Method and system for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm

Abstract

The invention relates to the technical field of optical fiber wiring, and discloses a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, and the method comprises the steps: constructing a spatial topology model corresponding to a wiring region; performing gridding processing on the spatial topology model to obtain a spatial topology grid, and calculating an optical fiber installation cost between an initial installation node and a subsequent installation node; planning an optical fiber installation line between the initial installation node and the subsequent installation node in the spatial topology grid, and carrying out adaptive modeling on the optical fiber and the spatial topology model in the optical fiber installation line to obtain an optical fiber adaptive virtual model; evaluating the optical fiber interference degree between the optical fibers in the optical fiber adaptive virtual model, calculating the line complexity corresponding to the optical fiber installation line, and calculating the environmental coupling degree corresponding to the optical fibers in the optical fiber installation line; and performing line optimization processing on the optical fiber installation line to obtain an optimized installation line of the optical fiber in the to-be-installed area. The invention mainly aims to solve the problem of low optical fiber wiring efficiency.

Description

Technical Field

[0001] The invention relates to a method and a system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, and belongs to the technical field of optical fiber wiring. Background Art

[0002] Fiber optic cabling plays a vital role in the field of modern communications and data transmission. With the rapid development of information technology, the demand for efficient and accurate fiber optic cabling is growing.

[0003] Existing fiber optic cabling planning mainly relies on manual experience and simple rules. After determining the starting and ending points of the cabling, engineers choose possible paths based on their experience, taking into account factors such as shortening the cabling length as much as possible and avoiding collisions with obstacles. However, this method has many limitations. First, manual planning relies on experience, and the plans of different engineers may vary greatly, lacking consistency and optimality. Second, for complex building structures or large-scale cabling scenarios, manual planning is difficult to fully consider various factors, such as space limitations, electromagnetic interference, future expansion needs, etc. Moreover, in the actual cabling process, unexpected situations may occur, resulting in the need to frequently adjust the plan, thereby reducing the efficiency of fiber optic cabling. Summary of the invention

[0004] The present invention provides a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, the main purpose of which is to solve the problem of low optical fiber wiring efficiency.

[0005] To achieve the above object, the present invention provides a method for implementing efficient optical fiber wiring planning based on an intelligent path planning algorithm, comprising:

[0006] Obtaining the area to be installed of the optical fiber and its corresponding regional wiring requirements, locating the wiring area in the area to be installed according to the regional wiring requirements, collecting regional building information and regional spatial data corresponding to the wiring area, and combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area;

[0007] The spatial topology model is gridded to obtain a spatial topology grid, and grid nodes and their corresponding node metadata in the spatial topology grid are identified, wherein the grid nodes include: a starting installation node and a subsequent installation node, and the optical fiber installation cost between the starting installation node and the subsequent installation node is calculated in combination with the node metadata;

[0008] In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, and optical fiber installation equipment and installation optical fiber information in the optical fiber installation route are queried. In combination with the optical fiber installation equipment and the installation optical fiber information, the optical fiber and the spatial topology model are adapted and modeled in the optical fiber installation route to obtain an optical fiber adaptation virtual model;

[0009] Evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environment attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environment attributes;

[0010] In combination with the optical fiber interference, the line complexity and the environmental coupling degree, the optical fiber installation line is optimized to obtain an optimized installation line of the optical fiber in the area to be installed.

[0011] Optionally, locating the wiring area in the area to be installed according to the area wiring requirement includes:

[0012] Performing text recognition on the wiring requirements of the area to obtain wiring requirement text;

[0013] Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category;

[0014] Based on the requirement category, extract key requirement information in the wiring requirement text;

[0015] Based on the key requirement information, a wiring area in the area to be installed is located.

[0016] Optionally, combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes:

[0017] Calculating the spatial distance value between each data in the regional spatial data, and calculating the distance variance between each data in the regional spatial data based on the spatial distance value;

[0018] Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data, and obtaining target spatial data;

[0019] Identify building entity elements in the regional building information, mark data corresponding to the building entity elements in the target space data, and obtain entity space data;

[0020] Analyzing the positional relationship between the entity space data, and determining the element topological relationship between the building entity elements according to the positional relationship;

[0021] The spatial topological model corresponding to the wiring area is constructed by combining the entity space data and the element topological relationship.

[0022] Optionally, the calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes:

[0023] Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata;

[0024] Calculate the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features;

[0025] Identify node obstacles between the starting installation node and the subsequent installation node, and calculate the optical fiber wiring length between the starting installation node and the subsequent installation node;

[0026] The optical fiber installation cost between the starting installation node and the subsequent installation node is calculated by combining the node obstacles, the installation complexity and the optical fiber wiring length.

[0027] Optionally, the combining the geometric metadata and the spatial geometric features to calculate the installation complexity corresponding to the subsequent installation node includes:

[0028] Determining, according to the geometric metadata, a feature metric value corresponding to the spatial geometric feature;

[0029] Querying the standard metric value corresponding to the spatial geometric feature, and calculating the complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value;

[0030] The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution through the following formula:

[0031]

[0032] Among them, A represents the installation complexity corresponding to the subsequent installation node, B arepresents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, q represents the number of features of the spatial geometric feature, D a Represents the complex contribution corresponding to the ath feature in the spatial geometric features.

[0033] Optionally, the combining the optical fiber installation cost and the preset installation expenditure and using a preset intelligent path planning algorithm to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid includes:

[0034] Identify the installation backup node corresponding to the successor installation node, and evaluate the node priority corresponding to the successor installation node based on the installation backup node;

[0035] In combination with the node priority, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation node in the spatial topological grid to obtain a node planning path;

[0036] Calculating the planned path cost corresponding to the node planned path according to the optical fiber installation cost;

[0037] In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

[0038] Optionally, the evaluating the fiber interference between optical fibers in the fiber adaptation virtual model includes:

[0039] Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model;

[0040] Traversing the model discrete points of the discrete optical fiber model to obtain the spatial coordinate information corresponding to the model discrete points;

[0041] Based on the spatial coordinate information, calculating the discrete point distances between the discrete points of the model;

[0042] The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between the optical fibers in the fiber adaptation virtual model can be calculated by the following formula:

[0043]

[0044] Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, L d，d+1 Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model, R dIndicates the fiber radius corresponding to the dth model in the discrete fiber model, R d+1 represents the fiber radius corresponding to the d+1th model in the discrete fiber model, and d and d+1 represent the serial numbers corresponding to the discrete fiber models respectively;

[0045] The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

[0046] Optionally, the calculating, based on the adaptation model diagram, the line complexity corresponding to the optical fiber installation line includes:

[0047] Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line;

[0048] Counting the crossing frequency of the lines in the smooth model line, and measuring the curvature of the lines in the smooth model line;

[0049] Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated by the following formula:

[0050]

[0051] Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line cross frequency, G0 represents the reference cross frequency, H e represents the line curvature corresponding to the e-th line in the smooth model line, r represents the number of smooth model lines, M0 represents the reference curvature, and I0 represents the cross-curvature correlation factor.

[0052] Optionally, the calculating, based on the node environment attribute, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line includes:

[0053] Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors;

[0054] Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes;

[0055] Standardizing the target environment attributes to obtain standard environment attributes;

[0056] According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

[0057] An efficient optical fiber wiring planning system is implemented based on an intelligent path planning algorithm, characterized in that the system comprises:

[0058] A spatial model building module is used to obtain the area to be installed of the optical fiber and its corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and build a spatial topology model corresponding to the wiring area in combination with the regional spatial data and the regional building information;

[0059] The installation cost calculation module is used to perform grid processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata;

[0060] A fiber adaptation modeling module is used to combine the fiber installation cost and the preset installation expenditure, plan the fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm, query the fiber installation equipment and the installation fiber information in the fiber installation route, and perform adaptation modeling on the fiber and the spatial topology model in the fiber installation route in combination with the fiber installation equipment and the installation fiber information to obtain a fiber adaptation virtual model;

[0061] An environmental coupling degree calculation module is used to evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes;

[0062] The line optimization module is used to optimize the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree to obtain the optimized installation line of the optical fiber in the area to be installed.

[0063] Compared with the problems described in the background technology, the present invention locates the wiring area in the area to be installed according to the wiring requirements of the area, and can clarify the specific scope of wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning, and collecting regional building information and regional spatial data corresponding to the wiring area, and can obtain relevant details of the building structure in the wiring area (such as walls, beams and columns, etc.) and spatial size, shape, channels and other data, which provides a basis for the subsequent construction of the spatial topological model corresponding to the wiring area. The present invention facilitates the spatial quantification of the spatial topological model by gridding the spatial topological model, and then converts the spatial topological model into a simpler visualization method, identifies the grid nodes in the spatial topological grid and their corresponding node metadata, and provides a basis for the subsequent starting installation node and the subsequent The present invention provides a basis for calculating the optical fiber installation cost between installation nodes. By combining the optical fiber installation cost and the preset installation expenditure, the present invention uses a preset intelligent path planning algorithm to plan the optical fiber installation line between the starting installation node and the subsequent installation node in the spatial topological grid, and can efficiently determine the optimal installation path within the cost control range. By evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the optical fiber layout, and provide a basis for the subsequent line optimization processing of the optical fiber installation line. The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree, and then obtains the optimal installation line of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Therefore, the present invention proposes a method and system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, thereby improving the efficiency of optical fiber wiring planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of a process for implementing an efficient optical fiber wiring planning method based on an intelligent path planning algorithm provided by an embodiment of the present invention;

[0065] Figure 2 A functional module diagram of an embodiment of the present invention for implementing an efficient optical fiber wiring planning system based on an intelligent path planning algorithm.

[0066] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0068] The embodiment of the present application provides a method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm. The execution subject of the method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0069] Embodiment 1:

[0070] Reference Figure 1 FIG. 1 is a flow chart of a method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm according to an embodiment of the present invention. In this embodiment, the method for implementing efficient fiber optic cabling planning based on an intelligent path planning algorithm includes:

[0071] S1. Obtain the area to be installed of the optical fiber and its corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and construct a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information.

[0072] The present invention locates the wiring area in the area to be installed according to the wiring requirements of the area, and can clarify the specific scope used for wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning, and collecting regional building information and regional spatial data corresponding to the wiring area, and can obtain relevant details of the building structure in the wiring area (such as walls, beams and column positions, etc.) and space size, shape, channels and other data, which provides a basis for the subsequent construction of a spatial topological model corresponding to the wiring area.

[0073] It should be explained that the optical fiber is a communication cable that needs to be installed; the area to be installed is the overall area where the optical fiber is planned to be installed; the regional wiring requirement is the conditions and requirements that should be met for the installation of the optical fiber in the area to be installed; the wiring area is the specific installation range specifically determined for the optical fiber in the area to be installed; the regional building information is the relevant information such as the building structure corresponding to the wiring area; the regional spatial data is the spatial point cloud data corresponding to the wiring area; further, the collection of regional building information and regional spatial data corresponding to the wiring area can be achieved through collection tools, such as a three-dimensional laser scanner, which can quickly and accurately obtain the three-dimensional coordinate information of the building structure in the wiring area, including the position, shape and size of walls, beams, ceilings and floors, so as to fully present the physical outline of the building.

[0074] In detail, locating the wiring area in the area to be installed according to the area wiring requirements includes:

[0075] Performing text recognition on the wiring requirements of the area to obtain wiring requirement text;

[0076] Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category;

[0077] Based on the requirement category, extract key requirement information in the wiring requirement text;

[0078] Based on the key requirement information, a wiring area in the area to be installed is located.

[0079] It should be explained that the wiring requirement text is the specific textual expression of the regional wiring requirement; the requirement text semantics is the meaning expressed by the wiring requirement text; the requirement category is the type of wiring requirement text divided according to different characteristics; the key requirement information is the important information in the wiring requirement text that plays a key role in locating the wiring area, such as key location points.

[0080] Furthermore, the text recognition of the regional wiring requirements can be achieved through optical character recognition (OCR) technology; the semantics of the requirement text corresponding to the wiring requirement text can be analyzed through semantic analysis; based on the semantics of the requirement text, the classification algorithm in machine learning (such as decision tree, support vector machine, etc.) can be used to implement the requirement classification processing of the wiring requirement text to obtain the requirement category; based on the requirement category, the key requirement information in the wiring requirement text can be extracted through an information extraction algorithm (such as a method based on pattern matching and statistical learning); based on the key requirement information, the wiring area in the area to be installed is located, assuming that the key position points in the key requirement information are the communication room A and various information points in the office area of ​​the building, and the restriction condition is that it cannot pass through the high-temperature pipeline area and should be as close to the wall as possible. First, the positions of the communication room A and various information points are marked on the building plan of the area to be installed, and then, according to the restriction condition, the area where the high-temperature pipeline is located is avoided, and possible paths are planned along the direction of the wall. The area covered by these qualified paths is the preliminary wiring area, and then after further optimization, such as considering avoiding narrow passages, the final wiring area is determined.

[0081] The present invention constructs a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information, and can obtain a three-dimensional spatial structure model of the wiring area, clearly presenting the building layout, spatial relationship and obstacle distribution in the wiring area, and providing accurate spatial reference for optical fiber wiring planning. It should be explained that the spatial topology model is a three-dimensional spatial structure model corresponding to the wiring area.

[0082] Specifically, the combining of the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes:

[0083] Calculating the spatial distance value between each data in the regional spatial data, and calculating the distance variance between each data in the regional spatial data based on the spatial distance value;

[0084] Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data, and obtaining target spatial data;

[0085] Identify building entity elements in the regional building information, mark data corresponding to the building entity elements in the target space data, and obtain entity space data;

[0086] Analyzing the positional relationship between the entity space data, and determining the element topological relationship between the building entity elements according to the positional relationship;

[0087] The spatial topological model corresponding to the wiring area is constructed by combining the entity space data and the element topological relationship.

[0088] It should be explained that the spatial distance value is a measure of the distance between each data in the regional spatial data, the distance variance represents the degree of discreteness between each data in the regional spatial data, the target spatial data is the data obtained after removing the discrete data in the regional spatial data, the building entity elements are structural elements in the regional building information, such as walls, columns, ceilings, etc., the physical spatial data are the data in the target spatial data corresponding to the building entity elements, the positional relationship is the corresponding relationship between the physical spatial data, and the element topological relationship is the connection relationship between the building entity elements.

[0089] Furthermore, the calculation of the spatial distance value between each data in the regional spatial data can be achieved through the Euclidean distance algorithm; the calculation of the distance variance between each data in the regional spatial data can be achieved through the variance formula; when the distance variance is less than the spatial distance value, the corresponding discrete data in the regional spatial data is eliminated to obtain the target spatial data; the identification of the building entity elements in the regional building information can be achieved through natural language processing; marking the data corresponding to the building entity elements in the target spatial data can be achieved through manual marking; the analysis of the positional relationship between the entity spatial data can be achieved through a spatial clustering algorithm; based on the positional relationship, the element topological relationship between the building entity elements is determined. Assuming that there are walls and columns in the building entity elements, if the columns partially overlap with the walls, this is an intersecting positional relationship, then their topological relationship is an intersection, which means that the columns may be the supporting structure of the wall or a design element embedded in the wall; the construction of the spatial topological model corresponding to the wiring area can be achieved through a three-dimensional mapping tool, such as a CAD mapping tool.

[0090] S2. Gridding the spatial topology model to obtain a spatial topology grid, identifying grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata.

[0091] The present invention facilitates spatial quantification of the spatial topological model by gridding the spatial topological model, and then converts the spatial topological model into a simpler visualization method, identifies the grid nodes in the spatial topological grid and their corresponding node metadata, and provides a basis for the subsequent calculation of the optical fiber installation cost between the starting installation node and the subsequent installation node. It should be explained that the spatial topological grid is a grid structure formed after the spatial topological model is gridded; the grid node is the basic unit point in the spatial topological grid, which is used to construct the connection and topological relationship of the grid; the node metadata is the relevant attribute information attached to the grid node; the starting installation node is a specific node in the grid node where the optical fiber wiring starts; the subsequent installation node is a node in the grid node that is located after the starting installation node in the optical fiber wiring sequence. Furthermore, the gridding of the spatial topological model can be achieved through a grid division module in a finite element analysis (FEA) software; the identification of the grid nodes in the spatial topological grid and their corresponding node metadata can be achieved through visualization tools, and many professional three-dimensional modeling and visualization software provide interactive functions to identify grid nodes and metadata. In these software, you can select grid nodes on the visualized spatial topology grid by mouse clicks, box selection, etc. The software will automatically display the relevant metadata of the node, which may be displayed in the form of attribute lists, information panels, etc.

[0092] The present invention calculates the fiber optic installation cost between the starting installation node and the subsequent installation node by combining the node metadata, and can calculate the cost of laying optical fiber between the starting installation node and the subsequent installation node to avoid budget overruns. It should be explained that the fiber optic installation cost is the installation cost between the starting installation node and the subsequent installation node.

[0093] Specifically, the calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes:

[0094] Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata;

[0095] Calculate the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features;

[0096] Identify node obstacles between the starting installation node and the subsequent installation node, and calculate the optical fiber wiring length between the starting installation node and the subsequent installation node;

[0097] The optical fiber installation cost between the starting installation node and the subsequent installation node is calculated by combining the node obstacles, the installation complexity and the optical fiber wiring length.

[0098] It should be explained that the spatial geometric features are the spatial morphological characteristics corresponding to the subsequent installation nodes, such as curvature, spatial height meter multi-layer structure, etc.; the geometric metadata are the specific data descriptions corresponding to the spatial geometric features in the node metadata; the installation complexity indicates the difficulty of optical fiber installation corresponding to the subsequent installation node; the node obstacle is the object that hinders the laying of optical fiber between the starting installation node and the subsequent installation node; the optical fiber wiring length is the actual length of the optical fiber laid between the starting installation node and the subsequent installation node.

[0099] Furthermore, the analysis of the spatial geometric features corresponding to the subsequent installation nodes can be achieved through a spatial analysis algorithm; the extraction of geometric metadata corresponding to the spatial geometric features from the node metadata can be achieved through an SQL query method; the identification of node obstacles between the starting installation node and the subsequent installation node can be achieved through millimeter wave radar detection, and can be achieved by calculating the node distance between the starting installation node and the subsequent installation node, the node distance being the optical fiber wiring length; the costs corresponding to the node obstacles and the optical fiber wiring length are determined respectively to obtain the obstacle cost and the optical fiber cost, the total installation cost = obstacle cost + optical fiber cost × optical fiber wiring length × installation complexity, and then the optical fiber installation cost between the starting installation node and the subsequent installation node is obtained.

[0100] Further, as an optional embodiment of the present invention, the combining the geometric metadata and the spatial geometric features to calculate the installation complexity corresponding to the subsequent installation node includes:

[0101] Determining, according to the geometric metadata, a feature metric value corresponding to the spatial geometric feature;

[0102] Querying the standard metric value corresponding to the spatial geometric feature, and calculating the complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value;

[0103] The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution through the following formula:

[0104]

[0105] Among them, A represents the installation complexity corresponding to the subsequent installation node, B arepresents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, q represents the number of features of the spatial geometric feature, D a Represents the complex contribution corresponding to the ath feature in the spatial geometric features.

[0106] It should be explained that the feature measurement value is the specific expression value corresponding to the spatial combination feature, the standard measurement value is the standard reference value corresponding to the spatial geometric feature, the complexity contribution degree indicates the influence of the subsequent installation node on the overall installation complexity, and the geometric weight indicates the importance corresponding to the spatial geometric feature. Furthermore, the feature measurement value corresponding to the spatial geometric feature can be determined by identifying the data value corresponding to the geometric metadata; the standard measurement value corresponding to the spatial geometric feature can be queried from the Internet through human-computer interaction, the measurement difference between the feature measurement value and the standard measurement value is calculated, and the measurement difference is divided by the standard measurement value to obtain the complexity contribution degree corresponding to the spatial geometric feature; the calculation of the geometric weight corresponding to the spatial geometric feature can be achieved through hierarchical analysis.

[0107] S3. In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, and the optical fiber installation equipment and the installed optical fiber information in the optical fiber installation route are queried. In combination with the optical fiber installation equipment and the installed optical fiber information, the optical fiber in the optical fiber installation route is adapted and modeled with the spatial topology model to obtain an optical fiber adaptation virtual model.

[0108] The present invention combines the optical fiber installation cost and the preset installation expenditure, and utilizes a preset intelligent path planning algorithm to plan the optical fiber installation line between the starting installation node and the subsequent installation node in the spatial topology grid, so as to efficiently determine the optimal installation path within the cost control range. It should be explained that the preset installation expenditure is the amount of funds used for optical fiber installation that is pre-set according to the overall planning, budget allocation and expected cost control goals before the optical fiber is installed. The preset intelligent path planning algorithm is a computer algorithm designed to determine the optical fiber installation line in a given spatial topology grid, such as algorithm A. The optical fiber installation line is the line used for optical fiber installation in the spatial topology grid.

[0109] In detail, the optical fiber installation route between the starting installation node and the subsequent installation node is planned in the spatial topology grid by combining the optical fiber installation cost and the preset installation expenditure using a preset intelligent path planning algorithm, including:

[0110] Identify the installation backup node corresponding to the successor installation node, and evaluate the node priority corresponding to the successor installation node based on the installation backup node;

[0111] In combination with the node priority, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation node in the spatial topological grid to obtain a node planning path;

[0112] Calculating the planned path cost corresponding to the node planned path according to the optical fiber installation cost;

[0113] In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

[0114] It should be explained that the installation backup node is the corresponding standby node when the subsequent installation node fails and cannot be used. The node priority represents the importance ranking of the subsequent installation nodes. The node planning path is the optimal connection route between the starting installation node and the subsequent installation node in the spatial topology grid. The planning path cost is the cost or resource consumption measure corresponding to the node planning path.

[0115] Furthermore, the identification of the installation backup node corresponding to the successor installation node can be achieved through functional equivalence judgment, analyzing the network topology structure to find nodes that are functionally equivalent to the successor installation node; evaluating the node priority corresponding to the successor installation node according to the number of the installation backup nodes, the greater the number, the higher the priority; connecting the successor installation node with a high node priority to the starting installation node to obtain a node planning path; summing the optical fiber installation costs corresponding to the node planning path to obtain a planning path cost; when the optical fiber installation cost is lower than the preset installation expenditure, filtering out the optical fiber installation line between the starting installation node and the successor installation node from the node planning path.

[0116] The present invention combines the optical fiber installation equipment and the installed optical fiber information, and adapts and models the optical fiber with the spatial topological model in the optical fiber installation line to obtain an optical fiber adaptation virtual model, thereby facilitating the subsequent calculation and processing of the optical fiber interference between optical fibers. It should be explained that the optical fiber installation equipment is a device for installing optical fibers, the installed optical fiber information is the introduction information corresponding to the optical fiber, and the optical fiber adaptation virtual model is a model obtained by adapting the virtual model corresponding to the optical fiber with the spatial topological model. Furthermore, the optical fiber installation equipment and the installed optical fiber information in the optical fiber installation line can be obtained by querying the network management system; the adaptation and modeling of the optical fiber with the spatial topological model in the optical fiber installation line can be achieved through 3D modeling software, such as 3ds Max.

[0117] S4. Evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes.

[0118] By evaluating the fiber interference between optical fibers in the fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the fiber layout, providing a basis for the subsequent line optimization processing of the fiber installation line. It should be explained that the fiber interference represents the degree of mutual influence of the layout between optical fibers in the fiber adaptation virtual model.

[0119] In detail, the evaluating the fiber interference between the optical fibers in the fiber adaptation virtual model includes:

[0120] Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model;

[0121] Traversing the model discrete points of the discrete optical fiber model to obtain the spatial coordinate information corresponding to the model discrete points;

[0122] Based on the spatial coordinate information, calculating the discrete point distances between the discrete points of the model;

[0123] The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between the optical fibers in the fiber adaptation virtual model can be calculated by the following formula:

[0124]

[0125] Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, L d，d+1 Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model, R d Indicates the fiber radius corresponding to the dth model in the discrete fiber model, R d+1 represents the fiber radius corresponding to the d+1th model in the discrete fiber model, and d and d+1 represent the serial numbers corresponding to the discrete fiber models respectively;

[0126] The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

[0127] It should be explained that the discrete optical fiber model is a discrete representation of the optical fiber model in the optical fiber adaptation virtual model, the model discrete points are basic elements of the discrete optical fiber model, the discrete point distance represents the distance value between the model discrete points, and the relative distance coefficient represents the relative spacing between optical fibers in the optical fiber adaptation virtual model.

[0128] Furthermore, the dynamic discrete processing of the optical fiber model in the optical fiber adaptation virtual model can be implemented by a discrete algorithm, such as a uniform grid discretization method; the traversal of the model discrete points of the discrete optical fiber model can be implemented by a loop structure in programming; the spatial coordinate information corresponding to the model discrete points can be obtained by a spatial coordinate tool, and the spatial coordinate tool is compiled by a scripting language, such as a JS scripting language; the discrete point distance between the model discrete points can be implemented by the above-mentioned Euclidean distance algorithm; according to the relative distance coefficient, the optical fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated, if the relative distance coefficient is greater than 1, it means that the distance between the optical fibers in the optical fiber adaptation virtual model is far, and the corresponding optical fiber interference is low, and the relative distance coefficient is less than 1, it means that the distance between the optical fibers in the optical fiber adaptation virtual model is close, and the corresponding optical fiber interference is high.

[0129] The present invention calculates the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, and the line complexity corresponding to each line in the optical fiber installation line can be used to understand the line complexity corresponding to each line in the optical fiber installation line, thereby laying a foundation for the subsequent line optimization processing of the optical fiber installation line. It should be explained that the adaptation model diagram is a visualization image corresponding to the optical fiber adaptation virtual model, and the line complexity represents the overall line complexity corresponding to the optical fiber installation line. Furthermore, the drawing of the adaptation model diagram corresponding to the optical fiber adaptation virtual model can be achieved through a drawing tool, and the drawing tool is compiled by a programming language.

[0130] In detail, the calculating the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram includes:

[0131] Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line;

[0132] Counting the crossing frequency of the lines in the smooth model line, and measuring the curvature of the lines in the smooth model line;

[0133] Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated by the following formula:

[0134]

[0135] Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line cross frequency, G0 represents the reference cross frequency, H e represents the line curvature corresponding to the e-th line in the smooth model line, r represents the number of smooth model lines, M0 represents the reference curvature, and I0 represents the cross-curvature correlation factor.

[0136] It should be explained that the model line is the corresponding installation line in the adaptation model diagram, the smooth model line is the line obtained after smoothing the jagged or discontinuous line in the model line, the line crossing frequency is the number of crossings in the smooth model line, and the line curvature is the degree of curvature in the smooth model line.

[0137] Furthermore, the line extraction processing of the adaptation model graph can be implemented by an edge detection algorithm; the smoothing processing of the model line can be implemented by a curve fitting algorithm; the statistics of the line crossing frequency in the smooth model line can be implemented by a geometric intersection judgment algorithm, traversing the line segments on the line, judging the intersection and counting; the measurement of the line curvature in the smooth model line can be implemented by calculating the curve curvature, such as obtaining the curvature of each segment by segmenting the line and taking the second-order derivative to measure the curvature; the reference crossing frequency and the reference curvature can be obtained by an existing professional library, which is a database of standard reference values ​​obtained by professional engineers through analysis tools; a large amount of optical fiber installation project case data can be collected, which should include line crossing frequency, curvature and engineers' subjective evaluation of installation complexity, and these data can be classified and statistically analyzed, for example, the complexity level is quantified (such as simple = 1, medium = 2, complex = 3, very complex = 4), and then an attempt is made to find the functional relationship between the crossing frequency and curvature and the complexity level, so as to calculate the crossing-bending correlation factor.

[0138] The present invention calculates the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes, and the degree of adaptation between the optical fiber and the corresponding installation environment can be understood through the environmental coupling degree, thereby improving the accuracy of subsequent line optimization processing of the optical fiber installation line. It should be explained that the node environmental attributes are the environmental characteristics corresponding to the grid nodes, and the environmental coupling degree represents the degree of adaptation between the optical fiber and the environment in the optical fiber installation line. Furthermore, the collection of the corresponding node environmental attributes corresponding to the grid nodes can be achieved through sensors, such as temperature sensors and humidity sensors.

[0139] Specifically, the step of calculating the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attribute includes:

[0140] Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors;

[0141] Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes;

[0142] Standardizing the target environment attributes to obtain standard environment attributes;

[0143] According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

[0144] It should be explained that the environmental attribute factors are the environmental factors corresponding to the node environmental attributes, such as temperature and humidity, etc., the optical fiber influencing factors are the environmental factors among the environmental attribute factors that affect the optical fiber, and the standard environmental attributes are the environmental attributes obtained after eliminating the differentiated effects between the target environmental attributes.

[0145] Further, the analysis of the environmental attribute factors corresponding to the node environmental attributes can be achieved through the principal component analysis (PCA) method; the optical fiber influencing factors can be identified from the environmental attribute factors according to a preset influencing factor table, and the influencing factor table can be constructed by an experimental design method, such as installing the same type of optical fiber in each simulated environment and testing the performance indicators of the optical fiber. The performance indicators may include the attenuation degree of the optical signal, the transmission bandwidth, the mechanical strength of the optical fiber (such as tensile strength), etc., so as to determine the corresponding environmental influencing factors; the standardization of the target environmental attributes can be achieved through the Z-Score standardization method; according to the standard environmental attributes, the preset geometric mean method is used to calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line. For example, if the standard environmental attributes are: temperature, humidity, and electromagnetic interference, the corresponding geometric mean method calculation formula is: The environmental coupling degree is calculated based on this.

[0146] S5. Based on the optical fiber interference, the line complexity and the environmental coupling degree, the optical fiber installation line is optimized to obtain an optimized installation line of the optical fiber in the area to be installed.

[0147] The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling, thereby obtaining the optimal installation line of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Furthermore, the line optimization of the optical fiber installation line can be achieved by combining the optical fiber interference, the line complexity and the corresponding values ​​of the environmental coupling. Assuming that the optical fiber interference is high, the line complexity is large and the environmental coupling is strong, the interference can be reduced by adjusting the direction of the optical fiber, such as avoiding interference sources, simplifying the crossing and bending parts for complex lines, and selecting more suitable protective materials and installation positions for harsh environments. These measures are combined to obtain an optimized installation line.

[0148] Compared with the problems described in the background technology, the present invention locates the wiring area in the area to be installed according to the wiring requirements of the area, and can clarify the specific scope of wiring in the area to be installed, providing an accurate layout space basis for subsequent optical fiber wiring planning, and collecting regional building information and regional spatial data corresponding to the wiring area, and can obtain relevant details of the building structure in the wiring area (such as walls, beams and columns, etc.) and spatial size, shape, channels and other data, which provides a basis for the subsequent construction of the spatial topological model corresponding to the wiring area. The present invention facilitates the spatial quantification of the spatial topological model by gridding the spatial topological model, and then converts the spatial topological model into a simpler visualization method, identifies the grid nodes in the spatial topological grid and their corresponding node metadata, and provides a basis for the subsequent starting installation node and the subsequent The present invention provides a basis for calculating the optical fiber installation cost between installation nodes. By combining the optical fiber installation cost and the preset installation expenditure, the present invention uses a preset intelligent path planning algorithm to plan the optical fiber installation line between the starting installation node and the subsequent installation node in the spatial topological grid, and can efficiently determine the optimal installation path within the cost control range. By evaluating the optical fiber interference between optical fibers in the optical fiber adaptation virtual model, the present invention can accurately understand the degree of mutual influence between optical fibers, and then analyze the rationality of the optical fiber layout, and provide a basis for the subsequent line optimization processing of the optical fiber installation line. The present invention optimizes the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree, and then obtains the optimal installation line of the optical fiber in the area to be installed, thereby improving the installation efficiency of the optical fiber. Therefore, the present invention proposes a method for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm, thereby improving the efficiency of optical fiber wiring planning.

[0149] Embodiment 2:

[0150] like Figure 21 is a functional module diagram of a system for realizing efficient optical fiber wiring planning based on an intelligent path planning algorithm provided by an embodiment of the present invention.

[0151] The efficient optical fiber wiring planning system 100 based on intelligent path planning algorithm of the present invention can be installed in an electronic device. According to the functions implemented, the efficient optical fiber wiring planning system 100 based on intelligent path planning algorithm can include a space model building module 101, an installation cost calculation module 102, an optical fiber adaptation modeling module 103, an environmental coupling degree calculation module 104 and a line optimization module 105. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0152] In this embodiment, the functions of each module / unit are as follows:

[0153] The spatial model building module 101 is used to obtain the area to be installed of the optical fiber and its corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and build a spatial topology model corresponding to the wiring area by combining the regional spatial data and the regional building information;

[0154] The installation cost calculation module 102 is used to perform grid processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata;

[0155] The optical fiber adaptation modeling module 103 is used to combine the optical fiber installation cost and the preset installation expenditure, plan the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid by using a preset intelligent path planning algorithm, query the optical fiber installation equipment and the installation optical fiber information in the optical fiber installation route, and combine the optical fiber installation equipment and the installation optical fiber information to perform adaptation modeling on the optical fiber and the spatial topology model in the optical fiber installation route to obtain an optical fiber adaptation virtual model;

[0156] The environmental coupling degree calculation module 104 is used to evaluate the fiber interference between the optical fibers in the optical fiber adaptation virtual model, draw the adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes;

[0157] The line optimization module 105 is used to optimize the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree to obtain an optimized installation line of the optical fiber in the area to be installed.

[0158] In detail, each module described in the system 100 for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm described in the embodiment of the present application is used in the same manner as described above. Figure 1 The technical means described in the text is the same as the method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm, and can produce the same technical effect, which will not be repeated here.

[0159] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm, characterized in that: The method comprises: Obtaining the area to be installed of the optical fiber and its corresponding regional wiring requirements, locating the wiring area in the area to be installed according to the regional wiring requirements, collecting regional building information and regional spatial data corresponding to the wiring area, and combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area; The spatial topology model is gridded to obtain a spatial topology grid, and grid nodes and their corresponding node metadata in the spatial topology grid are identified, wherein the grid nodes include: a starting installation node and a subsequent installation node, and the optical fiber installation cost between the starting installation node and the subsequent installation node is calculated in combination with the node metadata; In combination with the optical fiber installation cost and the preset installation expenditure, a preset intelligent path planning algorithm is used to plan an optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid, and optical fiber installation equipment and installation optical fiber information in the optical fiber installation route are queried. In combination with the optical fiber installation equipment and the installation optical fiber information, the optical fiber and the spatial topology model are adapted and modeled in the optical fiber installation route to obtain an optical fiber adaptation virtual model; Evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environment attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environment attributes; In combination with the optical fiber interference, the line complexity and the environmental coupling degree, the optical fiber installation line is optimized to obtain an optimized installation line of the optical fiber in the area to be installed.

2. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The step of locating the wiring area in the area to be installed according to the area wiring requirement includes: Performing text recognition on the wiring requirements of the area to obtain wiring requirement text; Analyzing the semantics of the requirement text corresponding to the wiring requirement text, and performing requirement classification processing on the wiring requirement text based on the semantics of the requirement text to obtain a requirement category; Based on the requirement category, extract key requirement information in the wiring requirement text; Based on the key requirement information, a wiring area in the area to be installed is located.

3. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The step of combining the regional spatial data and the regional building information to construct a spatial topology model corresponding to the wiring area includes: Calculating the spatial distance value between each data in the regional spatial data, and calculating the distance variance between each data in the regional spatial data based on the spatial distance value; Combining the distance variance and the spatial distance value, removing discrete data in the regional spatial data, and obtaining target spatial data; Identify building entity elements in the regional building information, mark data corresponding to the building entity elements in the target space data, and obtain entity space data; Analyzing the positional relationship between the entity space data, and determining the element topological relationship between the building entity elements according to the positional relationship; The spatial topological model corresponding to the wiring area is constructed by combining the entity space data and the element topological relationship.

4. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The calculating the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata includes: Analyzing the spatial geometric features corresponding to the subsequent installation node, and extracting geometric metadata corresponding to the spatial geometric features from the node metadata; Calculate the installation complexity corresponding to the subsequent installation node by combining the geometric metadata and the spatial geometric features; Identify node obstacles between the starting installation node and the subsequent installation node, and calculate the optical fiber wiring length between the starting installation node and the subsequent installation node; The optical fiber installation cost between the starting installation node and the subsequent installation node is calculated by combining the node obstacles, the installation complexity and the optical fiber wiring length.

5. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 4, characterized in that: The combining the geometric metadata and the spatial geometric features to calculate the installation complexity corresponding to the subsequent installation node includes: Determining, according to the geometric metadata, a feature metric value corresponding to the spatial geometric feature; Querying the standard metric value corresponding to the spatial geometric feature, and calculating the complex contribution corresponding to the spatial geometric feature by combining the feature metric value and the standard metric value; The geometric weight corresponding to the spatial geometric feature is calculated, and the installation complexity corresponding to the subsequent installation node is calculated by combining the geometric weight and the complexity contribution through the following formula: Among them, A represents the installation complexity corresponding to the subsequent installation node, B a represents the geometric weight corresponding to the ath feature in the spatial geometric feature, a represents the feature sequence number corresponding to the spatial geometric feature, q represents the number of features of the spatial geometric feature, D a Represents the complex contribution corresponding to the ath feature in the spatial geometric features.

6. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The method combines the optical fiber installation cost and the preset installation expenditure, and plans the optical fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm, including: Identify the installation backup node corresponding to the successor installation node, and evaluate the node priority corresponding to the successor installation node based on the installation backup node; In combination with the node priority, a preset intelligent path planning algorithm is used to perform path planning for the starting installation node and the subsequent installation node in the spatial topological grid to obtain a node planning path; Calculating the planned path cost corresponding to the node planned path according to the optical fiber installation cost; In combination with the optical fiber installation cost and the preset installation expenditure, the optical fiber installation route between the starting installation node and the subsequent installation node is screened out from the node planning path.

7. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The evaluating the fiber interference between the optical fibers in the optical fiber adaptation virtual model comprises: Dynamically discretizing the optical fiber model in the optical fiber adaptation virtual model to obtain a discrete optical fiber model; Traversing the model discrete points of the discrete optical fiber model to obtain the spatial coordinate information corresponding to the model discrete points; Based on the spatial coordinate information, calculating the discrete point distances between the discrete points of the model; The fiber radius corresponding to the discrete fiber model is determined. Combining the fiber radius and the discrete point distance, the relative distance coefficient between the optical fibers in the fiber adaptation virtual model can be calculated by the following formula: Where E represents the relative distance coefficient between optical fibers in the optical fiber adaptation virtual model, L d，d+1 Indicates the discrete point distance between the dth model and the d+1th model in the discrete fiber model, R d Indicates the fiber radius corresponding to the dth model in the discrete fiber model, R d+1 represents the fiber radius corresponding to the d+1th model in the discrete fiber model, and d and d+1 represent the serial numbers corresponding to the discrete fiber models respectively; The fiber interference between the optical fibers in the optical fiber adaptation virtual model is evaluated according to the relative distance coefficient.

8. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The calculating, based on the adaptation model diagram, the line complexity corresponding to the optical fiber installation line comprises: Performing line extraction processing on the adaptation model graph to obtain a model line, and performing smoothing processing on the model line to obtain a smoothed model line; Counting the crossing frequency of the lines in the smooth model line, and measuring the curvature of the lines in the smooth model line; Combined with the line crossing frequency and the line curvature, the line complexity corresponding to the optical fiber installation line is calculated by the following formula: Among them, F represents the line complexity corresponding to the optical fiber installation line, G represents the line cross frequency, G0 represents the reference cross frequency, H e represents the line curvature corresponding to the e-th line in the smooth model line, r represents the number of smooth model lines, M0 represents the reference curvature, and I0 represents the cross-curvature correlation factor.

9. The method for realizing efficient optical fiber wiring planning based on intelligent path planning algorithm according to claim 1, characterized in that: The step of calculating the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attribute includes: Analyzing environmental attribute factors corresponding to the node environmental attributes, and identifying optical fiber influencing factors from the environmental attribute factors; Based on the optical fiber influencing factors, filtering the node environment attributes to obtain target environment attributes; Standardizing the target environment attributes to obtain standard environment attributes; According to the standard environmental attributes, the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line is calculated using a preset geometric mean method.

10. An efficient optical fiber cabling planning system is implemented based on an intelligent path planning algorithm, characterized in that: The system comprises: A spatial model building module is used to obtain the area to be installed of the optical fiber and its corresponding regional wiring requirements, locate the wiring area in the area to be installed according to the regional wiring requirements, collect regional building information and regional spatial data corresponding to the wiring area, and build a spatial topology model corresponding to the wiring area in combination with the regional spatial data and the regional building information; The installation cost calculation module is used to perform grid processing on the spatial topology model to obtain a spatial topology grid, identify grid nodes in the spatial topology grid and their corresponding node metadata, wherein the grid nodes include: a starting installation node and a subsequent installation node, and calculate the optical fiber installation cost between the starting installation node and the subsequent installation node in combination with the node metadata; A fiber adaptation modeling module is used to combine the fiber installation cost and the preset installation expenditure, plan the fiber installation route between the starting installation node and the subsequent installation node in the spatial topology grid using a preset intelligent path planning algorithm, query the fiber installation equipment and the installation fiber information in the fiber installation route, and perform adaptation modeling on the fiber and the spatial topology model in the fiber installation route in combination with the fiber installation equipment and the installation fiber information to obtain a fiber adaptation virtual model; An environmental coupling degree calculation module is used to evaluate the fiber interference between optical fibers in the optical fiber adaptation virtual model, draw an adaptation model diagram corresponding to the optical fiber adaptation virtual model, calculate the line complexity corresponding to the optical fiber installation line based on the adaptation model diagram, collect the corresponding node environmental attributes corresponding to the grid nodes, and calculate the environmental coupling degree corresponding to the optical fiber in the optical fiber installation line based on the node environmental attributes; The line optimization module is used to optimize the optical fiber installation line by combining the optical fiber interference, the line complexity and the environmental coupling degree to obtain the optimized installation line of the optical fiber in the area to be installed.

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