A method for automatically generating a power transmission line engineering material table

Abstract

The embodiment of the application provides a power transmission line engineering material table automatic generation method, which is applied to the technical field of electric power systems and power transmission engineering, and constructs a full-digital derivation engine: firstly, line path and obstacle constraints are obtained through GIS analysis; then, the arrangement of the tower is automatically determined based on an optimization algorithm; then, conductor mechanics simulation and component intelligent matching are carried out; finally, the system topological relationship is constructed, and an accurate engineering bill of materials is automatically generated. The method remolds the traditional discrete mode which depends on manual judgment and manual statistics into a continuous automatic process based on a unified data model and physical laws, ensures design consistency, statistical accuracy and full-process traceability, and significantly improves design efficiency, safety and economy.

Description

Technical Field

[0001] This application relates to the field of power system and transmission engineering technology, and in particular to a method for automatically generating a material list for transmission line engineering. Background Technology

[0002] Traditional power transmission line design processes are characterized by significant decoupling and serialization. Each professional stage relies on unstructured information such as drawings and documents for manual transmission and experience-based judgment, forming a relay-style work model. Lacking the ability to effectively integrate and analyze multi-source information through big data processing, this model is highly susceptible to loss, ambiguity, and errors during information flow, resulting in severe information silos. Design changes are difficult to synchronize across disciplines in real time, often leading to inconsistencies between drawings and data, frequent later revisions, and becoming a major pain point in project cost and schedule control.

[0003] In key technology decision-making stages, such as tower positioning and selection, traditional methods heavily rely on designers' personal experience and rough estimates, failing to incorporate big data processing technology to mine and intelligently analyze historical engineering data, geographic information, and environmental parameters. Tower site layout requires manual, experience-based pre-arrangement using maps and manual verification of safety distances, a cumbersome process that makes global optimization difficult. Structural selection often relies on typical designs or conservative experience, lacking precise matching with real terrain and load conditions based on big data processing, resulting in a difficulty in balancing engineering economy and structural safety.

[0004] The current technology relies entirely on heavy manual labor for final material statistics. Designers need to manually identify, classify and count thousands of components from a large number of drawings and documents, which is prone to omissions, duplications or misinterpretations of specifications. Material information lacks digital correlation with upstream design parameters, has poor traceability, and it is difficult to update the material list synchronously after design modifications, which seriously affects the accuracy of procurement and construction and cost control. Summary of the Invention

[0005] The embodiments of this application provide a method for automatically generating a bill of materials for power transmission line projects, achieving seamless generation from design intent to an accurate bill of materials, eliminating information gaps, reliance on experience, and statistical errors inherent in traditional manual methods. To achieve the above objectives, this application adopts the following technical solution:

[0006] A method for automatically generating a material list for a power transmission line project, characterized in that the method includes:

[0007] Acquire information on the start and end points, turning points, and crossing sections of the line, and generate a three-dimensional spatial coordinate sequence of the line;

[0008] Based on the coordinate sequence, the coordinates of each tower pile position are determined by the span allocation algorithm, and the structural type is matched from the tower catalog library according to the terrain and load conditions at each pile position to generate a tower layout scheme.

[0009] Based on the tower layout scheme, query the tower structure database, extract the coordinates and elevations of the conductor suspension points of each tower, and generate a set of spatial parameters for the suspension points.

[0010] Based on the set of spatial parameters of the suspension point, the spatial shape, tension and sag data of the conductor and the ground wire are calculated by solving the catenary equation or performing finite element simulation, and a set of mechanical parameters of the conductor is generated.

[0011] Based on the conductor tension vector at each suspension point in the set of conductor mechanical parameters, and combined with the safety factor and insulation rules, insulators and fittings are matched and assembled from the insulator and fitting standard library to generate an insulator and fitting assembly chain.

[0012] Couple the set of mechanical parameters of the conductor with the insulator hardware assembly chain to construct a static analysis network. Use the static analysis network to calculate the entire load transfer path and the internal forces of the components, and generate a set of internal force transfer relationships.

[0013] Based on the set of internal force transmission relationships, combined with voltage level, number of circuits and environmental parameters, the engineering function attributes of each component are labeled to form a set of structured attributes;

[0014] Based on the attributes in the structured attribute set, the components are clustered according to the functional mapping rules to generate the circuit functional unit division results;

[0015] Based on the functional unit division results of the circuit, the component connections and force flow transmission relationships within and between each functional unit are analyzed, and then a material action path topology diagram is constructed.

[0016] By analyzing the material action path topology diagram, counting all components and their quantities, and matching them with the material coding library, a structured material table for power transmission line engineering is generated.

[0017] In some possible implementations, obtaining information on the start and end points, turning points, and crossed sections of the line, and generating a three-dimensional coordinate sequence of the line space, includes:

[0018] Input the coordinates of the starting point, ending point, and all turning points of the route;

[0019] Arrange the starting point coordinates, ending point coordinates, and corner point coordinates according to the actual path order to generate an ordered path node set;

[0020] Calculate the planar distance and azimuth angle between adjacent nodes in the ordered path node set to generate a path segmentation parameter set describing the geometric orientation of the path;

[0021] Based on the complete path geometry defined by the ordered path node set and the path segmentation parameter set, buffer analysis is performed along the path in the digital geographic information system.

[0022] Through the buffer analysis, the spatial range of important obstacles in the path corridor is identified and obtained, and a spatial information set of the cross-section is generated.

[0023] The ordered path node set, path segment parameter set, and cross-section spatial information set are fused together to form a three-dimensional spatial coordinate sequence of the line that includes path geometry and spatial constraints.

[0024] In some possible implementations, determining the coordinates of each tower pile position based on the coordinate sequence and the span allocation algorithm includes:

[0025] Read the ordered set of path nodes and the set of path segmentation parameters from the three-dimensional coordinate sequence of the line space;

[0026] Using the ordered path node set and path segmentation parameter set as input, and according to the preset standard span range, the span is divided within the straight line segment formed by adjacent ordered path nodes to generate an initial pile point set.

[0027] Using the initial pile point set and the spatial information set of the crossing section in the three-dimensional coordinate sequence of the line space as input, the initial pile point set falling into the crossing section is adjusted to avoid it, and an adjusted pile point set is generated.

[0028] Using the adjusted set of pile locations as input, longitudinal optimization is performed based on terrain elevation data to generate an optimized set of pile location coordinates;

[0029] Output the optimized pile position coordinate set as the pile position coordinates of each tower, which includes the three-dimensional position information of all towers.

[0030] In some possible implementations, the process of matching structural types from a tower catalog based on the terrain and load conditions at each pile location to generate a tower layout scheme includes:

[0031] Using the coordinates of each tower pile location as input, the elevation, slope and geomorphic feature data corresponding to each pile location are extracted from the digital elevation model to generate a terrain feature dataset. In the design stage of the coordinates of each tower pile location, the benchmark wind speed, ice thickness and temperature parameters on which the engineering line design is based are loaded to generate a meteorological load parameter set.

[0032] The terrain feature dataset and the meteorological load parameter set are associated to form a joint query condition;

[0033] Using the joint query conditions as input, a matching search is performed for each pile location in the predefined tower catalog library;

[0034] Based on the matching search results, the system outputs suggested tower models, nominal heights, and foundation configurations that meet the requirements for each pile location.

[0035] Summarize all tower location configuration suggestions for all pile locations and generate a tower layout scheme that includes tower type, tower height, pile location coordinates, and foundation type.

[0036] In some possible implementations, the process involves querying the tower structure database based on the tower layout scheme, extracting the coordinates and elevations of the conductor suspension points for each tower, and generating a set of spatial parameters for the suspension points, including:

[0037] Using the tower type and nominal height data included in the tower layout scheme as input, query the tower structure database to obtain the head size and hanging point layout parameters of the corresponding tower type;

[0038] Using the obtained hanging point layout parameters and the coordinates and elevations of each tower pile position in the tower layout scheme as input, calculate the actual three-dimensional spatial coordinates of each phase conductor and ground wire hanging point on each tower.

[0039] Based on the calculated actual three-dimensional spatial coordinates of all tower hanging points, the corresponding phase hanging points of adjacent towers are logically paired according to the direction of line advance to form a span unit describing the spatial span of each conductor and ground wire.

[0040] The coordinates, elevations, and span information of the starting and ending points of all span units are collected to construct a set of spatial parameters for suspension points used in subsequent mechanical calculations.

[0041] In some possible implementations, based on the set of spatial parameters of the suspension points, the spatial morphology, tension, and sag data of the conductor and ground wire are calculated by solving the catenary equation or performing finite element simulation to generate a set of conductor mechanical parameters, including:

[0042] The coordinates and elevation data of each suspension point in the set of spatial parameters of the suspension points are used as the calculation boundary conditions;

[0043] Based on the calculated boundary conditions, and by inputting the physical property parameters of the conductor and ground wire, as well as the wind load and ice load parameters used in the design, several typical calculation cases are selected.

[0044] According to the engineering design specifications, the typical calculation conditions are determined to include high temperature conditions, low temperature conditions, annual average temperature conditions, strong wind conditions, and icing conditions. For each selected typical calculation condition, the catenary equations that satisfy the calculation boundary conditions and physical states are solved by iterative method.

[0045] By solving the catenary equation, the spatial shape curves of the conductor and ground wire under this working condition, the horizontal and vertical tensions at each point, and the sag data of key control points are calculated.

[0046] The spatial morphology curves, horizontal and vertical tensions at each point, and sag data at key control points calculated under each working condition are structured according to span number and phase identifier to form a set of conductor mechanical parameters.

[0047] In some possible implementations, the process of matching and assembling insulators and fittings from an insulator and fitting standard library based on the conductor tension vector at each suspension point in the set of conductor mechanical parameters, combined with safety factors and insulation rules, to generate an insulator and fitting assembly chain includes:

[0048] Extract the comprehensive tension data of the conductor at the suspension point under each working condition from the set of conductor mechanical parameters;

[0049] Based on the extracted comprehensive tension data and the preset design safety factor, the rated mechanical failure load that the insulator string needs to match is calculated. According to the insulation rules determined by the line voltage level, altitude and pollution level, the insulation distance or number of discs that the insulator string needs to meet is calculated.

[0050] The calculated rated mechanical failure load is combined with the insulation distance or number of sheets parameter to form a joint matching condition;

[0051] Using the aforementioned joint matching conditions as an index, the applicable insulator model is queried and selected in the insulator and fitting standard library;

[0052] Based on the selected insulator model, associate and select matching connecting plates, hanging rings, wire clamps, and protective fittings. Logically connect the insulator and the fittings in the actual physical connection sequence to generate an insulator fitting assembly chain.

[0053] In some possible implementations, the set of conductor mechanical parameters is coupled with the insulator hardware assembly chain to construct a static analysis network. This static analysis network is then used to calculate the entire load transfer path and component internal forces, generating a set of internal force transfer relationships, including:

[0054] Based on the tower layout scheme and the insulator hardware assembly chain, an initial network topology is constructed, including tower nodes, conductor and ground wire units, and connection units.

[0055] The conductor and ground wire load data recorded in the set of conductor mechanical parameters are assigned to the corresponding conductor and ground wire units in the initial network topology to generate an intermediate network structure with applied load.

[0056] Based on the intermediate network structure and according to the mechanical properties of the components defined in the insulator hardware assembly chain, stiffness parameters are configured for all connecting units to form a computable network including complete property parameters.

[0057] Static equilibrium calculations were performed on the computable network under all design conditions to obtain the internal forces, bending moments and load transfer paths of each element.

[0058] Based on the internal forces, bending moments, and load transfer path results, a complete path describing the load transfer from the conductor / ground wire unit through the connection unit to the tower node, and a set of internal force transfer relationships for each component are generated.

[0059] In some possible implementations, based on the set of internal force transmission relationships, combined with voltage levels, number of circuits, and environmental parameters, engineering action attributes are labeled for each component to form a structured attribute set, including:

[0060] Read the set of internal force transmission relationships to obtain the internal force types and numerical data of each component;

[0061] Based on the internal force types and numerical data, a description of the mechanical functional attributes of each component is generated.

[0062] Based on the description of the mechanical functional attributes of each component, and in conjunction with the voltage level, number of circuits and environmental parameters, the corresponding engineering function attributes are uniformly labeled for the components of the corresponding category;

[0063] All engineering function attributes obtained for each component are summarized and encoded, and a set of structured attributes indexed by the component's unique identifier is output.

[0064] In some possible implementations, the step of clustering components according to functional mapping rules based on attributes in the structured attribute set to generate circuit functional unit partitioning results includes:

[0065] Read the structured attribute set to obtain a complete attribute description of all components;

[0066] Based on the function mapping rules, the complete attribute description is parsed to determine one or more functional unit categories corresponding to each component;

[0067] Based on the functional unit categories obtained from the analysis, components with the same category identifier are grouped and aggregated. Based on the grouping and aggregation results, specific functional unit instances are formed, and a list recording the correspondence between all components and their respective functional unit instances is output as the result of line functional unit division.

[0068] As can be seen from the above technical solution, this application has the following beneficial effects:

[0069] 1. This method constructs a fully digital and automated derivation engine from macroscopic geospatial data to microscopic materials, completely changing the traditional discrete and sequential working mode. It seamlessly integrates all aspects of the design process into a unified data model and workflow, ensuring the continuity, consistency, and losslessness of information flow. Once design intent and objective constraints, such as geographic information and load parameters, are input, subsequent decisions such as tower layout, mechanical simulation, and component selection are automatically derived and executed through built-in algorithms and rules. This eliminates information silos and design inconsistencies caused by human error and reliance on experience, ensuring the uniqueness and accuracy of design data from the source, and laying a solid foundation for efficient collaboration and controllable design quality.

[0070] 2. This method, based on GIS and optimization algorithms for automatic tower positioning and intelligent component matching based on real mechanical states and environmental conditions, elevates design decisions from reliance on experience to precise calculations based on data and physical laws. This significantly improves the safety and economy of power line engineering. By constructing a material action path topology map, the system can automatically and comprehensively analyze and count all components, generating a structured material list strongly correlated with upstream design parameters. This fundamentally eliminates errors from manual statistics, ensuring that the material quantity is a necessary result of design logic deduction. Furthermore, any design change can automatically update the material list, greatly improving efficiency, accuracy, and traceability. Attached Figure Description

[0071] The invention will now be further described with reference to the accompanying drawings.

[0072] Figure 1 A first flowchart of a method for automatically generating a material list for a power transmission line project, provided in an embodiment of this application;

[0073] Figure 2 A second flowchart of a method for automatically generating a material list for a power transmission line project, provided in an embodiment of this application;

[0074] Figure 3 A third flowchart of a method for automatically generating a material list for a power transmission line project, provided in an embodiment of this application;

[0075] Figure 4 The fourth flowchart of a method for automatically generating a material list for a power transmission line project is provided in an embodiment of this application. Detailed Implementation

[0076] The terms "first," "second," and "third," etc., used in this application specification, claims, and drawings are for distinguishing different objects, not for specifying a particular order.

[0077] In the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0078] Research has found that traditional heating or cooling compensation methods mostly rely on overall temperature control and lack the ability to quickly respond to local temperatures at the spinneret outlet. Existing technologies mostly operate temperature control and flow rate control independently, failing to form a synergistic control mechanism of two parameters. This makes it impossible to achieve a comprehensive effect of stable temperature and uniform flow rate, resulting in the fiber molecular chain orientation and crystallization process being difficult to achieve the best matching state.

[0079] To address the above problems, this application provides a method for automatically generating a material list for power transmission line projects:

[0080] Example 1; To solve the above problems, such as Figures 1-4 As shown, the core of this invention lies in constructing and driving a fully digitally linked derivation and execution engine that ranges from macroscopic geographic spatial constraints to microscopic component mechanical states and then to the mapping of standard material information. The engine's input consists of the most basic intentions expressed in engineering design and objective environmental parameters; its output is a precise bill of materials that can be directly used for procurement and construction. The underlying technical concept is to reshape the discrete, sequential work mode of traditional design, which relies on drawing transmission, experience-based judgment, and manual statistics, into an integrated process based on a unified data model, physical laws, and business rules that flows continuously and is automatically executed. In this process, the existence and quantity of each final material are not manually specified, but rather the inevitable result of rigorous calculation and logical deduction of its upstream design conditions. This method fundamentally eliminates inherent defects such as design inconsistencies, statistical errors, and poor traceability caused by information silos, experience biases, or manual mistakes.

[0081] Step S100: Obtain information on the start and end points, turning points, and crossing sections of the line, and generate a three-dimensional coordinate sequence of the line space.

[0082] This step is the spatial information perception and digital foundation stage of the entire automation process. Its purpose is to transform the engineer's initial conception of the route corridor into a semantically rich digital twin path model that can be accurately understood and processed by the computer. This model should not only depict where the route wants to go, but also clearly identify what obstacles are on the road, providing a real-world digital reflection for all subsequent automated decisions.

[0083] Data Input and Route Skeleton Generation: The system receives key control point information of the route from manual input or imported from the upstream planning system, including the latitude, longitude and elevation coordinates of the starting point, the ending point and all turning points along the route. The system connects these points strictly in the order of the route to form an ordered discrete point sequence, called the ordered path node set. This set constitutes the skeleton of the route.

[0084] Path geometric parameter calculation: The system automatically calculates the horizontal distance and the direction angle of the line connecting each pair of adjacent nodes in the ordered path node set. These parameters of all adjacent node pairs are systematically recorded to form a path segment parameter set. This set quantitatively describes the geometric characteristics of the path skeleton, which is composed of segments of straight lines.

[0085] Corridor spatial range modeling and intelligent obstacle recognition:

[0086] Buffer analysis generates a corridor: The system inputs the aforementioned ordered set of path nodes and their connections into the digital geographic information system. Using the centerline of the path as a reference, it extends to both sides by a pre-defined width based on voltage level and regulatory requirements—the corridor width. Through the buffer analysis function of GIS, a continuous three-dimensional strip-shaped spatial area is automatically generated. This area represents the maximum spatial extent that the railway line project may occupy legally and in design terms.

[0087] Overlay analysis accurately captures crossing points: In the GIS platform, the generated 3D model of the route corridor is spatially overlaid with pre-integrated high-precision geographic information layers, such as national topographic maps, transportation network maps, water system maps, building land use planning maps, and ecological protection zone boundary maps. By calculating spatial intersections, the system automatically and accurately identifies all sections where the route corridor intersects with or borders features requiring special design or safety avoidance, such as highways, railways, navigable rivers, important buildings, and large areas of forest. For each identified section, the system records its starting position, corresponding to the mileage, ending position, obstacle type, spatial boundary, and special processing level required by safety regulations, such as minimum vertical clearance and minimum horizontal distance, packaging them into a spatial information set of crossing sections. This process completely replaces the tedious and error-prone work of traditional design, which requires designers to repeatedly consult maps, conduct on-site surveys, and manually mark crossings.

[0088] Finally, the system integrates, associates, and uniformly encodes the three types of information—ordered path node set, path segment parameter set, and cross-section spatial information set—into a complete, structured data object, namely, a three-dimensional spatial coordinate sequence of the route. This object is the sole spatial data source for all subsequent automation steps.

[0089] In traditional methods, path information is typically represented only by lines and text markings on drawings. Crossings rely on manual identification and recording, resulting in isolated and volatile information. This step, by introducing GIS spatial analysis capabilities, including buffer and overlay analysis, automates and quantifies the perception of design environment constraints. The generated 3D spatial coordinate sequence of the route is no longer a simple line, but an intelligent navigation path with its own map of restricted areas and points of interest. This provides irrefutable spatial evidence for subsequent automatic tower placement algorithms, ensuring that the design is closely aligned with real-world conditions from the outset. It avoids major design changes later due to human oversight of crossings or measurement errors, laying a solid foundation for accurate and comprehensive constraints in the fully automated design process from the very beginning.

[0090] Step S200: Based on the coordinate sequence, determine the coordinates of each tower pile position using the span allocation algorithm, and match the structural type from the tower catalog library according to the terrain and load conditions at each pile position to generate a tower layout scheme.

[0091] This step is the decision-making center that transforms the abstract path into a concrete engineering entity. Its core is the span allocation algorithm, which is an automated optimization decision-making system that integrates electrical rules, spatial obstacle avoidance, and terrain adaptability. The goal is to find a safe, economical, and technically feasible installation point for each tower within the complex space defined by the three-dimensional coordinate sequence of the line space, and to assign it a suitable tower type and height.

[0092] Part 1: Determining Pile Location Coordinates Using the Span Allocation Algorithm

[0093] Baseline input: The algorithm reads the three-dimensional coordinate sequence of the route space to obtain the path skeleton and crossing constraint information.

[0094] Initial regularization partitioning: Within each straight segment of the path, defined by an ordered set of path nodes, the algorithm attempts to partition the spans evenly or approximately evenly, taking industry standards and experience-based standard span ranges as reference targets. This generates a series of initial tower locations on the centerline of the path, forming an initial set of pile locations. This step first satisfies the basic requirements of the electrical performance of transmission lines for span uniformity.

[0095] Intelligent spatial conflict resolution: The algorithm performs spatial relationship collision detection between the initial set of pile points and the spatial information set of the crossed sections. This is a crucial automated decision-making step.

[0096] Detection: The system determines whether each initial tower site falls within any crossing area, such as above a river or directly above a highway, or whether its distance from an obstacle is less than the safety regulations require.

[0097] Decision-making and execution: For conflicting tower sites, the algorithm does not simply delete them, but intelligently adjusts them according to a preset strategy.

[0098] Avoidance relocation: Move the tower site along the path direction until it exits the crossing area and meets the safety distance requirements.

[0099] Enhanced Function Configuration: For large and important crossing areas, such as major rivers and important trunk lines, the algorithm will automatically set up the pile positions of tension towers on both sides of the crossing area. The tension towers can withstand greater longitudinal tension and are used to anchor the conductors to achieve safe crossing. The algorithm will automatically increase the span in the crossing area, i.e., the crossing span, to ensure that the conductor sag meets the clearance requirements of the obstacles below.

[0100] This step generates an adjusted set of stake points that avoids all known spatial conflicts.

[0101] Terrain-Adaptive Refinement Adjustment: The algorithm incorporates high-precision digital elevation model data to perform terrain-adaptive optimization on the adjusted set of pile points. The system analyzes the ground elevation, slope, aspect, and geological conditions of each pile point.

[0102] Avoiding disadvantages and selecting advantages: The system automatically adjusts tower sites located in unfavorable locations such as steep cliffs, deep ravines, weak foundations, and areas prone to geological disasters to locations with more stable geological conditions and easier construction within a small permissible plane range.

[0103] Economic optimization: Fine-tune the tower elevation or horizontal position to achieve economic goals such as minimizing earthwork excavation, saving the amount of foundation concrete, and facilitating the construction of roads.

[0104] After completing this step, the final optimized pile position coordinate set is output, which is the precise three-dimensional coordinate of the center pile of each tower.

[0105] Part Two: Intelligent Tower Matching Based on Multidimensional Conditions

[0106] Constructing a tower site identity profile: For each tower site in the optimized pile location coordinate set, the system extracts its terrain feature dataset from the digital elevation model and geological database, such as altitude, ground slope, geomorphic unit, and foundation soil type. At the same time, it loads a unified set of meteorological load parameters for the entire project, such as design basic wind speed, ice thickness, and extreme temperature.

[0107] To create comprehensive matching query conditions: The terrain feature data of each tower site is bound with the engineering meteorological load parameters to form a joint query condition describing the unique environment and load scenario of that tower site. For example, the query conditions for a tower site located on a high-altitude ridge, with a strongly weathered rock foundation and subjected to heavy ice loads are completely different from those for a tower site located in a plain farmland, with soft soil layers and subjected to strong wind loads.

[0108] Precise retrieval in the catalog: Using the joint query conditions as the key, a search is performed in the pre-built tower catalog. This catalog is a relational database, where each record corresponds to a tower model and defines in detail the applicable conditions for that model, such as: maximum allowable wind speed, ice thickness, suitable terrain level, commonly used height range, and upper limit of foundation force.

[0109] Output and Integration: The system outputs a list of all eligible tower models for each tower location. Based on preset optimization goals, such as the lowest total cost or the fewest models to facilitate construction, it can automatically recommend or have the final selection confirmed by the engineer. The system summarizes the pile coordinates of all tower locations, the selected tower models, the nominal height, and the recommended foundation type to generate a complete tower layout plan.

[0110] Traditional pole and tower positioning and selection heavily rely on designers' experience and repeated manual adjustments, especially in complex mountainous areas and densely populated crossings. This approach is inefficient and difficult to optimize globally. The span allocation algorithm, however, achieves automated global optimization under spatial constraints. Through a three-stage logic of initial partitioning, conflict resolution, and terrain optimization, it systematically resolves the contradictions between electrical requirements, spatial safety, and engineering economics. When a line needs to cross a highway and a reservoir, the algorithm can automatically adjust the tower location to outside the safety zone stipulated by road administration and water conservancy departments, and may automatically configure a high tower to simultaneously meet the clearance requirements of both crossings. This process is fully automated, avoiding human error. Pole and tower matching based on environmental and load coupling conditions ensures that the selection of each tower is tailored to local conditions, achieving a precise balance between structural safety and engineering economy from the outset, avoiding the waste or hidden dangers caused by a one-size-fits-all design. The pole and tower layout scheme output in this step is a reliable scheme that has undergone automated verification from multiple dimensions of space, electrical, mechanical, and economics, serving as the physical basis for all subsequent detailed simulations.

[0111] Step S300: Based on the tower layout scheme, query the tower structure database, extract the coordinates and elevations of the conductor suspension points of each tower, and generate a set of spatial parameters for the suspension points.

[0112] The tower itself is the supporting structure, while the conductors and ground wires are the carriers of current and the main load-bearing bodies. The purpose of this step is to transform the physical location of the tower determined in the previous step into precise suspension constraint points for the conductors and ground wires in three-dimensional space. The generated set of spatial parameters for suspension points is the absolute spatial boundary condition for conductor mechanics calculations, defining the two fixed endpoints of each conductor segment in space.

[0113] Specific implementation process: Obtain detailed tower dimensions: The system reads the model and nominal height of each tower in the tower layout plan, and uses this as an index to query a detailed tower structure database. This database stores digital three-dimensional models or precise dimension tables of all standard tower models, and can obtain key geometric parameters such as crossarm length, vertical distance between upper and lower conductor suspension points, ground wire bracket height, and installation hole diameter of suspension point hardware.

[0114] Calculating absolute spatial coordinates: For each tower, the three-dimensional coordinates of its center point are used as the spatial reference origin. Combining the tower type dimension parameters retrieved from the database, through three-dimensional coordinate transformation, translation, and rotation, the three-dimensional coordinates of each phase conductor on the tower, such as phase A, phase B, phase C, and each ground wire suspension point (i.e., the center point of the hardware connecting the upper end of the insulator string to the tower body), are accurately calculated in the real world. The calculation process strictly considers the tower's tilt, the extension direction of the crossarm, and its length.

[0115] Logical pairing forms span units: The system logically associates and pairs the suspension points of the same phase or ground wire on adjacent towers according to the line route. Each pair of tower start and tower stop suspension points constitutes a span unit. For example, the B phase suspension point of tower No. 5 is paired with the B phase suspension point of tower No. 6 to form an independent B phase 5 span unit. This unit represents a section of conductor fixed at both ends and independent.

[0116] Generate a structured set: The system traverses all span units along the entire line, extracts and organizes the following information for each unit: the three-dimensional coordinates of the starting anchor point, the three-dimensional coordinates of the ending anchor point, the horizontal distance between the two anchor points, and the elevation difference between the two anchor points. This information from all span units is gathered together to form a structured set of suspension point spatial parameters. This set is the core input for subsequent steps. It clearly depicts the network of anchor points for all conductors and ground wires in the air along the entire line in the form of data.

[0117] The beneficial effects of step S300 are derived as follows: In traditional design, the coordinates of suspension points are usually implicit in the tower general drawing, requiring manual interpretation or secondary measurement before they can be used for mechanical calculations. This process is prone to errors and inefficient. By using a digital tower database and automatic coordinate conversion, a lossless and accurate conversion from design symbols, tower type, and tower height to physical world coordinates is achieved. The generated set of spatial parameters for suspension points is a pure and unambiguous dataset of boundary conditions. It decomposes the continuous line into a series of discrete span units that can be independently mechanically analyzed, laying a unique and definite geometric foundation for subsequent accurate conductor mechanical simulations. This ensures the accuracy of the source data for mechanical calculations and serves as a rigid bridge connecting structural layout and electrical mechanical analysis.

[0118] Step S400: Based on the set of spatial parameters of the suspension point, calculate the spatial shape, tension and sag data of the conductor and the ground wire by solving the catenary equation or performing finite element simulation, and generate a set of mechanical parameters of the conductor.

[0119] This step is the core simulation stage of the line's mechanical state. The conductor is not rigid, but rather exhibits a flexible catenary shape under its own weight, ice, and wind loads. Its shape and internal tension directly affect the line's safety, electrical clearance, tower load, and cost of conductor usage. Through precise physical simulation, the true spatial shape, internal tension distribution, and critical sag value of the conductor and ground wire are calculated under various possible weather conditions.

[0120] Specific implementation process: Setting calculation boundaries and operating conditions: The coordinates of the starting and ending points and the elevation difference of each span unit in the suspension point spatial parameter set are used as fixed boundary conditions. Simultaneously, the physical property parameters of the conductor and ground wire are input, such as cross-sectional area, mass per unit length, elastic modulus, and coefficient of linear expansion, as well as the meteorological conditions used in the design, such as wind speed, ice thickness, and temperature. According to national design codes, a series of typical operating conditions to be calculated are determined, such as: highest temperature condition, lowest temperature condition, annual average temperature condition, maximum wind speed condition, and icing condition. Each operating condition corresponds to a specific combination of temperature, wind speed, and ice thickness.

[0121] Iterative solution based on catenary theory: For each span element, under each design condition, the system employs an iterative numerical method to solve the catenary equation. This is a refined process that considers conductor stiffness and temperature deformation.

[0122] Initial assumptions: First, assume a horizontal tension value for the conductor.

[0123] Shape and length calculation: Based on the catenary formula, calculate the spatial curve shape and actual length of the conductor under the horizontal tension and current working load.

[0124] State equation verification: Introducing the conductor state equation. This equation describes the change in conductor length due to elastic deformation and thermal expansion and contraction under different operating conditions, such as temperature and load variations. The system uses the state equation to back-calculate the original length of the conductor under assumed tension, calculated in the previous step, back to a reference operating condition, such as the original length under average annual temperature, no wind, and no ice.

[0125] Iterative convergence: Compare the original length obtained from this back-calculation with the expected length of the conductor under the reference working condition, which is determined by the span and sag. If the two do not match, adjust the assumed horizontal tension value and repeat the above calculation until the difference is less than the preset small tolerance, thus achieving convergence. The horizontal tension and conductor space curve shape obtained at this time are the true solutions under this working condition.

[0126] Extracting key mechanical data: For each solution after convergence, the system extracts key data: the spatial coordinates of each point on the conductor, especially the conductor tension vector at the suspension points at both ends, including horizontal and vertical components, which is the direct basis for subsequent insulator string design, as well as the sag value at the center of the span or other control points, to verify whether the distance to the ground or crossing meets the safety requirements.

[0127] Organize and generate a set of mechanical parameters: Organize and store the spatial shape, tension vector, and sag data of all span units and all design conditions according to the hierarchical structure of span number, phase, and working condition to form a set of conductor mechanical parameters. This set is a multi-dimensional data cube that fully describes the mechanical response of the conductor system under all possible external environments.

[0128] Traditional methods often simplify conductor mechanics calculations or only perform calculations for individual controlled spans, making it difficult to comprehensively reflect the line's condition. By systematically solving the catenary equations numerically for all spans and all standard operating conditions along the entire line, a refined and comprehensive simulation of the line's mechanical state is achieved. It accurately reveals how conductor tension changes drastically with weather conditions; for example, tension may increase sharply during severe icing, and sag may increase during high temperatures. This multi-condition simulation capability, based on physical laws, provides a realistic and dynamic load spectrum for subsequent steps, rather than a static and conservative estimate. This ensures that the selection of insulators and fittings can be based on the most unfavorable and realistic stress conditions, guaranteeing safety and providing accurate data support for saving material costs under uncontrolled operating conditions. It is a key calculation step in achieving both safety and economic optimization.

[0129] Step S500: Based on the conductor tension vector at each suspension point in the set of conductor mechanical parameters, and in combination with the safety factor and insulation rules, insulators and fittings are matched and assembled from the insulator and fitting standard library to generate an insulator and fitting assembly chain.

[0130] The conductor needs to rely on insulator strings to achieve electrical isolation from the tower and on a series of fittings to achieve reliable mechanical connection. Based on the actual mechanical load and electrical insulation requirements transmitted by the conductor, a complete, compliant and safe set of insulator and fitting components is automatically assembled for each suspension point. The insulator and fitting assembly chain describes the type, specifications and connection sequence of all connecting parts from the tower crossarm to the conductor end.

[0131] Specific implementation process: Extracting design control loads: For each suspension point in the tower layout scheme, for example, phase B of tower 5, the system queries the set of conductor mechanical parameters to find the maximum value of the comprehensive tension of the conductor acting at that point under all design conditions. This maximum value is the control basis for mechanical strength design.

[0132] Determine mechanical and electrical requirements:

[0133] Mechanical requirements: Multiply the maximum comprehensive tension mentioned above by the safety factor specified in the standard to obtain the rated mechanical load that the insulator string at the suspension point needs to bear. For example, if the maximum tension is 10 tons and the safety factor is 2.5, then an insulator with a rated mechanical failure load of not less than 25 tons should be selected.

[0134] Electrical requirements: Based on the voltage level of the line, the altitude of the location, and the environmental pollution level, consult the insulation design code to calculate the minimum creepage distance or minimum number of insulator discs required for the string of insulators. A 220kV line in a Class III pollution area may require at least 16 standard insulator discs.

[0135] Joint search for matching insulators: The calculated rated mechanical load and insulation requirements, number of insulators or structural height are combined into a joint search condition. The system uses this condition to search the insulator and fitting standard library, selecting insulator models that simultaneously meet the mechanical strength and insulation length requirements. Each insulator in the standard library is marked with its rated mechanical breaking load and structural height.

[0136] Automatic Association and Logical Assembly of Fittings: After selecting the insulator model, the system automatically associates and selects the complete set of matching fittings from the standard library according to the standard assembly drawing or design rules. This forms a logical assembly chain, the sequence of which typically includes:

[0137] Tower end connection hardware: such as U-shaped hanging rings and ball-head hanging rings, used to connect to the hanging holes on the tower body.

[0138] Insulator string body: The selected type of insulator, which may be a disc suspension insulator or a composite insulator.

[0139] Conductor end fittings: such as bowl-shaped hangers and suspension clamps for suspension strings, or tension clamps for tension strings.

[0140] Protective fittings: such as equalizing rings to improve voltage distribution, and vibration dampers to suppress light wind vibrations, etc., should be added according to the rules.

[0141] Output Assembly Chain: The system generates an ordered list of components for each suspension point, i.e., the insulator hardware assembly chain. This chain not only lists all components but also implicitly includes their physical connections and interface compatibility.

[0142] In traditional design, the selection of insulator strings and fittings is often based on typical designs or experience, which may not accurately match the actual stress at a specific tower location and easily lead to the omission of small components. This step achieves customized solutions through automated matching and logical assembly based on precise mechanical calculations and electrical rules. For example, for a tower location in a windy mountain area with particularly high tension, the system will automatically match insulators with higher tonnage and reinforced fittings; for tower locations near heavily polluted industrial areas, it will automatically increase the number of insulator discs or select anti-pollution insulators. This dynamic configuration method, based on real-demand requirements, is more scientific, safer, and more economical than static, standardized configuration manuals. The generated assembly chain is a computable logical model, providing the possibility for the next step of constructing the entire line into a complete mechanical analysis network.

[0143] Step S600: Couple the set of mechanical parameters of the conductor with the insulator hardware assembly chain to construct a static analysis network. Use the static analysis network to calculate the entire load transfer path and the internal forces of the components, and generate a set of internal force transfer relationships.

[0144] The preceding steps calculated the forces acting on the conductor and selected the connecting components. However, the conductor, insulator, hardware, and tower form an interactive, integrated mechanical system. The purpose of this step is to digitally abstract this system, construct a complete static analysis network model, and perform simulation calculations to accurately determine how the load is transmitted from the conductor, through each hardware and insulator, to the tower foundation, and to obtain the actual internal forces of each intermediate connecting component. This is the ultimate mechanical verification for achieving accurate material selection and validation.

[0145] Specific implementation process:

[0146] Network topology abstraction: Based on the geometric position of the tower layout scheme and the connection relationship of the insulator hardware assembly chain, the system abstracts the physical system into a network topology diagram composed of nodes and units.

[0147] Nodes: These represent key locations such as pole hanging points, insulator string connection points, and hardware connection points.

[0148] Unit: Represents a load-bearing component, and is divided into several categories: cable unit, which simulates conductors and ground wires and only bears axial tensile force; rod unit, which simulates insulator strings and only bears axial tensile force; rigid connection unit or beam unit, which simulates hardware such as connecting plates and hanging rings and may bear tension, compression, bending and shear.

[0149] Attribute assignment: Assigning actual mechanical properties to each unit in the network.

[0150] From the set of conductor mechanical parameters, the loads and end tensions of the conductor under each working condition are applied to the corresponding cable elements in an equivalent manner.

[0151] Obtain the geometric dimensions and material properties, such as the modulus of elasticity, of each fitting unit from the insulator and fitting standard library, and calculate its stiffness, such as axial stiffness and bending stiffness.

[0152] Boundary conditions are applied: the connection between the tower and the foundation is set as a fixed constraint with zero displacement.

[0153] Overall static equilibrium solution: For the static analysis network constructed above with loads, properties, and constraints, the finite element method or rigid body statics method is applied to solve the large system of equations, and the static equilibrium state of the entire network is calculated:

[0154] The displacement of each node is usually very small, and the internal forces of each unit are: the tension of the conductor and ground wire, the tension of the insulator string, and the tension, compression, shear force or bending moment borne by each fitting, such as the U-ring and the connecting plate.

[0155] Clear visualization of load transfer paths: It can be seen, for example, how the wind load on the conductor is converted into the gripping force of the suspension clamp, which is then transferred to the hanging ring through the tension of the insulator string, and finally acts on the crossarm of the tower.

[0156] Generate a set of internal force transmission relationships: Extract, organize, and associate the internal force results of each component in the network, especially each hardware, under various working conditions obtained from the above solution to form a set of internal force transmission relationships. This set clearly records which hardware, under what conditions, and how much force it bears.

[0157] This is one of the core innovations of this invention. Traditional designs typically only verify the strength of conductors and insulator strings, often neglecting to accurately calculate the stress on numerous small fittings, such as hanging rings and connecting plates, assuming their strength is sufficient, which poses a safety hazard. This step, by constructing a static analysis network covering all stressed components of the entire line, achieves a globally refined simulation of the overall mechanical state. It can discover weaknesses that are difficult to detect using traditional methods. For example, a connecting plate linking two insulator strings may bear a huge bending moment under asymmetrical loads; a jumper support fitting experiences complex stress under specific wind conditions. Through this simulation, the selection of each fitting can be re-verified or re-matched based on the most unfavorable internal forces obtained from the simulation, ensuring the safety and reliability of every link in the force flow path from conductor to foundation. This marks a new stage in the mechanical design of railway lines, moving from verification of key components to refined protection of the entire path, greatly enhancing the inherent safety of the lines.

[0158] Step S700: Based on the set of internal force transmission relationships, combined with voltage level, number of circuits and environmental parameters, mark the engineering function attributes of each component to form a structured attribute set.

[0159] Having completed the aforementioned steps, the system already contains tens of thousands of components, including poles, conductors, insulators, and various hardware. The purpose of this step is to imbue these anonymous components with rich engineering semantics, transforming them from geometric and mechanical objects into engineering objects that embody design intent. This is a prerequisite for realizing intelligent material statistics based on function.

[0160] Specific implementation process: Read basic information and internal force data of components: The system traverses all components, reads their basic information, type, model, tower position or span, and obtains the key internal force types and values ​​of the component from the set of internal force transmission relationships, such as main tension, compression, and bending.

[0161] Rule-based automatic attribute labeling: The system automatically assigns multi-dimensional labels to each component based on a series of predefined business rules.

[0162] Mechanical functional attributes: marked according to internal force characteristics, such as main load-bearing cables, tension adjustment connectors, support fixings, load distribution components, and vibration damping and energy dissipation components.

[0163] Electrical functional attributes: According to the voltage level and location markings, such as providing main insulation, providing phase-to-phase insulation equipotential bonding, and preventing corona discharge.

[0164] Environmental adaptability attributes: According to the engineering environmental parameters, such as suitable for heavy icing areas, suitable for highly corrosive environments, and suitable for high altitudes.

[0165] Location and attribution: Marked according to information such as the number of circuits, such as belonging to phase A of the first circuit, belonging to the ground wire, or located on the jumper side of the tension tower.

[0166] Generate a set of structured attributes: Each component is assigned a unique identifier and all its engineering function attributes are associated with that identifier, forming a database with multiple attribute fields indexed by the component identifier, i.e., a set of structured attributes. A U-shaped hanging ring of model X is no longer just a part, but is described as a key load-bearing connection hardware located on tension tower No. 5, phase B of the first circuit, mainly responsible for the transmission of conductor tension, and suitable for high wind environments.

[0167] Step S800: Based on the attributes in the structured attribute set, cluster the components according to the functional mapping rules to generate the circuit functional unit division result.

[0168] Specific implementation process: Attribute reading and rule definition: The system reads the attributes of all components in the structured attribute set and loads predefined function mapping rules. These rules are if-then logical statements, for example:

[0169] "If the component type belongs to the main tower material, diagonal material, or transverse diaphragm and belongs to the same tower location, then classify it into the tower location number tower structure unit."

[0170] "If the component attributes include bearing the main insulation and being connected to the same suspension point, then it is classified into the same insulator string unit."

[0171] "If the component type is conductor or ground and it is located within the same span, then it is classified into the same conductor or ground unit."

[0172] "If the mechanical function of a component is vibration damping and energy dissipation and it is installed on a certain section of conductor or ground wire, then it is assigned to the corresponding conductor or ground wire unit."

[0173] Clustering algorithm execution: The system scans all components according to the above rules. For each component, it determines which rules its attributes meet and then adds it to the functional unit logic group corresponding to the rule.

[0174] Output partitioning results: After clustering, the system generates the functional unit partitioning results of the line. This result can be in the form of a list or a relationship diagram, clearly showing which functional units constitute the entire line, such as: 20 tower structural units, 80 insulator string units, several conductor units and ground wire units, and which functional unit each component belongs to.

[0175] Derivation of the beneficial effects of step S800: Traditional material statistics require manual counting of parts and manual classification, which is prone to repetition or omission. Through rule-based automated clustering, intelligent modular organization of engineering components is realized. It summarizes thousands of parts into dozens of functional modules with clear engineering significance, greatly reducing the complexity of management and making the presentation of the material list more in line with the cognitive habits of engineers, thus preparing for the generation of a material list with a clear structure and distinct hierarchy.

[0176] Step S900: Based on the functional unit division results of the line, analyze the component connection and force flow relationship within and between each functional unit, and construct a material action path topology diagram.

[0177] The functional unit division grouped the components vertically. This step, on the other hand, aims to clarify horizontally how these groups, as well as the components within each group, are physically connected and how mechanical forces are transmitted. The goal is to construct a global network model that describes the physical connections and mechanical interactions of the entire circuit system, i.e., a material action path topology diagram.

[0178] Specific implementation process:

[0179] Relationship Analysis: Based on the line functional unit division results and lower-level component connection information, derived from insulator hardware assembly chains and tower structures, the system performs in-depth analysis:

[0180] Intra-unit relationships: Analyze the connection sequence of components within each functional unit. For example, analyze the series connection of an insulator string unit from U-ring to ball head to insulator to cup head to clamp.

[0181] Inter-unit relationships: Analyzing the connections between different functional units. For example:

[0182] The endpoints of the conductor unit are connected to the lower clamp of the insulator string unit.

[0183] The upper end of the insulator string unit is connected to a hanging point of the tower structure unit.

[0184] The direction of the force flow load is from the conductor unit to the insulator string unit, and then to the tower structure unit.

[0185] Topology graph construction: All the connection relationships and force transmission relationships extracted above are combined with all component nodes and functional unit nodes to construct a complex graph data structure. In this graph, nodes can be the smallest components or functional units; edges represent connections or interactions. This graph is the material action path topology graph, which formally and comprehensively depicts the system essence of who is connected to whom and where the force is transmitted.

[0186] Derivation of the beneficial effects of step S900: The topology diagram is a digital mirror of the system's physical architecture. It transforms the wiring system in the computer from a jumble of scattered data tables into a network model with a clear structure. This diagram is the cornerstone for achieving accurate material statistics because the statistical process essentially involves traversing and counting all nodes (components) in this topology diagram. It ensures the completeness of the statistics, as the diagram contains all nodes and their accuracy. The connection relationships define the assembly relationships, avoiding redundant calculations. This diagram can also be used for design verification, checking the integrity of connections, construction simulation, generating assembly sequences, and operation and maintenance management, as well as locating specific components.

[0187] Step S1000: By parsing the material action path topology diagram, counting all components and their quantities, and matching them with the material coding library, a structured power transmission line engineering material table is generated.

[0188] This is the final output stage of the entire automated process, and its purpose is to generate an authoritative engineering materials list that can be directly used for procurement, construction, and management, based on the accurate, semantic, and structured data generated from all the preceding steps.

[0189] The specific implementation process involves the system performing a depth-first or breadth-first traversal of the material action path topology graph, visiting each leaf node representing the smallest physical component. During the traversal, the system identifies and categorizes components based on key characteristics such as type, model, and specifications, and automatically counts their occurrences. For example, it identifies all suspension clamp nodes of model ABC and counts their frequency of occurrence.

[0190] Linking Enterprise Material Master Data: For each type of component identified in the statistics, the characteristic information of the same model and specifications is aggregated and matched with the enterprise's standard material code library. The material code library is the core master data of the enterprise resource planning system, which includes information such as the unique code of the material, standard name, technical specifications, material, unit of measurement, and standard drawing number. Through automatic matching, the correct enterprise material code is assigned to each requirement item.

[0191] Generate a structured bill of materials: The system organizes the matching results into a structured table or document, namely, a bill of materials for power transmission line projects. This table typically has a clear hierarchy:

[0192] The chapters are divided according to functional units, such as the tower structure, insulators and hardware, conductors and grounding wires, and auxiliary facilities.

[0193] Each chapter includes a detailed list: listing the material code, material name, specifications, unit, quantity, reference weight, tower location or span, and remarks.

[0194] Automatic summary: Automatically calculates summary information such as the total weight and quantity of materials for each chapter and the entire line.

[0195] Output and publishing: The generated engineering material list can be output in multiple formats and can be directly published to the enterprise's project management system or procurement system.

[0196] Through the aforementioned nine progressive and interconnected automated processes, this method constructs a complete, closed, data-driven digital pipeline from the original design intent to the final bill of materials. In this pipeline, the existence and quantity of any final material item originate from the spatial constraints determined upstream, the optimized tower location, precise geometric boundaries, mechanical simulation based on physical laws, component matching and assembly according to rules and simulation, the assigned engineering semantics (S700), logical clustering, and relational modeling. The generation of the bill of materials is no longer a post-processing or statistical step in the design, but rather the inevitable endpoint and natural presentation of the entire digital design logic.

[0197] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that this application is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this application. Various changes and modifications can be made to this application without departing from the spirit and scope thereof, and all such changes and modifications fall within the scope of this application as claimed. The scope of protection of this application is defined by the appended claims and their equivalents.

Claims

1. A method for automatically generating a material list for a power transmission line project, characterized in that, The method includes: Acquire information on the start and end points, turning points, and crossing sections of the line, and generate a three-dimensional spatial coordinate sequence of the line; Based on the coordinate sequence, the coordinates of each tower pile position are determined by the span allocation algorithm, and the structural type is matched from the tower catalog library according to the terrain and load conditions at each pile position to generate a tower layout scheme. Based on the tower layout scheme, query the tower structure database, extract the coordinates and elevations of the conductor suspension points of each tower, and generate a set of spatial parameters for the suspension points. Based on the set of spatial parameters of the suspension point, the spatial shape, tension and sag data of the conductor and the ground wire are calculated by solving the catenary equation or performing finite element simulation, and a set of mechanical parameters of the conductor is generated. Based on the conductor tension vector at each suspension point in the set of conductor mechanical parameters, and combined with the safety factor and insulation rules, insulators and fittings are matched and assembled from the insulator and fitting standard library to generate an insulator and fitting assembly chain. Couple the set of mechanical parameters of the conductor with the insulator hardware assembly chain to construct a static analysis network. Use the static analysis network to calculate the entire load transfer path and the internal forces of the components, and generate a set of internal force transfer relationships. Based on the set of internal force transmission relationships, combined with voltage level, number of circuits and environmental parameters, the engineering function attributes of each component are labeled to form a set of structured attributes; Based on the attributes in the structured attribute set, the components are clustered according to the functional mapping rules to generate the circuit functional unit division results; Based on the functional unit division results of the circuit, the component connections and force flow transmission relationships within and between each functional unit are analyzed, and then a material action path topology diagram is constructed. By analyzing the material action path topology diagram, counting all components and their quantities, and matching them with the material coding library, a structured material table for power transmission line engineering is generated.

2. The method according to claim 1, characterized in that, The process of acquiring information on the start and end points, turning points, and crossed sections of the line, and generating a three-dimensional coordinate sequence of the line space, includes: Input the coordinates of the starting point, ending point, and all turning points of the route; Arrange the starting point coordinates, ending point coordinates, and corner point coordinates according to the actual path order to generate an ordered path node set; Calculate the planar distance and azimuth angle between adjacent nodes in the ordered path node set to generate a path segmentation parameter set describing the geometric orientation of the path; Based on the complete path geometry defined by the ordered path node set and the path segmentation parameter set, buffer analysis is performed along the path in the digital geographic information system. Through the buffer analysis, the spatial range of important obstacles in the path corridor is identified and obtained, and a spatial information set of the cross-section is generated. The ordered path node set, path segment parameter set, and cross-section spatial information set are fused together to form a three-dimensional coordinate sequence of the line space, including path geometry and spatial constraints.

3. The method according to claim 2, characterized in that, The step of determining the coordinates of each tower pile position based on the coordinate sequence and the span allocation algorithm includes: Read the ordered set of path nodes and the set of path segmentation parameters from the three-dimensional coordinate sequence of the line space; Using the ordered path node set and path segmentation parameter set as input, and according to the preset standard span range, the span is divided within the straight line segment formed by adjacent ordered path nodes to generate an initial pile point set. Using the initial pile point set and the spatial information set of the crossing section in the three-dimensional coordinate sequence of the line space as input, the initial pile point set falling into the crossing section is adjusted to avoid it, and an adjusted pile point set is generated. Using the adjusted set of pile locations as input, longitudinal optimization is performed based on terrain elevation data to generate an optimized set of pile location coordinates; Output the optimized pile position coordinate set as the pile position coordinates of each tower, which includes the three-dimensional position information of all towers.

4. The method according to claim 3, characterized in that, The process of matching structural types from the tower catalog based on the terrain and load conditions at each pile location to generate a tower layout scheme includes: Using the coordinates of each tower pile location as input, the elevation, slope and geomorphic feature data corresponding to each pile location are extracted from the digital elevation model to generate a terrain feature dataset. In the design stage of the coordinates of each tower pile location, the benchmark wind speed, ice thickness and temperature parameters on which the engineering line design is based are loaded to generate a meteorological load parameter set. The terrain feature dataset and the meteorological load parameter set are associated to form a joint query condition; Using the joint query conditions as input, a matching search is performed for each pile location in the predefined tower catalog library; Based on the matching search results, the system outputs suggested tower models, nominal heights, and foundation configurations that meet the requirements for each pile location. Summarize all tower location configuration suggestions for all pile locations and generate a tower layout scheme that includes tower type, tower height, pile location coordinates, and foundation type.

5. The method according to claim 4, characterized in that, The process involves querying the tower structure database based on the tower layout scheme, extracting the coordinates and elevations of the conductor suspension points for each tower, and generating a set of spatial parameters for the suspension points, including: Using the tower type and nominal height data included in the tower layout scheme as input, query the tower structure database to obtain the head size and hanging point layout parameters of the corresponding tower type; Using the obtained hanging point layout parameters and the coordinates and elevations of each tower pile position in the tower layout scheme as input, calculate the actual three-dimensional spatial coordinates of each phase conductor and ground wire hanging point on each tower. Based on the calculated actual three-dimensional spatial coordinates of all tower hanging points, the corresponding phase hanging points of adjacent towers are logically paired according to the direction of line advance to form a span unit describing the spatial span of each conductor and ground wire. The coordinates, elevations, and span information of the starting and ending points of all span units are collected to construct a set of spatial parameters for suspension points used in subsequent mechanical calculations.

6. The method according to claim 1, characterized in that, Based on the set of spatial parameters of the suspension point, the spatial shape, tension, and sag data of the conductor and ground wire are calculated by solving the catenary equation or performing finite element simulation, generating a set of conductor mechanical parameters, including: The coordinates and elevation data of each suspension point in the set of spatial parameters of the suspension points are used as the calculation boundary conditions; Based on the calculated boundary conditions, and by inputting the physical property parameters of the conductor and ground wire, as well as the wind load and ice load parameters used in the design, several typical calculation cases are selected. According to the engineering design specifications, the typical calculation conditions are determined to include high temperature conditions, low temperature conditions, annual average temperature conditions, strong wind conditions, and icing conditions. For each selected typical calculation condition, the catenary equations that satisfy the calculation boundary conditions and physical states are solved by iterative method. By solving the catenary equation, the spatial shape curves of the conductor and ground wire under this working condition, the horizontal and vertical tensions at each point, and the sag data of key control points are calculated. The spatial morphology curves, horizontal and vertical tensions at each point, and sag data at key control points calculated under each working condition are structured according to span number and phase identifier to form a set of conductor mechanical parameters.

7. The method according to claim 6, characterized in that, The method involves matching and assembling insulators and fittings from the insulator and fitting standard library based on the conductor tension vector at each suspension point in the set of conductor mechanical parameters, combined with safety factors and insulation rules, to generate an insulator and fitting assembly chain, including: Extract the comprehensive tension data of the conductor at the suspension point under each working condition from the set of conductor mechanical parameters; Based on the extracted comprehensive tension data and the preset design safety factor, the rated mechanical failure load that the insulator string needs to match is calculated. According to the insulation rules determined by the line voltage level, altitude and pollution level, the insulation distance or number of discs that the insulator string needs to meet is calculated. The calculated rated mechanical failure load is combined with the insulation distance or number of sheets parameter to form a joint matching condition; Using the aforementioned joint matching conditions as an index, the applicable insulator model is queried and selected in the insulator and fitting standard library; Based on the selected insulator model, associate and select matching connecting plates, hanging rings, wire clamps, and protective fittings. Logically connect the insulator and the fittings in the actual physical connection sequence to generate an insulator fitting assembly chain.

8. The method according to claim 1, characterized in that, The set of mechanical parameters of the conductor is coupled with the insulator hardware assembly chain to construct a static analysis network. This static analysis network is used to calculate the entire load transfer path and the internal forces of the components, generating a set of internal force transfer relationships, including: Based on the tower layout scheme and the insulator hardware assembly chain, an initial network topology is constructed, including tower nodes, conductor and ground wire units, and connection units. The conductor and ground wire load data recorded in the set of conductor mechanical parameters are assigned to the corresponding conductor and ground wire units in the initial network topology to generate an intermediate network structure with applied load. Based on the intermediate network structure and according to the mechanical properties of the components defined in the insulator hardware assembly chain, stiffness parameters are configured for all connecting units to form a computable network including complete property parameters. Static equilibrium calculations were performed on the computable network under all design conditions to obtain the internal forces, bending moments and load transfer paths of each element. Based on the internal forces, bending moments, and load transfer path results, a complete path describing the load transfer from the conductor / ground wire unit through the connection unit to the tower node, and a set of internal force transfer relationships for each component are generated.

9. The method according to claim 8, characterized in that, Based on the set of internal force transmission relationships, combined with voltage level, number of circuits, and environmental parameters, engineering action attributes are labeled for each component, forming a structured attribute set, including: Read the set of internal force transmission relationships to obtain the internal force types and numerical data of each component; Based on the internal force types and numerical data, a description of the mechanical functional attributes of each component is generated. Based on the description of the mechanical functional attributes of each component, and in conjunction with the voltage level, number of circuits and environmental parameters, the corresponding engineering function attributes are uniformly labeled for the components of the corresponding category; All engineering function attributes obtained for each component are summarized and encoded, and a set of structured attributes indexed by the component's unique identifier is output.

10. The method according to claim 9, characterized in that, The step of clustering components according to functional mapping rules based on the attributes in the structured attribute set to generate circuit functional unit partitioning results includes: Read the structured attribute set to obtain a complete attribute description of all components; Based on the function mapping rules, the complete attribute description is parsed to determine one or more functional unit categories corresponding to each component; Based on the functional unit categories obtained from the analysis, components with the same category identifier are grouped and aggregated. Based on the grouping and aggregation results, specific functional unit instances are formed, and a list recording the correspondence between all components and their respective functional unit instances is output as the result of line functional unit division.

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