Power distribution cable laying control method and system based on BIM platform

Abstract

The application discloses a power distribution cable laying control method and system based on a BIM platform, and relates to the technical field of cable laying. The method comprises the following steps: obtaining a cable space and discretizing the cable space into a node graph, and performing heuristic search to determine a laying path; determining an effective curve based on NURBS curve parameterized modeling and node vector adjustment; scanning and constructing a hierarchical bounding box tree, performing intersection test and optimization, and generating a BIM model; and performing cable laying control based on BIM and interaction with an execution end. The technical problems of inaccurate underground pipeline information reading, low line channel modeling efficiency, insufficient collision detection and optimization capability in the prior art, which result in low power distribution cable laying path design efficiency and insufficient construction control precision, are solved, and the technical effect of improving the power distribution cable laying path planning efficiency and laying control refinement level is achieved through the BIM platform-based cable laying path search, NURBS parameterized modeling and collision optimization control mechanism.

Description

Technical Field

[0001] This invention relates to the field of cable laying technology, and specifically to a method and system for controlling the laying of power distribution cables based on a BIM platform. Background Technology

[0002] In the engineering design and construction of power distribution cables, with the continuous expansion of urban scale and the sustained growth of electricity demand, the scale of power distribution cable laying is becoming increasingly large and the complexity is significantly increasing. On the one hand, urban underground space resources are becoming increasingly scarce, and various municipal pipelines are densely intertwined, making the space available for power distribution cable laying extremely limited. On the other hand, modern architecture and urban planning have placed higher demands on the accuracy, efficiency, and subsequent operation and maintenance management of cable laying, involving a large amount of precise geographic information, spatial data, and the specific data characteristics of the cable itself, as well as multiple dimensions such as electrical parameters.

[0003] However, in cable laying path planning, traditional methods often struggle to comprehensively consider various complex factors, such as spatial obstacles, cable bending radius limitations, and heat dissipation requirements. This results in suboptimal planned paths, increasing cable laying length and difficulty, thereby raising costs and extending construction periods. In collision detection, existing methods are inaccurate and untimely in judging collisions between cables and other pipelines or structures in complex environments, easily leading to collision accidents during construction, causing cable damage and construction delays. Furthermore, in the subsequent operation and maintenance management phase, the lack of effective information integration and management tools makes it difficult to quickly and accurately obtain detailed cable information, such as location, model, and laying time, greatly hindering troubleshooting and maintenance. The technical root of these problems lies in the fact that traditional methods are mostly based on two-dimensional CAD drawings for design and planning. Two-dimensional drawings cannot intuitively and comprehensively present complex three-dimensional spatial information, and cannot effectively process spatial data and perform three-dimensional collision detection. This limits the accuracy of path planning and collision detection. Simultaneously, the lack of effective integration and sharing mechanisms for information at various design, construction, and operation and maintenance stages creates information silos, hindering information transmission and failing to provide strong support for cable laying control throughout its entire lifecycle. In addition, existing methods do not adequately consider the physical and electrical characteristics of cables, and cannot adequately meet the requirements for cable bending and heat dissipation during route planning and laying, thus affecting the operational safety and reliability of cables. Summary of the Invention

[0004] This application provides a BIM platform-based control method and system for power distribution cable laying. The key feature is that, in response to the difficulties in selecting laying paths and low construction accuracy caused by complex underground spaces, dense pipelines, and inaccurate path planning in power distribution cable laying, a heuristic path search algorithm, NURBS curve modeling technology, and spatial hash index optimization are used. Combined with a BIM platform-based real-time data interaction and iterative adjustment mechanism, the method aims to optimize cable laying paths, improve construction accuracy, reduce construction risks, and achieve full-process visualized management.

[0005] The first aspect of this application provides a method for controlling the laying of power distribution cables based on a BIM platform, the method comprising: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on a heuristic function and turning radius constraints, a heuristic path search is performed to determine the cable laying path. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is implemented by limiting the directional changes between nodes. Based on the cable laying path, parametric modeling based on the cable NURBS curve and iterative adjustment based on node vectors are performed to determine the effective cable NURBS curve. The effective cable NURBS curve is scanned, and a hierarchical bounding box tree is constructed through mesh partitioning. Position intersection testing and planning optimization of candidate detection objects based on spatial hash indexing are performed to generate a cable BIM model. The cable BIM model includes a parametric BIM model and a physical BIM model. Based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control and management based on the cable BIM model are performed.

[0006] A second aspect of this application provides a power distribution cable laying control system based on a BIM platform, the system comprising: Path Search Module: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on a heuristic function and turning radius constraints, a heuristic path search is performed to determine the cable laying path. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is implemented by limiting the direction change between nodes. Curve Construction Module: Based on the cable laying path, parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors are performed to determine the effective cable NURBS curves. Object Testing and Planning Module: The effective cable NURBS curves are scanned. A hierarchical bounding box tree is constructed through mesh partitioning. Position intersection testing and planning optimization of candidate detection objects based on spatial hash index are performed to generate a cable BIM model. The cable BIM model includes a parametric BIM model and a physical BIM model. Laying Control Module: Based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control and management based on the cable BIM model are performed.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, the laying environment of power distribution cables can be digitally represented in the BIM platform, converting the laying space into a computable node network, and completing the cable path search based on comprehensive consideration of path accessibility and constraints. Then, based on the obtained path results, NURBS curve parametric modeling of the cable is performed, and the cable curve is adjusted through node vectors to better conform to actual laying requirements. Next, collision detection and local optimization are performed on the formed cable curve to establish a cable BIM model containing parameter information and physical morphology information. Finally, relying on data interaction between the BIM platform and on-site laying equipment, guidance, feedback, and control management of the cable laying process are achieved. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A schematic diagram of the power distribution cable laying control method based on a BIM platform provided in the embodiments of this application.

[0010] Figure 2 A schematic diagram of the power distribution cable laying control system based on the BIM platform provided in the embodiments of this application.

[0011] Explanation of reference numerals in the attached diagram: Path search module 11, Curve construction module 12, Object test planning module 13, Laying control module 14. Detailed Implementation

[0012] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0013] Example 1, as Figure 1 As shown, this application provides a BIM platform-based method for controlling the laying of power distribution cables, wherein the method includes: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on the heuristic function and turning radius constraint, the cable laying path is determined by performing a heuristic path search. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is implemented by limiting the directional changes between nodes.

[0014] In this embodiment, the basic data of the area to be laid is first acquired in the BIM platform, including underground pipeline geophysical data, CAD cable layer data, terrain elevation data, manhole and support location data, road red line range data, existing building or structure data, and related BIM model data. This data is then uniformly converted into a platform-recognizable data format and imported into the BIM platform to form the three-dimensional scene basis for power distribution cable laying. Subsequently, key spatial locations in the laying space are extracted based on the imported data. Manhole entrances / exits, pipe ends, corner locations, support installation points, terminal connection points, and candidate transition points for avoiding existing obstacles are designated as nodes. Any two nodes that meet the connectivity condition are connected to form an edge, thereby discretizing and reconstructing the continuous laying space into a node graph. Each node includes spatial coordinates, elevation, node type, and adjacent constraint information, while each edge includes length, direction, traffic status, environmental attributes, and edge weight. Subsequently, based on power engineering cable design standards or preset design rules, constraints such as minimum clearance, minimum bending radius, prohibited areas, and insurmountable obstacles are applied for filtering to remove nodes or edges that do not meet the laying conditions. Then, a starting node and a target node are set, and a heuristic path search algorithm is used to traverse the node graph. During the search, the sum of the current cumulative path cost and the estimated bending cost from the current node to the target node is used as a heuristic function to prioritize expanding candidate nodes with smaller evaluation values. Simultaneously, when expanding adjacent nodes, the direction change is checked in real-time to ensure it meets preset turning radius constraints, spatial clearance constraints, and accessibility constraints. If not, the candidate branch is discarded; if it does, the parent node, cumulative cost, and arrival direction are recorded. Once the target node is found, an ordered sequence of nodes from the starting point to the end point is obtained by backtracking based on the parent node relationships recorded for each node. This sequence is then checked for smoothness, redundant nodes are removed, and necessary local corrections are made. Finally, a cable laying path that meets spatial accessibility, laying specification requirements, and engineering implementation conditions is obtained. This enables rapid and accurate determination of power distribution cable laying paths in complex underground environments, improving path planning efficiency, design rationality, and construction feasibility.

[0015] Furthermore, each node in the node graph represents the spatial location traversed by the cable, and the edge weights are determined jointly by multiple laying features. These laying features include path length, bending cost, proximity to existing pipelines, and cable heat dissipation conditions. The spatial location satisfies a preset probability. Based on the node graph, a heuristic path search is performed according to a heuristic function and a turning radius constraint to determine the cable laying path. The heuristic function is the sum of the Euclidean distance from any current node to the endpoint and the estimated bending cost. The turning radius constraint is implemented by limiting the directional changes between nodes.

[0016] Preferably, candidate passage locations in the cable laying space are discretized and sampled. Manhole nodes, support nodes, corner candidate points, pipe connection points, and obstacle avoidance transition points are identified as graph nodes, so that each node represents the spatial location that the cable may pass through. These spatial locations all meet the requirements of preset probabilities, that is, the normalized weighted result of the safety distance margin index with existing pipelines, the openness index of space, the accessibility index of construction, and the heat dissipation environment adaptability index is greater than or equal to the preset probability. Among them, the safety distance margin index with existing pipelines can be quantified by the difference between the actual distance from the location to the nearest obstacle and the minimum clearance specified in the standard; the openness index of space can be characterized by the density of obstacles or the proportion of passable volume within a certain range around the location; the accessibility index of construction can be evaluated based on the connectivity with manholes, passage entrances, or equipment layout points; and the heat dissipation environment adaptability index can be estimated based on the density of surrounding cables or the degree of space enclosure. Subsequently, graph edges are established for any two nodes with a connectable relationship, and edge weights are assigned to each edge. These edge weights are obtained through joint calculation using multiple laying characteristics. Specifically, path length, bending cost, proximity to existing pipelines, and cable heat dissipation conditions are quantified separately and then weighted and summed to form the comprehensive cost of the corresponding graph edge as its weight. Path length is used to characterize the spatial distance between adjacent nodes; the longer the distance, the higher the corresponding cost. Bending cost is used to characterize the laying difficulty caused by changes in path direction, which can be measured based on the number of turns and the angle of the turn. That is, when the path changes direction at a node, if the number of turns increases or the angle of the turn increases, the weight of that node is increased. The bending cost of the corresponding transfer edge is used to encourage the search process to prioritize paths with fewer turns and gentler angles. The proximity to existing pipelines reflects the adjacency between the candidate path and existing water supply, drainage, gas, telecommunications, and power pipelines, and serves as a constraint on avoidance priority. That is, the closer the candidate path is to existing pipelines, the greater its edge weight, and the more likely it is to be judged as an unfavorable path, in order to reduce the risk of subsequent collisions and construction interference. The heat dissipation condition reflects the thermal environment adaptability of the cable when laid in different areas. Especially in areas with dense cable laying, when the candidate path is located in an area with dense laying and a high risk of temperature rise, the corresponding edge weight is increased to avoid laying the cable in a space that is not conducive to heat dissipation.

[0017] After constructing the node graph and assigning edge weights, path search is performed based on a heuristic function. In this process, the starting node is used as the initial search node, and the ending node as the target search node. Candidate nodes in the open list are expanded one by one. The heuristic function can be defined as the sum of the Euclidean distance from any current node to the ending node and the estimated bending cost. This comprehensively measures the potential arrival cost from the current node to the target node. That is, on the one hand, the Euclidean distance guides the search towards the endpoint quickly; on the other hand, the estimated bending cost suppresses the expansion of unreasonable sharp-turn paths. Each time the path expands from the current node to an adjacent node, in addition to calculating the cumulative path cost, the turning radius constraint must be checked simultaneously. Specifically, the angle between the current edge and the next candidate edge is extracted. Only path switching is allowed when the angle between adjacent edges is greater than a preset threshold. If the angle is less than the preset threshold, the path is considered to have too sharp a turn and cannot meet the minimum bending radius requirement of the cable, thus discarding the candidate expansion branch. If the angle threshold requirement is met, the candidate node is retained, and its parent node, cumulative cost, and direction information are updated. This process continues iterating until the endpoint node is found. Then, based on the parent node relationship, a complete path sequence is formed by backtracking. Finally, a cable laying path that takes into account path length, smoothness of turns, priority of pipeline avoidance, and reasonable heat dissipation is obtained, thereby improving the feasibility, standard compliance, and engineering application value of the path planning results.

[0018] Based on the cable laying path, perform parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors to determine the effective cable NURBS curves.

[0019] In one embodiment, after obtaining the cable laying path, key locations on the path are first extracted. The starting point, ending point, turning points, and connection points are used as a sequence of control points to describe the spatial orientation of the cable. Subsequently, a NURBS curve model of the cable is constructed based on the control points. By setting the curve order, weights, and node vectors, a continuous and smooth expression of the cable path is achieved, transforming the discrete path into a continuous curve that conforms to engineering reality. This solves the problem that the cable laying path is not smooth and cannot accurately reflect the actual laying pattern because it is expressed in the form of discrete nodes and the turning points are abrupt. After the initial curve is generated, iterative adjustments are made based on the node vectors. During this process, the position and weight of each control point are optimized according to its spatial location and corresponding tangential direction, making the curve smoother overall and meeting laying constraints. For areas with significant curvature changes, such as bends, connecting manholes, or equipment locations, nodes are added for local refinement to improve curve fitting accuracy. In areas with smaller curvature changes, nodes are appropriately merged to reduce redundant control points and improve model simplicity. This addresses the problem of cable paths failing to meet minimum bending radius requirements due to a lack of continuous curve constraints. Through this parametric modeling and iterative optimization process, an effective cable NURBS curve is obtained that satisfies both path continuity and smoothness requirements, as well as the minimum bending radius and laying specification constraints, improving the accuracy of cable 3D modeling and the feasibility of actual laying.

[0020] Furthermore, performing parametric modeling based on cable NURBS curves includes: Based on the cable laying path, cable path control points are extracted. These control points are key coordinate sequences representing the cable laying direction, including the start point, end point, intermediate turning points, and connection points with manholes, supports, and terminal heads. For each control point, a minimum permissible order is calculated, where the turning radius is negatively correlated with the order. Based on the control points and the minimum permissible order, a cable NURBS curve is constructed. Adaptive smoothing of the node vectors is used to insert nodes in areas of drastic curvature change and merge nodes in areas of gentle curvature change.

[0021] Preferably, based on the determined cable laying path, the three-dimensional coordinate points constituting the laying channel are read in sequence from the path nodes, and key points that control the cable route are identified as cable path control points. These key points include at least the starting point, ending point, intermediate turning points, and positioning points connecting to manholes, supports, and terminal heads. For continuous collinear or nearly collinear ordinary path points, redundancy can be eliminated, retaining only the key coordinate sequences that can characterize changes in route, elevation, and connection relationships, thus forming an initial control point set for curve modeling. Subsequently, the minimum allowable order is calculated for the cable path control points. The specific order can be determined based on the turning angle between adjacent path segments, the local turning radius requirements, and the overall complexity of the path. Generally, the turning radius is negatively correlated with the order. That is, when the local allowable turning radius is small and the path turning is obvious, a relatively high curve order is used to enhance the curve's ability to express local geometric changes. When the local allowable turning radius is large and the path is relatively gentle, a relatively low curve order is used to reduce modeling complexity and maintain the overall stability of the curve. Then, the curvature requirements are calculated for each local segment where each control point is located, and the minimum allowable order that satisfies the modeling requirements of all local segments is taken as the target order. Subsequently, a sequence of control vertices is generated according to the control point order. Corresponding node vectors are established based on the target order, and the weights of each control vertex are initialized to obtain an initial NURBS curve that is essentially consistent with the cable laying path. Adaptive smoothing is then performed on the node vectors. Specifically, the node distribution density is dynamically adjusted based on the curvature changes in different regions of the curve. When a region is detected to have abrupt corner changes, significant transitions at connection points, strong stress concentration trends, or drastic curvature changes, nodes are inserted in that region to enhance local control capabilities and improve the curve's fitting accuracy for complex paths. When a region is detected to have gentle curvature changes, continuous direction, and control redundancy, adjacent nodes in that region are merged to reduce unnecessary local fluctuations and improve the overall smoothness of the curve. Through repeated adjustments to the node vector distribution via node insertion and merging, the constructed NURBS curve accurately fits the actual cable laying path and meets the continuity and smoothness requirements at manhole entry / exit points, support brackets, terminal connections, and turning transitions. This ultimately yields a cable NURBS curve that can be used for subsequent iterative optimization and BIM modeling, providing a curve basis for subsequent collision detection, BIM modeling, and laying control.

[0022] For example, a set of cable path control points is obtained based on the path search results. The key coordinate sequence is as follows: starting point P0 (0,0,0), intermediate turning point P1 (10,0,0), P2 (20,5,0), entry point into the manhole P3 (30,5,-1.5), support transition point P4 (40,10,-1.5), and ending point P5 (50,10,-2.0). The minimum allowable order is then calculated based on the turning angles of adjacent path segments. The turning angle at P1 is 90° and the turning angle at P2 is approximately 45°. The overall path has obvious turning points, so a cubic NURBS curve is selected as the modeling order. Next, the control points are used as the control vertex sequence {P0,P1,P2,P3,P4,P5}, and the weight vector is initialized to {1,1,1,1,1,1}, constructing the corresponding node vector U={0,0,0,0,0.33,0.66,1,1,1,1}. The node vector uses a non-uniform distribution to reflect the changing characteristics of the middle and end segments of the path. After generating the initial NURBS curve based on the above parameters, curvature analysis is performed on the curve. It is found that there is a large curvature change in the region from P1 to P2. Therefore, a new node U=0.25 is inserted in this interval, and an auxiliary control point P1′(15,2,0) is introduced to enhance the fitting ability for the corner region. Simultaneously, a smoothness test is performed on the segment from P4 to P5, finding that this segment is relatively flat. Therefore, the original node 0.66 is merged with adjacent nodes to reduce control redundancy. After node insertion and merging, the control vertex sequence is updated to {P0,P1,P1′,P2,P3,P4,P5}, the node vector is adjusted to U={0,0,0,0,0.25,0.5,0.75,1,1,1,1}, and the curve shape is recalculated to make it smoother at the turning points and meet the minimum bending radius requirement, while maintaining accurate alignment at the connection point between the well and the support.

[0023] Furthermore, performing iterative adjustments based on node vectors includes: Extract the node vectors of the cable path control points, where each node vector represents the spatial coordinates and specified tangential direction of the cable path control points. Based on the node vectors, perform iterative adjustments to the weights and positions of each cable path control point to determine a first adjusted NURBS curve, where the iterative adjustment objective is to satisfy the node vectors and minimize the overall energy. For the first adjusted NURBS curve, perform node insertion in regions of drastic curvature change and node merging in regions of gentle curvature change to determine an effective cable NURBS curve, where regions of drastic curvature change include the stress cone region of the terminal head and the shielding layer disconnection position of the intermediate joint.

[0024] Optionally, during the iterative adjustment based on node vectors, the node vector information corresponding to each control point is first extracted from the established cable laying path control points. These node vectors include the spatial coordinates of each cable path control point and the specified tangential direction at the control point. The specified tangential direction can be determined according to the actual laying connection requirements. Typically, the coordinates of connection points of accessories such as manholes, supports, terminal heads, and intermediate joints can be extracted, and these coordinates are used to determine the directional constraints that the cable must meet when entering the connection point. For example, the cable may be required to enter vertically, horizontally, or with a preset inclined direction. Thus, the connection point position and the entry angle are written into the node vector set as hard constraints for cable laying. Subsequently, the iterative adjustment process is performed based on the initial cable NURBS curve as the base model. In each iteration, the actual spatial position and actual tangential direction of each control point are calculated based on the parametric equation of the current NURBS curve. Then, the deviations between these deviations and the target position and target tangential direction in the node vector are calculated. Positional deviations can be measured using Euclidean distance, and directional deviations can be quantified using vector angles. A joint optimization objective function is then constructed, encompassing positional error, directional error, and curve smoothing energy terms. The goal is to minimize overall energy, which means minimizing the change in the curve's second derivative or curvature, thus ensuring the curve is as smooth as possible without abrupt changes. During optimization, the positions and weights of the NURBS control vertices are fine-tuned to gradually reduce the aforementioned errors and energy function values. The curve model is updated after each iteration until the positional and directional errors at each node are less than preset thresholds and the overall smoothness meets the requirements, resulting in the first adjusted NURBS curve. Next, curvature adaptive analysis is performed on the first adjusted NURBS curve. This involves discretely sampling the curvature along the curve parameter direction, calculating the rate of curvature change between adjacent sampling points, and dividing the curve into regions of drastic curvature change and regions of gentle curvature based on the curvature segmentation standard value. For regions of drastic curvature change, especially the stress cone region of the terminal head and the shielding layer disconnection location of the intermediate joint, since these regions are sensitive to cable bending morphology and stress distribution, node insertion operations can be performed in the corresponding segments. This involves adding new parameter nodes to the node vector and refining the distribution of control vertices to improve the local control accuracy and fitting ability of the curve in these regions. For regions of gentle curvature change, a comprehensive judgment is made based on the spatial distance, directional change, and curvature change of adjacent control points. When the distance between adjacent control points is less than a preset distance threshold, and the tangential change of the curve in this segment is small and the rate of curvature change is lower than a preset threshold, the control point is determined to have little impact on the curve shape and is considered a redundant control point. In this case, adjacent nodes are merged or redundant control points are directly deleted to reduce model complexity and avoid unnecessary curve fluctuations. After each node insertion or merging, local curve reconstruction and smoothing are re-executed to maintain curve continuity and stability.Through the combined process of node vector constraints, position and weight iterative optimization, and curvature adaptive node adjustment, an effective cable NURBS curve is finally obtained that satisfies the entry angle requirements of key connection points and has both overall smoothness and local fine expression capabilities, thereby improving the engineering adaptability and subsequent construction controllability of cable path modeling.

[0025] The effective cable NURBS curves are scanned, a hierarchical bounding box tree is constructed through grid partitioning, and position intersection testing and planning optimization of candidate detection objects based on spatial hash index are performed to generate a cable BIM model, wherein the cable BIM model includes a parametric BIM model and a physical BIM model.

[0026] In one embodiment, after obtaining the valid cable NURBS curve, the curve is first discretely scanned, dividing the continuous curve into several segments to obtain the geometric distribution information of the cable in three-dimensional space. Subsequently, the space is meshed based on a uniform scale, mapping each discrete segment of the cable to its corresponding spatial grid. On this basis, a hierarchical bounding box tree structure is constructed for each cable, progressively wrapping the cable's geometric units from bottom to top to form a multi-level spatial bounding structure. This structure is used to quickly narrow the collision detection range, thus solving the problem of large collision detection range and low detection efficiency caused by the lack of efficient spatial indexing and hierarchical representation mechanisms for cable paths in complex underground spaces. After completing the spatial structure construction, a spatial hash indexing mechanism is introduced to establish index mapping relationships for each grid unit. During collision detection, based on the grid position of the cable bounding box, a hash table is used to quickly retrieve other cables, existing pipelines, structures, etc., within the same grid and its adjacent grids, and these are used as candidate detection objects. Next, a detailed intersection test is performed on the candidate objects to determine whether there is spatial overlap or insufficient distance, thereby obtaining information on the collision location and degree of collision. This addresses the problem of difficulty in timely detection of spatial conflicts between cables and existing pipelines and structures due to the lack of rapid candidate screening and detailed intersection analysis methods. After detecting a collision or potential conflict, path planning optimization is performed based on the collision information. For example, feasible avoidance paths are searched along the cable laying direction based on the collision location, and local curves are adjusted and updated to ensure that the optimized cable path meets spatial avoidance requirements while maintaining overall continuity and rationality. This solves the problem of cable paths being difficult to reasonably avoid due to the lack of an effective conflict optimization mechanism. After completing collision detection and path optimization, a cable BIM model is generated based on the optimized cable curve. This cable BIM model includes a parametric BIM model constructed with curve geometry information, node parameters, and related attributes, and a physical BIM model generated by combining engineering attributes such as cable outer diameter, material, and laying method. By combining the above-mentioned meshing, hierarchical bounding box tree and spatial hash index, the efficiency and accuracy of collision detection can be improved. Furthermore, the collaborative construction of parametric BIM model and physical BIM model can further improve the quality of 3D modeling and the feasibility of engineering implementation.

[0027] Furthermore, performing positional intersection tests on candidate detection objects based on spatial hash indexes includes: Based on the geometric information of the effective cable NURBS curve, a spatial hash index is established for each grid through uniform grid division of equal size, and an axial hierarchical bounding box tree is constructed for each cable pipeline. Based on the hierarchical bounding box tree, the hash table is queried according to the spatial grid position of each cable bounding box, and the cable structural components in the same grid and adjacent grids are extracted as candidate detection objects for intersection testing to determine collision information, wherein the collision information includes collision position and collision depth.

[0028] Preferably, when performing positional intersection tests on candidate detection objects based on spatial hash indexing, the effective cable NURBS curve is directly used as the collision analysis object. This effective cable NURBS curve can describe the actual direction of the cable in three-dimensional space, the outer diameter envelope range, the local turning radius, and the curvature changes. Therefore, lightweight geometric collision detection can be directly completed without constructing a highly complex twin physical entity. During the test, the effective cable NURBS curve is first discretely sampled at preset parameter intervals to extract continuous sampling points. Adjacent sampling points are then connected to form several small curve segments. Then, based on the cable's outer diameter, each small curve segment is expanded outward along its centerline to form a local envelope. Typically, a cylindrical envelope, capsule envelope, or axial bounding box can be used for approximation to characterize the actual space occupied by that cable segment. Subsequently, the entire area to be inspected is divided into uniformly sized grids, resulting in multiple cubic grid cells. A spatial hash table is then established based on the integer coordinate index of each grid cell, allowing any envelope to be quickly mapped to the corresponding hash table according to its center coordinates or outer bounding range. Next, the small curve segments are sorted from front to back according to the cable extension direction. The local envelope corresponding to each small curve segment is used as a leaf node bounding box, and adjacent two or more leaf nodes are merged upwards to form a parent bounding box. This process is recursively constructed layer by layer until a root bounding box covering the entire cable pipeline is formed. Each level of bounding box records its minimum circumscribed range, the number range of the curve segment it belongs to, and the grid number it occupies. Using this structure, objects that are obviously impossible to collide can be quickly eliminated using the upper-level bounding boxes, and drilling down to the next level bounding box is only performed when there is a tendency to overlap, thus reducing the number of fine-grained intersection calculations.

[0029] Next, the grid number corresponding to the current cable box is read, and the hash table contents of this grid and its surrounding adjacent grids are queried. Structural objects spatially close to the current bounding box are extracted as candidate detection objects. Adjacent grids include the six face adjacent grids of the current grid, and may further include edge and corner adjacent grids to avoid missing detections due to objects crossing grid boundaries. After obtaining candidate detection objects, a coarse intersection judgment is performed between the current cable box and the upper bounding box of the candidate object. For example, it checks whether the projection intervals of the two overlap in the X, Y, and Z directions. If there is no overlap, the candidate object is directly excluded. If there is an overlap, the search continues down to a smaller bounding box until a specific small curve segment and a specific candidate structural segment are located. For the local objects retained after this search, a fine intersection test is performed. Specifically, this is done by calculating the minimum distance between two center line segments and combining it with their respective outward expansion radii or safety clearance thresholds to determine whether a collision has occurred. When the minimum distance is less than the sum of the radii of the two envelopes, or less than the preset minimum safety clearance, a collision or insufficient clearance is determined. In this case, the nearest point corresponding to the minimum distance is determined as the collision location, or the center of the overlapping local envelope is determined as the collision location. The sum of the envelope radii of the two objects minus the minimum distance is used as the collision depth, or the preset safety clearance minus the actual minimum distance is used as the collision depth. After obtaining the collision information including the collision location and collision depth, the collision location is mapped back to the parameter range or control point segment of the effective cable NURBS curve, thereby identifying the specific cable segment where the conflict occurred, providing a basis for subsequent local offset, replanning, and curve updates. Through the above method, the complete detection process from curve discretization, envelope construction, mesh indexing, candidate screening, hierarchical bounding box progressive detection, fine intersection, and collision localization can be directly completed. This not only reduces the computational overhead of directly performing full geometric Boolean operations on the twin physical model, but also improves the detection efficiency and planning optimization response speed in large-scale cable scenarios while ensuring the accuracy of collision judgment.

[0030] Furthermore, the optimization of the execution plan includes: Read the collision information, search for avoidance directions along the cable laying direction with the collision point as the center, calculate the recommended offset based on the collision depth and cable outer diameter, and determine the avoidance information; through information interaction, migrate the avoidance information to the node graph, perform local path replanning, and update the effective cable NURBS curve and hierarchical bounding box tree.

[0031] Optionally, after obtaining collision information, the spatial coordinates of the collision point, collision depth, the cable curve segment where the collision occurred, and the corresponding candidate obstacle object type are first read. The collision point is then mapped inversely to the parameter position of the effective cable NURBS curve to determine the local curve segment range where the conflict occurred. Subsequently, a local avoidance search area is established centered on the collision point along the current cable laying direction. This local avoidance search area includes adjustment sections extending forward and backward along the cable tangential direction and offset spaces extending along the normal and lateral directions. Multiple candidate avoidance directions are generated within this area. Typically, the left and right normal directions, vertical upward lifting direction, vertical downward moving direction, and their combined oblique directions at the current collision point are used as candidate avoidance directions. Infeasible directions are then screened out by combining the distribution of surrounding obstacles, clearance margin, and construction accessibility. Next, the collision depth is added to the preset minimum safe clearance to obtain the theoretical minimum separation distance. Then, a structural compensation amount related to the cable's outer diameter is added to form the recommended offset corresponding to the collision point. If the collision object is a rigid structure or a high-risk existing pipeline, the offset can be appropriately increased to ensure a safety margin after avoidance. Then, the candidate avoidance directions are combined with the recommended offset to form multiple local avoidance schemes. Each avoidance scheme is quickly evaluated, and the evaluation indicators include at least the length of the new path, the change in turning radius, the change in local curvature, the minimum clearance with surrounding objects, and whether new potential collision risks are introduced. The scheme with the lowest overall cost is selected as the target avoidance information. This avoidance information includes the avoidance start node, the avoidance end node, the offset direction, the offset distance, and the length of the transition section.

[0032] For example, a collision point is located at the effective cable NURBS curve parameter position u=0.42, corresponding to spatial coordinates (35.200, 18.600, -1.800). The detection result shows that the cable outer diameter at this point is 120mm, or 0.12m, which intrudes into the existing drainage pipeline with a collision depth of 0.08m. The preset minimum safe clearance between such pipelines is 0.30m. In this case, the collision depth of 0.08m is first added to the minimum safe clearance of 0.30m to obtain the theoretical minimum separation distance of 0.38m. Then, the structural compensation amount is set according to the cable outer diameter. For example, 0.5 times the cable outer diameter is taken as compensation, that is, 0.12m×0.5=0.06m. Then the recommended foundation offset is 0.38m+0.06m=0.44m. If the candidate obstacle is a drainage pipeline, which is a typical existing municipal pipeline, no additional scaling is required. The final recommended offset is 0.44m, which is rounded up to 0.45m for engineering purposes.

[0033] After determining the avoidance information, it is transferred to the node graph through information interaction. That is, the local segment of the NURBS curve where the collision occurred is mapped to several path nodes and edges in the original node graph. Two boundary nodes before and after the collision area are selected as the start and end anchor points for local replanning. Then, based on the avoidance direction and offset, the node positions in the local area are corrected, or new transition nodes are inserted between the original nodes to form an alternative path around the collision area in the node graph. At the same time, the edge weights of the newly generated nodes and edges are reassigned. After the node graph is updated, a restricted heuristic path replanning is performed only once in the local area. That is, using the local start and end anchor points as the new start and end points, an alternative path that meets the minimum bending radius, clearance constraints, and avoidance requirements is searched again in the updated local node graph. This alternative path is then spliced ​​with the unaffected segments of the original path to obtain the updated complete laying path. Then, based on the updated node sequence, the corresponding control points and node vectors are recalculated, and the effective cable NURBS curves are locally reconstructed. This ensures that the new curve fits the replanned path within the avoidance zone, maintaining positional and tangential continuity with the original curve at both ends of the avoidance zone. Next, based on the updated effective cable NURBS curves, discrete curve segments and their bounding boxes for the corresponding zones are regenerated, and the hierarchical bounding box tree for this local zone is incrementally updated. Specifically, the bounding box nodes corresponding to the original conflict zones are deleted, and the leaf bounding boxes and their parent bounding boxes corresponding to the new curve segments are reconstructed, maintaining the bounding box tree structure consistent with the current curve geometry. Finally, based on the updated hierarchical bounding box tree and spatial hash index, a collision detection is re-performed in the local area. If collisions still exist, the above process is repeated until the local conflict is eliminated or a preset termination condition is met. This achieves dynamic avoidance optimization of the cable laying path, improving path adjustment efficiency and project implementation reliability.

[0034] Furthermore, generating a cable BIM model includes: A predefined coding rule library is provided, which includes component type identification rules, coding prefix mapping table, voltage level coding segment rules, and function type suffix rules. The valid cable NURBS curve and hierarchical bounding box tree are used as parametric BIM models, and cable model attribute parameters are determined. A physical BIM model is constructed based on the cable model attribute parameters. A cable BIM model is generated by mapping and associating the parametric BIM model and the physical BIM model.

[0035] Optionally, when generating a cable BIM model, a predefined coding rule library is first defined to unify the identification and attribute expression of cables and related components. This coding rule library includes component type identification rules, coding prefix mapping table, voltage level coding segment rules, and function type suffix rules. Among them, the component type identification rules are used to automatically identify the component type according to the category of the model object, such as cable body, terminal head, intermediate joint, bracket, manhole connection section, etc.; the coding prefix mapping table is used to map different system or professional categories to corresponding coding prefixes; the voltage level coding segment rules are used to generate corresponding coding fields according to the rated voltage level of the cable, such as 0.4kV, 10kV, 35kV, etc.; the function type suffix rules are used to distinguish the purpose or functional attributes of the cable, such as trunk cable, branch cable, spare cable, etc. Subsequently, the effective cable NURBS curve and hierarchical bounding box tree are used as the core expression of the parametric BIM model. Cable model attribute parameters are then determined, such as cable type, cross-sectional specifications, outer diameter, voltage rating, laying method, starting equipment, ending equipment, system, path length, and installation environment parameters. These attribute parameters are then bound to the corresponding curve parameters to form a complete parametric description model. Next, using the effective cable NURBS curve as the path reference, and combining the cable outer diameter and structural hierarchy parameters, cross-section sweep modeling is performed to generate a 3D solid model of the cable with realistic geometry. Simultaneously, corresponding parametric family components are called according to different component types, such as terminal head models, joint models, and bracket models. These are instantiated and arranged according to the cable path control point positions and connection relationships, allowing each physical component to form a complete cable laying entity structure in space. During the modeling process, corresponding attribute parameters are simultaneously written, ensuring that the physical model not only possesses geometric shape but also complete engineering information. Finally, based on the coding rule base, rule matching is performed on the cable model attribute parameters to generate a unified coding identifier. This identifier is then used as a key to map and bind the path parameters and attribute information in the parametric BIM model to the physical components in the physical BIM model. When the parametric model is adjusted, such as through path optimization or attribute changes, the physical model can be updated synchronously through this mapping relationship. Conversely, when the physical model changes position or state during construction or verification, the parametric model can be updated in reverse. This achieves bidirectional linkage between parametric and physical representations, ultimately forming a cable BIM model that possesses both accurate geometric shape and complete attribute information, as well as interactive capabilities.

[0036] Furthermore, mapping and associating the parametric BIM model with the physical BIM model includes: Based on the cable model attribute parameters, the rule matching engine executes the rule matching based on the coding rule base sequentially to generate KKS codes segment by segment; using forward reasoning, the KKS codes are derived layer by layer from the top-level system code to the component-level code to determine the hierarchical coding fields; according to the hierarchical coding fields, the parameter BIM model and the physical BIM model are mapped and associated.

[0037] Optionally, the cable model attribute parameters are first read and input into the rule matching engine. The rule matching engine then performs rule matching according to a pre-established coding rule library, generating KKS codes segment by segment. In the rule matching engine, the coding prefix is ​​first matched based on the professional or system category to determine the top-level system identifier corresponding to the cable or component. Next, the voltage level field is matched according to the voltage level coding segment rules. Then, the component category code is matched according to the component type identification rules. Finally, the final-level function identifier is generated by combining the function type suffix rules and the installation purpose. Thus, the complete KKS code is formed segment by segment in the order of system segment-voltage segment-type segment-function segment. If multiple candidate rules exist for a certain field, the optimal coding segment is selected according to preset priority, context constraints, or the nearest matching principle to ensure that the coding result is unique and conforms to engineering coding specifications. After the KKS code is generated segment by segment, a forward reasoning method is used to expand the KKS code hierarchically. Specifically, starting from the top-level system code, the code is deduced layer by layer down to the subsystem code, equipment unit code, component category code, and component instance code, thereby determining the coding fields at each level. The top-level system code identifies the overall power system or distribution system to which the model object belongs; intermediate level fields identify voltage levels, circuit categories, or installation areas; and final level fields identify specific component instances such as cable bodies, terminals, intermediate joints, and supports. Through forward reasoning, not only can the complete KKS coded string be obtained, but the semantic belonging of each coded segment within the hierarchical structure can also be clarified, thus forming a set of hierarchical coding fields that can be used for mapping.

[0038] After obtaining the hierarchical coding field, it is written as a unified primary key into the attribute tables of both the parametric BIM model and the physical BIM model. On the parametric BIM model side, the KKS code and its corresponding hierarchical field are bound to valid cable NURBS curves, hierarchical bounding box trees, and cable attribute parameters, ensuring that parametric paths, spatial analysis structures, and engineering attributes all have a unified identifier. On the physical BIM model side, the same KKS code is bound to geometric components such as cable entities, terminal head entities, joint entities, and support entities, ensuring that the entity models have the same hierarchical identifier as the parametric models. Subsequently, a one-to-one or one-to-many mapping relationship is established based on this hierarchical coding field. For example, a parametric cable path can be mapped to one or more physical entity components, and a system-level parametric model can be mapped to multiple component-level physical models under its jurisdiction. In this way, when the path parameters, attribute parameters, or system affiliation in the parametric BIM model change, the corresponding physical BIM model can be quickly located and synchronously updated based on the hierarchical coding field. Similarly, when the location, status, or installation information of components in the physical BIM model changes, it is possible to trace back to the parametric BIM model to achieve bidirectional mapping and linkage management, ultimately ensuring the consistency, traceability, and maintainability of the cable BIM model across the system layer, component layer, and entity layer.

[0039] Based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control and management based on the cable BIM model are implemented.

[0040] In one embodiment, after the cable BIM model is constructed, a communication and interaction mechanism is established between the BIM platform and the laying execution equipment to achieve data linkage between the design and construction execution ends. Specifically, the BIM platform parses the path information, spatial location, laying sequence, and key control parameters in the cable BIM model and generates corresponding laying guidance information, which is then sent to the laying execution equipment to guide the actual cable laying operation on site. During the laying process, the laying execution equipment collects the actual laying position, posture information, and construction progress data of the cable in real time and transmits the physical execution information back to the BIM platform. The BIM platform compares and analyzes the transmitted data with the cable BIM model to determine the deviation between the actual laying result and the design model, such as positional offset, bending that does not meet constraints, or insufficient distance from surrounding facilities. When deviations or anomalies are detected, the BIM platform makes feedback decisions based on the path and constraint information in the parametric BIM model, adjusts the cable laying path or construction parameters, and generates updated laying control instructions, which are then reissued to the laying execution equipment to guide corrective construction on site. Simultaneously, the laying process is managed in stages, such as by section, node, or time period, ensuring that each stage meets design and specification requirements. Through this interactive and control process, a closed-loop management system of design, execution, feedback, and adjustment is achieved during cable laying, ensuring consistency between cable laying and the BIM model, improving construction accuracy, process controllability, and overall project quality.

[0041] Furthermore, implementing cable laying control and management based on the cable BIM model includes: Establish communication and interaction between the BIM platform and the laying execution terminal equipment to perform phased and periodic control management of the cable laying project. The phased and periodic control management includes: generating the first laying guidance information based on the cable BIM model and sending it to the laying execution terminal to execute the phased cable laying guidance; the physical execution information of the laying execution terminal is transmitted back to the BIM platform, and positioning based on the physical BIM model and parametric BIM model feedback decision based on physical deviation are performed through a real-time synchronization mechanism.

[0042] Preferably, a communication and interaction mechanism is first established between the BIM platform and the laying execution equipment. This communication can be based on wired or wireless networks, with a unified data transmission format and interaction protocol agreed upon. This mechanism facilitates command issuance and status feedback between the BIM platform and the field equipment. The laying execution equipment may include field mobile terminals, positioning devices, measuring devices, and construction auxiliary equipment, used to receive laying guidance information and collect actual construction data. Subsequently, following the cable laying project workflow, the entire laying process is divided into several stages, such as the path layout stage, cable pulling stage, turning control stage, accessory installation stage, and verification and acceptance stage. Control and management are periodically implemented within each stage. At the beginning of each control cycle, the BIM platform generates the first laying guidance information based on the cable BIM model. Specifically, the system reads cable path parameters, key control point coordinates, turning radius constraints, and support and manhole connection locations from the parametric BIM model. It then selects corresponding sections based on the current construction stage to generate guidance data containing the target laying location, spatial coordinates, direction, allowable deviation range, and key construction points. Simultaneously, this guidance information is mapped to corresponding physical components in the physical BIM model to ensure consistency between the guidance information and the actual construction object. The first laying guidance information is then sent to the laying execution device via a communication interface to guide on-site personnel or construction equipment in phased cable laying according to the model. During on-site execution, the laying execution device performs cable laying operations based on the received guidance information and collects physical execution information in real time. This physical execution information includes the actual cable laying location coordinates, real-time elevation, path direction, turning angles, key connection point positioning, and relative spatial relationships with surrounding components. The collected information is transmitted back to the BIM platform via a communication interaction mechanism. After receiving physical execution information, the BIM platform maps it to the corresponding entity location in the physical BIM model through a real-time synchronization mechanism, achieving dynamic positioning and visual updates of the current construction status. Simultaneously, it compares the actual execution data with the design path and target parameters in the parametric BIM model, calculating the positional, directional, and clearance deviations between the actual and design data. Based on the deviation analysis results, the BIM platform executes feedback decisions. When the deviation is within acceptable limits, the current stage of construction is confirmed as qualified, and the process continues to the next cycle or stage. When the deviation exceeds a preset threshold, laying control instructions are generated according to the deviation type. These instructions may include suggestions for fine-tuning the local path, optimizing the construction sequence, repositioning key nodes, or performing partial updates to the parametric BIM model, while simultaneously updating the physical BIM model. Finally, the adjusted guidance information is re-sent to the laying execution equipment, forming a cyclical control process. This achieves phased, periodic, and closed-loop control management of the entire cable laying process, improving construction accuracy and process controllability.

[0043] In summary, the embodiments of this application have at least the following technical effects: First, in the BIM platform, the cable laying space is acquired and discretized into a node graph. Heuristic path search is then performed to determine the cable laying path. Subsequently, based on the cable laying path, parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors are performed to determine the effective cable NURBS curves. Next, the effective cable NURBS curves are scanned, and a hierarchical bounding box tree is constructed through mesh generation. Position intersection testing and planning optimization of candidate detection objects based on spatial hash indexing are performed to generate a cable BIM model, which includes both a parametric BIM model and a physical BIM model. Finally, based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control and management are performed based on the cable BIM model. This invention addresses the technical problems in existing technologies, such as inaccurate reading of underground pipeline information, low efficiency in line channel modeling, and insufficient collision detection and optimization capabilities, which lead to low efficiency in power cable laying path design and insufficient construction control precision. It achieves the technical effect of improving the efficiency of power cable laying path planning and the level of laying control precision by constructing a cable laying path search, NURBS parametric modeling, and collision optimization control mechanism based on the BIM platform.

[0044] Example 2, based on the same inventive concept as the BIM platform-based power distribution cable laying control method in the previous examples, such as... Figure 2 As shown, this application provides a power distribution cable laying control system based on a BIM platform, wherein the system includes: Path Search Module 11: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on the heuristic function and turning radius constraints, the cable laying path is determined by performing heuristic path search. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is achieved by limiting the direction change between nodes. Curve Construction Module 12: Based on the cable laying path, parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors are performed to determine the effective cable NURBS curves. Object Testing and Planning Module 13: The effective cable NURBS curves are scanned. A hierarchical bounding box tree is constructed through grid partitioning. Position intersection testing and planning optimization of candidate detection objects based on spatial hash index are performed to generate a cable BIM model. The cable BIM model includes a parametric BIM model and a physical BIM model. Laying Control Module 14: Based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control management based on the cable BIM model is performed.

[0045] Furthermore, the path search module 11 is used to perform the following methods: Each node in the node graph represents the spatial location traversed by the cable. The edge weights are determined jointly by multiple laying features, including path length, bending cost, proximity to existing pipelines, and cable heat dissipation conditions. The spatial location satisfies a preset probability. Based on the node graph, a heuristic path search is performed according to a heuristic function and a turning radius constraint to determine the cable laying path. The heuristic function is the sum of the Euclidean distance from any current node to the endpoint and the estimated bending cost. The turning radius constraint is implemented by limiting the directional changes between nodes.

[0046] Furthermore, the curve construction module 12 is used to perform the following method: Based on the cable laying path, cable path control points are extracted. These control points are key coordinate sequences representing the cable laying direction, including the start point, end point, intermediate turning points, and connection points with manholes, supports, and terminal heads. For each control point, a minimum permissible order is calculated, where the turning radius is negatively correlated with the order. Based on the control points and the minimum permissible order, a cable NURBS curve is constructed. Adaptive smoothing of the node vectors is used to insert nodes in areas of drastic curvature change and merge nodes in areas of gentle curvature change.

[0047] Furthermore, the curve construction module 12 is used to perform the following method: Extract the node vectors of the cable path control points, where each node vector represents the spatial coordinates and specified tangential direction of the cable path control points. Based on the node vectors, perform iterative adjustments to the weights and positions of each cable path control point to determine a first adjusted NURBS curve, where the iterative adjustment objective is to satisfy the node vectors and minimize the overall energy. For the first adjusted NURBS curve, perform node insertion in regions of drastic curvature change and node merging in regions of gentle curvature change to determine an effective cable NURBS curve, where regions of drastic curvature change include the stress cone region of the terminal head and the shielding layer disconnection position of the intermediate joint.

[0048] Furthermore, the object test planning module 13 is used to perform the following methods: Based on the geometric information of the effective cable NURBS curve, a spatial hash index is established for each grid through uniform grid division of equal size, and an axial hierarchical bounding box tree is constructed for each cable pipeline. Based on the hierarchical bounding box tree, the hash table is queried according to the spatial grid position of each cable bounding box, and the cable structural components in the same grid and adjacent grids are extracted as candidate detection objects for intersection testing to determine collision information, wherein the collision information includes collision position and collision depth.

[0049] Furthermore, the object test planning module 13 is used to perform the following methods: Read the collision information, search for avoidance directions along the cable laying direction with the collision point as the center, calculate the recommended offset based on the collision depth and cable outer diameter, and determine the avoidance information; through information interaction, migrate the avoidance information to the node graph, perform local path replanning, and update the effective cable NURBS curve and hierarchical bounding box tree.

[0050] Furthermore, the object test planning module 13 is used to perform the following methods: A predefined coding rule library is provided, which includes component type identification rules, coding prefix mapping table, voltage level coding segment rules, and function type suffix rules. The valid cable NURBS curve and hierarchical bounding box tree are used as parametric BIM models, and cable model attribute parameters are determined. A physical BIM model is constructed based on the cable model attribute parameters. A cable BIM model is generated by mapping and associating the parametric BIM model and the physical BIM model.

[0051] Furthermore, the laying control module 14 is used to perform the following methods: Based on the cable model attribute parameters, the rule matching engine executes the rule matching based on the coding rule base sequentially to generate KKS codes segment by segment; using forward reasoning, the KKS codes are derived layer by layer from the top-level system code to the component-level code to determine the hierarchical coding fields; according to the hierarchical coding fields, the parameter BIM model and the physical BIM model are mapped and associated.

[0052] Furthermore, the laying control module 14 is used to perform the following methods: Establish communication and interaction between the BIM platform and the laying execution terminal equipment to perform phased and periodic control management of the cable laying project. The phased and periodic control management includes: generating the first laying guidance information based on the cable BIM model and sending it to the laying execution terminal to execute the phased cable laying guidance; the physical execution information of the laying execution terminal is transmitted back to the BIM platform, and positioning based on the physical BIM model and parametric BIM model feedback decision based on physical deviation are performed through a real-time synchronization mechanism.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for controlling the laying of power distribution cables based on a BIM platform, characterized in that, The method includes: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on the heuristic function and turning radius constraint, the cable laying path is determined by performing a heuristic path search. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is achieved by limiting the directional changes between nodes. Based on the cable laying path, perform parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors to determine the effective cable NURBS curves; Scan the valid cable NURBS curves, construct a hierarchical bounding box tree through grid partitioning, perform position intersection testing and planning optimization of candidate detection objects based on spatial hash index, and generate a cable BIM model, wherein the cable BIM model includes a parametric BIM model and a physical BIM model; Based on the interaction between the BIM platform and the laying execution terminal equipment, cable laying control and management based on the cable BIM model are implemented.

2. The power distribution cable laying control method based on a BIM platform as described in claim 1, characterized in that, Each node in the node graph represents the spatial location through which the cable passes. The edge weight is determined jointly by multiple laying features, including path length, bending cost, proximity to existing pipelines, and cable heat dissipation conditions. The spatial location satisfies a preset probability.

3. The power distribution cable laying control method based on a BIM platform as described in claim 1, characterized in that, Perform parametric modeling based on cable NURBS curves, including: Based on the cable laying path, cable path control points are extracted, wherein the cable path control points are the key coordinate sequence of the cable laying direction, and the key coordinate sequence includes the starting point, the ending point, the intermediate turning point, and the connection and positioning points with the manhole, support, and terminal head. For the cable path control points, calculate the minimum allowable order, where the turning radius is negatively correlated with the order; Based on the cable path control points and the minimum allowable order, a cable NURBS curve is constructed. In this curve, node insertion is performed in regions of drastic curvature change and node merging is performed in regions of gentle curvature change through adaptive smoothing of node vectors.

4. The power distribution cable laying control method based on a BIM platform as described in claim 3, characterized in that, Perform iterative adjustments based on node vectors, including: Extract the node vectors of the cable path control points, wherein the node vectors are the spatial coordinates and specified tangential direction of each cable path control point; Based on the node vector, perform iterative adjustment of the weights and positions of each cable path control point to determine the first adjusted NURBS curve, wherein the iterative adjustment objective is to satisfy the node vector and minimize the overall energy. For the first adjusted NURBS curve, node insertion in the region of drastic curvature change and node merging in the region of gentle curvature change are performed to determine the effective cable NURBS curve. The region of drastic curvature change includes the stress cone region of the terminal head and the shielding disconnection position of the intermediate joint.

5. The power distribution cable laying control method based on a BIM platform as described in claim 1, characterized in that, Perform positional intersection tests on candidate detection objects based on spatial hash indexes, including: Based on the geometric information of the effective cable NURBS curve, a spatial hash index is established for each grid through uniform grid division of equal size, and an axial hierarchical bounding box tree is constructed for each cable pipeline. Based on the hierarchical bounding box tree, a hash table is queried according to the spatial grid position of each cable bounding box to extract cable structure components in the same grid and adjacent grids as candidate detection objects for intersection testing to determine collision information, wherein the collision information includes collision position and collision depth.

6. The power distribution cable laying control method based on a BIM platform as described in claim 5, characterized in that, Execution plan optimization, including: Read the collision information, search for the avoidance direction along the cable laying direction with the collision point as the center, calculate the recommended offset based on the collision depth and the cable outer diameter, and determine the avoidance information. Through information exchange, the avoidance information is migrated to the node graph, local path replanning is performed, and the effective cable NURBS curves and hierarchical bounding box trees are updated.

7. The power distribution cable laying control method based on a BIM platform as described in claim 6, characterized in that, Generate a cable BIM model, including: A predefined coding rule library, wherein the coding rule library includes component type identification rules, coding prefix mapping table, voltage level coding segment rules and function type suffix rules; The effective cable NURBS curve and hierarchical bounding box tree are used as a parametric BIM model, and the cable model attribute parameters are determined. Based on the cable model attribute parameters, a physical BIM model is constructed; A cable BIM model is generated by mapping and associating the parameter BIM model with the physical BIM model.

8. The power distribution cable laying control method based on a BIM platform as described in claim 7, characterized in that, Mapping and associating the parameter BIM model with the physical BIM model includes: Based on the cable model attribute parameters, the rule matching engine executes the rule matching based on the encoding rule base sequentially to generate KKS codes segment by segment; Using forward reasoning, the KKS coding is derived layer by layer from the top-level system coding down to the component-level coding to determine the hierarchical coding fields; Based on the hierarchical coding field, the parameter BIM model and the physical BIM model are mapped and associated.

9. The power distribution cable laying control method based on a BIM platform as described in claim 1, characterized in that, Implement cable laying control and management based on the cable BIM model, including: Establish communication and interaction between the BIM platform and the laying execution terminal equipment to implement phased and periodic control and management of cable laying projects; The phased, periodic control management includes: The first laying guidance information is generated based on the cable BIM model and sent to the laying execution end to implement the phased cable laying guidance. The physical execution information of the laying execution end is transmitted back to the BIM platform, and positioning based on the physical BIM model and parametric BIM model feedback decision based on physical deviation are carried out through a real-time synchronization mechanism.

10. A power distribution cable laying control system based on a BIM platform, characterized in that, The system is used to implement the power distribution cable laying control method based on a BIM platform as described in any one of claims 1-9, the system comprising: Path search module: In the BIM platform, the cable laying space is acquired and discretized into a node graph. Based on the heuristic function and turning radius constraint, the cable laying path is determined by performing heuristic path search. The heuristic function is the sum of the Euclidean distance from any node to the endpoint and the estimated bending cost. The turning radius constraint is achieved by limiting the direction change between nodes. Curve construction module: Based on the cable laying path, it performs parametric modeling based on cable NURBS curves and iterative adjustment based on node vectors to determine the effective cable NURBS curves; Object testing planning module: Scans the effective cable NURBS curves, constructs a hierarchical bounding box tree through grid division, performs position intersection testing and planning optimization of candidate detection objects based on spatial hash index, and generates a cable BIM model, wherein the cable BIM model includes a parametric BIM model and a physical BIM model; Laying Control Module: Based on the interaction between the BIM platform and the laying execution terminal equipment, it performs cable laying control management based on the cable BIM model.

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