A Smart Calculation Method and System for Overhead Line Construction Tension Based on GIM Model

Abstract

This invention proposes an intelligent calculation method and system for overhead power line construction tension based on a GIM model, relating to the field of power grid construction technology. The method includes: parsing the target GIM model using an automatic extraction algorithm to obtain parameter information data corresponding to the target GIM model; collecting multi-source environmental data from the construction area, fusing the parameter information data with the multi-source environmental data using a fusion algorithm to generate a working condition data object, and obtaining key construction parameters based on a construction parameter generation algorithm and the working condition data object; calculating safety verification data corresponding to the target GIM model based on a safety assessment algorithm and the key construction parameters; and integrating and structuring the key construction parameters and safety verification data to generate a structured construction calculation report. This application helps improve the installation accuracy of overhead transmission lines.

Description

Technical Field

[0001] This invention relates to the field of power grid construction technology, and in particular to an intelligent calculation method and system for overhead line construction tension based on a GIM model. Background Technology

[0002] In the field of high-voltage overhead transmission line construction, accurate calculation of construction tension and conductor sag is a key technical aspect to ensure project safety and quality. Currently, the industry generally adopts a traditional calculation method based on a combination of two-dimensional drawings and manual experience. This method requires technicians to manually extract basic parameters such as conductor type, continuous span, and suspension point height difference from the design drawings, and then perform mechanical estimation by combining sag tension tables or empirical formulas.

[0003] Chinese patent CN117371949B discloses a method and system for monitoring the safety of transmission line construction based on a 3D visualization model. The method includes: acquiring GIM models of the transmission line towers and 3D measurement data in a transmission line construction project; using a data fusion algorithm to fuse all 3D measurement data from multiple construction measurement schemes into a multi-source data fusion model to obtain a field 3D model; fusing the tower GIM model and the field 3D model to obtain a 3D visualization model; importing project construction plan data into the 3D visualization model; performing construction simulation of the transmission line construction project through the 3D visualization model, monitoring the construction simulation process, and generating safety risk information; if safety risk information is detected, identifying the relevant parties based on the project construction plan data and sending the safety risk information to the relevant parties. However, the above solution only focuses on the 3D visualization safety monitoring process and struggles to convert design parameters and real-time environmental data into corresponding tension control parameters, easily leading to insufficient installation accuracy of overhead transmission lines. Therefore, it is essential to provide a GIM model-based intelligent tension calculation method and system for overhead line construction to improve the installation accuracy of overhead transmission lines. Summary of the Invention

[0004] In view of this, the present invention proposes an intelligent calculation method and system for overhead line construction tension based on GIM model.

[0005] This invention provides an intelligent calculation method for overhead line construction tension based on a GIM model, the method comprising: The target GIM model is parsed based on an automatic extraction algorithm to obtain the parameter information data corresponding to the target GIM model; Collect multi-source environmental data of the construction area, and fuse the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object. Based on the construction parameter generation algorithm and the working condition data object, obtain key construction parameters. Based on the safety assessment algorithm and the key construction parameters, calculate the safety verification data corresponding to the target GIM model; The key construction parameters and safety verification data are integrated and structured to generate a structured construction calculation report.

[0006] Based on the above technical solutions, preferably, the step of parsing the target GIM model using an automatic extraction algorithm to obtain parameter information data corresponding to the target GIM model specifically includes: Collect the internal data structure of the GIM digitized engineering files in the target GIM model, and construct an object relationship graph and a unified data dictionary corresponding to the internal data structure; The specific attribute parameters of the conductor objects, hardware components, and tower models in the object relationship graph are input into a preset data encapsulation algorithm to obtain a set of structured parameters. The structured parameter set is validated to output the parameter information data corresponding to the target GIM model.

[0007] Based on the above technical solutions, preferably, the step of fusing the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object specifically includes: Based on the spatial coordinate information in the target GIM model, the environmental monitoring points and spans within the construction area are spatially correlated to assign a corresponding influence weight to each environmental monitoring point. For multi-source environmental data within any span coverage area, the influence weights corresponding to the environmental monitoring points within the span are fused with the multi-source environmental data to obtain the fused environmental parameters corresponding to the span. The fused environmental parameters are combined and encapsulated with the conductor physical parameters, span length, and hanging point elevation data in the parameter information data to construct a working condition data object corresponding to the span.

[0008] More preferably, the acquisition of key construction parameters based on the construction parameter generation algorithm and the working condition data object specifically includes: Based on the physical parameters of the conductor, span length, elevation difference of the suspension point, and integrated environmental parameters in the working condition data object, a conductor mechanical model based on catenary theory is constructed. Based on the aforementioned conductor mechanical model, the elastic properties of the conductor material, and temperature change factors, a state constraint relationship with the influence of conductor thermal expansion and elastic elongation is constructed. The working condition data object is used as the input of the conductor mechanical model, and the conductor mechanical model is solved by a numerical iterative solution algorithm to obtain the solution results and model parameters corresponding to the conductor mechanical model; When the model parameters meet the convergence condition, the laying tension, maximum traction force and conductor sag value corresponding to each span are calculated based on the solution results of the conductor mechanical model, and the laying tension, maximum traction force and conductor sag value are output as key construction parameters.

[0009] More preferably, the step of calculating the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and the key construction parameters specifically includes: Based on the key construction parameters and the target GIM model, the envelope angle corresponding to the contact area between the trolley and the conductor is calculated, and the envelope angle is compared with a preset envelope angle threshold to obtain the envelope angle verification result. Based on the key construction parameters and the target GIM model, the vertical span at the shared tower is calculated, and the vertical span is compared with the standard vertical span to obtain the upward verification result. Based on the key construction parameters and the target GIM model, the tension safety factor is calculated, and the tension safety factor is compared with the preset safety factor threshold to obtain the safety factor verification result; The envelope angle verification result, the upward verification result, and the safety factor verification result are integrated to generate the safety verification data corresponding to the target GIM model.

[0010] More preferably, after calculating the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and the key construction parameters, the method further includes: The key construction parameters are visualized in three dimensions using a dynamic rendering algorithm to generate three-dimensional scene data with parameter labels.

[0011] More preferably, the process of integrating and structuring the key construction parameters and the safety verification data to generate a structured construction calculation report specifically includes: Based on the identification information of each tower and each span in the target GIM model, the key construction parameters and the safety verification data are indexed and associated. The string tension, maximum traction force, conductor sag, envelope angle verification results, upward verification results and safety factor verification results corresponding to each tower and each span are respectively bound to the corresponding model objects in the target GIM model. After the key construction parameters and safety verification data are associated, they are classified and organized. Project overview information, working condition parameter information, tension and sag calculation results information, and safety assessment results information are collected into the corresponding structured data segments to form a structured construction calculation report dataset.

[0012] A second aspect of this application provides an intelligent calculation system for overhead line construction tension based on a GIM model. The intelligent calculation system includes a model parsing module, a data processing module, and a result reporting module. The model parsing module is used to parse the target GIM model based on an automatic extraction algorithm to obtain the parameter information data corresponding to the target GIM model; The data processing module is used to collect multi-source environmental data of the construction area, and to fuse the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object. Based on the construction parameter generation algorithm and the working condition data object, key construction parameters are obtained. Based on the safety assessment algorithm and the key construction parameters, the safety verification data corresponding to the target GIM model is calculated. The results reporting module is used to integrate and structure the key construction parameters and the safety verification data to generate a structured construction calculation report.

[0013] A third aspect of this application provides an electronic device including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory.

[0014] In a fourth aspect of this application, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, the computer program being executed by a processor to implement the steps of an intelligent calculation method for overhead line construction tension based on a GIM model.

[0015] The intelligent calculation method and system for overhead line construction tension based on GIM model provided by this invention has the following advantages over existing technologies: (1) By parsing the target GIM model, the corresponding parameter information is obtained and fused with multi-source environmental data. Compared with the traditional calculation method that relies only on empirical values ​​or single parameters, the calculation under multi-dimensional parameter constraints significantly improves the accuracy and stability of tension calculation results. Furthermore, the automatic extraction algorithm is used to parse the GIM model, reducing the error and workload caused by manual reading and manual input of model parameters. The construction parameter generation algorithm and safety assessment algorithm are used to automatically output key construction parameters and safety verification data, realizing the full-process automation from data collection, parameter generation to safety verification. At the same time, by conducting safety assessment on key construction parameters, the safety verification data corresponding to the target GIM model is obtained and compared with the rated safety verification data, which can detect potential safety hazards in tension settings in advance. Multi-source environmental data is uniformly processed through the fusion algorithm, so that the generated working condition data object can cover a variety of complex application scenarios. In areas with large fluctuations in environmental parameters or complex construction conditions, the controllability and consistency of tension calculation results can still be maintained, thereby improving the installation accuracy of overhead transmission lines.

[0016] (2) By collecting the internal data structure of GIM digital engineering files and constructing an object relationship graph and a unified data dictionary, systematic modeling of elements such as conductor objects, hardware components, and tower models can be achieved, avoiding parameter omissions and misunderstandings caused by manual reading. Using a preset data encapsulation algorithm, multi-source and heterogeneous model attribute parameters are transformed into a structured parameter set in a unified format, eliminating format differences between different design files and different modelers. Data verification of the structured parameter set can promptly detect and eliminate abnormal values, missing values, or logically conflicting data, ensuring the semantic and logical consistency and accuracy of the output parameter information data. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating an intelligent calculation method for overhead line construction tension based on a GIM model provided by this invention; Figure 2 This is a schematic diagram of the functional architecture layering provided by the present invention; Figure 3 This is a schematic diagram of the intelligent tension calculation system for overhead line construction provided by the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention.

[0019] Explanation of reference numerals in the attached diagram: 1. Intelligent calculation system for tension during overhead line construction; 11. Model analysis module; 12. Data processing module; 13. Result reporting module; 2. Electronic equipment; 21. Processor; 22. Communication bus; 23. User interface; 24. Network interface; 25. Memory. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] This invention discloses an intelligent calculation method for overhead line construction tension based on a GIM model, with reference to... Figure 1 The steps of this method include S1 to S4.

[0022] Step S1: The target GIM model is parsed based on an automatic extraction algorithm to obtain the parameter information data corresponding to the target GIM model.

[0023] This step also includes steps S11 to S13.

[0024] Step S11: Collect the internal data structure of the GIM digitized engineering files in the target GIM model, and construct an object relationship graph and a unified data dictionary corresponding to the internal data structure.

[0025] In this step, the GIM digital engineering file is loaded, and the internal data structure of the project is obtained through the decompression module; based on the GIM standard specification, a complete object relationship graph including the engineering level, system level, equipment level and component level is constructed; a unified data dictionary is established to record the unique identifier, type definition, attribute association and spatial reference relationship of each object.

[0026] The correspondence between nodes and edges in the object relationship graph corresponds to the four core levels defined in the GIM standard specification, and its specific entities can be represented as follows: Engineering level: Project / Section; System level: Pole level, a specific tower location and its corresponding large or small side and its surrounding objects; Equipment level: Model level, such as towers, hardware strings, foundations, and conductor objects; Component level: Specific objects, such as tower heads, tower bodies, tower legs, hardware, insulators, steel strands, spacers, and vibration dampers.

[0027] Step S12: Input the specific attribute parameters of the conductor objects, hardware components and tower models in the object relationship graph into the preset data encapsulation algorithm to obtain a structured parameter set.

[0028] In this step, based on the object relationship graph, a dedicated extraction engine is used to extract the physical property parameters of the conductor objects from their attribute files. These parameters include cross-sectional area, outer diameter, elastic modulus, coefficient of linear expansion, and rated breaking force. The dedicated extraction engine is used to parse the data hierarchy and reference relationships within the GIM model file, and includes the following steps:

[0029] Load and parse external models such as STL and IFC; construct physical models in parallel based on the parametric description of the geometric model and the spatial transformation matrix; reconstruct the entire 3D model through hierarchy and reference relationships, perform a 1:1 restoration, and write the fam attribute information of the model object during the reconstruction process; finally, generate a lightweight 3D model and related parameters.

[0030] After a dedicated extraction engine parses external models such as STL and IFC, the precise spatial coordinates of the hanging points are obtained through a spatial coordinate transformation calculation module based on the tower geometry model and transformation matrix. The type, specifications, material properties, and connection parameters of the hardware components are then retrieved from their attributes.

[0031] Specifically, it loads and parses external models such as STL and IFC, and constructs physical models in parallel based on the parameterized description of the geometric model and the spatial transformation matrix, including: After parsing external models such as STL and IFC, the dedicated extraction engine generates a unique identifier for each parsed geometric entity (such as an insulator or a conductor segment). This identifier is then matched and bound to predefined standard objects within the target GIM model's object system, such as "conductor JL / G1A-400 / 35" and "disc suspension insulator." The matching is based on a pre-built semantic rule library.

[0032] For example, when parsing an IFC file, if the IFC type of a component is identified as a cable conduit, it is directly mapped to a "conduit" object in the GIM. For an STL file without semantic meaning, its shape, size, and position in the entire assembly are used to infer which component in the target GIM model it corresponds to. Ultimately, each external geometry finds a unique GIM logical object in the target GIM model as its "identity".

[0033] After mapping, the system contains two types of models: physical models and GIM objects. The physical model, built by the engine, is the entity with position and shape that is ultimately seen in the 3D scene. It is only responsible for geometric rendering and spatial positioning. GIM objects are logical entities existing in the data dictionary and relational graph. GIM objects are responsible for storing all engineering meanings and business attributes, such as the material, specifications, and mechanical parameters of the conductors.

[0034] A single GIM object (such as a vibration damper of a certain model) can derive multiple physical models (installed on many conductor spans), but conversely, a specific physical model can only belong to one GIM object, such as a vibration damper on conductor B of tower A. The two are associated through a unique identifier.

[0035] Once the mapping relationship is established, data begins to flow, following these fixed rules: Attributes extracted from external models to GIM objects: The engine extracts the parameters that can be found in the external model, such as the dimensions defined in the IFC and the model number implied in the STL file name, and fills them into the attribute bar of the corresponding GIM object.

[0036] GIM object attribute injection into the physical model: When assembling the entire 3D scene based on the object relationship graph, the engine will reverse the process and write the complete attribute set (especially the fam attribute) of the GIM object into the corresponding physical model. In this way, a lightweight 3D model comes with all the business information.

[0037] Geometry is generated according to GIM rules: the precise position and orientation of the physical model in 3D space are not directly determined by the external model. The engine reads the spatial transformation matrix defined in the object relation graph of the GIM object, uses this matrix to calculate and place the geometry, and ensures that all components are assembled strictly according to GIM standards.

[0038] Furthermore, in the spatial coordinate transformation calculation, a local rectangular coordinate system with the geocentric coordinate system (ECEF) of the first tower as the origin is adopted. The specific process is as follows: First, the CGCS2000 geographic coordinates of all GIM objects are converted to geocentric and geofixed coordinates using standard formulas. Then, the ECEF coordinates of the first tower are used as a reference for zeroing and translation to establish a local computational space centered on the tower and with its axis parallel to the global ECEF coordinate system. Its coordinate origin is the precise geocentric position of the first tower, and the reference plane is the plane passing through this point and parallel to the ECEF coordinate axis. The actual vertical attitude of the model in the local area needs to be corrected using the ENU to ECEF rotation matrix.

[0039] Step S13: Perform data validation on the structured parameter set to output parameter information data corresponding to the target GIM model.

[0040] In this step, the extracted structured parameter set is reorganized and encapsulated according to the data specifications for overhead line calculations, generating a machine-readable structured parameter set. This reorganization and encapsulation utilizes industry-standard data processing functions and frameworks. Customized adaptations of function parameters were made for the business scenarios of overhead line calculations. For example, based on the parameter characteristics of conductors, attachment points, and hardware, the mapping rules, association logic, and verification threshold settings of data fields were adjusted to ensure that the output structured data accurately matches the calculation requirements of subsequent overhead line safety assessments.

[0041] The verification process includes parameter integrity verification, parameter value validity verification, object attribute logical consistency verification, spatial relationship and geometric consistency verification, and cross-object association integrity verification. Parameter integrity verification involves checking the integrity of fields in the encapsulated structured data set. Based on the parameter list required for overhead line calculations, essential fields for objects such as conductors, tower attachment points, and hardware components are verified to ensure that key physical parameters and spatial coordinate information are complete. When a missing parameter or a null value is detected, an anomaly is automatically marked and the subsequent calculation process is terminated.

[0042] Parameter value validity verification, after the integrity verification has passed, involves determining the validity of the numerical type and range of each parameter. This includes verifying the positive values ​​of physical quantities such as cross-sectional area, elastic modulus, and rated tensile force; verifying that material parameters such as the coefficient of linear expansion are within the allowable range for engineering applications; and checking the validity of spatial coordinate values. Parameters that do not meet the validity requirements will be recorded and output as data quality anomalies.

[0043] Object attribute logical consistency verification is based on the object relationship graph to check the consistency of parameter logical relationships within and between objects. It focuses on checking the matching relationship between conductor geometric parameters and material properties, as well as the compatibility between hardware specifications and conductor / attachment type, to prevent unreasonable parameter combinations from entering the calculation process.

[0044] Spatial relationship and geometric consistency verification is performed based on the spatial coordinates of the hanging points obtained through analysis, to verify the spatial geometric relationships within the span. This includes verifying the validity of the hanging points on both sides of the span, the rationality of the spatial distance between the hanging points, and whether the elevation difference meets the allowable range for the project, to prevent the failure of the catenary model construction due to spatial anomalies.

[0045] Cross-object association integrity verification addresses the multi-object relationships involved in overhead line calculations. The system verifies the association integrity between conductors, suspension points, towers, and hardware. When missing object references or broken associations are detected, the system automatically identifies the data as structurally abnormal and prevents it from participating in subsequent calculations.

[0046] In this embodiment, by collecting the internal data structure of GIM digital engineering files and constructing an object relationship graph and a unified data dictionary, systematic modeling of elements such as conductor objects, hardware components, and tower models is achieved. This avoids parameter omissions and misunderstandings caused by manual reading. Using a preset data encapsulation algorithm, multi-source and heterogeneous model attribute parameters are transformed into a structured parameter set in a unified format, eliminating format differences between different design files and different modelers. Data verification of the structured parameter set can promptly detect and eliminate outliers, missing values, or logically conflicting data, ensuring the semantic and logical consistency and accuracy of the output parameter information data.

[0047] Step S2: Collect multi-source environmental data of the construction area, and fuse the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object. Based on the construction parameter generation algorithm and the working condition data object, obtain key construction parameters.

[0048] In this step, corresponding environmental data monitoring equipment is deployed in the construction area, and the data is transmitted in real time to a preset data parsing platform for analysis to obtain real-time environmental data. Temperature sensors, wind speed sensors, and wind direction sensors are deployed at key locations in the transmission line construction area to collect environmental data required for line construction calculations in real time, forming on-site monitoring points to ensure continuous and stable acquisition of dynamic environmental parameters reflecting the actual construction conditions.

[0049] This step also includes steps S21 to S27.

[0050] Step S21: Based on the spatial coordinate information in the target GIM model, spatially associate each environmental monitoring point and span within the construction area to assign a corresponding influence weight to each environmental monitoring point.

[0051] In this step, environmental data needs to be integrated with the parameter information extracted from the GIM model to form a working condition input that can be directly used for overhead line mechanics calculations. First, the environmental data is quality-verified, and the continuity and reliability of temperature, wind speed, and wind direction over time are ensured through limit checks and short-time interpolation.

[0052] Based on the spatial coordinate information of the target GIM model, a correlation is established between each environmental monitoring point and the specific span of the line in the construction area. The layout of environmental monitoring points in the construction area follows the core principles of prioritizing key points, adapting to terrain, and gradient coverage. First, mandatory placement of monitoring points is required at key tension control points such as towers at both ends of the construction section, long-span towers, and important corner towers. Second, adaptive supplementation is needed based on the terrain undulations, micro-meteorological characteristics (such as wind gaps and valleys), and important crossing locations along the line corridor to ensure that the monitoring points can represent the actual environmental conditions of the spans they cover, and to avoid areas directly below the line or obstructed by large features, thus ensuring the spatial representativeness of the monitoring data.

[0053] The number and spacing of sensors are not fixed, but rather determined through dynamic planning based on project scale, terrain complexity, and meteorological risk. In flat hilly areas, a standard spacing of 3-5 kilometers is recommended to ensure the spatial relevance of environmental data. In mountainous areas with significant terrain undulations or pronounced micro-meteorological conditions, the spacing should be increased to 1-3 kilometers, or even shorter, to ensure that each interval has at least one monitoring point with an effective influence weight of no less than 0.3. Furthermore, for Level 1 risk operation sections, the number of sensors should be further increased within a 500-meter radius in front and behind, forming a hierarchical and verifiable monitoring network. This provides a reliable and continuous data foundation for subsequent distance-weighted fusion algorithms.

[0054] Based on the spatial distance between environmental monitoring points and spans, monitoring points within the coverage area are selected for each span, and weights are calculated according to the distance attenuation principle, so that monitoring points that are closer and less affected by terrain obstruction have a more prominent impact on that span. The weight calculation formula is as follows:

[0055]

[0056] in, No. The monitoring point to the first The influence weight of gear distance Indicates the first The monitoring point to the first Spatial distance between gears, Indicates the terrain shading coefficient. This represents the attenuation coefficient.

[0057] Step S22: For multi-source environmental data within the coverage area of ​​any span, the influence weights corresponding to the environmental monitoring points within the span are fused with the multi-source environmental data to obtain the fused environmental parameters corresponding to the span.

[0058] Based on this, multi-source environmental data within the same coverage area are fused. Temperature and wind speed A representative result is obtained by using a weighted average method:

[0059]

[0060]

[0061] wind direction As an angle variable, it is first converted into a unit vector. Then, after weighting and combining, the final wind direction is calculated:

[0062]

[0063] in, Indicates the first i The fused wind direction unit vector for each range Indicates the first j Temperatures measured at each monitoring point Indicates the first j Wind speeds measured at each monitoring point Indicates the first j The monitoring point to the first i The influence weight of each gear range Indicates the first j The unit vector of wind direction at each monitoring point. Indicates the first j The wind direction angle measured at each monitoring point Represents the fusion vector x Component (east direction) Represents the fusion vector y Component (north direction). Indicates the first i The final blended wind direction angle for each gear.

[0064] Step S23: Combine and encapsulate the physical parameters of the conductor, span length, and hanging point elevation data from the integrated environmental parameters and parameter information data to construct the working condition data object for the corresponding span.

[0065] In this step, if data from a monitoring point is missing or fluctuates abnormally at a certain moment, its weight is reduced to 0, and it is supplemented by other monitoring points to ensure the stability and usability of the fusion results.

[0066] Data quality verification includes identifying and removing outlier data. This applies to wind direction data. A multi-level decision-making strategy is adopted to ensure its reliability:

[0067] Limit value verification: Wind direction angles exceeding the range of [0°, 360°) are considered invalid.

[0068] Timing jump verification: Calculate the minimum angular difference of wind direction between adjacent sampling times. If the value exceeds the set dynamic threshold (e.g., 50°), the data at that moment is determined to be an abnormal jump.

[0069] Spatial consistency verification: If the wind direction at a certain monitoring point differs from the average wind direction at neighboring normal monitoring points for an extended period of time, exceeding the historical statistical range, the data is deemed suspicious.

[0070] Volatility check: Calculate the standard deviation of wind direction within a short time window. If it exceeds the typical volatility threshold under calm wind speed, it is judged as an abnormal volatility.

[0071] When data is identified as outlier, its influence weight in the fusion formula is... Will be dynamically downgraded or set to zero (e.g.) =0), ensuring that abnormal data does not contaminate the fusion results, and is supplemented by data from other normal monitoring points, thereby guaranteeing the fused wind direction. Stability and availability.

[0072] Ultimately, a unified operating condition data object is constructed. The physical parameters of the conductor, span length, and anchor point elevation, along with the real-time fused environmental parameters, are written into the data object for this working condition.

[0073] in, Indicates the first i The length of each gear interval Indicates the first i The elevation difference or elevation information of the two hanging points at each span is continuously updated in time series, providing input conditions consistent with the site conditions for tension calculation, sag calculation, and construction safety verification, thus achieving efficient integration of construction design information and real-time environmental data.

[0074] Step S24: Based on the physical parameters of the conductor, span length, elevation difference of the suspension point, and integrated environmental parameters in the working condition data object, construct a conductor mechanical model based on the catenary theory.

[0075] In this step, the fused multi-source data is input into the calculation engine. Based on the catenary theory, a precise mechanical model is constructed and iteratively calculated using a state equation solving algorithm to accurately output key construction parameters such as string tension, maximum traction force, and sag at each level. At the same time, multiple safety assessments, including upward verification, are completed.

[0076] Based on the catenary theory, an accurate mechanical model of the conductor is established. The fundamental equation of the catenary is expressed as:

[0077]

[0078]

[0079] in, This indicates that the catenary is in a horizontal position. The vertical coordinates at that location, Indicates the characteristic parameters of the catenary. Indicates the horizontal tension of the conductor. This indicates the comprehensive load per unit length (including self-weight, wind load, etc.). This represents the first integration constant determined by the boundary conditions. This represents the second integral constant determined by the boundary conditions.

[0080] Step S25: Based on the conductor mechanical model, the elastic properties of the conductor material, and the temperature change factor, construct a state constraint relationship that has the influence of conductor thermal expansion and elastic elongation.

[0081] In this step, considering the effects of temperature changes and elastic deformation, the state constraint equations are established:

[0082] in, This indicates the conductor length under the current operating conditions. Indicates reference temperature. Indicates the current temperature. Indicates the original length at the reference temperature. Indicates the coefficient of thermal expansion of the conductor. This represents the elastic modulus of the conductor. This indicates the cross-sectional area of ​​the conductor.

[0083] Step S26: Use the working condition data object as the input of the conductor mechanics model, and solve the conductor mechanics model through a numerical iterative solution algorithm to obtain the solution results and model parameters corresponding to the conductor mechanics model.

[0084] In this step, for complex nonlinear equation systems, Newton's iteration method is used for numerical solutions. The residual vector is established:

[0085]

[0086] in, Let be the unknown vector to be solved. The iterative formula is:

[0087]

[0088] in, The residual vector is represented by the residual functions of each equation in the nonlinear system of equations. composition; Indicates the first nThe residual function after writing a nonlinear equation in zero function form; In Newton's iterative method, the first... k Approximate value of the unknown vector at the next iteration; Represents the Jacobian matrix, Jacobian matrix The specific form can be expressed as:

[0089] The iterative process continues until the convergence condition is met. ,in, This is the preset tolerance.

[0090] Step S27: When the model parameters meet the convergence condition, calculate the laying tension, maximum traction force and conductor sag value corresponding to each span based on the solution results of the conductor mechanics model, and output the laying tension, maximum traction force and conductor sag value as key construction parameters.

[0091] In this step, once the convergence condition is met, it means that the numerical iterative solution has found parameter values ​​that satisfy the system of equations. These parameter values ​​can be used to calculate key construction parameters. The specific calculation process is as follows:

[0092] First, confirm that Newton's iteration method or other numerical methods have converged, i.e., the residual vector... The norm is less than the preset tolerance. At this point, the obtained parameter vector X contains the values ​​of all unknown parameters, such as horizontal tension. First integral constant Integral constant and second integral constant C, etc.

[0093] The specific shape of the catenary is calculated using the catenary equation, which is the state of the transmission line when it is erected.

[0094] Calculate the conductor length and sag using the state constraint equations:

[0095] Substitute the converged H value and other known parameters (such as...) Calculate the conductor length L under the current temperature and tension.

[0096] In this embodiment, high-precision intelligent calculation of key parameters for overhead power line construction is achieved through multi-source environmental data fusion and conductor mechanics solution based on catenary theory. Based on the spatial coordinate information of the target GIM model, each environmental monitoring point within the construction area is spatially correlated with its corresponding span, and influence weights are assigned to different monitoring points. Multi-source environmental data such as temperature, wind speed, and icing within any span range are weighted and fused to obtain fused environmental parameters that accurately reflect non-uniform environmental conditions. Subsequently, the fused environmental parameters are combined and encapsulated with conductor physical parameters, span length, and anchor point elevation data to construct a span-level working condition data object, forming a unified, standardized, and directly usable input data unit. Based on this, a conductor mechanics model is established according to catenary theory, incorporating the elastic properties of the conductor material and temperature variation factors. A state constraint relationship that considers both thermal expansion and elastic elongation is constructed. Numerical iterative solution and convergence criteria are set to ensure the stability of the model solution process and the reliability of the results. Once the model parameters meet the convergence conditions, the system automatically calculates key construction parameters such as the laying tension, maximum traction force, and conductor sag value for each span, achieving a closed-loop support throughout the entire process from environmental condition modeling to tension control parameter output.

[0097] Step S3: Calculate the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and key construction parameters.

[0098] This step also includes steps S31 to S34.

[0099] Step S31: Based on key construction parameters and the target GIM model, calculate the envelope angle corresponding to the contact area between the trolley and the conductor, and compare the envelope angle with the preset envelope angle threshold to obtain the envelope angle verification result.

[0100] In this step, by analyzing the mechanical balance at the hanging point, the system automatically identifies whether there is a risk of upward movement, providing a basis for decision-making regarding the configuration of the wire clamping device; the maximum tension is compared with the rated tension of the conductor to verify whether it meets the safety factor required by the specifications, ensuring the safety of the construction process. Safety parameters include upward movement, envelope angle, and safety factor, among others.

[0101] The envelope angle is the central angle corresponding to the contact area between the pulley and the conductor. First, calculate the corresponding suspension angle:

[0102]

[0103] in, This indicates the suspension angle corresponding to the conductor on the front side of the target tower. This indicates the suspension angle of the conductor on the rear side of the target tower. This indicates the span in front of the target tower. This indicates the span behind the target tower. This indicates the height difference of the conductor suspension point on the front side of the target tower. This indicates the height difference of the conductor suspension point on the back side of the target tower. This indicates the horizontal tension of the front span adjacent to the target tower. This indicates the horizontal tension of the rear span adjacent to the target tower. This represents the weight per unit length of an overhead power line.

[0104] The formula for calculating the envelope angle can be expressed as:

[0105] in, Indicates the envelope angle of the target tower. This indicates the angle of rotation of the angle tower. For other conductors, safety measures are required when the envelope angle is greater than 30°, while for optical cables, the envelope angle for which safety measures are required can be increased to 60°.

[0106] Step S32: Based on key construction parameters and the target GIM model, calculate the vertical span at the shared tower, and compare the vertical span with the standard vertical span to obtain the upward verification result.

[0107] In this step, the vertical span of the shared towers of two adjacent spans is calculated. To determine whether the conductor is rising.

[0108]

[0109] in, Indicates the height difference angle between the suspension points of the front gear. This indicates the height difference angle between the suspension points of the rear track. Based on the calculation results, if the vertical track distance is greater than zero, the line will not rise; otherwise, the line will rise, and there is no acceptable boundary. If rising exists, measures need to be taken (such as using a line-pressing pulley).

[0110] Step S33: Based on key construction parameters and the target GIM model, calculate the tension safety factor, and compare the tension safety factor with the preset safety factor threshold to obtain the safety factor verification result.

[0111] In this step, the safety factor The expression is:

[0112] in, This indicates the breaking force of the conductor. This represents the maximum tension, which can also be calculated using the horizontal tension obtained earlier and the parameters derived from GIM analysis.

[0113] Step S34: Integrate the envelope angle verification results, uplift verification results, and safety factor verification results to generate safety verification data corresponding to the target GIM model.

[0114] Furthermore, key construction parameters are visualized in 3D using a dynamic rendering algorithm to generate 3D scene data with parameter labels. The precise mapping between the 3D traverse shape and the catenary parameters is achieved sequentially through processes such as local coordinate system construction, parametric curve generation, and 3D spatial reconstruction.

[0115] First, a local planar coordinate system is established with the two ends of the span as the boundary. A two-dimensional point sequence is generated in this plane according to the catenary equation. Then, the two-dimensional point sequence is restored to the real three-dimensional world coordinates through the spatial coordinate transformation matrix, and the wind displacement is superimposed laterally along the direction of the vertical conductor. Finally, with the generated three-dimensional spatial path as the center line and the outer diameter of the conductor as the cross section, a continuous three-dimensional tubular mesh model is generated through the geometric lofting algorithm, thereby accurately transforming the abstract parameters of mechanical calculation into a visualized spatial geometric shape.

[0116] In this embodiment, the solution can provide early warnings of potential risks such as excessive envelope angle, conductor spiking, and tension overload at the model level, reducing reliance on manual experience and improving the objectivity and accuracy of safety verification. This effectively reduces the probability of construction safety accidents and enhances the inherent safety level and controllability of overhead line construction.

[0117] Step S4 involves integrating and structuring key construction parameters and safety verification data to generate a structured construction calculation report.

[0118] This step also includes steps S41 to S42.

[0119] Step S41: Based on the identification information of each tower and each span in the target GIM model, index and associate the key construction parameters and safety verification data, and bind the string tension, maximum traction force, conductor sag, envelope angle verification results, uplift verification results and safety factor verification results of each tower and each span to the corresponding model object in the target GIM model.

[0120] Step S42: Classify and organize the key construction parameters and safety verification data after the association is completed. Collect the project overview information, working condition parameter information, tension and sag calculation results information and safety assessment results information into the corresponding structured data segments to form a structured construction calculation report dataset.

[0121] In one example, construction parameter data and safety verification data are collected, including key construction parameters such as string tension, maximum traction force, sag at each span, upward angle, and clearance margin. The data is categorized by construction unit, span, and node, generating a unified data object that forms a structured information table containing parameter values, calculation formulas, boundary conditions, and verification results. A predefined report template, including tables, text descriptions, and placeholders for attached diagrams, is used to fill in the structured data, and construction parameter tables for each segment are automatically generated based on the span number. Based on node coordinates and sag data, curve diagrams, tension distribution diagrams, and safety margin diagrams are generated for visual presentation. Finally, a construction calculation report is generated to ensure it can be directly used for on-site construction guidance and archiving.

[0122] In one example, such as Figure 2 As shown, Figure 2 This is a layered functional architecture diagram of an intelligent method for overhead line tension based on a GIM model. The functional structure includes a GIM model parsing and data extraction module, an environmental data access and fusion module, an intelligent algorithm engine calculation module, and a 3D visualization and simulation verification module. The GIM model parsing and data extraction module is used to parse the GIM model created in the design phase, automatically identify and extract key information such as conductor physical parameters, line geometric parameters, and hardware parameters, and realize the seamless transfer of design data to the construction phase.

[0123] The environmental data access and fusion module is used to monitor various environmental data within the construction area and to fuse parameters extracted from the GIM model with environmental data. This module includes temperature sensors, wind speed sensors, and wind direction sensors. Each sensor node transmits measurement data such as temperature, wind speed, and wind direction to the data receiving platform in real time using the MQTT protocol via its built-in data transmission unit.

[0124] The data receiving platform acts as a message broker for the MQTT protocol, receiving and temporarily storing all sensor data. The internal data acquisition service, acting as a subscriber, continuously monitors the data stream and acquires environmental data packets in real time. The acquisition service decrypts and decodes the received packets, extracting key fields such as temperature, wind speed, and wind direction, along with their acquisition timestamps, from the JSON-formatted data packets to provide structured data for subsequent processing. The data transmission unit can be a 4G / 5G communication unit or an IoT communication unit; the data receiving platform can be a cloud-based data platform.

[0125] The intelligent algorithm engine calculation module is used to input the obtained parameters and data into the preset algorithm for calculation and to obtain the results, as well as to verify whether the tension distribution in the calculation results meets the safety factor required by the specifications, so as to ensure the safety of the construction process.

[0126] The 3D visualization and simulation verification module is used to dynamically render the calculation results in a 3D scene to generate accurate conductor sag curves, and to perform safety distance verification through multi-view observation function.

[0127] The results input and report generation module is used to automatically integrate all calculation and verification results and generate a structured construction calculation report containing key information such as tension control values, sag data, and safety assessment conclusions.

[0128] In this embodiment, by parsing the target GIM model to obtain corresponding parameter information and fusing it with multi-source environmental data, compared with the traditional calculation method that relies solely on empirical values ​​or single parameters, the calculation under multi-dimensional parameter constraints significantly improves the accuracy and stability of tension calculation results. Furthermore, an automatic extraction algorithm is used to parse the GIM model, reducing errors and workload caused by manual reading and manual input of model parameters. Using construction parameter generation algorithms and safety assessment algorithms, key construction parameters and safety verification data are automatically output, realizing fully automated processing from data acquisition and parameter generation to safety verification. At the same time, by conducting safety assessments on key construction parameters, safety verification data corresponding to the target GIM model is obtained and compared with rated safety verification data, which can detect potential safety hazards in tension settings in advance. Multi-source environmental data is uniformly processed through a fusion algorithm, enabling the generated working condition data object to cover a variety of complex application scenarios. Even in areas with large fluctuations in environmental parameters or complex construction conditions, the controllability and consistency of tension calculation results can still be maintained, thereby improving the installation accuracy of overhead transmission lines.

[0129] Based on the above method, this application discloses an intelligent tension calculation system for overhead line construction based on a GIM model, with reference to... Figure 3 The intelligent tension calculation system 1 for overhead line construction includes a model analysis module 11, a data processing module 12, and a result reporting module 13. Model parsing module 11 is used to parse the target GIM model based on an automatic extraction algorithm to obtain the parameter information data corresponding to the target GIM model; The data processing module 12 is used to collect multi-source environmental data of the construction area, and to fuse parameter information data with multi-source environmental data according to the fusion algorithm to generate working condition data objects. Based on the construction parameter generation algorithm and the working condition data objects, key construction parameters are obtained. Based on the safety assessment algorithm and key construction parameters, the safety verification data corresponding to the target GIM model is calculated. The results report module 13 is used to integrate and structure key construction parameters and safety verification data to generate a structured construction calculation report.

[0130] In one example, the model parsing module 11 is used to collect the internal data structure of the GIM digital engineering files in the target GIM model, and construct an object relationship graph and a unified data dictionary corresponding to the internal data structure; input the specific attribute parameters of the conductor objects, hardware components and tower models in the object relationship graph into the preset data encapsulation algorithm to obtain a set of structured parameters; perform data verification on the set of structured parameters to output the parameter information data corresponding to the target GIM model.

[0131] In one example, the data processing module 12 is used to spatially associate each environmental monitoring point and span within the construction area based on the spatial coordinate information in the target GIM model, and assign a corresponding influence weight to each environmental monitoring point; for multi-source environmental data within the coverage area of ​​any span, the influence weight corresponding to the environmental monitoring point within the span is fused with the multi-source environmental data to obtain the fused environmental parameters corresponding to the span; the fused environmental parameters are combined and encapsulated with the conductor physical parameters, span length and hanging point elevation data in the parameter information data to construct the working condition data object corresponding to the span.

[0132] In one example, the data processing module 12 is used to construct a conductor mechanical model based on the catenary theory, using the conductor physical parameters, span length, hanging point elevation difference, and integrated environmental parameters in the working condition data object; based on the conductor mechanical model, the elastic properties of the conductor material, and temperature change factors, it constructs state constraint relationships with the influence of conductor thermal expansion and elastic elongation; using the working condition data object as input to the conductor mechanical model, it solves the conductor mechanical model through a numerical iterative solution algorithm to obtain the solution results and model parameters corresponding to the conductor mechanical model; when the model parameters meet the convergence condition, it calculates the laying tension, maximum traction force, and conductor sag value corresponding to each span based on the solution results of the conductor mechanical model, and outputs the laying tension, maximum traction force, and conductor sag value as key construction parameters.

[0133] In one example, the data processing module 12 is used to calculate the envelope angle corresponding to the contact area between the pulley and the conductor based on key construction parameters and the target GIM model, and compare the envelope angle with a preset envelope angle threshold to obtain the envelope angle verification result; calculate the vertical span at the shared tower based on key construction parameters and the target GIM model, and compare the vertical span with the standard vertical span to obtain the upward verification result; calculate the tension safety factor based on key construction parameters and the target GIM model, and compare the tension safety factor with a preset safety factor threshold to obtain the safety factor verification result; and integrate the envelope angle verification result, the upward verification result, and the safety factor verification result to generate the safety verification data corresponding to the target GIM model.

[0134] In one example, after calculating the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and key construction parameters, the process also includes: performing 3D visualization processing on the key construction parameters based on the dynamic rendering algorithm to generate 3D scene data with parameter labels.

[0135] In one example, the results reporting module 13 is used to index and associate key construction parameters and safety verification data based on the identification information of each tower and each span in the target GIM model. It binds the string tension, maximum traction force, conductor sag, envelope angle verification results, uplift verification results, and safety factor verification results corresponding to each tower and each span to the corresponding model objects in the target GIM model. After the association is completed, the key construction parameters and safety verification data are classified and organized. The project overview information, working condition parameter information, tension and sag calculation results information, and safety assessment results information are collected into the corresponding structured data segments to form a structured construction calculation report dataset.

[0136] Please see Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 2 may include: at least one processor 21, at least one network interface 24, user interface 23, memory 25, and at least one communication bus 22.

[0137] The communication bus 22 is used to enable communication between these components.

[0138] The user interface 23 may include a display screen and a camera. Optionally, the user interface 23 may also include a standard wired interface and a wireless interface.

[0139] The network interface 24 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0140] The processor 21 may include one or more processing cores. The processor 21 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 25, and by calling data stored in the memory 25. Optionally, the processor 21 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 21 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 21.

[0141] The memory 25 may include random access memory (RAM) or read-only memory. Optionally, the memory 25 may include non-transitory computer-readable storage medium. The memory 25 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 25 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 25 may also be at least one storage device located remotely from the aforementioned processor 21. Figure 4 As shown, the memory 25, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for an intelligent calculation method of overhead line construction tension based on a GIM model.

[0142] exist Figure 4In the electronic device 2 shown, the user interface 23 is mainly used to provide an input interface for the user and obtain the user input data; while the processor 21 can be used to call an application program stored in the memory 25 that is a smart calculation method for overhead line construction tension based on a GIM model. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0143] A non-transitory computer-readable storage medium stores instructions that, when executed by one or more processors, cause a computer to perform one or more methods as described in the above embodiments.

[0144] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0145] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0146] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0147] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0148] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0149] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0150] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent calculation of tension during overhead power line construction based on a GIM model, characterized in that, The method includes: The target GIM model is parsed based on an automatic extraction algorithm to obtain the parameter information data corresponding to the target GIM model; Collect multi-source environmental data of the construction area, and fuse the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object. Based on the construction parameter generation algorithm and the working condition data object, obtain key construction parameters. Based on the safety assessment algorithm and the key construction parameters, calculate the safety verification data corresponding to the target GIM model; The key construction parameters and safety verification data are integrated and structured to generate a structured construction calculation report.

2. The intelligent calculation method for overhead line construction tension based on GIM model as described in claim 1, characterized in that, The step of parsing the target GIM model based on an automatic extraction algorithm to obtain parameter information data corresponding to the target GIM model specifically includes: Collect the internal data structure of the GIM digitized engineering files in the target GIM model, and construct an object relationship graph and a unified data dictionary corresponding to the internal data structure; The specific attribute parameters of the conductor objects, hardware components, and tower models in the object relationship graph are input into a preset data encapsulation algorithm to obtain a set of structured parameters. The structured parameter set is validated to output the parameter information data corresponding to the target GIM model.

3. The intelligent calculation method for overhead line construction tension based on a GIM model as described in claim 1, characterized in that, The step of fusing the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object specifically includes: Based on the spatial coordinate information in the target GIM model, the environmental monitoring points and spans within the construction area are spatially correlated to assign a corresponding influence weight to each environmental monitoring point. For multi-source environmental data within any span coverage area, the influence weights corresponding to the environmental monitoring points within the span are fused with the multi-source environmental data to obtain the fused environmental parameters corresponding to the span. The fused environmental parameters are combined and encapsulated with the conductor physical parameters, span length, and hanging point elevation data in the parameter information data to construct a working condition data object corresponding to the span.

4. The intelligent calculation method for overhead line construction tension based on a GIM model as described in claim 3, characterized in that, The acquisition of key construction parameters based on the construction parameter generation algorithm and the working condition data object specifically includes: Based on the physical parameters of the conductor, span length, elevation difference of the suspension point, and integrated environmental parameters in the working condition data object, a conductor mechanical model based on catenary theory is constructed. Based on the aforementioned conductor mechanical model, the elastic properties of the conductor material, and temperature change factors, a state constraint relationship with the influence of conductor thermal expansion and elastic elongation is constructed. The working condition data object is used as the input of the conductor mechanical model, and the conductor mechanical model is solved by a numerical iterative solution algorithm to obtain the solution results and model parameters corresponding to the conductor mechanical model; When the model parameters meet the convergence condition, the laying tension, maximum traction force and conductor sag value corresponding to each span are calculated based on the solution results of the conductor mechanical model, and the laying tension, maximum traction force and conductor sag value are output as key construction parameters.

5. The intelligent calculation method for overhead line construction tension based on a GIM model as described in claim 1, characterized in that, The step of calculating the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and the key construction parameters specifically includes: Based on the key construction parameters and the target GIM model, the envelope angle corresponding to the contact area between the trolley and the conductor is calculated, and the envelope angle is compared with a preset envelope angle threshold to obtain the envelope angle verification result. Based on the key construction parameters and the target GIM model, the vertical span at the shared tower is calculated, and the vertical span is compared with the standard vertical span to obtain the upward verification result. Based on the key construction parameters and the target GIM model, the tension safety factor is calculated, and the tension safety factor is compared with the preset safety factor threshold to obtain the safety factor verification result; The envelope angle verification result, the upward verification result, and the safety factor verification result are integrated to generate the safety verification data corresponding to the target GIM model.

6. The intelligent calculation method for overhead line construction tension based on a GIM model as described in claim 1, characterized in that, After calculating the safety verification data corresponding to the target GIM model based on the safety assessment algorithm and the key construction parameters, the process further includes: The key construction parameters are visualized in three dimensions using a dynamic rendering algorithm to generate three-dimensional scene data with parameter labels.

7. The intelligent calculation method for overhead line construction tension based on a GIM model as described in claim 1, characterized in that, The process of integrating and structuring the key construction parameters and safety verification data to generate a structured construction calculation report specifically includes: Based on the identification information of each tower and each span in the target GIM model, the key construction parameters and the safety verification data are indexed and associated. The string tension, maximum traction force, conductor sag, envelope angle verification results, upward verification results and safety factor verification results corresponding to each tower and each span are respectively bound to the corresponding model objects in the target GIM model. After the key construction parameters and safety verification data are associated, they are classified and organized. Project overview information, working condition parameter information, tension and sag calculation results information, and safety assessment results information are collected into the corresponding structured data segments to form a structured construction calculation report dataset.

8. A smart tension calculation system for overhead line construction based on a GIM model, characterized in that, The intelligent tension calculation system (1) for overhead line construction includes a model analysis module (11), a data processing module (12), and a result reporting module (13), wherein, The model parsing module (11) is used to parse the target GIM model based on the automatic extraction algorithm and obtain the parameter information data corresponding to the target GIM model; The data processing module (12) is used to collect multi-source environmental data of the construction area, and to fuse the parameter information data with the multi-source environmental data according to the fusion algorithm to generate a working condition data object. Based on the construction parameter generation algorithm and the working condition data object, key construction parameters are obtained. Based on the safety assessment algorithm and the key construction parameters, the safety verification data corresponding to the target GIM model is calculated. The result reporting module (13) is used to integrate and structure the key construction parameters and the safety verification data to generate a structured construction calculation report.

9. An electronic device, characterized in that, The device includes a processor (21), a memory (25), a user interface (23), and a network interface (24). The memory (25) is used to store instructions. The user interface (23) and the network interface (24) are used to communicate with other devices. The processor (21) is used to execute the instructions stored in the memory (25) to cause the electronic device (2) to perform the method as described in any one of claims 1-7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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