A method, system, device, and medium for three-dimensional modeling of an overhead line

Abstract

The application discloses a kind of three-dimensional modeling method, system, equipment and medium of overhead line, in response to received overhead line modeling request, determine tower sub-element to be modeled parameter, to be modeled tower selection element and overhead line construction path, adopt tower sub-element to be modeled parameter input preset tower sub-element three-dimensional model database, output multiple initial tower sub-element model, adopt to be modeled tower selection element input preset optimization tower selection rule model, output multi-objective optimization tower selection rule, based on multi-objective optimization tower selection rule, match multiple target tower sub-element model, using each target tower sub-element model input preset optimization tower three-dimensional model database, output multiple optimization tower three-dimensional model, parse overhead line construction path, based on multiple optimization tower three-dimensional model Construction target overhead line;Solve the technical problem that traditional overhead line cannot fully meet the needs of multi-objective when modeling.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional modeling technology, and in particular to a three-dimensional modeling method, system, device and medium for overhead power lines. Background Technology

[0002] The 3D modeling of overhead lines in power distribution network projects requires extensive tower modeling work. This involves precise calculations, component modeling, and positioning of the components relative to the main pole, considering factors such as the tower's assembly form, dimensions, on-pole components, and their relative positions to the main pole. Accurate construction of various tower components, such as the main pole, clamps, crossarms, diagonal braces, insulators, and conductor attachment points, is crucial. The accuracy of the modeling directly impacts the accuracy of subsequent tower analysis and route design. Currently, the 3D models used in power distribution network engineering require building fixed models based on project needs before 3D visualization. Each project requires specific modeling, making it difficult to reuse existing models.

[0003] 3D engineering of power distribution networks separates the modeling of the main pole and the pole head, enabling automatic combination and adjustment during the drawing process, achieving a "design-as-you-go" approach. Traditional selection methods are often based on engineers' experience and subjective judgment, lacking systematicity and objectivity. This leads to inconsistencies and inaccuracies in the selection results. Furthermore, they typically only consider a single objective, such as cost minimization or strength maximization. However, in actual engineering, multiple objectives need to be balanced, such as cost, reliability, and sustainability. Single-objective optimization cannot fully meet the needs of multiple objectives. Summary of the Invention

[0004] This invention provides a three-dimensional modeling method, system, equipment, and medium for overhead lines, which solves the problem that in traditional overhead line modeling, the selection of main poles and pole heads is often based on engineers' experience and subjective judgment, resulting in inconsistencies and inaccuracies in the selection results. Furthermore, it usually only considers a single objective, thus failing to fully meet the multi-objective requirements of overhead line modeling.

[0005] The first aspect of this invention provides a three-dimensional modeling method for overhead power lines, comprising:

[0006] In response to a received overhead line modeling request, determine the modeling parameters of the tower sub-components corresponding to the overhead line modeling request, the selection elements of the tower to be modeled, and the overhead line construction path;

[0007] The parameters to be modeled for the tower sub-components are input into a preset three-dimensional model database of tower sub-components, and multiple corresponding initial tower sub-component models are output.

[0008] The selected tower elements to be modeled are used as input to a preset optimized tower selection rule model, and the corresponding multi-objective optimized tower selection rules are output.

[0009] Based on the multi-objective optimization tower selection rules, multiple target tower sub-component models for constructing each optimized tower 3D model are matched from multiple initial tower sub-component models.

[0010] Each target tower sub-component model is input into a preset optimized tower 3D model database, and multiple corresponding optimized tower 3D models are output.

[0011] The overhead line construction path is analyzed, and the target overhead line is constructed based on multiple optimized tower 3D models.

[0012] Optionally, it also includes:

[0013] Extract the rule elements of the tower components;

[0014] Based on the rule elements of the tower sub-components, establish a modeling parameter table corresponding to each tower sub-component;

[0015] Based on the modeling parameters in the modeling parameter table, a 3D model database of each tower sub-element is constructed.

[0016] Optionally, the pole sub-components include key elements of the main pole, key elements of the crossarm, elements of the hanging point, elements of the insulator, elements of the pole top clamp, elements of the angle steel, and elements of the diagonal brace.

[0017] The key elements of the main pole rule include name, color, material, pole height, embedment depth, tip diameter, taper, and inclination angle;

[0018] The key elements of the crossarm rule include name, color, type, rotation angle, angle steel length, leg width, leg thickness, position, whether there are left and right diagonal braces, and the size data of the left and right diagonal braces;

[0019] The hanging point rule elements include the names of the left and right hanging point groups, the number of hanging points, the location of the hanging point groups, and the insulator where each hanging point is located;

[0020] The insulator rule elements include name, color, type, total length, number of pieces, piece radius, rotation angle around the axis, x-angle, z-angle, etc., the angle steel to which it belongs, and location;

[0021] The pole top clamp rule elements include name, color, type, pole height, clamp height, clamp spacing, steel plate width, steel plate thickness, and rotation angle around the pole;

[0022] The standard elements of the angle steel include color, length, leg width, and leg thickness;

[0023] The diagonal bracing rule elements include color, whether there is a left diagonal bracing, whether there is a right diagonal bracing, the vertical height of the diagonal bracing, the horizontal length of the diagonal bracing, and the length of the bottom edge of the diagonal bracing.

[0024] Optionally, it also includes:

[0025] Based on the tower selection rule elements, multiple corresponding selection data tables are established;

[0026] Based on the selection constraints, link the various selection data tables to construct a pole and tower selection rule dataset;

[0027] The preset initial pole selection rule model is trained using the pole selection rule dataset as input to generate the corresponding optimized pole selection rule model.

[0028] Optionally, the pole selection rule elements include load conditions, geographical conditions, pole structure type, material type, pole height, pole type, meteorological conditions, reliability conditions, and cost conditions;

[0029] The load requirements include current, voltage, and equipment capacity;

[0030] The geographical conditions include geological type and burial depth;

[0031] The meteorological conditions include the highest temperature, lowest temperature, annual average temperature, basic wind speed, maximum icing, switching overvoltage, lightning overvoltage, temperature, wind speed, and icing thickness under the conditions of installation status and accidental line disconnection.

[0032] The reliability conditions include the distance between the conductor and the ground, the safe distance to objects crossed, the avoidance of contaminated areas, and the corrosion resistance of the porcelain insulator.

[0033] The cost terms include the prices of each pole sub-component and the pole head.

[0034] Optionally, it also includes:

[0035] Detect the dimensional and shape data of each tower sub-component model;

[0036] Based on the dimensional data and the shape data, determine the component type information of each of the tower sub-component models;

[0037] The preset sub-component attachment point model is input with the component type information, and the corresponding attachment point information is output.

[0038] Based on the component type information, determine the main pole component model from each of the pole sub-component models;

[0039] Based on the attachment point information, a series of local coordinate systems with the center coordinates of the main rod sub-component model as the origin are established using a 3D modeling platform;

[0040] Based on the component type information and the attachment point information, each of the tower sub-component models is placed in the corresponding local coordinate system to establish multiple optimized tower 3D models;

[0041] Based on DirectX rendering technology, multiple optimized tower 3D models are rendered to generate multiple rendered tower 3D models.

[0042] The formats of multiple rendered tower 3D models are converted to construct an optimized tower 3D model database.

[0043] Optionally, the step of parsing the overhead line construction path and constructing the target overhead line based on multiple optimized tower 3D models includes:

[0044] Analyze the overhead line construction path to determine multiple optimized tower locations corresponding to the target overhead line;

[0045] Based on the order of the optimized tower locations, corresponding 3D models of the constructed towers are selected from multiple optimized tower 3D models and placed in the associated optimized tower locations.

[0046] Based on the type of the constructed tower 3D model, match the corresponding constructed pole head 3D model;

[0047] The target overhead line is constructed by connecting multiple three-dimensional models of the construction towers with conductors.

[0048] The second aspect of this invention provides a three-dimensional modeling system for overhead power lines, comprising:

[0049] The response module is used to respond to the received overhead line modeling request and determine the modeling parameters of the tower sub-components, the selection elements of the tower to be modeled, and the overhead line construction path corresponding to the overhead line modeling request.

[0050] The initial tower sub-component model module is used to input the tower sub-component model parameters to be modeled into a preset tower sub-component 3D model database and output multiple corresponding initial tower sub-component models.

[0051] The tower selection optimization rule module is used to input the tower selection elements to be modeled into a preset tower selection optimization rule model and output the corresponding multi-objective tower selection optimization rules.

[0052] The target tower sub-component model module is used to match multiple target tower component models from multiple initial tower sub-component models to construct the three-dimensional models of each optimized tower, based on the multi-objective optimized tower selection rules.

[0053] The optimized tower 3D model module is used to input the target tower sub-component models into a preset optimized tower 3D model database and output multiple corresponding optimized tower 3D models.

[0054] The target overhead line module is used to parse the overhead line construction path and construct the target overhead line based on multiple optimized tower 3D models.

[0055] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the three-dimensional modeling method for overhead lines as described in any of the preceding claims.

[0056] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the three-dimensional modeling method for overhead lines as described in any of the preceding claims.

[0057] As can be seen from the above technical solutions, the present invention has the following advantages:

[0058] In response to a received overhead line modeling request, the system determines the modeling parameters of the corresponding tower sub-components, the tower selection elements, and the overhead line construction path. It inputs the modeling parameters of the tower sub-components into a pre-defined 3D model database, outputting multiple corresponding initial tower sub-component models. It inputs the tower selection elements into a pre-defined optimized tower selection rule model, outputting corresponding multi-objective optimized tower selection rules. Based on these rules, it matches multiple target tower sub-component models from the initial models to construct the 3D models of each optimized tower. It inputs these target models into a pre-defined optimized tower 3D model database, outputting multiple corresponding optimized tower 3D models. Finally, it parses the overhead line construction path and, based on multiple... This paper proposes an optimized 3D model for constructing target overhead power lines. It addresses the problem that traditional overhead power line modeling often relies on engineers' experience and subjective judgment, leading to inconsistencies and inaccuracies in the selection of main poles and pole heads. Furthermore, it typically only considers a single objective, failing to fully meet the multi-objective requirements of overhead power line modeling. The paper reduces the number of 3D pole models required for constructing 3D overhead power line models, thus adapting to the complex and ever-changing design of overhead power lines in distribution network projects. This improves the efficiency and quality of 3D design work in distribution network projects. Simultaneously, during the modeling process, based on the conductors associated with the poles, the paper automatically adapts the pole head angle to generate a 3D overhead power line for the distribution network, enabling dynamic combination and adjustment of poles and pole heads. Attached Figure Description

[0059] 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.

[0060] Figure 1 A flowchart illustrating the steps of a three-dimensional modeling method for overhead power lines provided in Embodiment 1 of the present invention;

[0061] Figure 2 A flowchart illustrating the steps of a three-dimensional modeling method for an overhead power line provided in Embodiment 2 of the present invention;

[0062] Figure 3 This is a structural block diagram of a three-dimensional modeling system for overhead power lines provided in Embodiment 3 of the present invention. Detailed Implementation

[0063] This invention provides a three-dimensional modeling method, system, equipment, and medium for overhead lines, which addresses the problem that in traditional overhead line modeling, the selection of main poles and pole heads is often based on engineers' experience and subjective judgment, resulting in inconsistencies and inaccuracies in the selection results. Furthermore, it typically only considers a single objective, thus failing to fully meet the multi-objective requirements of overhead line modeling.

[0064] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0065] Please see Figure 1 , Figure 1 The flowchart illustrates the steps of a three-dimensional modeling method for overhead power lines provided in Embodiment 1 of the present invention.

[0066] This invention provides a three-dimensional modeling method for overhead power lines, comprising:

[0067] Step 101: In response to the received overhead line modeling request, determine the modeling parameters of the tower sub-components, the tower selection elements, and the overhead line construction path corresponding to the overhead line modeling request.

[0068] An overhead line modeling request refers to a response to receiving a request to model overhead lines for a power distribution network overhead line project.

[0069] The parameters to be modeled for pole sub-components refer to the modeling requirements parameters for each pole sub-component in the three-dimensional model of the overhead line project of the distribution network carried in the overhead line modeling request.

[0070] The tower selection elements to be modeled refer to the tower model selection conditions for constructing a three-dimensional model of an overhead power distribution network project carried in the overhead line modeling request.

[0071] The overhead line construction path refers to the path information of the three-dimensional model of the overhead line project carried in the overhead line modeling request.

[0072] In this embodiment of the invention, in response to receiving a request for modeling overhead lines for a power distribution network overhead line project, the request information is read, and the modeling parameters of the pole sub-components, the selection elements of the pole to be modeled, and the overhead line construction path carried in the request information are obtained.

[0073] Step 102: Input the modeling parameters of the tower sub-components into the preset tower sub-component 3D model database, and output multiple corresponding initial tower sub-component models.

[0074] The pre-set 3D model database of pole and tower sub-components refers to a 3D model database composed of multiple 3D models of pole and tower sub-components established based on the modeling parameters of the association of regular elements of pole and tower sub-components.

[0075] In this embodiment of the invention, the parameters to be modeled for the pole sub-components are input into a preset three-dimensional model database of pole sub-components, and multiple initial pole sub-component models that conform to the parameters to be modeled for the pole sub-components are output.

[0076] Step 103: Input the selected tower selection elements to be modeled into the preset optimized tower selection rule model, and output the corresponding multi-objective optimized tower selection rules.

[0077] The preset optimized pole selection rule model refers to the optimized pole selection rule model generated after training the preset initial pole selection rule model using a pole selection rule dataset that associates pole selection rule elements.

[0078] In this embodiment of the invention, the selected elements of the tower to be modeled are input into a pre-trained preset optimized tower selection rule model, and the output is a multi-objective optimized tower selection rule for filtering out the target tower sub-element model.

[0079] Step 104: Based on the multi-objective optimization tower selection rules, match multiple target tower sub-component models from multiple initial tower sub-component models to construct the three-dimensional models of each optimized tower.

[0080] Multi-objective optimization tower selection rules refer to pre-trained optimized tower selection rule models based on the input elements of the towers to be modeled, and output multi-objective optimization tower selection rules used to filter out target tower sub-component models.

[0081] In this embodiment of the invention, based on the multi-objective optimization tower selection rules, multiple target tower sub-component models that conform to the multi-objective optimization tower selection rules are selected from multiple initial tower sub-component models. The target tower sub-component models are specifically used to construct the three-dimensional model of the optimized tower.

[0082] Step 105: Input the sub-component models of each target tower into the preset optimized tower 3D model database, and output multiple corresponding optimized tower 3D models.

[0083] The pre-set optimized tower 3D model database refers to an optimized tower 3D model database composed of multiple tower 3D models constructed using component assembly technology.

[0084] In this embodiment of the invention, each target tower sub-component model is input into a preset optimized tower 3D model database, and multiple corresponding optimized tower 3D models are output.

[0085] Step 106: Analyze the overhead line construction path and construct the target overhead line based on multiple optimized tower 3D models.

[0086] In this embodiment of the invention, the overhead line construction path is analyzed to determine multiple optimized pole and tower locations corresponding to the target overhead line; based on the order of each optimized pole and tower location, the corresponding construction pole and tower 3D models are selected from multiple optimized pole and tower 3D models and placed in the associated optimized pole and tower locations; according to the type of the construction pole and tower 3D model, the corresponding construction pole head 3D model is matched; multiple construction pole and tower 3D models are connected by conductors to construct the target overhead line.

[0087] In this invention, in response to a received overhead line modeling request, the modeling parameters of the tower sub-components, the selection elements of the towers to be modeled, and the overhead line construction path corresponding to the overhead line modeling request are determined. The modeling parameters of the tower sub-components are input into a preset 3D model database of tower sub-components, outputting multiple corresponding initial tower sub-component models. The selection elements of the towers to be modeled are input into a preset optimized tower selection rule model, outputting corresponding multi-objective optimized tower selection rules. Based on the multi-objective optimized tower selection rules, multiple target tower sub-component models for constructing each optimized tower 3D model are matched from the multiple initial tower sub-component models. Each target tower sub-component model is input into a preset optimized tower 3D model database, outputting multiple corresponding optimized tower 3D models. The overhead line construction path is then analyzed. This method constructs target overhead lines based on multiple optimized 3D models of towers. It addresses the problem that traditional overhead line modeling often relies on engineers' experience and subjective judgment, leading to inconsistencies and inaccuracies in tower selection. Furthermore, it typically considers only a single objective, failing to fully meet the multi-objective requirements of overhead line modeling. This method reduces the number of tower 3D models and the workload involved in constructing the 3D model of an overhead line, adapting to the complex and ever-changing design of overhead lines in distribution network engineering. It improves the efficiency and quality of 3D design work in distribution network engineering. Simultaneously, during the modeling process, based on the conductors associated with the towers, it can automatically adapt the tower head angle to generate a 3D overhead line for the distribution network, enabling dynamic combination and adjustment of towers and tower heads.

[0088] Please see Figure 2 , Figure 2 The flowchart illustrates the steps of a three-dimensional modeling method for overhead power lines provided in Embodiment 2 of the present invention.

[0089] This invention provides a three-dimensional modeling method for overhead power lines, comprising:

[0090] Step 201: In response to the received overhead line modeling request, determine the modeling parameters of the pole sub-components, the pole selection elements to be modeled, and the overhead line construction path corresponding to the overhead line modeling request.

[0091] In this embodiment of the invention, the specific implementation process of step 201 is similar to that of step 101, and will not be repeated here.

[0092] Furthermore, step 202 also includes the following:

[0093] S11, Extract the rule elements of the pole sub-components.

[0094] Furthermore, the structural elements of the pole sub-components include key structural elements of the main pole, key structural elements of the crossarm, structural elements of the hanging point, structural elements of the insulator, structural elements of the pole top clamp, structural elements of the angle steel, and structural elements of the diagonal brace;

[0095] Key elements of the main pole rule include name, color, material, pole height, embedment depth, tip diameter, taper, and inclination angle;

[0096] Key elements of the crossarm specification include name, color, type, rotation angle, angle steel length, leg width, leg thickness, location, presence of left and right diagonal braces, and dimensions of the left and right diagonal braces;

[0097] The hanging point rule elements include the names of the left and right hanging point groups, the number of hanging points, the location of the hanging point groups, and the insulator where each hanging point is located;

[0098] The insulator specification elements include name, color, type, total length, number of discs, disc radius, rotation angle around the axis, x-angle, z-angle, etc., the angle steel to which it belongs, and location;

[0099] The standard elements for pole top clamps include name, color, type, pole height, clamp height, clamp spacing, steel plate width, steel plate thickness, and rotation angle around the pole.

[0100] The standard elements for angle steel include color, length, leg width, and leg thickness;

[0101] The elements of the diagonal brace rule include color, whether there is a left diagonal brace, whether there is a right diagonal brace, vertical height of the diagonal brace, horizontal length of the diagonal brace, and bottom edge length of the diagonal brace.

[0102] It is worth mentioning that the 3D model of the overhead line is constructed by connecting the front and rear tower suspension points using conductors to form the 3D model of the tower and the tower head.

[0103] A pole or tower consists of a main pole, crossarms, and suspension points; the main pole consists of the main pole and the pole top clamp; the crossarm consists of angle steel, insulators, and diagonal braces; the suspension points are the points where the conductor is suspended on the insulator, and are divided into front suspension points, rear suspension points, and jumper suspension points;

[0104] Key elements of the main pole rules include, but are not limited to, parameters such as name, color, material, pole height, embedment depth, tip diameter, taper, and inclination angle; they also include geometric constraints and business rules. For example, business rules such as the main pole naming rules have various forms depending on the requirements of different regions, such as "tip diameter + height", "material + height", and "pole type + voltage level + height". Geometric constraints include, for example, that the tip diameter of the main pole is smaller than the diameter at the base of the main pole.

[0105] Key elements of crossarm specifications include, but are not limited to, name, color, type, rotation angle, angle steel length, leg width, leg thickness, location, presence of left and right diagonal braces, and dimensions of the left and right diagonal braces. Business rules, for example, require that corner pole crossarms have a single-sided diagonal brace added in the direction of the line corner bisector to increase the lateral and vertical tension on the crossarm. Geometric constraints include that the crossarm length must be greater than the diameter of the main pole at the height of the main pole.

[0106] The elements of the hanging point rules include, but are not limited to, the names of the left and right hanging point groups, the number of hanging points, the location of the hanging point groups, and the insulators to which each hanging point is located. For example, the hanging point modeling rules require that the location of the hanging point group cannot deviate from the center line of the insulator.

[0107] Insulator specifications include, but are not limited to, name, color, type, total length, number of discs, disc radius, rotation angle around the axis, x-angle, z-angle, and the angle steel to which it belongs and its location.

[0108] The specifications for pole top clamps include, but are not limited to, name, color, type, pole height, clamp height, clamp spacing, steel plate width, steel plate thickness, and rotation angle around the pole.

[0109] Angle steel and diagonal bracing are important components of crossarms. The standard elements of angle steel include, but are not limited to, color, length, leg width, and leg thickness.

[0110] The elements of the diagonal bracing rules include, but are not limited to, color, whether there is a left (right) diagonal bracing, vertical height of the diagonal bracing, horizontal length of the diagonal bracing, and bottom edge length of the diagonal bracing.

[0111] In this embodiment of the invention, according to typical design specifications, the rule elements of the pole and tower sub-components are extracted. The rule elements of the pole and tower sub-components include business requirements, geometric constraints, and stress analysis.

[0112] S12. Based on the rule elements of pole and tower sub-components, establish the modeling parameter table corresponding to each pole and tower sub-component.

[0113] In this embodiment of the invention, a modeling parameter table for each pole sub-element is established based on the rule elements of the pole sub-element. The rule elements of the pole sub-element serve as parameter fields of the parameter table, responsible for storing the geometric parameters of the element. Business rules, geometric constraints, force constraints, and other conditions are defined in the software.

[0114] S13. Based on the modeling parameters in the modeling parameter table, construct a 3D model database of each tower sub-component.

[0115] In this embodiment of the invention, a three-dimensional model database of each pole and tower sub-element is constructed based on the modeling parameters in the modeling parameter table. By inputting reasonable parameters into the three-dimensional model database of each pole and tower sub-element, three-dimensional models of each pole and tower element such as main pole, crossarm and hanging point can be constructed. The rationality of the model is guaranteed by business rules, geometric constraints, force constraints and other conditions.

[0116] Step 202: Input the modeling parameters of the tower sub-components into the preset tower sub-component 3D model database, and output multiple corresponding initial tower sub-component models.

[0117] In this embodiment of the invention, the modeling requirements parameters of each pole sub-component of the overhead line project for the construction of the three-dimensional model of the overhead line are input into the preset three-dimensional model database of the pole sub-component. It is worth mentioning that the preset three-dimensional model data of the pole sub-component here refers to the three-dimensional model database of the pole sub-component constructed in steps S11-S13, and outputs multiple corresponding initial pole sub-component models.

[0118] Furthermore, step 203 includes the following preceding steps:

[0119] S21. Based on the tower selection rule elements, establish multiple corresponding selection data tables.

[0120] Furthermore, the elements of the pole selection rules include load conditions, geographical conditions, pole structure type, material type, pole height, pole type, meteorological conditions, reliability conditions, and cost conditions;

[0121] The load requirements include current, voltage, and equipment capacity.

[0122] Geographical conditions include geological type and burial depth;

[0123] Meteorological conditions include maximum temperature, minimum temperature, annual average temperature, basic wind speed, maximum icing, switching overvoltage, lightning overvoltage, installation conditions, and temperature, wind speed, and icing thickness under fault conditions.

[0124] Reliability conditions include conductor-to-ground distance, safe distance from crossings, avoidance of contaminated areas, and corrosion resistance of porcelain insulators;

[0125] The cost terms include the prices of each pole component and the pole head.

[0126] It is worth mentioning that the analysis should consider the load conditions, geographical conditions, tower structure type, material type, tower height, tower type, meteorological conditions, reliability conditions, and cost conditions of the project area.

[0127] The selection of power poles and towers needs to take into account the load requirements of the power distribution system, including current, voltage, and equipment capacity.

[0128] These requirements will determine the load-bearing capacity and design parameters of the tower.

[0129] Geographical and weather conditions are crucial for pole selection, as factors such as topography, soil type, wind speed, and climate directly affect pole design and wind resistance.

[0130] The properties and characteristics of materials affect the strength, durability, and weight of the tower, and also determine the cost of the tower.

[0131] In this embodiment of the invention, relevant parameters for pole selection are extracted, including engineering geographical conditions: geology (ordinary soil, firm soil, rock, loose sand and gravel, muddy pit), burial depth; meteorological conditions (temperature, wind speed, and ice thickness under various working conditions such as high temperature, low temperature, strong wind, icing, windy external passage, windless external passage, internal passage, annual average, installation, accident, and over-traction); and pole height, pole type, material, economic indicators, etc. Corresponding data tables are established by category, and the data is input.

[0132] In practical applications: When the temperature and the load on the power line (wind, ice) change, the stress and sag in the power line also change. To ensure the safe and reliable operation of the line, the tension and sag of the power line after changes in external conditions (temperature, load) are generally calculated according to at least eight operating conditions during the line design.

[0133] Maximum temperature: Calculate the maximum sag of the power line and check the safe distance between the power line and the ground and objects it crosses.

[0134] Lowest temperature: Power lines may experience maximum stress; check for insulator lifting or tower pull-up. Tension difference in load-bearing towers.

[0135] Average annual temperature: shockproof design of power lines.

[0136] Maximum wind speed: Checking the strength and stability of the tower. Safe distance after the conductor deviates from its position on the tower or within the span.

[0137] Normal icing: Checking the strength and stability of the tower. Checking unbalanced tension of the power lines, proximity of conductors and ground wires within the span, and safe distances from objects being crossed, etc.

[0138] Lightning overvoltage: Lightning protection design for power lines.

[0139] Operating overvoltage: Line insulation level design.

[0140] Installation: Check the installation conditions of the pole / tower. S22. Based on the selection constraints, associate the various selection data tables to construct a pole / tower selection rule dataset.

[0141] Selection constraints refer to the constraints imposed based on the type of main components. These constraints are used to link multiple selection data tables. For example, the usage conditions of a common pole require linking data tables or parameters such as meteorological conditions, geological conditions, number of circuits, voltage level, span range, and turning angle range to create a linkage table.

[0142] It is worth mentioning that, based on the selection constraints, various selection data tables are linked, thereby digitizing the tower selection rules.

[0143] Of course, there are at least dozens of related tables, including tables for burial depth, economic indicators, crossarms, crossarm hanging points, and foundations, etc.

[0144] The selection rules for steel pipe poles, gate poles, triple poles, and large-pole poles are the same as those for ordinary poles, only the selection conditions are different.

[0145] In this embodiment of the invention, based on the selection constraints, each selection data table is associated to construct a pole selection rule dataset consisting of multiple pole selection rules.

[0146] It's worth noting that after the pole selection rules are established, multi-objective selection conditions need to be created for different types of equipment, regions, or users. In the software, this corresponds to a dynamic relational table.

[0147] For example, for customers in a certain project area, in addition to the selection criteria required by the standard design, users prioritize the following factors: design safety, low cost, ease of construction, and reliable operation.

[0148] Therefore, the weight of rules related to design safety (such as the distance between conductors and the ground, and the safe distance between conductors and objects) should be increased.

[0149] Economic indicators (such as market prices of shaft and clubhead materials) are secondary;

[0150] Convenient construction (e.g., distance for manual transport, construction site, assembly workload);

[0151] Operational reliability (e.g., avoidance of contaminated areas, corrosion resistance of porcelain insulators) should be considered last.

[0152] S23. Use the pole selection rule dataset as input to train the preset initial pole selection rule model and generate the corresponding optimized pole selection rule model.

[0153] The preset initial tower selection rule model refers to the initial selection rule model built using a convolutional neural network as the initial network.

[0154] In this embodiment of the invention, a preset initial pole selection rule model is trained by inputting a pole selection rule dataset. Through continuous training, the rule weights related to each selection condition are adjusted to generate a corresponding optimized pole selection rule model.

[0155] It's worth noting that after the pole selection rules are established, multi-objective selection conditions need to be created for different types of equipment, regions, or users. In the software, this corresponds to a dynamic relational table.

[0156] For example, for customers in a certain project area, in addition to the selection criteria required by the standard design, users prioritize the following factors: design safety, low cost, ease of construction, and reliable operation.

[0157] Therefore, the relevant rule weights of design safety (such as conductor-to-ground distance and safe distance from crossing objects) in the preset initial tower selection rule model should be increased;

[0158] Economic indicators (such as market prices of shaft and clubhead materials) are secondary;

[0159] Convenient construction (e.g., distance for manual transport, construction site, assembly workload);

[0160] Operational reliability (e.g., avoidance of contaminated areas, corrosion resistance of porcelain insulators) should be considered last.

[0161] Among the multiple options that meet the selection rules given in the pole selection process, the decision is made according to different weights in the pole selection rule model based on the multi-objective selection conditions, and an optimal solution is selected. Corresponding objective constraints are established for different types of equipment, different regions, and even different users. Users can adjust the priority and weight ratio of the multi-objectives.

[0162] Step 203: Input the tower selection elements to be modeled into the preset optimized tower selection rule model, and output the corresponding multi-objective optimized tower selection rules.

[0163] In this embodiment of the invention, the tower model selection conditions for constructing a three-dimensional model of an overhead power line project are used as inputs to a preset optimized tower selection rule model. It is worth mentioning that the preset optimized tower selection rule model here refers to the optimized tower selection rule model constructed in steps S21-S23. The preset optimized tower selection rule model outputs a set of optimal solutions, that is, multi-objective optimized tower selection rules.

[0164] Step 204: Based on the multi-objective optimization tower selection rules, match multiple target tower sub-component models from multiple initial tower sub-component models to construct the three-dimensional models of each optimized tower.

[0165] In this embodiment of the invention, based on the multi-objective optimization tower selection rules, multiple target tower sub-component models that conform to the multi-objective optimization tower selection rules are selected from multiple initial tower sub-component models. The target tower sub-component models are specifically used to construct the three-dimensional model of the optimized tower.

[0166] Furthermore, step 205 includes the following:

[0167] S31. Detect the dimensional and shape data of each tower sub-component model.

[0168] In this embodiment of the invention, the size and shape data of each tower sub-component model are detected.

[0169] S32. Based on the dimensional and shape data, determine the component type information of each tower sub-component model.

[0170] Component type information refers to the specific type of the tower sub-component model, such as the trunk sub-component model, crossarm sub-component model, etc.

[0171] In this embodiment of the invention, the component type information of each tower sub-component model is determined based on the size data and shape data.

[0172] S33. Input the preset sub-component attachment point model with the information of each component type, and output the corresponding attachment point information.

[0173] The pre-set sub-component attachment point model refers to a pre-trained neural network model of sub-component attachment points. By analyzing and learning from a large amount of existing 3D model data, it can automatically identify and extract the size and shape parameters of most components (a small number cannot be identified and extracted, requiring manual processing, such as the identification of the pole head of a gate pole. Because the sample size is small, machine learning is not necessary). Through image recognition and machine learning techniques, the model's size, relationships, and constraints are automatically identified and labeled to determine the attachment point information of each tower sub-component model.

[0174] The attachment point information refers to the specific attachment point information of the pole sub-component model.

[0175] In this embodiment of the invention, the preset sub-element attachment point model is input with information on each element type, and the corresponding attachment point information is output.

[0176] S34. Based on the information of each component type, determine the main pole component model from each pole sub-component model.

[0177] In this embodiment of the invention, based on the information of each component type, it is possible to directly determine which models are main pole component models from multiple pole sub-component models.

[0178] S35. Based on the attachment point information, use a 3D modeling platform to establish a series of local coordinate systems with the center coordinates of the main rod component model as the origin.

[0179] In this embodiment of the invention, a series of local coordinate systems with the center coordinates of the main rod component model as the origin are established on the three-dimensional modeling platform, with the main rod component model's main component model's main component model as the center.

[0180] The centerline of the main rod component model is the x-axis, the positive z-axis points to the center of the main rod component model, and the y-axis is established using the right-hand coordinate system rule.

[0181] S36. Based on the component type information and the attachment point information, place the sub-component models of each tower in the corresponding local coordinate system to establish multiple optimized tower 3D models.

[0182] In this embodiment of the invention, based on the component type information and the attachment point information, each tower sub-component model is placed in the corresponding local coordinate system to establish multiple optimized tower 3D models.

[0183] For example, a three-dimensional model of a cement pole is assembled from components such as the main pole, crossarm, clamps, insulators, and bolts.

[0184] During component assembly, dependencies between components will be established, and collision checks and safety distance verifications will be performed to ensure compliance with equipment assembly logic.

[0185] For example, when a crossarm is attached to a main pole, the parameter constraints include: the main pole to which the crossarm belongs, the distance of the crossarm from the top of the pole, etc.

[0186] Insulators are attached to crossarms or clamps, and the parameters constrained include: the crossarm to which the insulator belongs, the distance from the starting point of the crossarm, etc.

[0187] S37. Based on DirectX rendering technology, render multiple optimized tower 3D models to generate multiple rendered tower 3D models.

[0188] DirectX rendering technology, specifically D3D11 rendering, is a 3D graphics rendering technology based on the DirectX API. The rendering principle of D3D11 is based on parallel computing on the GPU, which can efficiently process large amounts of graphics data, thus achieving high-quality 3D rendering. The D3D11 rendering process can be divided into several key steps, including geometry processing, rasterization, and shader processing. Geometry processing converts the 3D model into a data format that the GPU can process; rasterization maps 2D graphics onto the screen; and shader processing performs color calculations on pixels.

[0189] In this embodiment of the invention, DirectX rendering technology is used to render multiple optimized tower 3D models, generating multiple rendered tower 3D models, and completing the 3D modeling of each component of the tower in a 3D scene.

[0190] S38. Convert the formats of multiple rendered tower 3D models and build an optimized tower 3D model database.

[0191] In this embodiment of the invention, the completed model is finally published in a data format used by the 3D platform to establish an optimized 3D model database for towers.

[0192] Step 205: Input the sub-component models of each target tower into the preset optimized tower 3D model database, and output multiple corresponding optimized tower 3D models.

[0193] In this embodiment of the invention, the target tower sub-component models are input into a preset optimized tower 3D model database, and multiple corresponding optimized tower 3D models are output. It is worth noting that the optimized tower 3D model database refers to the optimized tower 3D model database constructed in steps S31-S38.

[0194] It is worth mentioning that multiple corresponding optimized tower 3D models are output in the form of files, and the output model files are encrypted in AES mode to ensure the security of model data.

[0195] Step 206: Analyze the overhead line construction path and determine multiple optimized tower locations corresponding to the target overhead line.

[0196] Optimizing tower locations refers to the placement of each tower sub-component model at its designated location.

[0197] In this embodiment of the invention, the overhead line construction path is analyzed to determine multiple optimized tower locations corresponding to the target overhead line.

[0198] Step 207: Based on the order of each optimized tower location, select the corresponding constructed tower 3D model from multiple optimized tower 3D models and place it in the associated optimized tower location.

[0199] In this embodiment of the invention, based on the order of each optimized tower location, the corresponding constructed tower 3D model is selected from multiple optimized tower 3D models and placed in the associated optimized tower location.

[0200] For example, if the user's project is an overhead line project with a voltage level of 10kV and a double-circuit line, the software will automatically filter out the 3D model of the 10kV double-circuit pole type (optimized to meet multiple objectives of safety, reliability, and economy) for the user to choose from.

[0201] When the user selects the first tower, the system will automatically match the 3D model of the 10kV double-circuit terminal tower.

[0202] The second tower uses a 10kV double-circuit straight-line tower construction tower three-dimensional model.

[0203] Once the location of the third tower is determined, the type of the second tower will be adjusted according to its location. Depending on the business rules, it will be adjusted to an angle tower, a tension tower, or the straight tower type will remain unchanged. The 3D model of the tower will then be placed in the associated optimized tower location.

[0204] Step 208: Match the corresponding 3D model of the pole head according to the type of the 3D model of the pole tower.

[0205] In this embodiment of the invention, the selection of the type of the subsequent base tower will affect the selection of the pole head of the previous base tower. Therefore, it is necessary to match the corresponding three-dimensional model of the pole head according to the type of the three-dimensional model of the tower.

[0206] For example: if it is a high-voltage line with a low-voltage line, the pole head should also be a high-voltage line with a low-voltage line.

[0207] If the user selects a dual-loop tower but only draws one loop, the dual-loop tower model must still be used, and the other loop will be drawn later.

[0208] If branch lines are drawn on tension poles or straight poles, the branch pole head of the tension pole or straight pole needs to be replaced; if it is a front (rear) terminal pole, the conductor needs to be correctly connected to the rear (front) suspension point group, and the front (rear) suspension point group needs to be deleted.

[0209] At the same time, the pole head angle needs to be adjusted according to the route. The default pole head is 0 degrees. The angle of the crossarm and insulator of the pole head needs to be rotated according to the actual route angle, and the conductor is correctly connected to the corresponding hanging point group.

[0210] Step 209: Connect multiple 3D models of the towers using wires to construct the target overhead line.

[0211] In this embodiment of the invention, multiple front and rear tower hanging point groups that construct a three-dimensional model of a tower are connected by wires to construct the target overhead line.

[0212] In this invention, in response to a received overhead line modeling request, the modeling parameters of the tower sub-components, the selection elements of the towers to be modeled, and the overhead line construction path corresponding to the overhead line modeling request are determined. The modeling parameters of the tower sub-components are input into a preset 3D model database of tower sub-components, outputting multiple corresponding initial tower sub-component models. The selection elements of the towers to be modeled are input into a preset optimized tower selection rule model, outputting corresponding multi-objective optimized tower selection rules. Based on the multi-objective optimized tower selection rules, multiple target tower sub-component models for constructing each optimized tower 3D model are matched from the multiple initial tower sub-component models. Each target tower sub-component model is input into a preset optimized tower 3D model database, outputting multiple corresponding optimized tower 3D models. The overhead line construction path is then analyzed. This method constructs target overhead lines based on multiple optimized 3D models of towers. It addresses the problem that traditional overhead line modeling often relies on engineers' experience and subjective judgment, leading to inconsistencies and inaccuracies in tower selection. Furthermore, it typically considers only a single objective, failing to fully meet the multi-objective requirements of overhead line modeling. This method reduces the number of tower 3D models and the workload involved in constructing the 3D model of an overhead line, adapting to the complex and ever-changing design of overhead lines in distribution network engineering. It improves the efficiency and quality of 3D design work in distribution network engineering. Simultaneously, during the modeling process, based on the conductors associated with the towers, it can automatically adapt the tower head angle to generate a 3D overhead line for the distribution network, enabling dynamic combination and adjustment of towers and tower heads.

[0213] Please see Figure 3 , Figure 3 This is a structural block diagram of a three-dimensional modeling system for overhead power lines provided in Embodiment 3 of the present invention.

[0214] This invention provides a three-dimensional modeling system for overhead power lines, comprising:

[0215] The response module 301 is used to respond to the received overhead line modeling request and determine the modeling parameters of the pole sub-components, the modeling elements of the pole to be modeled, and the overhead line construction path corresponding to the overhead line modeling request.

[0216] The initial tower sub-component model module 302 is used to input the tower sub-component model parameters to be modeled into a preset tower sub-component 3D model database and output multiple corresponding initial tower sub-component models.

[0217] The tower selection optimization rule module 303 is used to take the tower selection elements to be modeled as input to the preset tower selection optimization rule model and output the corresponding multi-objective tower selection optimization rules.

[0218] The target tower sub-component model module 304 is used to match multiple target tower sub-component models from multiple initial tower sub-component models to construct the three-dimensional models of each optimized tower based on multi-objective optimization tower selection rules.

[0219] The optimized tower 3D model module 305 is used to input the model of each target tower sub-component into the preset optimized tower 3D model database and output multiple corresponding optimized tower 3D models.

[0220] The target overhead line module 306 is used to parse the overhead line construction path and construct the target overhead line based on multiple optimized tower 3D models.

[0221] Furthermore, it also includes:

[0222] The pole / tower sub-component rule element module is used to extract pole / tower sub-component rule elements;

[0223] The modeling parameter table module is used to create a modeling parameter table for each tower sub-component based on the tower sub-component rule elements.

[0224] The tower sub-component 3D model database module is used to construct a 3D model database for each tower sub-component based on the modeling parameters in the modeling parameter table.

[0225] Furthermore, the structural elements of the pole sub-components include key structural elements of the main pole, key structural elements of the crossarm, structural elements of the hanging point, structural elements of the insulator, structural elements of the pole top clamp, structural elements of the angle steel, and structural elements of the diagonal brace;

[0226] Key elements of the main pole rule include name, color, material, pole height, embedment depth, tip diameter, taper, and inclination angle;

[0227] Key elements of the crossarm specification include name, color, type, rotation angle, angle steel length, leg width, leg thickness, location, presence of left and right diagonal braces, and dimensions of the left and right diagonal braces;

[0228] The hanging point rule elements include the names of the left and right hanging point groups, the number of hanging points, the location of the hanging point groups, and the insulator where each hanging point is located;

[0229] The insulator specification elements include name, color, type, total length, number of discs, disc radius, rotation angle around the axis, x-angle, z-angle, etc., the angle steel to which it belongs, and location;

[0230] The standard elements for pole top clamps include name, color, type, pole height, clamp height, clamp spacing, steel plate width, steel plate thickness, and rotation angle around the pole.

[0231] The standard elements for angle steel include color, length, leg width, and leg thickness;

[0232] The elements of the diagonal brace rule include color, whether there is a left diagonal brace, whether there is a right diagonal brace, vertical height of the diagonal brace, horizontal length of the diagonal brace, and bottom edge length of the diagonal brace.

[0233] Furthermore, it also includes:

[0234] The selection data table module is used to create multiple corresponding selection data tables based on tower selection rule elements;

[0235] The pole and tower selection rule dataset module is used to construct a pole and tower selection rule dataset by associating various selection data tables according to selection constraints.

[0236] The model training module is used to train a preset initial pole selection rule model by inputting a pole selection rule dataset, and to generate a corresponding optimized pole selection rule model.

[0237] Furthermore, the elements of the pole selection rules include load conditions, geographical conditions, pole structure type, material type, pole height, pole type, meteorological conditions, reliability conditions, and cost conditions;

[0238] The load requirements include current, voltage, and equipment capacity.

[0239] Geographical conditions include geological type and burial depth;

[0240] Meteorological conditions include maximum temperature, minimum temperature, annual average temperature, basic wind speed, maximum icing, switching overvoltage, lightning overvoltage, installation conditions, and temperature, wind speed, and icing thickness under fault conditions.

[0241] Reliability conditions include conductor-to-ground distance, safe distance from crossings, avoidance of contaminated areas, and corrosion resistance of porcelain insulators;

[0242] The cost terms include the prices of each pole component and the pole head.

[0243] Furthermore, it also includes:

[0244] The detection module is used to detect the dimensional and shape data of each tower sub-component model;

[0245] The component type information module is used to determine the component type information of each tower sub-component model based on the size data and shape data;

[0246] The attachment point information module is used to input the preset sub-component attachment point model with the information of each component type and output the corresponding attachment point information.

[0247] The main pole sub-component module is used to determine the main pole component model from the sub-component models of each pole based on the component type information.

[0248] The local coordinate system module is used to establish a series of local coordinate systems with the center coordinates of the main rod sub-component model as the origin based on the attachment point information and the 3D modeling platform.

[0249] The component splicing module is used to place each tower sub-component in the corresponding local coordinate system according to the component type information and the attachment point information, and to establish multiple optimized tower 3D models.

[0250] The rendering module is used to render multiple optimized tower 3D models based on DirectX rendering technology, generating multiple rendered tower 3D models.

[0251] The format conversion module is used to convert the formats of multiple rendered tower 3D models and build an optimized tower 3D model database.

[0252] Furthermore, the target overhead line module 306 includes:

[0253] The parsing submodule is used to parse the overhead line construction path and determine multiple optimized tower locations corresponding to the target overhead line to be constructed.

[0254] The selection submodule is used to select the corresponding 3D model of the building tower from multiple 3D models of the optimized towers and place it in the associated optimized tower points based on the order of each optimized tower point.

[0255] The matching submodule is used to match the corresponding 3D model of the pole head based on the type of 3D model of the pole tower being constructed.

[0256] The conductor connection submodule is used to connect multiple 3D models of building towers using conductors to construct the target overhead line.

[0257] In this invention, in response to a received overhead line modeling request, the modeling parameters of the tower sub-components, the selection elements of the towers to be modeled, and the overhead line construction path corresponding to the overhead line modeling request are determined. The modeling parameters of the tower sub-components are input into a preset 3D model database of tower sub-components, outputting multiple corresponding initial tower sub-component models. The selection elements of the towers to be modeled are input into a preset optimized tower selection rule model, outputting corresponding multi-objective optimized tower selection rules. Based on the multi-objective optimized tower selection rules, multiple target tower sub-component models for constructing each optimized tower 3D model are matched from the multiple initial tower sub-component models. Each target tower sub-component model is input into a preset optimized tower 3D model database, outputting multiple corresponding optimized tower 3D models. The overhead line construction path is then analyzed. This method constructs target overhead lines based on multiple optimized 3D models of towers. It addresses the problem that traditional overhead line modeling often relies on engineers' experience and subjective judgment, leading to inconsistencies and inaccuracies in tower selection. Furthermore, it typically considers only a single objective, failing to fully meet the multi-objective requirements of overhead line modeling. This method reduces the number of tower 3D models and the workload involved in constructing the 3D model of an overhead line, adapting to the complex and ever-changing design of overhead lines in distribution network engineering. It improves the efficiency and quality of 3D design work in distribution network engineering. Simultaneously, during the modeling process, based on the conductors associated with the towers, it can automatically adapt the tower head angle to generate a 3D overhead line for the distribution network, enabling dynamic combination and adjustment of towers and tower heads.

[0258] An electronic device according to an embodiment of the present invention includes: a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor performs a three-dimensional modeling method for overhead lines as described in any of the above embodiments.

[0259] The memory can be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory has storage space for program code used to perform any of the method steps described above. For example, the storage space for program code may include individual program codes for implementing the various steps in the methods described above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above.

[0260] This invention provides a computer-readable storage medium storing a computer program that, when executed, implements a three-dimensional modeling method for overhead lines as described in any embodiment of this invention.

[0261] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0262] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods 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 coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0263] 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.

[0264] Furthermore, the functional units in the various embodiments of the present invention 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.

[0265] 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 medium. Based on this understanding, the technical solution of the present invention, 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 storage medium 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 described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0266] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A three-dimensional modeling method for overhead power lines, characterized in that, include: In response to a received overhead line modeling request, determine the modeling parameters of the tower sub-components corresponding to the overhead line modeling request, the selection elements of the tower to be modeled, and the overhead line construction path; The parameters to be modeled for the tower sub-components are input into a preset three-dimensional model database of tower sub-components, and multiple corresponding initial tower sub-component models are output. The selected tower elements to be modeled are used as input to a preset optimized tower selection rule model, and the corresponding multi-objective optimized tower selection rules are output. Based on the multi-objective optimization tower selection rules, multiple target tower sub-component models for constructing each optimized tower 3D model are matched from multiple initial tower sub-component models. Each target tower sub-component model is input into a preset optimized tower 3D model database, and multiple corresponding optimized tower 3D models are output. The overhead line construction path is analyzed, and the target overhead line is constructed based on multiple optimized tower 3D models; Also includes: Extract the rule elements of the tower components; Based on the rule elements of the tower sub-components, establish a modeling parameter table corresponding to each tower sub-component; Based on the modeling parameters in the modeling parameter table, a three-dimensional model database of each tower sub-element is constructed. The pole sub-components include key elements of the main pole, key elements of the crossarm, elements of the hanging point, elements of the insulator, elements of the pole top clamp, elements of the angle steel, and elements of the diagonal brace. The key elements of the main pole rule include name, color, material, pole height, embedment depth, tip diameter, taper, and inclination angle; The key elements of the crossarm rule include name, color, type, rotation angle, angle steel length, leg width, leg thickness, position, whether there are left and right diagonal braces, and the size data of the left and right diagonal braces; The hanging point rule elements include the names of the left and right hanging point groups, the number of hanging points, the location of the hanging point groups, and the insulator where each hanging point is located; The insulator rule elements include name, color, type, total length, number of pieces, piece radius, rotation angle around the axis, x-angle, z-angle, associated angle steel, and position; The pole top clamp rule elements include name, color, type, pole height, clamp height, clamp spacing, steel plate width, steel plate thickness, and rotation angle around the pole; The standard elements of the angle steel include color, length, leg width, and leg thickness; The diagonal bracing rule elements include color, whether there is a left diagonal bracing, whether there is a right diagonal bracing, vertical height of the diagonal bracing, horizontal length of the diagonal bracing, and bottom edge length of the diagonal bracing; Also includes: Detect the dimensional and shape data of each tower sub-component model; Based on the dimensional data and the shape data, determine the component type information of each of the tower sub-component models; The preset sub-component attachment point model is input with the component type information, and the corresponding attachment point information is output. Based on the component type information, determine the main pole component model from each of the pole sub-component models; Based on the attachment point information, a series of local coordinate systems with the center coordinates of the main rod sub-component model as the origin are established using a 3D modeling platform; Based on the component type information and the attachment point information, each of the tower sub-component models is placed in the corresponding local coordinate system to establish multiple optimized tower 3D models; Based on DirectX rendering technology, multiple optimized tower 3D models are rendered to generate multiple rendered tower 3D models. The formats of multiple rendered tower 3D models are converted to construct an optimized tower 3D model database.

2. The three-dimensional modeling method for overhead lines according to claim 1, characterized in that, Also includes: Based on the tower selection rule elements, multiple corresponding selection data tables are established; Based on the selection constraints, link the various selection data tables to construct a pole and tower selection rule dataset; The preset initial pole selection rule model is trained using the pole selection rule dataset as input to generate the corresponding optimized pole selection rule model.

3. The three-dimensional modeling method for overhead lines according to claim 2, characterized in that, The elements of the pole and tower selection rules include load conditions, geographical conditions, pole and tower structure type, material type, pole height, pole type, meteorological conditions, reliability conditions, and cost conditions; The load conditions include current, voltage, and equipment capacity; The geographical conditions include geological type and burial depth; The meteorological conditions include the highest temperature, lowest temperature, annual average temperature, basic wind speed, maximum icing, switching overvoltage, lightning overvoltage, temperature, wind speed, and icing thickness under the conditions of installation status and accidental line disconnection. The reliability conditions include the distance between the conductor and the ground, the safe distance to objects crossed, the avoidance of contaminated areas, and the corrosion resistance of the porcelain insulator. The cost terms include the prices of each pole sub-component and the pole head.

4. The three-dimensional modeling method for overhead lines according to claim 1, characterized in that, The step of analyzing the overhead line construction path and constructing the target overhead line based on multiple optimized tower 3D models includes: Analyze the overhead line construction path to determine multiple optimized tower locations corresponding to the target overhead line; Based on the order of the optimized tower locations, corresponding 3D models of the constructed towers are selected from multiple optimized tower 3D models and placed in the associated optimized tower locations. Based on the type of the constructed tower 3D model, match the corresponding constructed pole head 3D model; The target overhead line is constructed by connecting multiple three-dimensional models of the construction towers with conductors.

5. A three-dimensional modeling system for overhead power lines, characterized in that, The three-dimensional modeling system for overhead lines is used to implement the three-dimensional modeling method for overhead lines as described in any one of claims 1-4, wherein the three-dimensional modeling system for overhead lines comprises: The response module is used to respond to the received overhead line modeling request and determine the modeling parameters of the tower sub-components, the selection elements of the tower to be modeled, and the overhead line construction path corresponding to the overhead line modeling request. The initial tower sub-component model module is used to input the tower sub-component model parameters to be modeled into a preset tower sub-component 3D model database and output multiple corresponding initial tower sub-component models. The tower selection optimization rule module is used to input the tower selection elements to be modeled into a preset tower selection optimization rule model and output the corresponding multi-objective tower selection optimization rules. The target tower sub-component model module is used to match multiple target tower component models from multiple initial tower sub-component models to construct the three-dimensional models of each optimized tower, based on the multi-objective optimized tower selection rules. The optimized tower 3D model module is used to input the target tower sub-component models into a preset optimized tower 3D model database and output multiple corresponding optimized tower 3D models. The target overhead line module is used to parse the overhead line construction path and construct the target overhead line based on multiple optimized tower 3D models.

6. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the three-dimensional modeling method for overhead lines as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the three-dimensional modeling method for overhead lines as described in any one of claims 1-4.

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