

[0060] In this embodiment of the invention, a combination of hierarchical feature mapping and entity boundary definition is used to perform hierarchical structural entity identification processing on the preliminary 3D model of the electrical cabinet using hierarchical entity structural feature data. First, the frame outline and support point coordinates in the load-bearing structure layer feature data are mapped to the preliminary model. Through 3D spatial boundary fitting technology, the spatial range of the load-bearing structure layer is defined in the model, marked with a specific structural texture, and its core parameters such as steel material and 100mm×80mm column cross-section are also marked. Then, the channel outline, cross-sectional dimensions, and connected nodes in the wiring area layer feature data are mapped to the model. Spatial region segmentation technology is used to divide the entity boundaries of the longitudinal main channel and the transverse branch channel, distinguished from the load-bearing structure layer with differentiated textures, and the cross-sectional dimensions and wiring capacity limit of each channel are marked (e.g., the main channel can accommodate 30 10mm diameter cables). Finally, the guide rail distribution, mounting plate position, and fixing hole coordinates in the component mounting area layer feature data are mapped to the model, accurately identifying the mounting area of ​​the guide rail and the fixing range of the mounting plate, and marking the hole size and compatible bolt specifications at the fixing hole positions. Through the above-mentioned identification process, the spatial boundaries of the three levels are clearly defined in the model, realizing the visual association between the functional attributes and core parameters of each level, generating a three-dimensional model of the electrical cabinet structure, and ensuring that the model can accurately represent the structural features of the electrical cabinet divided by functional levels.

[0061] Furthermore, step S16 includes the following steps:

[0062] Step S161: Perform electrical component interface parsing processing on the electrical component interface data of the mine electrical cabinet to generate electrical component interface parsing data;

[0063] In this embodiment of the invention, a combination of classification analysis and parameter quantification extraction is used to perform interface analysis processing on the interface data of electrical components in a mining electrical cabinet. First, the electrical components are categorized into three core types: circuit breakers, contactors, and relays. The interface data for each type of component is then analyzed one by one. For the three-phase power interface of the circuit breaker, the interface type is analyzed as threaded locking, with a 3×1 linear pin arrangement, a pin spacing of 20mm, pin 1 for phase A power input, pin 2 for phase B power input, and pin 3 for phase C power input. The signal transmission type is a power signal, with a rated voltage of AC380V, a rated current of 50A, and a cylindrical structure with an outer diameter of 25mm, an inner diameter of 18mm, and a depth of 15mm. For the contactor's coil interface, the interface type is identified as pluggable, with a 2×1 symmetrical pin arrangement and a pin spacing of 15mm. Pin 1 is the positive input of the coil, and pin 2 is the negative input. The signal transmission type is a control signal, with a rated voltage of DC24V and a rated current of 2A. The physical dimensions of the interface are a rectangular structure with a width of 12mm and a height of 8mm, and a insertion / removal travel of 5mm. For the relay's signal input / output interface, the interface type is identified as pin-type, with a 2×5 matrix pin arrangement and a pin spacing of 10mm. Pins 1-5 are signal inputs, and pins 6-10 are signal outputs. The signal transmission type is a digital signal, with a rated voltage of DC12V and a rated current of 1A. The physical dimensions of the interface are a rectangular structure with a length of 50mm and a width of 20mm, and a pin diameter of 1.5mm. All the analyzed interface attribute parameters are integrated in a unified format to generate electrical component interface analysis data, ensuring that the data completely covers the core characteristics such as interface type, pin features, signal parameters, and physical dimensions.

[0064] Step S162: Based on the three-dimensional model of the electrical cabinet structure, perform spatial relationship analysis and processing on the interface data of the electrical components of the mine electrical cabinet to generate spatial relationship data of the structural model and component interfaces;

[0065] In this embodiment of the invention, a three-dimensional model of the electrical cabinet structure is used as the spatial reference. This model adopts a three-dimensional rectangular coordinate system with the center of the bottom surface of the cabinet as the origin, the X-axis along the length direction, the Y-axis along the width direction, and the Z-axis along the height direction, with the unit being millimeters. First, the precise spatial coordinates of each electrical component in the three-dimensional model are located. The circuit breaker is installed in the left area of ​​the middle partition, with a three-dimensional coordinate range of X∈[-380,-280]mm, Y∈[250,350]mm, and Z∈[600,700]mm; the contactor is installed in the adjacent area to the right of the circuit breaker, with a coordinate range of X∈[-270,-170]mm, Y∈[250,350]mm, and Z∈[600,700]mm; the relay is installed in the corresponding area of ​​the upper partition, with a coordinate range of X∈[-380,-280]mm, Y∈[250,350]mm, and Z∈[900,1000]mm. Based on component coordinates, a spatial distance measurement and boundary fitting approach is used to analyze the relative position of each interface to its component. For example, the three-phase power interface of the circuit breaker is located in the center of the front of the component, 30mm from the left edge and 40mm from the bottom edge. The spatial relationship between the interface and surrounding structural components is analyzed. The horizontal distance from the circuit breaker interface to the left vertical guide rail is measured to be 20mm, and the vertical distance from the upper partition is 300mm. It is confirmed that there are no obstructing structures around the interface, and the accessible spatial range is a spherical area with a radius of 50mm centered on the interface. The interface coordinates, relative positions, distances to surrounding structures, and accessible spatial ranges of all components are integrated to generate structural model-component interface spatial relationship data, establishing a precise spatial association between the 3D model and the component interfaces.

[0066] Step S163: Map the parsed data of electrical component interfaces to the three-dimensional model of electrical cabinet structure through the spatial relationship data of structural model-component interface to perform electrical component interface attribute identification processing of electrical cabinet and generate an interface-identified three-dimensional model of electrical cabinet structure.

[0067] In this embodiment of the invention, a mapping relationship between electrical component interface parsing data and the three-dimensional model of the electrical cabinet structure is constructed through structural model-component interface spatial relationship data. First, the three-dimensional coordinates of each interface in the structural model-component interface spatial relationship data are extracted. The attribute parameters of the corresponding interface in the electrical component interface parsing data are then bound to these coordinates. For example, parameters such as the threaded locking type, 3×1 linear pin arrangement, and AC380V rated voltage of the circuit breaker three-phase power interface are bound to the interface position at coordinates (-330, 300, 650) in the model. Subsequently, the electrical component interface attribute identification processing of the electrical cabinet is carried out. Visual identifiers are generated at the corresponding interface positions in the three-dimensional model, using different colors to distinguish interface types: red for power signal interfaces, blue for control signal interfaces, and green for digital signal interfaces. The identifier content includes core attributes such as interface type, pin arrangement, signal type, and rated parameters. The identifier information is dynamically associated with the model structure. When the model viewpoint is switched or zoomed, the identifier remains fixed at the corresponding interface position, ensuring the stability and accuracy of the attribute information visualization. Through the above mapping and identification processing, the three-dimensional model of the electrical cabinet structure is fully integrated with the attribute information of each electrical component interface, generating an interface-identified three-dimensional model of the electrical cabinet structure, thus realizing the integrated representation of structural form and interface attributes.

[0068] Furthermore, step S2 includes the following steps:

[0069] Step S21: Extract and process electrical control logic rule information based on the encapsulated electrical cabinet structure-interface model to generate electrical control logic rule information data;

[0070] In this embodiment of the invention, an implementation method combining attribute association parsing and logical rule extraction is adopted. Electrical control logic rule information extraction is performed based on the encapsulated electrical cabinet structure-interface model. Relying on the association relationships between the encapsulated structural attributes, interface attributes, and functional attributes in the model, the functional positioning of each electrical component and the interface signal interaction logic are located, with a focus on extracting the logical rules of the core control circuit of the mining electrical cabinet. For the main power supply circuit, the logic rule "the contactor coil interface can only receive the energized signal after the circuit breaker's three-phase power interface output signal is valid" is extracted. The valid signal determination conditions are defined as the circuit breaker interface output voltage reaching AC380V±5% and the current stabilizing within the 0-50A range. For the signal detection circuit, the logic rule "after the relay signal input interface receives the digital signal transmitted by the sensor, its signal output interface sends a trigger signal to the controller" is extracted. The signal trigger thresholds are defined as a high level of digital signal ≥ DC11V, a low level ≤ DC1V, and a signal transmission delay not exceeding 10ms. For the protection circuit, the logic rule "when the circuit breaker interface detects a current exceeding the rated value of 50A, the three-phase power output is immediately cut off, and a power-off signal is sent to the contactor coil interface" is extracted. The overcurrent detection response time is defined as not exceeding 20ms. All extracted logic rules are categorized by circuit type, clarifying the component interface relationships, signal trigger conditions, parameter thresholds, and response actions corresponding to each rule. This generates electrical control logic rule information data, ensuring complete data coverage of the electrical cabinet's core control logic.

[0071] Step S22: Perform electrical connection feature analysis based on electrical control logic rule information data to generate electrical connection feature data;

[0072] In this embodiment of the invention, a combination of logical rule mapping and connection parameter extraction is employed to perform electrical connection feature analysis based on electrical control logic rule information data. First, each control logic rule is mapped to its corresponding electrical component interface, clarifying the start and end interfaces of the connection. For example, the logic rule "circuit breaker three-phase power interface supplies power to contactor power interface" is mapped to the corresponding connection relationship between the circuit breaker A / B / C three-phase power interfaces and the contactor three-phase power interfaces. Based on the mapping relationship, electrical connection feature parameters are extracted, including the signal type, rated voltage, rated current, connection path extension direction, and length. For the connection of "relay signal output interface transmitting signals to controller interface" in the signal control loop, the signal type is extracted as digital signal, rated voltage DC12V, rated current 1A, the connection path extends along the horizontal branch channel below the upper partition, the path length is estimated to be 120mm, and the cable conductor cross-sectional area is not less than 0.75mm². All connection start and end interfaces, signal parameters, path direction, cable specifications, and other feature parameters are integrated to generate electrical connection feature data, achieving accurate characterization of the core features of each electrical connection.

[0073] Step S23: Perform electrical connection standardization verification on the electrical connection feature data to generate verified electrical connection feature data;

[0074] In this embodiment of the invention, a combination of standard comparison and deviation correction is used to perform standardized verification processing on electrical connection characteristic data. A unified standardized verification standard is established, covering four main categories: signal parameter matching standards, interface type adaptation standards, cable specification selection standards, and path compliance standards. The signal parameter matching standard stipulates that the voltage deviation of power signal connections should not exceed ±5%, and the current deviation should not exceed ±10%. The interface type adaptation standard stipulates that threaded locking interfaces are only compatible with threaded connectors of power signal cables, and plug-in interfaces are only compatible with plug-in connectors of control signal cables. The cable specification selection standard stipulates that AC380V / 50A power signals must be matched with copper core cables with a cross-sectional area ≥6mm², and DC12V / 1A digital signals must be matched with copper core cables with a cross-sectional area ≥0.75mm². The path compliance standard stipulates that the connection path must be entirely within the cabling area layer, with a minimum distance of 10mm from the supporting structure layer. Each connection in the electrical connection characteristic data was verified one by one. For example, the power connection between the circuit breaker and the contactor was verified to confirm that the AC380V voltage and 50A current met the parameter matching standards, the threaded locking interface was compatible with the power cable connector, the 6mm² copper core cable met the specifications, and the path extended along the wiring area above the middle partition conformed to the routing standards. A deviation was found in the selection of 0.5mm² cable for a relay signal connection, which was corrected to 0.75mm² copper core cable; a deviation was found in the path of a connection intruding into the load-bearing structure layer, which was adjusted to the lateral branch channel. The verified and corrected connection characteristic data were integrated to generate verified electrical connection characteristic data, ensuring that all electrical connections met the standardization requirements.

[0075] Step S24: Analyze the electrical connection topology relationship based on the verified electrical connection feature data to generate electrical connection topology relationship data;

[0076] In this embodiment of the invention, a combination of node-edge mapping and topology hierarchy partitioning is employed to analyze the electrical connection topology based on verified electrical connection feature data. An electrical connection topology network is constructed using electrical component interfaces as topology nodes and verified electrical connections as topology edges. Each topology node is assigned a unique identifier, containing the component type, interface location coordinates, and signal type of the corresponding interface. For example, the A-phase power interface of a circuit breaker is identified as "Circuit Breaker-(-330,300,650)-Power Signal". Each topology edge is labeled with corresponding connection feature parameters, including signal type, rated parameters, cable specifications, and path direction. Based on the topological network, topological structure relationship analysis is conducted, dividing the topological hierarchy into three layers. The first layer is the power supply topology layer, containing interfaces for power components such as circuit breakers and contactors, and their corresponding power connections, forming a star topology with circuit breakers at its core. The second layer is the control signal topology layer, containing contactor coil interfaces, relay input / output interfaces, and their corresponding control connections, forming a chain topology with relays as intermediate nodes. The third layer is the detection signal topology layer, containing sensor interfaces, relay input interfaces, and their corresponding detection connections, forming a point-to-point linear topology. The relationships between each topology layer are clarified; for example, the relay output connection in the control signal topology layer connects to the contactor coil interface in the power supply topology layer, enabling the control signal to trigger the power circuit. The topology node information, topology edge parameters, topology hierarchy division, and hierarchical relationships are integrated to generate electrical connection topology structure relationship data.

[0077] Step S25: Based on the electrical connection topology relationship data, perform bundle management analysis and processing of cable connection topology requirements to generate cable connection topology requirement bundle management data.

[0078] In this embodiment of the invention, a multi-dimensional attribute fusion and bundled rule matching approach is adopted to perform bundled management analysis and processing of cable connection topology requirements based on electrical connection topology relationship data. The core basis for bundled management is determined, including topology level attributes, signal type attributes, cable specification attributes, and path direction attributes. Bundled rules are formulated: connections at the same topology level and with the same signal type are grouped into one bundle; connections with the same cable specification and roughly the same path direction are grouped into one bundle; the number of cables in each bundle does not exceed 15, the spacing between cables within a bundle is not less than 2mm, and the minimum spacing between bundles is not less than 15mm. A unique bundle identifier is assigned to each cable bundle, indicating the number of cables, specifications, signal type, path range, and installation requirements within the bundle. All bundled information is integrated to generate cable connection topology requirement bundled management data, realizing systematic bundled planning for cable connections and providing clear bundled guidance for subsequent wiring.

[0079] Furthermore, step S25 includes the following steps:

[0080] Step S251: Analyze the basic information of cable connections based on the electrical connection topology relationship data to generate basic information data of cable connections;

[0081] In this embodiment of the invention, a combination of topology node-edge analysis and basic parameter quantification extraction is used to analyze the basic information of cable connections based on the electrical connection topology data. The relationships between nodes and edges in the topology are analyzed to locate the starting and ending interfaces of each cable connection, clarifying the component type and interface parameters corresponding to the node identifiers. For the "circuit breaker-contactor" connection in the power supply topology layer, the starting interface is extracted as the circuit breaker A / B / C three-phase power interface (identified as "circuit breaker-(-330,300,650)-power signal", etc.), and the ending interface is the contactor A / B / C three-phase power interface (identified as "contactor-(-250,300,650)-power signal", etc.). The signal type is power signal, rated voltage AC380V, rated current 50A, cable conductor cross-sectional area 6mm², estimated connection path length 80mm, and the path extends laterally along the upper part of the middle partition. For the "relay-contactor coil" connection in the control signal topology layer, the starting interface is extracted as the relay output interface (labeled "relay-(-330,300,950)-control signal"), and the ending interface is the contactor coil interface (labeled "contactor-(-250,300,680)-control signal"). The signal type is control signal, the rated voltage is DC24V, the rated current is 2A, the cable conductor cross-sectional area is 1.5mm², the estimated path length is 320mm, and the path extends downwards along the longitudinal main channel before connecting laterally. All starting and ending interface labels, signal parameters, cable basic specifications, and path basic information are integrated to generate basic cable connection information data, achieving accurate characterization of the core basic characteristics of the cable connection.

[0082] Step S252: Perform multi-level cable connection relationship analysis on the basic cable connection information data to generate multi-level cable connection relationship data;

[0083] In this embodiment of the invention, a multi-level connection relationship analysis of cable connections is conducted on the basic information data of cable connections. First, with electrical control logic as the core, single cable connections are associated according to control links to form multi-level connection links, clarifying the hierarchical order and connection node relationships within the links. For the main power supply multi-level links, a three-level connection link is formed: "Power input interface - Circuit breaker power input interface - Circuit breaker power output interface - Contactor power input interface - Contactor power output interface - Load interface". The first level is from power input to circuit breaker (cable cross-section 10mm², path along the longitudinal main channel at the rear of the cabinet), the second level is from circuit breaker to contactor (cable cross-section 6mm², path along the upper part of the middle partition), and the third level is from contactor to load (cable cross-section 4mm², path along the longitudinal channel at the front of the cabinet). The relationships between the starting and ending interfaces, cable specifications, and path directions of each level of connection are clarified. It is noted that the first and second levels achieve signal conversion through the circuit breaker interface, and the second and third levels achieve on / off control through the contactor interface. For multi-level control signal links, a two-level connection link is established: "controller output interface - relay coil interface - relay signal output interface - contactor coil interface". The first level is from the controller to the relay (cable cross-section 1.0mm², path along the upper longitudinal channel), and the second level is from the relay to the contactor (cable cross-section 1.5mm², path along the longitudinal main channel + middle transverse channel). The signal transmission direction and logical control relationship of each level connection are clearly defined. The hierarchical division of all multi-level connection links, the connection relationships of each level, and the logical control sequence are integrated to generate multi-level cable connection relationship data, realizing a systematic representation of the hierarchical logic of cable connections.

[0084] Step S253: Perform cable connection engineering attribute analysis based on cable connection basic information data and cable multi-level connection relationship data to generate cable connection engineering attribute data;

[0085] In this embodiment of the invention, cable connection engineering attribute analysis is conducted based on basic cable connection information data and multi-level cable connection relationship data. For different levels and types of cable connections, engineering attribute parameters suitable for the operating conditions of mining electrical cabinets are extracted. The engineering attributes of power cable connections (such as circuit breaker-contactor) include: laying method as open laying above the middle partition, fixed spacing of 300mm, using metal clips for fixing, rubber padding at the contact point between the clips and the cable, bending radius not less than 48mm (6 times the cable outer diameter of 8mm), protection level IP54, and allowable temperature rise not exceeding 40℃ during operation; the engineering attributes of control cable connections (such as relay-contactor coil) include: laying method as laying through flame-retardant insulating sleeves along the longitudinal main channel, sleeve inner diameter 25mm. The specifications for cable connections are as follows: Fixed spacing 200mm, bending radius not less than 30mm (6 times the cable outer diameter of 5mm), protection level IP54, and allowable temperature rise not exceeding 35℃. For detection cable connections (such as sensor-relay connections), the engineering attributes include: laying method along the wiring trough below the upper partition, wiring trough cross-section size 50mm×30mm, cable spacing within the trough 2mm, bending radius not less than 24mm (6 times the cable outer diameter of 4mm), protection level IP54, and allowable temperature rise not exceeding 30℃. Simultaneously, the construction priority of all cable connections is extracted, with power cable connections having the highest priority, followed by control cables, and detection cables the lowest. The spacing requirements for adjacent cable levels are clearly defined (power and control cables should be at least 15mm apart, and control and detection cables at least 10mm apart). All cable connection laying methods, fixed parameters, bending radii, protection levels, temperature rise requirements, and construction priorities are integrated to generate cable connection engineering attribute data, ensuring that the engineering attributes are adapted to the harsh working conditions and construction specifications of the mine.

[0086] Step S254: Perform bundle management analysis and processing of cable connection topology requirements through cable connection basic information data, cable multi-level connection relationship data and cable connection engineering attribute data to generate cable connection topology requirement bundle management data.

[0087] In this embodiment of the invention, a combination of multi-attribute fusion and bundled rule matching is employed. Bundled management analysis of cable connection topology requirements is conducted using basic cable connection information data, multi-level cable connection relationship data, and cable connection engineering attribute data. Clear bundled rules are established: cables of the same multi-level link hierarchy, signal type, and laying area are grouped into one bundle; each bundle contains no more than 15 cables, with a 2mm spacing between cables within the bundle, wrapped with flame-retardant wrapping tape at a 400mm spacing; the minimum spacing between bundles is no less than 15mm, and the spacing between power bundles and control / detection bundles is no less than 20mm; the bundle identifier includes bundle type, cable quantity, core specifications, and laying path. Based on the bundling rules, the following bundling analysis is conducted: The first bundling is the main power bundling, integrating all power cable connections (including 9 6mm² cables for the second-level circuit breaker-contactor connection of 3 multi-level links, and 9 4mm² cables for the third-level contactor-load connection of 3 multi-level links). 12 cables are actually selected (excluding 3 redundant spare cables), labeled "Power Bundling - 12 Cables - 6mm² / 4mm² - AC380V - Middle Layer Partition + Front Longitudinal Channel". During installation, the cables are bundled in two sections along the top of the middle layer partition and the front longitudinal channel, secured with metal clips. The second bundling is the control bundling, integrating all control cable connections (including relay-contactor connections of 3 secondary links). The first bundle consists of six 1.5mm² cables and three primary link controller-relay connections (six 1.0mm² cables in total). Eight of these are selected and labeled "Control Bundle - 8 Cables - 1.0mm² / 1.5mm² - DC24V - Vertical Main Channel + Middle Layer Horizontal Channel," and laid in 25mm flame-retardant conduits with a 200mm spacing between the conduits. The third bundle is the detection bundle, which integrates all detection cable connections (including four sensor-relay connections with four 0.75mm² cables). Four of these are selected and labeled "Detection Bundle - 4 Cables - 0.75mm² - DC12V - Upper Layer Wiring Tray," and arranged orderly within the wiring trough and secured with cable ties. The bundle division range, cable details, labeling information, and laying requirements of each bundle are integrated to generate cable connection topology requirement bundle management data. This enables systematic and standardized bundle division planning for cable connections, providing precise bundle division guidance for subsequent 3D cabling.

[0088] Furthermore, step S3 includes the following steps:

[0089] Step S31: Perform spatial calculation domain analysis of the electrical cabinet based on the encapsulated electrical cabinet structure-interface model, and generate electrical cabinet spatial calculation domain data;

[0090] In this embodiment of the invention, the spatial computational domain analysis of the electrical cabinet is carried out based on the encapsulated electrical cabinet structure-interface model. Using the three-dimensional Cartesian coordinate system set in the encapsulation model (originating at the center of the cabinet bottom surface, with the X-axis along the length direction, the Y-axis along the width direction, and the Z-axis along the height direction, in millimeters) as a reference, the overall spatial boundary of the electrical cabinet is first extracted, defining the overall spatial range as X∈[-400,400]mm, Y∈[-300,300]mm, and Z∈[0,1200]mm. Based on the functional attribute characteristics of the model encapsulation, spatial areas related to cable wiring are selected, excluding non-wiring spaces such as the solid structure of the cabinet frame and the areas occupied by electrical components. The core range of the spatial computational domain is defined as all spaces covered by the wiring area layer and the reserved wiring space around the component installation area. The computational domain is specifically divided into sub-regions: the vertical main channel computational domain is X∈[-390,-370]mm, Y∈[-290,290]mm, Z∈[0,1200]mm; the middle layer horizontal channel computational domain is X∈[-380,380]mm, Y∈[280,290]mm, Z∈[600,700]mm; the upper layer horizontal branch channel computational domain is X∈[-380,380]mm, Y∈[280,290]mm, Z∈[900,1000]mm; and the reserved computational domain around components is the cubic range corresponding to the spherical space with a radius of 50mm around the interface of each electrical component. Through spatial boundary coordinate quantization and sub-region division, the spatial range, functional positioning, and positional relationship with the surrounding structure of each computational domain are clarified, generating electrical cabinet spatial computational domain data to ensure that the computational domain completely covers all possible wiring spaces.

[0091] Step S32: Perform spatial voxelization discretization on the spatial computational domain data of the electrical cabinet to generate spatial voxelized discrete data of the electrical cabinet;

[0092] In this embodiment of the invention, spatial voxel discretization is performed on the computational domain data of the electrical cabinet. The voxel size is determined to be 3mm × 3mm × 3mm, which is based on the minimum cable outer diameter of 4mm required for wiring, ensuring that the voxel accuracy can accurately characterize the spatial details of cable laying. Using the overall boundary of the electrical cabinet's computational domain as a reference, a uniform mesh is divided along the X, Y, and Z axes according to the voxel size, discretizing the continuous computational domain space into several independent cubic voxel units. Each voxel unit is uniquely encoded with coordinates according to the rule (i,j,k), where i is the voxel number in the X-axis direction, j is the voxel number in the Y-axis direction, and k is the voxel number in the Z-axis direction. The numbers increase from the smallest coordinate end of the computational domain. For example, in the vertical main channel computational domain, i=1 to i=7 (each voxel occupies 3mm, and there are 7 voxels in a 20mm range) corresponds to the range X∈[-390,-370]mm, j=1 to j=194 corresponds to the range Y∈[-290,290]mm, and k=1 to k=400 corresponds to the range Z∈[0,1200]mm. The spatial coordinate range of each voxel is recorded synchronously. For example, voxel (1,1,1) corresponds to X∈[-390,-387]mm, Y∈[-290,-287]mm, and Z∈[0,3]mm, while voxel (7,194,400) corresponds to X∈[-373,-370]mm, Y∈[287,290]mm, and Z∈[1197,1200]mm. The encoding information, spatial coordinate range, and sub-region information of all voxels are integrated to generate spatial voxelized discrete data of the electrical cabinet.

[0093] Step S33: Divide the voxelized spatial wiring type according to the voxelized discrete data of the electrical cabinet space, and generate voxelized spatial wiring type data;

[0094] In this embodiment of the invention, voxelized spatial wiring type classification is performed based on the voxelized discrete data of the electrical cabinet space. Based on the spatial coordinate range of each voxel, the functional and structural attributes in the encapsulated electrical cabinet structure-interface model are associated to determine the wiring type characteristics corresponding to the voxel. All voxels within the longitudinal main channel calculation domain are classified as longitudinal main cabling voxels. These voxels extend continuously along the Z-axis, can carry multiple cable bundles laid in parallel, and each voxel's cabling capacity along the Z-axis is no less than three 10mm diameter cables. Voxels within the mid-layer lateral channel calculation domain are classified as mid-layer lateral cabling voxels. These voxels extend continuously along the X-axis, are suitable for the lateral laying of power and control cables, and each voxel's cabling capacity along the X-axis is no less than two 8mm diameter cables. Voxels within the upper-layer lateral branch channel calculation domain are classified as upper-layer branch cabling voxels. These voxels extend along the X-axis with a narrower spatial range, are suitable for laying fine-diameter detection cables, and each voxel's cabling capacity does not exceed one 5mm diameter cable. Voxels within the component periphery reserved calculation domain are classified as component periphery transition voxels. These voxels are distributed around electrical component interfaces to facilitate cable and interface connection transitions. The cabling direction must adapt to the interface orientation; for example, voxels around circuit breaker interfaces are only allowed to connect cables in the positive or negative X-axis direction. Add a type identifier to each voxel for each cabling type to clarify the passability, compatible cable specifications, and cabling direction restrictions of each type of voxel, and generate voxelized spatial cabling type data.

[0095] Step S34: Perform voxelized spatial cable routing constraint feature analysis based on voxelized spatial routing type data to generate voxelized spatial cable routing constraint feature data;

[0096] In this embodiment of the invention, voxelized spatial cable routing constraint feature analysis is performed based on voxelized spatial routing type data. For voxels of different routing types, specific constraint feature parameters are extracted in conjunction with the engineering requirements and structural limitations of mine electrical cabinet routing. The constraint features for the longitudinal main routing voxel type are: the bending angle along the Z-axis during cable laying does not exceed 15°, the cable spacing within the voxel is not less than 15mm, the minimum distance to the voxel supporting the rear of the cabinet is not less than 10mm, and the maximum allowable cable outer diameter does not exceed 12mm. The constraint features for the middle layer transverse routing voxel type are: the bending angle along the X-axis does not exceed 20°, the spacing between power cables and control cables within the voxel is not less than 20mm, the minimum distance to the middle layer partition supporting structure is not less than 5mm, and the maximum allowable cable outer diameter does not exceed 10mm. The constraint characteristics of the upper-layer branch cabling voxel type are as follows: the bending angle along the X-axis does not exceed 10°, only a single bundle of small-diameter cables is allowed to be laid within the voxel, the minimum distance from the upper-layer partition and surrounding components is not less than 8mm, and the maximum outer diameter of the cable allowed to be laid does not exceed 5mm; the constraint characteristics of the component peripheral transition voxel type are as follows: the cable bending angle does not exceed 30°, the bending radius is not less than 6 times the corresponding cable outer diameter (e.g., the bending radius of a 4mm diameter cable is not less than 24mm), the distance from the component interface is not greater than 10mm, ensuring no stress concentration when the cable is connected to the interface. The constraint characteristic parameters of each voxel are associated with the voxel code and cabling type identifier, clarifying the specific values ​​and applicable conditions of the constraint parameters, generating voxelized spatial cable cabling constraint characteristic data, and achieving accurate characterization of the cabling constraints of each voxel.

[0097] Step S35: Perform three-dimensional cable routing constraint domain integration processing based on voxelized spatial cable routing constraint feature data to generate three-dimensional cable routing constraint domain data.

[0098] In this embodiment of the invention, a correspondence between voxel encoding and constraint features is established. Voxels of the same wiring type and adjacent spatial positions are associated in coordinate order to form continuous constraint subdomains. For example, the longitudinal main wiring constraint subdomain is formed by connecting all longitudinal main wiring voxels in ascending order along the Z-axis, covering the complete space of X∈[-390,-370]mm, Y∈[-290,290]mm, and Z∈[0,1200]mm; the middle layer horizontal wiring constraint subdomain is formed by connecting the middle layer horizontal wiring voxels in ascending order along the X-axis, covering the spatial range of X∈[-380,380]mm, Y∈[280,290]mm, and Z∈[600,700]mm. The connection relationships between each constraint subdomain are clearly defined. For example, the longitudinal main cabling constraint subdomain and the mid-layer lateral cabling constraint subdomain are connected in voxel regions of X∈[-390,-380]mm, Y∈[280,290]mm, and Z∈[600,700]mm. The constraint features of the connected regions are executed according to the strict constraint parameters of the two types of subdomains. All constraint subdomains undergo unified spatial coordinate calibration to ensure seamless and non-overlapping boundary connections between subdomains. Simultaneously, the constraint feature parameters of voxels within each subdomain are integrated to form the overall constraint requirements for each constraint subdomain. The spatial extent, connection relationships, overall constraint requirements, and detailed constraint parameters of voxels within all constraint subdomains are integrated to generate 3D cable routing constraint domain data.

[0099] Furthermore, as an embodiment of the present invention, reference is made to... Figure 2 As shown, Figure 1 A detailed flowchart illustrating the implementation steps of step S4 is provided in this embodiment. Step S4 includes:

[0100] Step S41: Based on the cable connection topology requirements and bundle management data, establish cable connection path units and generate cable connection path unit data;

[0101] In this embodiment of the invention, the core information of the three cable bundles in the bundle management data is analyzed. The first power bundle is identified as "Power Bundle - 12 strands - 6mm² / 4mm² - AC380V - Middle Layer Partition + Front Longitudinal Channel". The connection starting point is the circuit breaker three-phase power interface (coordinates (-330, 300, 650), (-310, 300, 650), (-290, 300, 650)), and the connection ending point is the contactor three-phase power interface (coordinates (-250, 300, 650), (-230, 300, 650), (-210, 300, 650)) and the load interface. The wiring priority is set to level 1 (highest). The second control bundle is identified as... The first cable bundle is identified as "Control Bundle - 8 strands - 1.0mm² / 1.5mm² - DC24V - Vertical Main Channel + Middle Layer Horizontal Channel". Its connection start point is the controller output interface (coordinates (-100, 300, 950)), and its connection end point is the contactor coil interface (coordinates (-250, 300, 680)). Its wiring priority is set to level 2. The second cable bundle is identified as "Detection Bundle - 4 strands - 0.75mm² - DC12V - Upper Layer Wiring Slot". Its connection start point is the sensor output interface (coordinates (-380, 250, 950)), and its connection end point is the relay input interface (coordinates (-350, 300, 950)). Its wiring priority is set to level 3. Based on this information, an independent path unit is established for each cable bundle. Each path unit includes core parameters such as unit identifier, start and end point coordinates, cable specifications, priority, and expected wiring area. This generates cable connection path unit data containing the corresponding path units for the three cable bundles, realizing the conversion of bundle requirements into path units.

[0102] Step S42: Map the cable connection path unit data to the three-dimensional cable routing constraint domain data to perform feasible search space analysis of the path units and generate feasible search space data of the path units;

[0103] In this embodiment of the invention, the start and end coordinates and the expected wiring area of ​​each path unit are extracted. The start coordinates (-330, 300, 650) and end coordinates (-250, 300, 650) of the power beam path unit are mapped to the middle layer lateral wiring constraint sub-domain (X∈[-380, 380] mm, Y∈[280, 290] mm, Z∈[600, 700] mm) of the three-dimensional cable wiring constraint domain. The range of the constraint sub-domain corresponding to the path unit is determined by spatial coordinate comparison. Prohibited wiring voxels within the constraint domain are removed, including voxels that overlap with the middle layer partition bearing structure (voxel area Z∈[600, 605] mm) and voxels occupied by electrical component entities (voxel area around the contactor Z∈[650, 700] mm, X∈[-270, -170] mm). The feasible search space for the dynamic beam path unit is determined as the set of voxels within the middle-layer lateral wiring constraint subdomain, where X∈[-330,-210]mm, Y∈[280,290]mm, and Z∈[605,695]mm. The feasible search space for the control beam path unit is the set of connected voxels between the longitudinal main wiring constraint subdomain (X∈[-390,-370]mm, Y∈[-290,290]mm, Z∈[0,1200]mm) and the middle-layer lateral wiring constraint subdomain. The feasible search space for the detection beam path unit is the set of voxels within the upper-layer branch wiring constraint subdomain (X∈[-380,380]mm, Y∈[280,290]mm, Z∈[900,1000]mm), where X∈[-380,-350]mm. Path unit feasible search space data containing the voxel codes and ranges of each path unit's feasible search space is generated.

[0104] Step S43: Analyze the prior data of feasible cable connection paths based on the feasible search space data of the path unit, and generate the prior data of feasible cable connection paths;

[0105] In this embodiment of the invention, taking the feasible search space of the dynamic beam path unit (a set of voxels within the mid-layer lateral wiring constraint subdomain, where X∈[-330,-210]mm, Y∈[280,290]mm, and Z∈[605,695]mm) as an example, the encoding sequence and coordinate relationship of all voxels in the space are first analyzed to determine that the voxel encoding follows the (i,j,k) rule, where i corresponds to the X-axis index, j corresponds to the Y-axis index, and k corresponds to the Z-axis index. Within this space, the value range of i is 23 to 63, the value range of j is 3 to 7, and the value range of k is 202 to 232, forming a continuous voxel cluster. The voxel distribution is determined to be uniform through voxel coordinate spacing calculation, with a voxel density of 1 / (3mm×3mm×3mm) per unit space, and no areas of missing or densely packed voxels. Based on the spatial connectivity of voxels, feasible turning nodes are identified. Voxel clusters at X∈[-300,-297]mm (i=34) and Z∈[605,608]mm (k=202) are determined to be turning nodes that can turn vertically because they are connected to continuous voxels in the X-axis and Z-axis directions. Voxel clusters at X∈[-250,-247]mm (i=50) and Y∈[285,288]mm (j=5) are determined to be turning nodes that can turn forward and backward because they are connected to continuous voxels in the X-axis and Y-axis directions. Similarly, the feasible search space of the control bundle (the set of connected voxels in the longitudinal main wiring constraint subdomain and the middle layer lateral wiring constraint subdomain) is analyzed, and its voxel encoding sequence is extracted as i=1 to 7, j=1 to 194, k=227 to 317 (longitudinal segment) and i=50 to 63, j=3 to 7, k=227 (lateral segment). The turning node is located at X∈[-390,-387]mm, Y∈[287,290]mm, Z∈[680,683]mm. This node connects the longitudinal and lateral voxel clusters. The feasible search space of the detection bundle (the set of voxels in the upper layer branch wiring constraint subdomain X∈[-380,-350]mm) is analyzed, and the voxel encoding sequence is extracted as i=1 to 10, j=3 to 7, k=300 to 303. The voxels are distributed in a straight line along the X-axis and there are no turning nodes. By integrating the topological features of all path units, such as connected voxel combinations, voxel density distribution, turning node locations, and connection directions, prior data of feasible cable connection paths are generated, providing a spatial topological foundation for subsequent cost analysis and path search.

[0106] Step S44: Perform spatial feasible path movement cost analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path movement cost data;

[0107] In this embodiment of the invention, the movement cost is quantified based on path length and voxel traversal difficulty. A base value of 1 is set for the movement cost per voxel. The cost coefficient is 1.0 for continuous voxel movement along a straight line, 1.5 for movement along a turning node, and 1.0 for traversing a region with uniform voxel density. Taking prior data of feasible dynamic beam paths as an example, the movement costs of different potential paths are calculated: Path 1 moves along the X-axis from the starting voxel (23,5,218) to the ending voxel (63,5,218), passing through 40 voxels with no turning nodes; the movement cost is 40 × 1 × 1.0 = 40. Path 2 moves from the starting voxel (23,5,218) along the X-axis to voxel (34,5,218), turns along the Z-axis to voxel (34,5,228), and then along the X-axis to the ending voxel (63,5,228), passing through 49 voxels. For each voxel, including one turning node, the movement cost is (11×1.0+10×1.0+28×1.0)+1×1.5=49.5. Path 3 starts from the starting voxel (23,5,218) along the X-axis to voxel (50,5,218), turns along the Y-axis to voxel (50,7,218), and then along the X-axis to the ending voxel (63,7,218), passing through 46 voxels, including one turning node, with a movement cost of (27×1.0+2×1.0+13×1.0)+1×1.5=43.5. The movement costs of each potential path in the control and detection bundles are calculated in this way, generating spatial feasible path movement cost data containing the movement cost values ​​of each path and the calculation basis.

[0108] Step S45: Perform spatial feasible path occupancy cost analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path occupancy cost data;

[0109] In this embodiment of the invention, the occupancy cost is quantified based on the scarcity of wiring resources in the voxel's region. The baseline value for the occupancy cost of voxels in ordinary wiring areas is set to 1, the baseline value for the occupancy cost of voxels in core wiring channels is 2, and the baseline value for the occupancy cost of voxels in reserved areas around components is 3. Taking the feasible search space of the control bundle as an example, its feasible space includes the core channel voxels (X∈[-390,-370]mm, Y∈[-290,290]mm, Z∈[0,1200]mm) of the vertical main wiring constraint subdomain and the ordinary area voxels of the middle layer horizontal wiring constraint subdomain. Calculate the potential path occupancy cost: Path 1 runs along the longitudinal main channel core voxels from Z∈[950,953]mm (k=317) to Z∈[680,683]mm (k=227), then along the middle layer horizontal ordinary voxels to the endpoint, occupying 90 core voxels and 20 ordinary voxels, with an occupancy cost of 90×2+20×1=200; Path 2 runs along the longitudinal main channel edge voxels (Y∈[-290,-287]mm, j=1) from Z∈[950,953]mm to Z∈[680,683]mm. [mm], then along the middle layer laterally to the endpoint, occupying 90 core voxels and 25 ordinary voxels, with an occupation cost of 90×2+25×1=205; Path 3 along the longitudinal main channel and the reserved area voxels connected to the middle layer laterally (X∈[-390,-387]mm, Y∈[287,290]mm, Z∈[680,700]mm) to the endpoint, occupying 15 reserved voxels, 80 core voxels, and 18 ordinary voxels, with an occupation cost of 15×3+80×2+18×1=213. Similarly, calculate the occupation cost of each potential path for the dynamic beam and the detection beam, generating spatial feasible path occupation cost data containing the occupation cost values ​​of each path and the proportion of voxel types.

[0110] Step S46: Perform spatial feasible path turning impact analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path turning impact data;

[0111] In this embodiment of the invention, the steering influence is quantified based on the number of steering nodes, steering angle, and signal transmission characteristics. The influence coefficient is set to 1.0 when the single steering angle is ≤15°, 1.5 when 15° < steering angle ≤30°, and 2.0 when the steering angle >30°. The steering influence value = number of steering nodes × steering angle influence coefficient × signal type weight (power signal weight 1.0, control signal weight 1.2, detection signal weight 1.5). Taking the prior data of the feasible path of the detection bundle as an example, its signal type is digital signal, with a weight of 1.5. The potential path steering situations within the feasible space are as follows: Path 1 runs along the X-axis from the starting voxel (10,5,300) to the ending voxel (17,5,300), with no steering nodes, and the steering influence value = 0; Path 2 starts from the starting voxel (10,5,300), turns along the Z-axis to voxel (10,5,303), and then turns again along the X-axis to the ending voxel (17,5,303). Path 03 contains two turning nodes, each with a turning angle of 90°, an influence coefficient of 2.0, and a turning influence value of 2 × 2.0 × 1.5 = 6.0. Path 3 turns from the starting voxel (10,5,300) along the Y-axis to voxel (10,7,300), then turns along the X-axis to the ending voxel (17,7,300), containing two turning nodes, each with a turning angle of 90°, an influence coefficient of 2.0, and a turning influence value of 2 × 2.0 × 1.5 = 6.0. Similarly, the turning influence values ​​of each potential path in the power bundle and control bundle are calculated to generate spatial feasible path turning influence data containing the number, angle, and influence value of each path's turning nodes.

[0112] Step S47: Design a search strategy for cable connection and cabling paths by using spatially feasible path movement cost data, spatially feasible path occupancy cost data, and spatially feasible path turning impact data, and generate a cable connection and cabling path search strategy.

[0113] In this embodiment of the invention, a cost weight allocation is set. Based on wiring priority and functional requirements, the movement cost weight for the power beam path is 0.4, the occupancy cost weight is 0.3, and the turning influence cost weight is 0.3; the movement cost weight for the control beam path is 0.3, the occupancy cost weight is 0.4, and the turning influence cost weight is 0.3; the movement cost weight for the detection beam path is 0.3, the occupancy cost weight is 0.3, and the turning influence cost weight is 0.4. A comprehensive cost calculation model is established: Comprehensive cost = Movement cost × Corresponding weight + Occupancy cost × Corresponding weight + Turning influence cost × Corresponding weight. The search criteria are designed: Prioritize searching for the path with the lowest comprehensive cost. When multiple paths with the same comprehensive cost exist, the power beam prioritizes the path with the fewest core channel voxels, the control beam prioritizes the path with the fewest turning nodes, and the detection beam prioritizes the path extending along a straight line. The search termination condition is defined: When three paths with comprehensive costs lower than the set thresholds (power beam threshold 50, control beam threshold 250, detection beam threshold 10) are found, the search for that path unit is stopped. By integrating cost weights, comprehensive cost models, search criteria, and termination conditions, a cable connection and cabling path search strategy is generated, which includes a search strategy specific to each path unit.

[0114] Step S48: Utilize the cable connection and wiring path search strategy to perform spatially constrained intelligent search processing of the feasible search space data of the path unit for cable 3D wiring candidate paths, and generate cable 3D wiring candidate path data.

[0115] In this embodiment of the invention, taking the dynamic beam path unit as an example, its dedicated search strategy is matched, and the voxel unit sequence in the feasible search space is traversed to calculate the comprehensive cost of each potential path: the comprehensive cost of path one is 40×0.4+(40×1)×0.3+0×0.3=28, which is lower than the threshold of 50, so it is selected as the first candidate path. Its voxel sequence is (23,5,218)→(24,5,218)→…→(63,5,218), and the wiring direction extends in a straight line along the positive X-axis; the comprehensive cost of path two is 49.5×0.4+(49×2)×0.3+(1×1.5)×0.3=48.75, which is lower than the threshold of 50, so it is selected as the second candidate path. Its voxel sequence is (23,5,218)→ …→(34,5,218)→(34,5,219)→…→(34,5,228)→(35,5,228)→…→(63,5,228), the routing direction is first along the positive X-axis, then along the positive Z-axis, and finally along the positive X-axis; the comprehensive cost of path three = 43.5×0.4+(46×1)×0.3+(1×1.5)×0.3=32.25, which is lower than the threshold of 50, so it is used as the third candidate path. The voxel sequence is (23,5,218)→…→(50,5,218)→(50,6,218)→(50,7,218)→…→(63,7,218), the routing direction is first along the positive X-axis, then along the positive Y-axis, and finally along the positive X-axis. The candidate path search for the control bundle and detection bundle is completed in the same way. Each candidate path has a defined voxel unit sequence, wiring direction and comprehensive cost, generating cable 3D wiring candidate path data containing candidate path information of all path units.

[0116] Furthermore, step S5 includes the following steps:

[0117] Step S51: Perform cable routing cooperative conflict feature analysis based on the cable 3D routing candidate path data to generate cable routing cooperative conflict feature data;

[0118] In this embodiment of the invention, the core spatial information of the candidate paths of the three cable bundles is extracted. The three candidate paths of the power bundle are all located in the middle layer lateral wiring constraint subdomain (X∈[-330,-210]mm, Y∈[280,290]mm, Z∈[605,695]mm), and the voxel encoding covers i=23 to 63, j=3 to 7, k=202 to 232; the three candidate paths of the control bundle cover the longitudinal main wiring constraint subdomain (i=1 to 7, j=1 to 194, k=227 to 317) and the middle layer lateral wiring constraint subdomain (i=50 to 63, j=3 to 7, k=227); the three candidate paths of the detection bundle are located in the upper layer branch wiring constraint subdomain (i=1 to 10, j=3 to 7, k=300 to 303). By comparing the occupancy range of voxel units, the conflict types and characteristics were identified: First, voxel overlap conflict: the lateral segment of the second candidate path of the control bundle (i=50 to 63, j=5, k=227) and the first candidate path of the power bundle (i=23 to 63, j=5, k=218) have vertical overlap in the voxel regions of i=50 to 63, j=5, k=227 and k=218, involving 14 voxels. The spatial coordinates of the overlapping area are X∈[-250,-210]mm, Y∈[285,288]mm, Z∈[650,683]mm; Second, orientation intersection conflict: the third candidate path of the control bundle has a vertical intersection between the main channel and the middle layer. At the horizontal channel connecting node (i=1, j=194, k=227), there is a spatial intersection with the turning segment (i=50, j=5 to 7, k=218) of the third candidate path of the power beam. The coordinates of the intersection point are X∈[-250,-247]mm, Y∈[287,290]mm, and Z∈[650,653]mm. Thirdly, there is a density exceeding limit conflict. The second and third candidate paths of the detection beam are laid in parallel in the voxel region of i=5 to 10, j=5, k=300. Only a single 5mm diameter cable is allowed to pass through this voxel region. The parallel laying of two 4mm diameter cables results in a wiring density exceeding the limit, with 6 voxels in the exceeding area. The conflict location coordinates, involved path bundles, number of conflicting voxels, conflict type identifier, and conflict impact range for each type of conflict are clearly defined, generating cable wiring collaborative conflict feature data containing complete conflict feature information.

[0119] Step S52: Based on the cable routing coordination conflict characteristic data, perform cable conflict relationship assessment processing to generate cable conflict relationship assessment data;

[0120] In this embodiment of the invention, a method combining conflict feature association and evaluation parameter quantification is adopted to evaluate cable conflict relationships based on cable cabling collaborative conflict feature data. A three-level evaluation index system is established: the first-level index is the priority of the conflict-involved path, the second-level index is the importance of the conflict area, and the third-level index is the degree of functional impact of the conflict. The weights of each index are set to 0.5, 0.3, and 0.2, respectively. Priority evaluation criteria: Level 1 (power bundle) weight coefficient 1.0, Level 2 (control bundle) weight coefficient 0.8, Level 3 (detection bundle) weight coefficient 0.6; Area importance evaluation criteria: Core cabling channels (vertical main channels, middle layer horizontal channels) weight coefficient 1.0, branch channels weight coefficient 0.7, and component surrounding areas weight coefficient 0.5; Functional impact evaluation criteria: Signal interference weight coefficient 1.0, impact on cabling construction weight coefficient 0.8, and only occupying redundant space weight coefficient 0.3. The conflicts identified by S51 were quantitatively evaluated: Voxel overlap conflict (power beam level 1 + control beam level 2, core channel area, which may cause power signal interference with control signal) evaluation score = (1.0×0.5+0.8×0.5)×0.3×1.0+1.0×0.2=0.87, which is judged as a high-priority conflict; directional intersection conflict (power beam level 1 + control beam level 2, connecting node area, affecting construction) evaluation score = (1.0×0.5+0.8×0.5)×0.3×1.0+0.8×0.2=0.79, which is judged as a medium-priority conflict; density over-limit conflict (detection beam level 3 + detection beam level 3, branch channel area, affecting construction) evaluation score = (0.6×0.5+0.6×0.5)×0.3×0.7+0.8×0.2=0.32, which is judged as a low-priority conflict. The assessment scores, priority levels, and urgency of each conflict are clearly defined, and cable conflict relationship assessment data is generated.

[0121] Step S53: Use the cable conflict relationship assessment data to perform local replanning of the conflict paths in the cable 3D routing candidate path data, and generate replanned cable 3D routing candidate path data;

[0122] In this embodiment of the invention, for high-priority voxel overlap conflicts, the second candidate path of the control beam with lower priority is adjusted first, while the first candidate path of the dynamic beam (high priority) remains unchanged. Within the feasible search space of the control beam, voxel units are re-selected to avoid overlapping regions (X∈[-250,-210]mm, Y∈[285,288]mm, Z∈[650,683]mm). A new lateral segment path is planned as i=50 to 63, j=3, k=227, corresponding to spatial coordinates X∈[-250,-210]mm, Y∈[280,283]mm, Z∈[680,683]mm. The vertical distance between this path and the dynamic beam path is 5mm, which meets the spacing constraint. To address the crossover conflict of the medium-priority path, the turning node of the third candidate path of the control beam is adjusted. The original turning node (i=1, j=194, k=227) is adjusted to i=2, j=193, k=228, corresponding to coordinates X∈[-387,-384]mm, Y∈[284,287]mm, Z∈[683,686]mm. The new path's lateral segment is i=51 to 63, j=4, k=228, avoiding the intersection with the power beam path. For low-priority density over-limit conflicts, the third candidate path of the detection bundle was adjusted, changing its lateral segment from i=5 to 10, j=5, k=300 to i=5 to 10, j=3, k=301, corresponding to coordinates X∈[-365,-350]mm, Y∈[280,283]mm, Z∈[903,906]mm, with a distance of 6mm from the second candidate path of the detection bundle, meeting the density requirements. The replanned paths were verified to conform to the bending angle, spacing, and other constraint parameters of the 3D cable routing constraint domain, generating replanned 3D cable routing candidate path data containing the voxel sequence and spatial coordinates of each replanned path.

[0123] Step S54: Perform global optimization processing on the candidate paths of the replanned cable 3D routing to generate cable 3D routing path data.

[0124] In this embodiment of the invention, a combined approach of global planning and optimization screening of replanned paths is adopted to perform global optimization processing on candidate paths for 3D cable routing based on the replanned cable routing candidate path data. Global spatial distribution information of all replanned paths is extracted, including the voxel occupancy range, routing length, number of turning nodes, spacing with surrounding structures, and signal interference risk for each path. A global optimization evaluation model is established, with evaluation indicators including total routing length (weight 0.3), number of turning nodes (weight 0.2), spatial distribution uniformity (weight 0.3), and signal interference risk (weight 0.2). The optimization objective is set to minimize the total evaluation value. The replanned paths for each cable bundle are combined for evaluation: the power bundle selects the first candidate path (80mm length, 0 turning nodes, uniform distribution); the control bundle selects the second candidate path after replanning (325mm length, 1 turning node, no interference); and the detection bundle selects the first and second candidate paths after replanning (total length 100mm, 0 turning nodes, compliant spacing). The distribution of all bundle paths was comprehensively assessed, verifying that the wiring density in the middle layer's horizontal area was 2 bundles / m and the density in the vertical main channel was 1 bundle / m, both meeting density constraints. The minimum distance between each path and the supporting structure was no less than 5mm, meeting safety constraints. The third replanning path for the detection bundle, which posed a potential interference risk, was eliminated, and the globally optimal path combination was selected. The voxel unit sequence, spatial coordinate range, wiring direction, and constraint satisfaction of the final path were defined, generating 3D cable wiring path data. This ensured that the wiring path corresponding to this data fully met the bundle distribution requirements, spatial constraints, engineering specifications, and functional requirements.

[0125] This specification provides a three-dimensional integrated cabling system for mine electrical cabinet cable networks, used to implement the three-dimensional integrated cabling method for mine electrical cabinet cable networks as described above. The three-dimensional integrated cabling system for mine electrical cabinet cable networks includes:

[0126] The electrical cabinet structure-interface model building module is used to acquire heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets; based on the heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets, the module designs the electrical cabinet encapsulation model of structure and interface, and generates the encapsulated electrical cabinet structure-interface model.

[0127] The cable connection topology requirement analysis module is used to perform bundle management analysis and processing of cable connection topology requirements based on the encapsulated electrical cabinet structure-interface model, and generate cable connection topology requirement bundle management data.

[0128] The cable routing constraint domain analysis module is used to perform three-dimensional cable routing constraint domain analysis on the structure-interface model of the encapsulated electrical cabinet and generate three-dimensional cable routing constraint domain data.

[0129] The cabling candidate path analysis module is used to map cable connection topology requirement bundle management data to three-dimensional cable cabling constraint domain data for spatial constraint three-dimensional cable cabling candidate path analysis, and generate three-dimensional cable cabling candidate path data.

[0130] The cable 3D routing path analysis module is used to optimize the cable conflict of the candidate path data and generate cable 3D routing path data.

[0131] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0132] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A three-dimensional integrated cabling method for electrical cabinet cable networks in mines, characterized in that, Includes the following steps: Step S1: Obtain heterogeneous physical structure data of the mining electrical cabinet and interface data of electrical components in the mining electrical cabinet; Based on the heterogeneous physical structure data of mining electrical cabinets and the interface data of electrical components in mining electrical cabinets, an electrical cabinet encapsulation model of structure and interface is designed to generate an encapsulated electrical cabinet structure-interface model. Step S1 includes the following steps: Step S11: Obtain heterogeneous physical structure data of the mining electrical cabinet and interface data of electrical components of the mining electrical cabinet; Step S12: Perform heterogeneous geometric analysis on the physical structure heterogeneous data of the mine electrical cabinet to generate heterogeneous geometric data of the electrical cabinet structure; Step S13: Perform three-dimensional spatial mapping processing for heterogeneous geometry alignment based on the heterogeneous geometric data of the electrical cabinet structure to generate heterogeneous geometric spatial mapping data of the electrical cabinet; Step S14: Analyze the functional components of the electrical cabinet based on the heterogeneous physical structure data of the mine electrical cabinet, and generate functional component data of the electrical cabinet; Step S15: Based on the heterogeneous geometric space mapping data of the electrical cabinet and the functional component data of the electrical cabinet, establish a three-dimensional model of the hierarchical structure of the electrical cabinet and generate a three-dimensional model of the electrical cabinet structure. Step S16: Based on the interface data of the electrical components of the mine electrical cabinet, perform spatial interface characteristic identification processing on the three-dimensional model of the electrical cabinet structure to generate an interface-identified three-dimensional model of the electrical cabinet structure. Step S17: Perform model attribute feature encapsulation processing on the 3D model of the interface identifier electrical cabinet structure to generate an encapsulated electrical cabinet structure-interface model; Step S2: Based on the encapsulated electrical cabinet structure-interface model, perform bundle management analysis and processing of cable connection topology requirements to generate cable connection topology requirement bundle management data; Step S2 includes the following steps: Step S21: Extract and process electrical control logic rule information based on the encapsulated electrical cabinet structure-interface model to generate electrical control logic rule information data; Step S22: Perform electrical connection feature analysis based on electrical control logic rule information data to generate electrical connection feature data; Step S23: Perform electrical connection standardization verification on the electrical connection feature data to generate verified electrical connection feature data; Step S24: Analyze the electrical connection topology relationship based on the verified electrical connection feature data to generate electrical connection topology relationship data; Step S25: Based on the electrical connection topology relationship data, perform bundle management analysis and processing of cable connection topology requirements to generate cable connection topology requirement bundle management data; Step S3: Perform 3D cable routing constraint domain analysis on the encapsulated electrical cabinet structure-interface model to generate 3D cable routing constraint domain data; Step S3 includes the following steps: Step S31: Perform spatial calculation domain analysis of the electrical cabinet based on the encapsulated electrical cabinet structure-interface model, and generate electrical cabinet spatial calculation domain data; Step S32: Perform spatial voxelization discretization on the spatial computational domain data of the electrical cabinet to generate spatial voxelized discrete data of the electrical cabinet; Step S33: Divide the voxelized spatial wiring type according to the voxelized discrete data of the electrical cabinet space, and generate voxelized spatial wiring type data; Step S34: Perform voxelized spatial cable routing constraint feature analysis based on voxelized spatial routing type data to generate voxelized spatial cable routing constraint feature data; Step S35: Perform three-dimensional cable routing constraint domain integration processing based on voxelized spatial cable routing constraint feature data to generate three-dimensional cable routing constraint domain data; Step S4: Map the cable connection topology requirement bundle management data to the three-dimensional cable routing constraint domain data to perform spatial constraint cable three-dimensional routing candidate path analysis and generate cable three-dimensional routing candidate path data; Step S4 includes the following steps: Step S41: Based on the cable connection topology requirements and bundle management data, establish cable connection path units and generate cable connection path unit data; Step S42: Map the cable connection path unit data to the three-dimensional cable routing constraint domain data to perform feasible search space analysis of the path units and generate feasible search space data of the path units; Step S43: Analyze the prior data of feasible cable connection paths based on the feasible search space data of the path unit, and generate the prior data of feasible cable connection paths; Step S44: Perform spatial feasible path movement cost analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path movement cost data; Step S45: Perform spatial feasible path occupancy cost analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path occupancy cost data; Step S46: Perform spatial feasible path turning impact analysis based on the prior data of feasible cable connection paths, and generate spatial feasible path turning impact data; Step S47: Design a search strategy for cable connection and cabling paths by using spatially feasible path movement cost data, spatially feasible path occupancy cost data, and spatially feasible path turning impact data, and generate a cable connection and cabling path search strategy. Step S48: Utilize the cable connection wiring path search strategy to perform spatially constrained intelligent search processing of the feasible search space data of the path unit for cable 3D wiring candidate paths, and generate cable 3D wiring candidate path data. Step S5: Optimize the cable conflict of the candidate paths in the 3D cable routing candidate path data to generate 3D cable routing path data; Step S5 includes the following steps: Step S51: Perform cable routing cooperative conflict feature analysis based on the cable 3D routing candidate path data to generate cable routing cooperative conflict feature data; Step S52: Based on the cable routing coordination conflict characteristic data, perform cable conflict relationship assessment processing to generate cable conflict relationship assessment data; Step S53: Use the cable conflict relationship assessment data to perform local replanning of the conflict paths in the cable 3D routing candidate path data, and generate replanned cable 3D routing candidate path data; Step S54: Perform global optimization processing on the candidate paths of the replanned cable 3D routing to generate cable 3D routing path data.

2. The three-dimensional integrated cabling method for cable networks in mining electrical cabinets according to claim 1, characterized in that, Step S15 includes the following steps: Step S151: Establish a preliminary three-dimensional structural model of the electrical cabinet based on the heterogeneous geometric space mapping data and the functional component data of the electrical cabinet; Step S152: Perform hierarchical solid structure feature analysis of the electrical cabinet based on the functional component data of the electrical cabinet, and generate hierarchical solid structure feature data of the electrical cabinet. The hierarchical solid structure feature data of the electrical cabinet includes feature data of the electrical cabinet load-bearing structure layer, feature data of the electrical cabinet wiring area layer, and feature data of the electrical cabinet component installation area layer. Step S153: Use the hierarchical entity feature data of the electrical cabinet to perform hierarchical structure entity identification processing on the preliminary three-dimensional model of the electrical cabinet structure, and generate a three-dimensional model of the electrical cabinet structure.

3. The three-dimensional integrated cabling method for cable networks in mining electrical cabinets according to claim 1, characterized in that, Step S16 includes the following steps: Step S161: Perform electrical component interface parsing processing on the electrical component interface data of the mine electrical cabinet to generate electrical component interface parsing data; Step S162: Based on the three-dimensional model of the electrical cabinet structure, perform spatial relationship analysis and processing on the interface data of the electrical components of the mine electrical cabinet to generate spatial relationship data of the structural model and component interfaces; Step S163: Map the parsed data of electrical component interfaces to the three-dimensional model of electrical cabinet structure through the spatial relationship data of structural model-component interface to perform electrical component interface attribute identification processing of electrical cabinet and generate an interface-identified three-dimensional model of electrical cabinet structure.

4. The three-dimensional integrated cabling method for cable networks in mining electrical cabinets according to claim 1, characterized in that, Step S25 includes the following steps: Step S251: Analyze the basic information of cable connections based on the electrical connection topology relationship data to generate basic information data of cable connections; Step S252: Perform multi-level cable connection relationship analysis on the basic cable connection information data to generate multi-level cable connection relationship data; Step S253: Perform cable connection engineering attribute analysis based on cable connection basic information data and cable multi-level connection relationship data to generate cable connection engineering attribute data; Step S254: Perform bundle management analysis and processing of cable connection topology requirements through cable connection basic information data, cable multi-level connection relationship data and cable connection engineering attribute data to generate cable connection topology requirement bundle management data.

5. A three-dimensional integrated cabling system for electrical cabinets in mines, characterized in that, For implementing the three-dimensional integrated cabling method for mine electrical cabinet cable networks as described in claim 1, the three-dimensional integrated cabling system for mine electrical cabinet cable networks includes: The electrical cabinet structure-interface model building module is used to acquire heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets; based on the heterogeneous physical structure data of mining electrical cabinets and interface data of electrical components in mining electrical cabinets, the module designs the electrical cabinet encapsulation model of structure and interface, and generates the encapsulated electrical cabinet structure-interface model. The cable connection topology requirement analysis module is used to perform bundle management analysis and processing of cable connection topology requirements based on the encapsulated electrical cabinet structure-interface model, and generate cable connection topology requirement bundle management data. The cable routing constraint domain analysis module is used to perform three-dimensional cable routing constraint domain analysis on the structure-interface model of the encapsulated electrical cabinet and generate three-dimensional cable routing constraint domain data. The cabling candidate path analysis module is used to map cable connection topology requirement bundle management data to three-dimensional cable cabling constraint domain data for spatial constraint three-dimensional cable cabling candidate path analysis, and generate three-dimensional cable cabling candidate path data. The cable 3D routing path analysis module is used to optimize the cable conflict of the candidate path data and generate cable 3D routing path data.

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