Three-dimensional space shortest wiring path planning method for charging pile and meter position

Abstract

The invention discloses a three-dimensional space shortest wiring path planning method for charging pile and meter positions, and belongs to the technical field of charging pile wiring. Comprising the following steps: establishing a corresponding relation among a shear wall, a reserved sleeve and a space obstacle through a three-dimensional semantic layering method, and generating a voxel grid with a grade mark; writing constraints such as structural safety, mechanical performance and occupancy state into the voxel grid to form a dynamic weight map; a hybrid heuristic strategy is adopted, a wiring path with the optimal length and weight is searched in the dynamic weight map, and a through-wall and bending node coordinate sequence is recorded; calculating the deformation inhibition coefficient of the protection pipe, and dynamically adjusting the specification and the bending radius of the protection pipe; and finally, integrating and outputting through a three-dimensional visual interface. According to the method, the multi-objective optimization problem that the wiring path in the multi-layer underground garage needs to meet the shortest distance, the structural safety and the construction feasibility at the same time is solved, structural damage and construction rework are effectively avoided, and the planning efficiency and the engineering reliability are improved.

Description

Technical Field

[0001] This invention relates to the field of charging pile wiring, and more specifically, to a method for planning the shortest three-dimensional wiring path between the charging pile and the meter location. Background Technology

[0002] With the increasing popularity of electric vehicles, the installation of charging stations in existing or newly built multi-story underground parking garages has become a common requirement. The power supply cables need to start from a fixed meter location, pass through the shear walls of each floor, bypass various structural obstacles, and finally reach the dispersed parking spaces. This wiring path planning is essentially a multi-constraint path optimization problem in three-dimensional space, and existing technologies have significant limitations in their solutions.

[0003] In the field of three-dimensional spatial path planning, the core logic of traditional methods can be summarized into two categories:

[0004] Graph search algorithms, such as Dijkstra's algorithm and A* algorithm, achieve shortest path search by constructing a network of nodes and calculating the cost between nodes. These methods are often used for macro-level site selection in charging pile layout planning, but their computational complexity increases exponentially with the degree of environmental discretization (number of nodes), and they are usually based on static, predefined maps, making it difficult to dynamically incorporate real-time changing spatial constraints and physical attributes.

[0005] Sampling search algorithms, such as RRT (Rapid Exploratory Random Tree), construct path trees through random sampling and are suitable for high-dimensional complex spaces. However, the paths they generate often have poor smoothness and high randomness, posing a risk of getting trapped in local optima, making it difficult to guarantee the economic efficiency and feasibility of the paths in engineering.

[0006] Furthermore, 3D spatial modeling techniques that form the basis of planning, such as the raster method, octree method, and voxel method, each have their own focus: the raster method is simple but has low accuracy; the octree method can dynamically adjust the resolution but has high computational overhead; and the voxel method has high accuracy but relies on high-quality point cloud data. These methods provide tools for environmental characterization, but they do not solve the problem of efficiently encoding complex engineering constraints (such as structural bearing capacity and cable mechanical properties) and deeply integrating them with path search algorithms.

[0007] Related patents (such as CN110245189A) and academic papers (Ant Colony Algorithm Optimization in 3D Cabling), Automation of Electric Power Systems, 2020, also propose combining BIM models or point cloud data with improved graph algorithms or swarm intelligence algorithms for cabling planning.

[0008] However, these existing solutions generally suffer from the following drawbacks, making them difficult to directly apply to the intricate engineering wiring scenarios between charging piles and meters:

[0009] 1. Insufficient integration of dynamic and semantic constraints: Existing methods mostly focus on geometric obstacle avoidance and path smoothing, failing to directly and efficiently embed rigid constraints such as the impassability of shear walls, the limited capacity and spatial location of reserved sleeves, and the minimum bending radius of cables into the search process. They typically use penalty functions for ex-post processing, which may lead to planned paths violating key engineering specifications and lacking construction feasibility.

[0010] 2. Lack of consideration for "structural safety": The current path planning only treats walls as obstacles, ignoring the structural safety risks posed by unauthorized openings in load-bearing shear walls or the overloading of pre-installed sleeves. The planning results may induce structural damage during the construction phase or require costly post-construction reinforcement.

[0011] 3. Lack of construction and operation-oriented output: The existing solution stops at outputting spatial coordinate sequence, without linking with specific pipe selection, bending process, material list, and construction procedures. It cannot form a complete technical document to guide on-site construction, resulting in a disconnect between planning and implementation, which easily leads to rework.

[0012] Therefore, existing technologies lack an intelligent, integrated cabling planning method that can systematically integrate semantic information of building structures, spatial geometric constraints, physical characteristics of cables, and construction process requirements, automatically generate a three-dimensional cabling plan that satisfies both shortest path economy and ensures structural safety and construction feasibility, and directly guides construction and operation and maintenance. This invention is proposed to fill this technological gap. Summary of the Invention

[0013] To address the aforementioned problems, this invention provides a three-dimensional spatial shortest wiring path planning method for charging pile and meter locations. It uses a three-dimensional semantic hierarchical method to uniformly map the geometric characteristics of shear walls, reserved conduits, and spatial obstacles onto a hierarchical voxel grid. Combining a dynamic weighted graph and a hybrid heuristic strategy, it generates wiring paths with optimal length and weight, simultaneously satisfying the requirements of shortest path, structural safety, and construction feasibility. Based on the coordinate sequence of wall-penetrating and bending nodes, the deformation suppression coefficient is calculated, and the conduit specifications and bending radius are dynamically adjusted to effectively reduce the risk of conduit buckling and springback, maintain cable integrity and structural stability, and reduce cable stress damage and fatigue failure. Finally, a three-dimensional visualization interface integrates the path, bill of materials, and construction sequence file, shortening rework time, reducing the probability of structural verification, and improving the positioning accuracy for later maintenance, thus solving the problems mentioned in the background art.

[0014] To achieve the above objectives, the present invention provides the following technical solution: a three-dimensional shortest wiring path planning method for charging piles and meter locations, comprising the following steps:

[0015] Step S1: Construct a three-dimensional semantic model of the underground parking garage that includes shear walls, reserved sleeves and spatial obstacles. Discretize the space of the underground parking garage into a uniform voxel grid. Assign a level label to each voxel based on its positioning relationship with the elements in the three-dimensional semantic model, representing whether it is traversable and its traversal capability, to form a voxel grid with level labels.

[0016] Step S2: In the voxel grid with grade markings, for each voxel, calculate the weight value based on its corresponding structural safety factor, minimum bending radius of the cable, and remaining capacity of the reserved sleeve, and generate a dynamic weight map.

[0017] Step S3: Based on the dynamic weight graph, a hybrid heuristic strategy is used to search for the path, obtain the wiring path with the optimal length and weight from the meter location to the charging pile location, and record the coordinate sequence of the wall-penetrating node and the coordinate sequence of the bending node on the wiring path.

[0018] Step S4: Calculate the deformation suppression coefficient of the protective pipe according to the bending node coordinate sequence, and adjust the specifications of the protective pipe and / or the local bending radius of the protective pipe at the bending node according to the deformation suppression coefficient;

[0019] Step S5: Visualize the cabling path in 3D and output the corresponding bill of materials and construction sequence file.

[0020] Preferably, in step S2, the structural safety factor is calculated as follows: the bearing capacity of the reserved sleeve corresponding to the voxel minus the existing pipeline load divided by the load of the cable to be laid; the remaining capacity of the reserved sleeve is calculated as follows: the cross-sectional area of ​​the reserved sleeve minus the occupied cross-sectional area divided by the cross-sectional area of ​​the cable to be laid.

[0021] Preferably, in step S2, the weight value is calculated by weighting the reciprocal of the structural safety factor, the reciprocal of the minimum bending radius of the cable, and the reciprocal of the remaining capacity of the reserved sleeve; when the structural safety factor is lower than a preset threshold or the remaining capacity of the reserved sleeve is less than or equal to zero, the weight value of the corresponding voxel is set to the maximum value representing the impassable value.

[0022] Preferably, in step S3, the hybrid heuristic strategy is a strategy that combines the A algorithm and the ant colony algorithm; wherein, the A algorithm is first used to generate an initial path in the dynamic weight graph, and then the ant colony algorithm is used to optimize the initial path to minimize the total path cost, wherein the total path cost is the weighted sum of the path length and the voxel weight values ​​on the path.

[0023] Preferably, in step S3, after obtaining the wiring path, the wiring path is smoothed by Bézier curve and the path trajectory is adjusted by curve interpolation method; wherein, the wall-penetrating node is the voxel corresponding to the center of the reserved sleeve when the path passes through the shear wall, and the bending node is the voxel where the path direction changes.

[0024] Preferably, in step S4, calculating the deformation suppression coefficient of the protective tube includes:

[0025] The local bending radius is determined based on the coordinate sequence of the bending node, and the local bending stress of the protective pipe at that location is calculated.

[0026] Calculate the remaining buckling margin of the liner based on local bending stress and the yield strength of the liner material. ;

[0027] Calculate the bending springback resistance index based on local bending stress and yield strength. ;

[0028] Based on the remaining margin of the sheath buckling and the bending springback resistance index, a deformation suppression coefficient is generated. .

[0029] Preferably, the formula for calculating the remaining margin of the protective pipe buckling is:

[0030]

[0031] in, The yield strength of the protective pipe material; This is local bending stress; The elastic modulus of the protective tube; The diameter of the protective tube; The radius of curvature is the local bending radius.

[0032] Preferably, the formula for calculating the bending springback resistance index is: when hour,

[0033] otherwise .

[0034] Preferably, the deformation suppression coefficient It is the ratio of the normalized value of the remaining margin of the pipe bending to a nonlinear amplification factor based on the bending spring resistance index.

[0035] Preferably, when the deformation suppression coefficient Less than the set threshold When this happens, adjustments are triggered:

[0036]

[0037] in, For the new diameter of the protective pipe; The diameter of the protective tube;

[0038]

[0039] in, The new local radius of curvature for the protective pipe; The radius of curvature is the local bending radius. The yield strength of the protective pipe material.

[0040] The present invention has the following technical effects:

[0041] (1) Achieving optimal overall path and improving engineering economy and electrical performance: By constructing a dynamic weighted graph that integrates structural semantics and physical constraints, and using a hybrid heuristic strategy (combining A algorithm and ant colony algorithm) for search, this invention can automatically generate the shortest wiring path with the lowest overall weight (reflecting safety, capacity, and bending difficulty) in complex three-dimensional space. This directly reduces the amount of cable used, lowers line voltage drop and loss, and improves power supply economy and reliability from the source.

[0042] (2) Ensuring building structural safety and eliminating the risk of illegal construction: Through three-dimensional semantic layered modeling, shear walls and reserved sleeves are precisely embedded into the voxel mesh as rigid constraints. During path planning, the system forces cables to pass only through identified reserved sleeves with sufficient capacity, fundamentally avoiding the risks of blindly drilling holes in shear walls or overloading sleeves. This ensures that the main building structure is not damaged, greatly reducing the probability and cost of subsequent structural review and reinforcement.

[0043] (3) Enhanced construction feasibility and reliability, reducing on-site changes and rework: This invention not only plans the route, but also dynamically recommends matching conduit specifications and bending radii by recording the sequence of wall penetration and bending nodes and calculating the deformation suppression coefficient based on a mechanical model. This ensures that the planned route meets the mechanical performance requirements of cable bending, and that the conduit has sufficient resistance to compression bending and springback, allowing the "paper plan" to be directly used in construction, significantly reducing on-site adjustments and rework caused by physical conflicts or insufficient strength.

[0044] (4) Achieve digital delivery of planning results and improve the efficiency of full life cycle management: Through a three-dimensional visualization interface, a smooth wiring path, key nodes, material list and construction sequence Gantt chart are integrated and displayed, and it supports exporting to standard engineering files such as CAD and PDF, realizing the lossless and accurate transmission of planning results to the construction and operation and maintenance stages. This not only guides construction to be more efficient and accurate, but also provides accurate digital archives for later maintenance and renovation, greatly improving the positioning accuracy and traceability of operation and maintenance. Attached Figure Description

[0045] Figure 1This is a flowchart illustrating the three-dimensional shortest wiring path planning method for the charging pile and meter locations according to the present invention. Detailed Implementation

[0046] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] This invention proposes a three-dimensional spatial shortest wiring path planning method for charging pile and meter locations. Through scientific modeling and hierarchical analysis, it generates an optimized and safe wiring path.

[0048] like Figure 1 As shown, the method of the present invention includes the following steps:

[0049] Step S1 transforms the complex three-dimensional spatial structure into a computable mesh model, providing data support for subsequent path search.

[0050] Step S1 specifically includes:

[0051] 3D semantic hierarchical modeling:

[0052] A three-dimensional digital model of the underground parking garage's architectural structure was created, with a focus on processing data on shear walls, reserved sleeves, and spatial obstacles.

[0053] As load-bearing components, shear walls impose strict constraints on cable routing paths due to their location and geometry. Therefore, it is necessary to accurately record the spatial coordinates and boundary range of shear walls.

[0054] The reserved conduit is the only channel for cables to pass through shear walls. Its spatial location, diameter, and availability directly determine the feasibility of the wiring path, and these attributes must be fully recorded.

[0055] Spatial obstacles include beams, columns, pipelines, and air ducts, which restrict the cabling space, so it is necessary to accurately describe their three-dimensional location and occupied area.

[0056] By performing three-dimensional modeling on these elements, a digital model reflecting the physical structure of the underground parking garage is generated.

[0057] Shear walls, pre-installed conduits, and spatial obstacles are key factors affecting cabling paths. Accurate modeling can comprehensively capture the spatial characteristics of these elements. The generated model provides accurate structural data for subsequent path planning, ensuring that the cabling scheme is consistent with the actual environment and avoiding planning errors caused by missing data.

[0058] Generation of traversable cross-section sets:

[0059] After the 3D modeling is completed, a set of all traversable sections in the underground parking garage is identified and generated. Traversable sections include pre-installed sleeves in shear walls, which are safe passageways for cables. The specific processing procedure is as follows:

[0060] The system iterates through the reserved sleeves recorded in the 3D model, extracts the spatial location and physical properties of each reserved sleeve cross-section, such as the diameter of the reserved sleeve or the cross-sectional area of ​​the opening, and organizes these cross-sections into a set. Each element in this set represents a potential wiring channel.

[0061] Reserved conduits are fixed areas where cables cross in underground parking garages. Clearly defining the location and attributes of these areas provides clear boundary conditions for path planning. By centrally managing traversable sections, the path planning process can quickly locate legal routes, avoiding wasting computational resources in traversable areas, thereby improving planning efficiency and cabling security.

[0062] Voxel mesh generation:

[0063] To transform the complex three-dimensional space of the underground parking garage into a computable structure, the entire space is divided into a uniform voxel mesh. A voxel is a basic unit in three-dimensional space, resembling a cube, with its side length determined according to accuracy requirements, for example, set to 0.1 meters. The processing procedure is as follows:

[0064] Using the spatial boundaries of the underground parking garage as a reference, the space is uniformly divided into multiple voxels, with each voxel recording the 3D coordinates of its center point. After partitioning, a mesh structure containing all voxels is generated. This partitioning method discretizes the continuous 3D space into discrete units, facilitating data processing and pathfinding by the computer.

[0065] Discretizing complex spaces transforms geometric problems into gridded computational problems, simplifying the complexity of subsequent analysis. Voxel grids provide a unified computational framework for path planning, enabling spatial search algorithms to run efficiently while supporting flexible adjustments for different precision requirements.

[0066] Assigning a grade marker:

[0067] After the voxel mesh is generated, each voxel is assigned a level label to reflect whether it can be traversed by cables and its traversal capability. The specific processing procedure is as follows:

[0068] Based on the spatial location of the voxel, determine its relationship with shear walls, pre-installed sleeves, and spatial obstacles in the 3D model. If the center point of the voxel is located inside a shear wall or spatial obstacle, it is marked as non-passable; if the voxel is located inside a pre-installed sleeve or in free space (free space refers to the area not occupied by shear walls, pre-installed sleeves, or spatial obstacles, including cavities inside the garage where wiring can be installed), it is marked as passable, and its passability is further recorded (including whether it is passable and the number of cables or equivalent cross-sectional area it can accommodate). After assignment, each voxel has a clear passability attribute.

[0069] By quantifying the traversal characteristics of space, physical constraints can be transformed into computer-recognizable attributes, facilitating the rapid selection of feasible areas during path searching. Hierarchical labeling allows path planning to directly avoid inaccessible areas while optimizing the use of areas with limited traversal capabilities, thereby improving the rationality and security of cabling schemes.

[0070] Establishment of correspondence:

[0071] After completing the grade labeling, semantic associations are established between the shear walls, reserved sleeves, and spatial obstacles in the 3D model and the voxel mesh. The specific processing procedure is as follows:

[0072] Each voxel in the voxel mesh is traversed, and its corresponding building component is determined based on its spatial location, with relevant attributes attached. For example, if a voxel is located inside a reserved sleeve, the sleeve's number is recorded; if it is located inside a spatial obstacle, the obstacle type is recorded. After association, each voxel not only contains its geometric location but also semantic information, forming a comprehensive spatial data structure.

[0073] Simple geometric data is insufficient to support complex path planning; adding semantic attributes can provide richer contextual information. This data structure enhances the accuracy of path planning, enabling the planning results to fully consider the actual functions and constraints of building components, thereby improving the reliability and construction feasibility of the wiring scheme.

[0074] Through the five sub-steps described above, step S1 transforms the complex three-dimensional spatial structure of the underground parking garage into a voxel mesh model with hierarchical labels. This model captures the physical structure through three-dimensional semantic hierarchical modeling, clarifies passage areas through a set of traversable cross-sections, achieves spatial discretization through voxel meshes, quantifies traversal attributes through hierarchical labels, and integrates semantic information through correspondences. Abstracting the physical environment into a computable mathematical model enables efficient path planning algorithms.

[0075] Step S2 transforms the structural safety threshold, line mechanical performance, and real-time occupancy status into quantifiable weights, generating a dynamic weight graph that provides a comprehensive basis for path search in step S3.

[0076] Step S2 specifically includes:

[0077] Structural safety factor written in:

[0078] In the planning of wiring routes for underground parking garages, the structural safety of shear walls is the primary consideration. To ensure that wiring does not weaken the load-bearing capacity of the shear walls, the safety status of each reserved sleeve is assessed.

[0079] The assessment process begins by obtaining the load-bearing capacity data of the sleeve, which is derived from the structural parameters recorded in the architectural design drawings. Next, through site surveys or Building Information Modeling (BIM) data, the load exerted on the sleeve by existing pipelines is determined; this is called the existing pipeline load. Then, based on the specifications of the proposed cable, the load exerted on the sleeve by the proposed cable is calculated; this is called the proposed cable load. The remaining load-bearing capacity of the sleeve is obtained by subtracting the existing pipeline load from its load-bearing capacity. The remaining load-bearing capacity is then divided by the proposed cable load to calculate the structural safety factor. If the calculated structural safety factor is less than one, it indicates that the remaining load-bearing capacity of the sleeve is insufficient to support the new cable; this sleeve is marked as impassable, and the marking information is recorded in the voxel attribute field corresponding to the sleeve in the voxel mesh. If the structural safety factor is greater than or equal to one, the sleeve is considered to have sufficient load-bearing capacity and is marked as permissible.

[0080] By quantifying the load-bearing capacity and load relationship of conduits, it is ensured that the wiring path will not pose a safety hazard to the building structure. The process of calculating the structural safety factor can identify conduits with insufficient load-bearing capacity in advance, avoiding rework or reinforcement requirements due to structural problems during the construction phase, thereby reducing project risks and implementation costs.

[0081] Circuit mechanical properties are written in:

[0082] Cables must meet mechanical performance requirements during installation and operation to prevent damage caused by physical stress. Minimum bending radius and maximum tensile force must be considered.

[0083] The minimum bending radius refers to the minimum permissible radius of curvature for a cable when bent, used to limit the curvature of corners in the cabling path. The maximum tensile force refers to the maximum force a cable can withstand when stretched, used to limit the upper limit of tensile force on the cable in the path. In the voxel mesh, for voxels marked as traversable, the system records the minimum bending radius and maximum tensile force in the corresponding attribute fields. These parameters are used in subsequent path planning to verify whether the path meets the mechanical performance constraints of the cable. Specifically, if the curvature of a path corner is less than the minimum bending radius, or if the force on the cable in the path exceeds the maximum tensile force, the path is considered infeasible.

[0084] By incorporating the cable's mechanical performance parameters into a voxel grid, the feasibility of the path can be automatically verified during the path planning phase, ensuring that the cable is not damaged by excessive bending or stretching. This ensures the reliability of the cabling solution and guarantees the performance stability of the cable during long-term use.

[0085] Real-time occupancy status writing:

[0086] The real-time occupancy status of the reserved conduit directly affects whether it can accommodate new cables. This can be assessed by calculating the remaining capacity of the conduit.

[0087] First, obtain the cross-sectional area of ​​the conduit, which is obtained from design drawings or on-site measurements. Then, calculate the total cross-sectional area of ​​existing cables, i.e., the sum of the cross-sectional areas of all cables that have passed through the conduit. Subtract the total cross-sectional area of ​​existing cables from the conduit's cross-sectional area to obtain the remaining cross-sectional area of ​​the conduit. Next, based on the cross-sectional area of ​​the proposed cable, calculate the remaining cross-sectional area divided by the proposed cable's cross-sectional area to determine the number of proposed cables the conduit can accommodate, called the remaining capacity. If the remaining capacity is less than or equal to zero, it indicates that the conduit has no space to accommodate new cables, the system marks this conduit as unpassable, and records the remaining capacity information in the voxel attribute field corresponding to the conduit in the voxel grid. If the remaining capacity is greater than zero, it is marked as passable, and the corresponding data is recorded.

[0088] By calculating and recording the remaining capacity of the bushings in real time, the usage status of the bushings can be dynamically reflected, avoiding the selection of bushings that are already full or have insufficient capacity for wiring. This method ensures the feasibility of the wiring scheme and retains flexibility for possible future expansion needs.

[0089] Dynamic weight graph generation:

[0090] To comprehensively consider the impact of structural safety, cable mechanical properties, and conduit occupancy status on the cabling path, the system generates a weight value for each voxel in the voxel grid. The weight value calculation includes three factors: structural safety risk factor, bending constraint factor, and occupancy pressure factor.

[0091] The structural safety risk factor is determined by taking the reciprocal of the structural safety factor; the smaller the structural safety factor, the larger the factor value, indicating a higher structural risk. The bending limitation factor is determined by taking the reciprocal of the minimum bending radius; the smaller the minimum bending radius, the larger the factor value, indicating a stricter corner restriction. The occupancy pressure factor is determined by taking the reciprocal of the remaining capacity; the smaller the remaining capacity, the larger the factor value, indicating a higher capacity pressure. These three factors are multiplied by their respective adjustment coefficients and then summed to obtain the weight value for each voxel. The adjustment coefficients are pre-set according to specific engineering requirements to balance the influence of each factor. If the structural safety factor of the sleeve corresponding to a voxel is less than one, or the remaining capacity is less than or equal to zero, the weight value is directly set to a maximum value, indicating that the voxel cannot be traversed. Finally, a dynamic weight map is generated based on the weight values ​​of all voxels, serving as input data for path search.

[0092] Dynamic weighted graphs transform multiple constraints into unified weight values, enabling path search algorithms to determine the optimal cabling path based on a comprehensive evaluation of structural safety, mechanical performance, and capacity limitations. This improves the comprehensiveness and adaptability of planning, ensuring that cabling solutions balance economy and safety.

[0093] Step S3, based on the dynamic weight graph from step S2, uses a hybrid heuristic strategy to search for the shortest and lowest-weighted cabling path, solving the optimization problem of power cables crossing shear walls and spatial obstacles in multi-story underground parking garages. The synchronously recorded coordinate sequences of wall-penetrating and bending nodes provide precise data support for adjusting conduit specifications and bending radii in step S4, ensuring comprehensive optimization of the cabling scheme in terms of economy, safety, and construction feasibility.

[0094] Step S3 specifically includes:

[0095] Design of hybrid heuristic strategies:

[0096] In the process of planning the wiring path in the underground parking garage, in order to achieve the dual optimization goals of minimizing the path length and the path weight, a hybrid heuristic strategy combining the A algorithm and the ant colony algorithm is adopted. The combination of the two can simultaneously take into account both computational efficiency and global optimality.

[0097] The specific implementation method is as follows: First, using the meter location as the starting point and the charging pile location as the ending point, an A algorithm search is performed in a voxel grid. During the search, the straight-line distance from the starting point to the ending point is used as a guiding function to prioritize exploring voxels closer to the ending point. Simultaneously, the weight value of each voxel in the dynamic weight graph is combined to avoid selecting high-risk or impassable areas. Second, based on the initial path generated by the A algorithm, an ant colony algorithm is deployed for optimization. Each ant represents a possible path solution, and the path is gradually adjusted through a pheromone update mechanism to optimize its overall performance.

[0098] The pheromone update rule is as follows: the pheromone concentration gradually decreases over time, while increasing based on the incremental pheromone left by ants. The pheromone increment is proportional to the reciprocal of the total path cost. The total path cost is defined as the weighted sum of the path length and the voxel weights along the path. The path length is the sum of the straight-line distances between adjacent voxels, and the weights are the sum of the weight values ​​of all voxels along the path. An adjustment coefficient is used to balance the priority of path length and weights.

[0099] The total path cost is comprehensively evaluated by weighting the path length and the voxel weights along the path, while the pheromone update mechanism drives path optimization towards the lowest cost. The ant colony algorithm's rapid localization capability shortens the initial path generation time, and its global optimization characteristics further improve path quality in complex environments. This hybrid strategy can efficiently search for short and safe paths in multi-level underground parking garage wiring scenarios, ensuring a balance between economy and safety.

[0100] Path search and optimization:

[0101] Based on a dynamic weight graph, path search and optimization are performed to ensure that the wiring path is optimal in both length and weight. The dynamic weight graph assigns a weight value to each voxel in the voxel mesh, reflecting its traversal difficulty or risk level.

[0102] The specific implementation method is as follows: First, starting from the meter location, voxels with low weight values ​​and close to the destination are explored first to generate an initial path. During the exploration process, the weight values ​​of adjacent voxels are compared with the expected distance to the destination, and the voxel extension path with the lowest overall cost is selected until the charging pile location is reached. Second, based on the initial path, the ants explore in the voxel grid, prioritizing paths with low weight and high pheromone concentration. The path is adjusted through multiple iterations until the overall path performance tends to stabilize.

[0103] The optimization objectives include two aspects: first, the path length should be close to the theoretical shortest value, which is achieved through the guiding function of the initial search; second, the cumulative weight value on the path should be minimized, which is achieved through global exploration by ants and pheromone updates, thus meeting the requirements of structural safety and mechanical performance.

[0104] A multi-objective optimization method is employed to generate a set of paths that perform well in both path length and weight values. The path with the lowest total cost is then selected as the optimal solution. Multi-objective optimization compares the length and weight performance of different paths to identify the solution with the best overall performance.

[0105] To further determine the feasibility of the cabling path, the tensile force at any point along the path is estimated. If the tensile force exceeds the maximum tensile force of the cable, the path is deemed infeasible and eliminated, and the search is repeated following the steps described above.

[0106] This invention predetermines or sets the target cable model before route planning. The mechanical parameters of this model, such as the maximum allowable tensile force, unit weight, and friction coefficient between the cable outer sheath and the conduit / support, can be obtained from the product manual or relevant specifications. After generating candidate wiring paths, the path is discretized into several straight segments and curved segments. For the straight segments, the traction force is calculated based on the cable unit weight, segment length, and friction coefficient. For the curved segments, the force is accumulated and superimposed using the tensile force amplification relationship known in the art based on the bending angle and friction coefficient. The estimated tensile force at each position on the path is obtained by accumulating segment by segment from the starting point to the ending point. The estimated tensile force is then compared with the maximum allowable tensile force of the set cable model. If the estimated tensile force at any position on the path exceeds the maximum allowable tensile force, the candidate path is determined to be mechanically infeasible and is eliminated. This ensures that the final determined wiring path is geometrically feasible while meeting the cable tensile strength safety requirements.

[0107] Node coordinate sequence record:

[0108] During the path search process, the coordinate sequences of wall penetration nodes and bend nodes are recorded simultaneously, providing crucial data for subsequent adjustments to the pipe specifications and bending radii. Wall penetration nodes and bend nodes are important feature points in the path, corresponding to the locations where shear walls are crossed and where the path direction changes, respectively.

[0109] The specific implementation method is as follows: when the path passes through the shear wall, the voxel at the center of the reserved sleeve is identified, its three-dimensional coordinates are recorded, and it is marked as a wall-penetrating node; when the direction of adjacent voxels in the path changes, the coordinates of the changed voxels are recorded and marked as bending nodes.

[0110] The node identification process is as follows: by calculating the angle of change of the direction of the line connecting adjacent voxels, it is determined whether it exceeds a preset threshold. If it does, it is marked as a bent node. Based on the semantic attributes of the voxels, it is determined whether they are located in the shear wall area. If so, they are marked as through-wall nodes.

[0111] By judging the angle of directional changes and the semantic attributes of voxels, key nodes in the path can be accurately identified and recorded. Recording the coordinates of wall penetration nodes and bend nodes can accurately identify important locations in the path, providing an accurate basis for the selection of conduit specifications and the design of bend radii, ensuring the feasibility and reliability of the cabling scheme during construction and operation.

[0112] Output and transmission:

[0113] Generate the optimal path and output relevant data for subsequent construction and verification steps to ensure the integrity and feasibility of the planning results.

[0114] The specific implementation method is as follows: From the optimization results of the ant colony algorithm, the path with the lowest total cost is selected as the final cabling path, and the coordinate sequences of the wall-penetrating nodes and the bending nodes are output together. Before output, the path is smoothed using Bézier curves, and the path trajectory is adjusted using curve interpolation methods to reduce the bending angle and improve the smoothness of cable laying. The curve interpolation method generates smooth transition curves based on the coordinates between adjacent nodes on the path, replacing the original straight-line connections.

[0115] Path smoothing optimizes the path shape through curve interpolation, reducing sharp changes at corners. Smoothing reduces stress concentration at corners, improving cabling quality and cable lifespan; outputting complete path and node data ensures accurate input for subsequent steps, guaranteeing the operability and consistency of the planning results.

[0116] This method employs a hybrid heuristic strategy to search for the optimal cabling path in a dynamic weighted graph, finding the path length and weight values ​​that are optimal in both cases. It also records the coordinate sequences of wall-penetrating and bending nodes, ultimately outputting the optimized path data. In multi-story underground parking garage cabling scenarios, this approach effectively balances economy, safety, and construction feasibility, ensuring the scientific rigor, reliability, and practicality of the cabling solution.

[0117] During wall penetration and bending, the conduit is subjected to complex stresses, and its deformation characteristics directly affect the safety and service life of the cable. Therefore, step S4 requires accurate calculation of the conduit's buckling margin and bending springback impedance index, and the generation of a deformation suppression coefficient using a mechanically coupled model, thereby achieving adaptive adjustment of the conduit specifications and bending radius. This process must rely on the wall penetration node coordinate sequence and bending node coordinate sequence provided in step S3 to ensure seamless integration of the calculation logic with the aforementioned path planning results.

[0118] Step S4 specifically includes:

[0119] Calculate the remaining margin for pipe buckling:

[0120] The calculation of the buckling margin of the protective pipe aims to evaluate its load-bearing capacity under actual bending conditions, reflecting the remaining strength of the pipe against buckling failure at a specific bending radius. It is based on beam bending theory and the yield strength of the material.

[0121] First, the local bending radius of each bending node is extracted from the coordinate sequence of the bending nodes. The local bending radius is determined using the coordinate data of three adjacent nodes and a circular arc fitting method. The cross-section of the protective pipe is circular, and its diameter and elastic modulus are input into the system as known parameters.

[0122] Next, the local bending stress at each bend is calculated. The calculation of local bending stress is based on the relationship between the elastic modulus, the sheath diameter, and the local bending radius; specifically, the elastic modulus is multiplied by the sheath diameter and then divided by twice the local bending radius. The sheath buckling margin is defined as the difference between the sheath material's yield strength and the local bending stress. If the sheath buckling margin is less than or equal to zero, it indicates that the stress at that bend has reached or exceeded the yield strength, and buckling failure may occur. For example, the calculation logic can be as follows:

[0123] Based on the coordinate sequence of the bending nodes The local bending radius of each bending node can be determined. The load-bearing capacity of the protective casing is related to its material yield strength and bending stress. The buckling margin of the protective casing... Defined as the difference between the yield strength and the actual bending stress, the specific calculation is as follows:

[0124] The protective pipe has a circular cross-section, and its diameter is denoted as . .

[0125] The elastic modulus of the protective tube is Yield strength is .

[0126] For each bending node, the local bending stress Calculations were performed using beam bending theory:

[0127]

[0128] in, The bending radius of this node is given by... The coordinates of three adjacent points are determined by circular arc fitting.

[0129] Remaining margin for pipe buckling for:

[0130]

[0131] like This indicates that the protective tube has exceeded its yield limit and there is a risk of buckling.

[0132] Based on beam bending theory and material mechanics parameters, the mechanical safety space of the conduit under bending conditions is quantified. This accurately reflects the strength state of the conduit along the cabling path, preventing structural failure caused by localized stress concentration. By calculating the conduit's buckling margin, potential risk points in the cabling scheme can be identified, ensuring the conduit has sufficient load-bearing capacity during construction and operation, thereby improving the overall safety of the cabling project.

[0133] Calculate the bending springback resistance index:

[0134] The bending springback resistance index is calculated to characterize the difficulty of the sheath resisting springback after bending, reflecting the energy dissipation characteristics of the sheath material during cyclic deformation. The calculation process is based on the plastic deformation behavior of the sheath.

[0135] First, the initial bending angle of each bending node is calculated from the coordinate sequence of the bending nodes. The initial bending angle is determined using geometric relationships based on the coordinate data of three adjacent nodes.

[0136] Next, based on the calculated local bending stress and the yield strength of the sheath material, the springback angle is estimated. The springback angle is estimated as follows: when the local bending stress exceeds the yield strength, the springback angle is proportional to the initial bending angle and the difference between the local bending stress and the yield strength; if the local bending stress does not exceed the yield strength, the springback angle is considered zero. The bending springback resistance index is defined as the ratio of the springback angle to the initial bending angle, and its value ranges from zero to one. A ratio of zero indicates that the sheath completely recovers its original shape after bending, which is elastic deformation; a ratio of one indicates that the sheath completely retains its deformation after bending, with no springback, which is plastic deformation. For example, the calculation logic can be as follows:

[0137] The springback resistance is related to the elastic potential energy and the degree of plastic deformation of the sheath. (Based on the bending node coordinate sequence) The initial bending angle and springback angle can be estimated, and the specific calculation is as follows:

[0138] Initial bending angle The angle of deflection of the protective pipe at the bend is calculated by using the coordinates of three adjacent points.

[0139] spring angle Related to the plastic deformation of materials, defined as:

[0140] (when Otherwise

[0141] in, The aforementioned bending stress.

[0142] Bending springback resistance index Defined as the ratio of the rebound angle to the initial angle:

[0143] (when Otherwise

[0144] The value range is from 0 to 1. Indicates perfect elastic rebound. This indicates complete plastic deformation with no springback.

[0145] By employing plastic deformation theory and stress analysis, the deformation stability of the cable sheath after bending is quantified. This allows for accurate assessment of the sheath material's springback characteristics within the cabling path, preventing path deviation caused by springback. Calculating the bending springback impedance index helps identify the sheath's deformation behavior, ensuring the cabling path maintains geometric stability over long-term use and preventing additional stress on the cable due to path changes.

[0146] Deformation suppression coefficient:

[0147] The deformation suppression coefficient is generated to comprehensively assess the deformation risk of the conduit in the wiring path, providing a basis for subsequent adjustments to conduit specifications and bending radii. The calculation process is based on the coupling effect of the conduit buckling margin and the bending springback resistance index.

[0148] First, the sheath buckling margin is normalized to a dimensionless index, namely, the sheath buckling margin divided by the yield strength of the sheath material, yielding the relative load-bearing capacity. Next, a nonlinear amplification factor is constructed using the bending springback resistance index, specifically the square of the bending springback resistance index plus a constant of one, to enhance the impact of springback characteristics on deformation risk. The deformation suppression coefficient is defined as the ratio of the relative load-bearing capacity to the nonlinear amplification factor, ranging from zero to one. The smaller the deformation suppression coefficient, the higher the deformation risk of the sheath in the current cabling path.

[0149] A nonlinear coupling model is used to synthesize the load-bearing capacity and resilience characteristics of the conduit, generating a comprehensive risk assessment index. This index can fully reflect the mechanical behavior of the conduit in the cabling path.

[0150] Adjust the specifications and bending radius of the protective pipe:

[0151] The adjustment of conduit specifications and bending radius is based on the calculation of the deformation suppression coefficient, aiming to reduce the risk of conduit deformation and optimize the wiring path. The adjustment process first sets a threshold for the deformation suppression coefficient, such as 0.8, as a criterion. If the calculated deformation suppression coefficient is less than this threshold, the adjustment mechanism is activated. The adjustment includes two aspects:

[0152] One method is to increase the diameter of the protective pipe to improve the load-bearing capacity. The new diameter of the protective pipe is calculated by multiplying the original diameter of the protective pipe by the square root of the ratio of the deformation inhibition coefficient threshold to the current deformation inhibition coefficient.

[0153] Second, the local bending radius is increased to reduce local bending stress. The new local bending radius is calculated by multiplying the original local bending radius by the ratio of the yield strength of the sheath material to the difference between the yield strength and the remaining buckling margin of the sheath (when the remaining buckling margin is less than the yield strength). After adjustment, the system recalculates the remaining buckling margin, bending springback resistance index, and deformation suppression coefficient to verify whether the adjusted results meet the threshold requirements of the deformation suppression coefficient. For example, the calculation logic can be as follows:

[0154] Based on deformation suppression coefficient The value automatically adjusts the diameter of the protective tube. and bending radius :

[0155] Set threshold (e.g., 0.8), if This triggers an adjustment.

[0156] Upgraded pipe specifications: larger To improve and New diameter for

[0157]

[0158] Bending radius correction: Increase To reduce New radius for:

[0159]

[0160] Recalculate after adjustment , and Verify whether it meets the requirements. .

[0161] Based on a feedback mechanism using a deformation suppression coefficient, the system adaptively adjusts conduit parameters and path geometry. It can optimize cabling schemes in real time based on existing data, avoiding the inefficiency of manual intervention. This ensures the deformation safety and structural stability of the conduit in complex cabling environments, while improving the reliability and construction efficiency of cabling projects without incurring additional hardware costs.

[0162] By analyzing the coordinate sequence of bending nodes, the remaining margin of pipe buckling and the bending springback resistance index are calculated sequentially to generate a deformation suppression coefficient. Based on the calculation results, the pipe diameter and local bending radius are adaptively adjusted. This method is suitable for wiring scenarios in multi-story underground parking garages, effectively reducing the failure risk of pipes caused by buckling and springback, and ensuring that the wiring path meets design constraints while taking into account the load-bearing capacity and deformation stability of the pipes.

[0163] Step S5 integrates the wiring path, bill of materials, and construction sequence documents into a 3D visualization interface, enabling an intuitive display and efficient transmission of the wiring planning results for charging piles in multi-level underground parking garages. Smooth interpolation of path curves, precise node labeling, and the construction of an interactive interface ensure that the construction team can accurately understand the path details; the structured display of the construction sequence and bill of materials further guides on-site operations, reducing the need for construction adjustments.

[0164] Step S5 specifically includes:

[0165] Data integration and formatting:

[0166] First, the cabling paths, bill of materials, and construction sequence documents from the preceding steps are collected and organized. The cabling path is represented by a series of voxel coordinate sequences. These sequences are converted into continuous three-dimensional path curves, and a smooth trajectory is generated using cubic spline interpolation. The bill of materials is a structured list of physical materials such as cables and conduits required along the cabling path, compiled based on the path solution results. It includes the path length of each segment determined by the voxel coordinate sequence and bend nodes, the corresponding cable type and number (determined by the aforementioned cable mechanical parameters and power distribution requirements), and the specifications of each conduit segment (diameter, length, etc., determined by the aforementioned conduit specifications and local bending radius correction results). The construction sequence document is a sequence of construction steps based on the nodes, segment information, and floor / area of ​​the same path, arranging conduit pre-embedding or installation, cable threading, and other procedures according to spatial location and dependencies. It originates from the cabling path voxel coordinate sequence, bend node locations, conduit specifications and quantities, and corresponding cable types obtained in the preceding steps.

[0167] Cubic spline interpolation ensures the continuity and smoothness of the path curve by constructing a smooth polynomial curve between every two adjacent coordinate points. Specifically, for every two adjacent coordinate points on the path, a cubic polynomial curve is calculated, ensuring that the position, slope, and curvature of this curve remain continuous at the connection points, ultimately generating a complete and smooth path curve. This method accurately reflects the geometric characteristics of the cabling path while ensuring that the curvature at bends meets the minimum bending radius requirement of the cable, avoiding physical damage to the cable from sharp corners.

[0168] Simultaneously, the coordinate sequences of wall penetration nodes and bending nodes were labeled, recording the precise three-dimensional position of each node and associating it with corresponding parameters such as pipe specifications and bending radii. This labeled information plays a crucial role in subsequent visualization and construction guidance, helping construction personnel quickly identify important locations and specific construction requirements along the path. Furthermore, the material list and construction sequence files were organized into structured data and stored using JSON format. JSON format organizes data using key-value pairs, facilitating reading, transmission, and parsing, and ensuring efficient data transfer between different systems and devices.

[0169] Construction of a 3D visualization interface:

[0170] In the sub-step of constructing the 3D visualization interface, the calibrated 3D path curves, the coordinate sequences of wall-passing nodes, and the coordinate sequences of bending nodes are mapped onto a 3D coordinate system, and OpenGL rendering technology is used to generate a visualization image. OpenGL is a high-efficiency graphics rendering tool, adept at handling the drawing of 3D graphics and user interaction. The 3D path curves are presented in the form of lines in the 3D scene, and spheres of different colors are used to mark wall-passing nodes and bending nodes so that users can quickly distinguish key locations in the path. For example, wall-passing nodes are represented by red spheres, and bending nodes are represented by yellow spheres.

[0171] For through-wall nodes, a cross-sectional view of the sleeve is generated at the node location, showing the sleeve's diameter and the number of cables passing through it. The cross-sectional view is achieved by drawing a circular cross-section at the node, with the radius of the circle matching the sleeve's diameter. For bend nodes, a local curvature circle is drawn, showing the bend radius and the sleeve's diameter. The radius of the local curvature circle is equal to the bend radius, visually reflecting the degree of curvature of the path at that point. Furthermore, multi-view interactive functionality is supported. Users can rotate the viewpoint around the Z-axis of the 3D scene using rotation, zoom in or out using scaling, and move the scene in 3D space using translation, thus viewing path details from different angles.

[0172] Display of construction sequence and materials list:

[0173] In the sub-step of presenting the construction sequence and bill of materials, the formatted construction sequence file is broken down into a series of construction stages, and the construction progress is displayed in the form of a Gantt chart. The Gantt chart uses time on the horizontal axis and lists each construction stage on the vertical axis, visually displaying the start time, end time, and duration of each stage. Based on the data in the construction sequence file, the Gantt chart is automatically generated, and by summing the durations of all construction stages, the estimated completion time of the entire construction process, i.e., the total construction time, is calculated.

[0174] Meanwhile, the materials list is presented in tabular form, listing the name, specifications, and quantity of each material. The table supports sorting by material specifications or name, making it easy for users to quickly find and verify material information. In addition, a filtering function is provided, allowing users to select specific types of materials or specifications to view according to their needs, further improving the convenience of materials management.

[0175] Displaying the construction sequence in Gantt chart format clearly presents the construction progress and schedule, helping the construction team to rationally plan the construction process and reduce the possibility of delays. The bill of materials is presented in tabular format and supports sorting and filtering functions, simplifying the management and verification process of materials and ensuring accurate supply and efficient use of materials during construction.

[0176] Data export and transfer:

[0177] The system exports the 3D visualization interface, 3D path curves, node annotations, construction sequence files, and bill of materials into multiple formats to meet the needs of different construction scenarios and equipment. First, the 3D visualization interface from the current viewpoint is exported as a PNG image, recording the wiring path and node views, allowing users to quickly view path information when the 3D interface is inaccessible. Second, CAD drawings are generated, including approximate polyline representations of the 3D path curves and node locations, stored in DXF format. DXF is a common file format for CAD software, supporting opening and editing on various CAD platforms, facilitating direct construction guidance for the construction team. Furthermore, the bill of materials and construction sequence files are exported as PDF documents, including material tables and Gantt charts. PDF format offers broad compatibility and readability, suitable for printing and viewing on the construction site.

[0178] By integrating and formatting data, constructing a 3D visualization interface, displaying construction sequence and material lists, and exporting and transmitting data, the corrected wiring paths, material lists, and construction sequence files are integrated and presented in the 3D visualization interface, achieving intuitive display and efficient transmission of planning results. This method is particularly suitable for charging pile wiring scenarios in multi-story underground parking garages, significantly improving construction efficiency and structural safety, and ensuring the feasibility and reliability of wiring schemes in complex environments.

[0179] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0180] It should be noted that the system of the present invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting a variety of hardware environments and usage requirements.

[0181] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0182] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely to distinguish one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0183] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for planning the shortest three-dimensional spatial wiring path between charging piles and meter locations, characterized in that, Includes the following steps: Step S1: Construct a three-dimensional semantic model of the underground parking garage that includes shear walls, reserved sleeves and spatial obstacles. Discretize the space of the underground parking garage into a uniform voxel grid. Assign a level label to each voxel based on its positioning relationship with the elements in the three-dimensional semantic model, representing whether it is traversable and its traversal capability, to form a voxel grid with level labels. Step S2: In the voxel grid with grade markings, for each voxel, calculate the weight value based on its corresponding structural safety factor, minimum bending radius of the cable, and remaining capacity of the reserved sleeve, and generate a dynamic weight map. Step S3: Based on the dynamic weight graph, a hybrid heuristic strategy is used to search for the path, obtain the wiring path with the optimal length and weight from the meter location to the charging pile location, and record the coordinate sequence of the wall-penetrating node and the coordinate sequence of the bending node on the wiring path. Step S4: Calculate the deformation suppression coefficient of the protective pipe according to the bending node coordinate sequence, and adjust the specifications of the protective pipe and / or the local bending radius of the protective pipe at the bending node according to the deformation suppression coefficient; Step S5: Visualize the cabling path in 3D and output the corresponding bill of materials and construction sequence file.

2. The three-dimensional shortest wiring path planning method for charging piles and meter locations according to claim 1, characterized in that, In step S2, the structural safety factor is calculated as follows: the bearing capacity of the reserved sleeve corresponding to the voxel minus the existing pipeline load divided by the load of the cable to be laid; the remaining capacity of the reserved sleeve is calculated as follows: the cross-sectional area of ​​the reserved sleeve minus the occupied cross-sectional area divided by the cross-sectional area of ​​the cable to be laid.

3. The three-dimensional shortest wiring path planning method for charging pile and meter locations according to claim 1, characterized in that, In step S2, the weight value is calculated by weighting the reciprocal of the structural safety factor, the reciprocal of the minimum bending radius of the cable, and the reciprocal of the remaining capacity of the reserved sleeve. When the structural safety factor is lower than the preset threshold or the remaining capacity of the reserved sleeve is less than or equal to zero, the weight value of the corresponding voxel is set to the maximum value representing the impassable value.

4. The three-dimensional shortest wiring path planning method for charging piles and meter locations according to claim 1, characterized in that, In step S3, the hybrid heuristic strategy is a strategy that combines the A algorithm and the ant colony algorithm; wherein, the A algorithm is first used to generate an initial path in the dynamic weight graph, and then the ant colony algorithm is used to optimize the initial path to minimize the total path cost, wherein the total path cost is the weighted sum of the path length and the voxel weight values ​​on the path.

5. The three-dimensional shortest wiring path planning method for the location of charging piles and meters according to claim 1, characterized in that, In step S3, after obtaining the wiring path, the wiring path is smoothed by Bézier curve and the path trajectory is adjusted by curve interpolation method; wherein, the wall-penetrating node is the voxel corresponding to the center of the reserved sleeve when the path passes through the shear wall, and the bending node is the voxel where the path direction changes.

6. The three-dimensional shortest wiring path planning method for the location of charging piles and meters according to claim 1, characterized in that, In step S4, the calculation of the deformation suppression coefficient of the protective tube includes: The local bending radius is determined based on the coordinate sequence of the bending node, and the local bending stress of the protective pipe at that location is calculated. Calculate the remaining buckling margin of the liner based on local bending stress and the yield strength of the liner material. ; Calculate the bending springback resistance index based on local bending stress and yield strength. ; Based on the remaining margin of the sheath buckling and the bending springback resistance index, a deformation suppression coefficient is generated. .

7. The three-dimensional shortest wiring path planning method for charging pile and meter locations according to claim 6, characterized in that, The formula for calculating the remaining margin of the protective pipe buckling is as follows: ； in, The yield strength of the protective pipe material; This is local bending stress; The elastic modulus of the protective tube; The diameter of the protective tube; The radius of curvature is the local bending radius.

8. The three-dimensional shortest wiring path planning method for charging pile and meter locations according to claim 6, characterized in that, The formula for calculating the bending springback resistance index is: when hour, ; otherwise .

9. The three-dimensional shortest wiring path planning method for charging pile and meter locations according to claim 6, characterized in that, The deformation suppression coefficient It is the ratio of the normalized value of the remaining margin of the pipe bending to a nonlinear amplification factor based on the bending spring resistance index.

10. The three-dimensional shortest wiring path planning method for charging piles and meter locations according to claim 6, characterized in that, When the deformation suppression coefficient Less than the set threshold When the adjustment is triggered: ； in, For the new diameter of the protective pipe; The diameter of the protective tube; ； in, The new local radius of curvature for the protective pipe; The radius of the local bending point; The yield strength of the protective pipe material.

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