Power distribution equipment point cloud data modeling processing method, system, equipment and medium

Abstract

The invention discloses a power distribution equipment point cloud data modeling processing method, system, equipment and medium, and belongs to the technical field of power equipment modeling and simulation, and the method comprises the steps: obtaining meteorological data and point cloud data, constructing a three-dimensional model, and adjusting the modeling parameters of the three-dimensional model through the meteorological data; establishing a state equation according to the adjusted modeling parameters, and calculating stress distribution data; introducing a windage yaw influence parameter through the stress distribution data in combination with sag data, and generating sag distribution data; combining the stress distribution data, the sag distribution data and the point cloud data to establish a macroscopic three-dimensional model and a microscopic three-dimensional model; and fusing the macroscopic three-dimensional model and the microscopic three-dimensional model to generate a multi-scale comprehensive model, and performing simulation analysis on the comprehensive model. According to the invention, accurate modeling of the power distribution equipment under different meteorological conditions is realized, and the stress distribution and the motion trail of the wire under different working conditions are simulated.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of power equipment modeling and simulation, in particular to a power distribution equipment point cloud data modeling processing method and system device and medium. BACKGROUND

[0002] With the rapid development of the power system, efficient operation and maintenance of power distribution equipment become more and more important, and with the continuous progress of three-dimensional laser scanning technology and point cloud data processing technology, the modeling method based on point cloud data gradually becomes a research hotspot, through high-resolution point cloud data, a high-precision three-dimensional model can be generated, which provides a new means for structural analysis and fault diagnosis of power distribution equipment, and the existing point cloud data modeling method still has some deficiencies in processing power distribution equipment under complex environmental conditions, especially in dynamic modeling combined with meteorological data, and the existing technology is particularly insufficient.

[0003] The existing modeling method ignores the high-resolution characteristics and geometric details of the point cloud data when processing the point cloud data, resulting in low precision of the generated model, which cannot accurately reflect the real state of the equipment under different working conditions, and in the calculation of conductor stress and sag, the existing method usually adopts a simplified mathematical model, which cannot accurately simulate the stress distribution and sag change of the conductor under different meteorological conditions. SUMMARY

[0004] In view of the above problems, the present application is proposed.

[0005] Therefore, the technical problem solved by the present application is: how to use a power distribution equipment point cloud data modeling processing method to collect meteorological data and point cloud data, construct a three-dimensional model, establish a state equation to calculate stress distribution data according to model parameters, use stress distribution data to generate sag distribution data combined with sag data and wind deflection influence parameters, combine stress distribution data, sag distribution data, and point cloud data to establish macro three-dimensional model and micro three-dimensional model, and finally fuse macro three-dimensional model and micro three-dimensional model and simulate and analyze feedback data, effectively solving the problem that the existing point cloud data modeling cannot correctly reflect the real state under different working conditions in dynamic modeling of meteorological data, and solving the problem that the conductor stress and sag calculation cannot correctly simulate the stress distribution and sag change of the conductor under different meteorological conditions.

[0006] To solve the above technical problems, the present application provides the following technical scheme: a power distribution equipment point cloud data modeling processing method, comprising the following steps,

[0007] The meteorological data and the point cloud data are acquired, a three-dimensional model is constructed, and modeling parameters of the three-dimensional model are adjusted through the meteorological data; a state equation is established according to the adjusted modeling parameters, stress distribution data are calculated; through the stress distribution data, in combination with sag data, a wind deviation influence parameter is introduced, and sag distribution data are generated; the stress distribution data, the sag distribution data, and the point cloud data are combined to establish a macro three-dimensional model and a micro three-dimensional model; the macro three-dimensional model and the micro three-dimensional model are fused to generate a multi-scale comprehensive model, and simulation analysis is performed on the comprehensive model.

[0008] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the meteorological data and the point cloud data are acquired, modeling is performed according to the meteorological data, and modeling parameters are adjusted through the meteorological data, including the following steps: the meteorological data of a region where the power distribution equipment is located are acquired; the point cloud data are acquired, and noise reduction processing is performed on the point cloud data; the meteorological data and the point cloud data after the noise reduction processing are modeled to obtain a three-dimensional model, and parameters in the three-dimensional model are adjusted according to changes in the acquired meteorological data.

[0009] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the state equation is established according to the modeling parameters to calculate stress distribution data, including the following steps: the state equation is established according to the modeling parameters, the stress value is calculated through the modeling parameters, the stress value is arranged according to the spatial position distribution of the conductor to obtain stress distribution data.

[0010] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the stress distribution data are combined with sag data to introduce a wind deviation influence parameter to generate sag distribution data, including the following steps: the stress distribution data are calculated to obtain a tension parameter through a stress distribution formula; the tension parameter and the sag data are introduced into a slant parabola equation to generate a wind deviation sag calculation model by introducing the wind deviation influence parameter; the wind deviation sag calculation model is applied to a spatial coordinate system of the three-dimensional model to calculate three-dimensional coordinates and generate sag distribution data; the sag data are calculated according to the stress distribution data of the conductor under different meteorological conditions, in combination with the conductor sag without wind deviation, and by using the slant parabola equation. The three-dimensional model of the preferred technical scheme expands the two-dimensional sag problem to a three-dimensional space problem, and shows the real spatial position of the conductor under complex meteorological conditions.

[0011] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the stress distribution data, the sag distribution data and the point cloud data are combined to generate macro three-dimensional models and micro three-dimensional models through modeling technology, including: taking the point cloud data as the basis, combining the stress distribution data and the sag data, and constructing a power transmission line overall structure model through vectorization modeling technology to generate a macro three-dimensional model.

[0012] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the stress distribution data, the sag distribution data and the point cloud data are combined to generate macro three-dimensional models and micro three-dimensional models through modeling technology, including: taking the point cloud data as the basis, combining the stress distribution data and the sag data, and constructing a power transmission line overall structure model through vectorization modeling technology to generate a macro three-dimensional model.

[0013] As a preferred scheme of the power distribution equipment point cloud data modeling processing method, the stress distribution data, the sag distribution data and the point cloud data are combined to generate macro three-dimensional models and micro three-dimensional models through modeling technology, including: taking the point cloud data as the basis, combining the stress distribution data and the sag data, and constructing a power transmission line overall structure model through vectorization modeling technology to generate a macro three-dimensional model.

[0014] The application provides a power distribution equipment point cloud data modeling processing system.

[0015] To solve the above technical problems, the application further provides the following technical solutions: a power distribution equipment point cloud data modeling processing system, comprising: a data collection and meteorological model establishment module, acquiring meteorological data and point cloud data, modeling according to the meteorological data, and adjusting modeling parameters through the meteorological data; a stress distribution data calculation and analysis module, establishing a state equation with the modeling parameters, and calculating stress distribution data; an arc sag distribution data calculation module, generating arc sag distribution data by introducing a wind deviation influence parameter through a slant parabola equation, combining the stress distribution data and arc sag data; a three-dimensional model construction module, combining the stress distribution data, the arc sag distribution data, and the point cloud data, and generating macroscopic and microscopic three-dimensional models through modeling technology; and a model fusion and simulation analysis module, fusing the macroscopic and microscopic three-dimensional models to generate a multi-scale comprehensive model, and performing simulation analysis on the comprehensive model.

[0016] The application provides a computer device, comprising a memory and a processor, and the memory stores a computer program, and the processor implements the steps of the power distribution equipment point cloud data modeling processing method when executing the computer program.

[0017] The application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the power distribution equipment point cloud data modeling processing method.

[0018] The application has the beneficial effects that: by collecting meteorological data and point cloud data and preprocessing, modeling of power distribution equipment under different meteorological conditions is realized, a state equation is formed by combining temperature, humidity and wind speed, stress distribution of a conductor under different meteorological conditions is calculated, the arc sag of the conductor under no wind deviation and wind load is combined, the arc sag of the wind deviation conductor is calculated by using a slant parabola equation, accurate calculation of the conductor arc sag is realized, the conductor stress and arc sag data are combined with the point cloud data, a macroscopic three-dimensional model is generated by using vectorization modeling technology, a microscopic three-dimensional model is generated by using geometric modeling technology, the multi-scale model can reflect the overall structure and local details of the power distribution equipment at the same time, and simulation can simulate the stress distribution and motion trajectory of the conductor under different working conditions, which is crucial for evaluating the safety and stability of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0020] Figure 1An overall flowchart is provided for an embodiment of the present application.

[0021] Figure 2 A flowchart for generating sag distribution data is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0023] Embodiment 1, reference Figure 1 For the first embodiment of the present application, the embodiment provides a power distribution equipment point cloud data modeling processing method, comprising:

[0024] S100: Obtain meteorological data and point cloud data, and construct a three-dimensional model, and adjust the modeling parameters of the three-dimensional model through the meteorological data.

[0025] S200: Establish a state equation according to the adjusted modeling parameters, and calculate stress distribution data.

[0026] S300: Through the stress distribution data, combined with the sag data, introduce the wind deviation influence parameter, generate the sag distribution data.

[0027] S400: Combine the stress distribution data, the sag distribution data, and the point cloud data to establish a macro three-dimensional model and a micro three-dimensional model.

[0028] S500: Fuse the macro three-dimensional model and the micro three-dimensional model to generate a multi-scale comprehensive model, and perform simulation analysis on the comprehensive model.

[0029] It should be noted that the existing point cloud data modeling method in the processing of meteorological data for dynamic modeling, when processing point cloud data, ignores the high resolution characteristics and geometric details of point cloud data, resulting in low precision of the generated model, which cannot accurately reflect the real state of the equipment under different working conditions; At the same time, in the calculation of conductor stress and sag, the existing method usually uses a simplified mathematical model, which cannot accurately simulate the stress distribution and sag change of the conductor under different meteorological conditions.

[0030] Therefore, in order to solve the problems that the real state of the equipment under different working conditions cannot be accurately reflected and the stress distribution and sag change of the conductor under different weather conditions cannot be accurately simulated, the power distribution equipment point cloud data modeling processing is performed through the steps S100-S500. Firstly, the weather data and the point cloud data are obtained, and a three-dimensional model is constructed. Secondly, a state equation is established according to the modeling parameters, and the stress distribution data is calculated. Then, the stress distribution data is combined with the sag data, the wind deflection influence parameter is introduced, and the sag distribution data is generated. Then, the stress distribution data, the sag distribution data, and the point cloud data are used to construct a macro three-dimensional model and a micro three-dimensional model. Finally, the macro three-dimensional model and the micro three-dimensional model are fused to generate a multi-scale comprehensive model, which realizes the accurate modeling of the power distribution equipment under different weather conditions, and simulates the stress distribution and the motion trajectory of the conductor under different working conditions.

[0031] Embodiment 2, refer to Figure 1 and Figure 2 The second embodiment of the present application provides a power distribution equipment point cloud data modeling processing method.

[0032] In the embodiment of the present application, the weather data and the point cloud data are obtained in step S100, and a three-dimensional model is constructed, and the modeling parameters of the three-dimensional model are adjusted through the weather data. The weather data includes temperature, humidity and wind speed, and includes the following steps A1-A3.

[0033] A1: Obtain the weather data of the region where the power distribution equipment is located.

[0034] A2: Obtain the point cloud data and perform noise reduction processing on the point cloud data.

[0035] A3: Model the weather data and the noise-reduced point cloud data to obtain a three-dimensional model, and adjust the parameters in the three-dimensional model according to the changes in the obtained weather data.

[0036] In an optional embodiment, the weather data of the region where the power distribution equipment is located can also be obtained by standard weather data API to obtain temperature, humidity and wind speed parameters.

[0037] In another optional embodiment, the weather data of the region where the power distribution equipment is located can also be obtained by deploying wireless sensor nodes to collect real-time field weather data.

[0038] It should be noted that when modeling the weather data and the point cloud data, the spatial scale consistency needs to be maintained, which can be achieved by establishing a hierarchical parameter adjustment mechanism, using the weather data to make macro adjustments to the overall model, and then fine-tuning the details according to the local climate characteristics in the point cloud data. This method not only ensures the consistency of the whole, but also reflects the particularity of the local.

[0039] In the embodiment of the present application, the state equation is established according to the modeling parameters in step S200, and the stress distribution data is calculated, including the following steps B1-B2:

[0040] B1: The state equation is established by the modeling parameters, and the stress value is calculated.

[0041] B2: The stress value is arranged according to the spatial position distribution of the conductor to obtain the stress distribution data.

[0042] In an optional embodiment, the meteorological data of the area where the power distribution equipment is located can also obtain temperature, humidity, and wind speed parameters through a standard meteorological data API.

[0043] In another optional embodiment, the meteorological data of the area where the power distribution equipment is located can also be obtained by deploying wireless sensor nodes to collect real-time field meteorological data.

[0044] Specifically, in step B2, the specific form of calculating the stress distribution data is:

[0045]

[0046] Where σ(T, H, V) is the conductor stress, T is the current temperature, H is the humidity, V is the wind speed, L(T) is the conductor length, γ is the specific load, F w (V) is the wind load, E(H) is the elastic modulus, and A is the windward area of the conductor.

[0047] In the embodiment of the present application, in step S300, the stress distribution data is combined with the sag data to introduce the windage influence parameter to generate the sag distribution data, including the following steps C1-C3:

[0048] C1: The stress distribution data is calculated to obtain the tension parameter through the stress distribution formula.

[0049] C2: The tension parameter and the sag data are introduced into the oblique parabolic equation by introducing the windage influence parameter to generate a windage sag calculation model.

[0050] C3: The windage sag calculation model is applied to the spatial coordinate system of the three-dimensional model to calculate the three-dimensional coordinates and generate the sag distribution data; the sag data is calculated by the oblique parabolic equation according to the stress distribution data of the conductor under different meteorological conditions, combined with the conductor sag without windage.

[0051] Specifically, in step C3, the specific form of calculating the conductor sag without windage is:

[0052]

[0053] Where f total(T, H, V) is the conductor comprehensive sag, T is the temperature, H is the humidity, V is the wind speed, f0 is the conductor sag when there is no wind bias, F w (V) is the wind load, U is the span, Y is the horizontal tension, E(H) is the elastic modulus, σ(T, H, V) is the conductor stress.

[0054] Specifically, in step C3, the specific form of the sag distribution data is calculated as:

[0055]

[0056] Wherein, D(x, y, z) is the fused comprehensive data, P(x, y, z) is the point cloud data, L is the length of the conductor, D is the position of the coordinate point (x, y, z) in the fused comprehensive data, P is the position of the coordinate point (x, y, z) in the point cloud data, x is the horizontal coordinate in the three-dimensional space, y is the vertical coordinate in the three-dimensional space, and z is the elevation coordinate in the three-dimensional space.

[0057] Further, the stress distribution of the conductor under different working conditions is calculated, the stress values of the conductor at different positions are recorded, and the stress distribution diagram is generated using a visualization tool to display the stress values of the conductor at different positions, helping engineers to evaluate the stress of the conductor under different working conditions and ensure the safety and stability of the conductor.

[0058] According to the wind load of the conductor, the position of the conductor at different time points is calculated as:

[0059]

[0060] Wherein, m is the mass of the conductor, t is the time, x(t) is the position of the conductor in the x direction at t time, x0 is the initial position of the conductor in the x direction, is the initial velocity of the conductor in the x direction, t is the time, F wx is the wind load on the conductor in the x direction;

[0061] Wherein, y(t) is the position of the conductor in the y direction at t time, y0 is the initial position of the conductor in the y direction, is the initial velocity of the conductor in the y direction, F wy is the wind load on the conductor in the y direction;

[0062] Wherein, z(t) is the position of the conductor in the z direction at t time, z0 is the initial position of the conductor in the z direction, is the initial velocity of the conductor in the z direction, F wz is the wind load on the conductor in the z direction.

[0063] According to the wind load of the conductor, the attitude of the conductor at different time points is calculated as:

[0064]

[0065] wherein θ x (t) is the rotation angle of the conductor around the x-axis at time t, is the initial rotation angle of the conductor around the x-axis, ω x is the angular velocity of the conductor around the x-axis.

[0066] wherein θ y (t) is the rotation angle of the conductor around the y-axis at time t, y is the angular velocity of the conductor around the y-axis, is the initial rotation angle of the conductor around the y-axis.

[0067] wherein θ z (t) is the rotation angle of the conductor around the z-axis at time t, is the initial rotation angle of the conductor around the z-axis, ω z is the angular velocity of the conductor around the z-axis.

[0068] In an alternative embodiment, the calculation of the three-dimensional coordinates in the spatial coordinate system of the three-dimensional model in step C3 by applying the windage sag calculation model can be achieved by a geometric transformation matrix, by converting the two-dimensional sag parabolic equation into homogeneous coordinates, constructing a composite rotation matrix containing the windage angle, the line direction and the terrain inclination, and mapping the plane coordinate points one by one to the three-dimensional space. This method is suitable for engineering calculation scenarios that require precise control of spatial transformation.

[0069] In another alternative embodiment, the calculation of the three-dimensional coordinates in the spatial coordinate system of the three-dimensional model in step C3 by applying the windage sag calculation model can be achieved by using CAD modeling technology, by establishing a three-dimensional sag model through professional software such as AutoCAD or SolidWorks. Set up the spatial coordinate system in the software, calibrate the control points, and use the spline curve or equation curve function to generate the sag shape. Parametric programs can be written to automatically update the model according to the meteorological conditions, support visual inspection and engineering verification.

[0070] In the embodiments of the present application, the stress distribution data, the sag distribution data, and the point cloud data are combined in step S400 to establish a macro three-dimensional model and a micro three-dimensional model, including the following steps D1-D3:

[0071] D1: The point cloud data is used as the basis, combined with the stress distribution data and the sag data.

[0072] D2: The overall structure model of the transmission line is constructed by vectorization modeling technology to generate a macro three-dimensional model.

[0073] D3: Using the details of the point cloud data, a micro three-dimensional model of the power distribution line components is generated by geometric modeling technology.

[0074] In an alternative embodiment, the vectorization modeling technology used in step S400 can also be implemented through BIM modeling technology. By integrating the geometric information and engineering attribute information of the transmission line in a unified three-dimensional model, a geographic coordinate system of the line corridor is first established, and then the conductors and insulator components are placed according to the design standards. Each component contains attribute parameters such as material, specification, and installation position. The system ensures that the spatial relationship between components meets the engineering specifications through parameter constraints, forming a digital model containing complete engineering information. This method supports multi-specialty collaboration and is convenient for later operation and maintenance management and data sharing.

[0075] In another alternative embodiment, the vectorization modeling technology used in step S400 can also be implemented through parameterization modeling technology. Parameterization modeling technology constructs a transmission line model by establishing a parameter-driven geometric relationship. Key parameters such as span, tower height, and conductor type are defined during modeling, and then constraint relationships and calculation formulas between parameters are established. When input parameters change, the model automatically updates the geometric shape and spatial layout.

[0076] In the embodiments of the present application, the macro three-dimensional model and the micro three-dimensional model are fused in step S500 to generate a multi-scale comprehensive model, and the comprehensive model is simulated and analyzed, including the following steps E1-E6:

[0077] E1: Using the ICP algorithm, the macro model and the micro model data are unified to the same coordinate system.

[0078] E2: Using a data fusion algorithm, the macro three-dimensional model and the micro three-dimensional model are fused to generate a multi-scale comprehensive model.

[0079] E3: Using a physics engine, the multi-scale model is simulated in detail.

[0080] E4: Setting the initial conditions of the simulation environment, adjusting the simulation parameters according to the meteorological data.

[0081] E5: Calculating the stress distribution of the conductor under different working conditions, recording the stress values of the conductor at different positions, and generating a stress distribution map.

[0082] E6: Calculate the motion trajectory of the conductor under different working conditions, simulate the dynamic behavior of the conductor, record the position and attitude of the conductor at different time points, and generate a motion trajectory map.

[0083] Specifically, in step E2, the specific form of the fused model is:

[0084]

[0085] Wherein, C(x, y, z) is the position of the coordinate point (x, y, z) in the multi-scale integrated model, M(x, y, z) is the position of the coordinate point (x, y, z) in the macroscopic three-dimensional model, m(x, y, z) is the position of the coordinate point (x, y, z) in the microscopic three-dimensional model, x is the horizontal coordinate in the three-dimensional space, y is the vertical coordinate in the three-dimensional space, and z is the elevation coordinate in the three-dimensional space.

[0086] In an optional embodiment, in step S500, the data fusion algorithm can fuse model data of different scales by establishing a tree structure through hierarchical modeling technology, taking the macroscopic line corridor as the root node and the microscopic components as the leaf nodes. The fusion process is realized through the association relationship between parent and child nodes, and each node maintains data links pointing to the upper and lower levels.

[0087] In another optional embodiment, in step S500, the data fusion algorithm can also use microscopic grids at important sites and macroscopic grids in simple regions through multi-resolution grid technology, realize smooth connection of different density regions through gradual transition algorithm, dynamically adjust resolution according to requirements, and unify display.

[0088] In summary, by collecting meteorological data and point cloud data and performing preprocessing, the application realizes modeling of power distribution equipment under different weather conditions, forms a state equation by combining temperature, humidity and wind speed, calculates the stress distribution of the conductor under different weather conditions, combines the conductor sag when there is no wind deviation and the wind load, uses a parabolic equation to calculate the sag of the wind deviation conductor, realizes accurate calculation of the conductor sag, combines the conductor stress and sag data with the point cloud data, uses vector modeling technology to generate a macroscopic three-dimensional model, uses geometric modeling technology to generate a microscopic three-dimensional model, and the multi-scale model can reflect the overall structure and local details of the power distribution equipment at the same time. The simulation can simulate the stress distribution and motion trajectory of the conductor under different working conditions, which is crucial for evaluating the safety and stability of the equipment.

[0089] Example 3, refer to Figure 1 and Figure 2For the third embodiment of the present application, the power distribution equipment point cloud data modeling processing system comprises a data collection and meteorological model establishment module, which acquires meteorological data and point cloud data, models according to the meteorological data, and adjusts the modeling parameters through the meteorological data; a stress distribution data calculation and analysis module, which establishes a state equation according to the modeling parameters, and calculates stress distribution data; an arc sag distribution data calculation module, which generates arc sag distribution data by introducing a windage influence parameter through a slant parabolic equation, according to the stress distribution data and in combination with arc sag data; a three-dimensional model construction module, which combines the stress distribution data, the arc sag distribution data, and the point cloud data, and generates macroscopic and microscopic three-dimensional models through modeling technology; and a model fusion and simulation analysis module, which fuses the macroscopic and microscopic three-dimensional models, generates a multi-scale comprehensive model, and performs simulation analysis on the comprehensive model.

[0090] Embodiment 4, which is different from the first three embodiments, is that the function, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium, includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0091] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered a list of executable instructions for implementing logic functions, and can be specifically embodied in any computer-readable medium for use by an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute the instructions, or in conjunction with these instructions execution systems, apparatus or devices. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by an instruction execution system, apparatus or device, or in conjunction with these instruction execution systems, apparatus or devices.

[0092] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer readable medium can be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example via optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and stored in a computer memory.

[0093] It should be understood that portions of the application can be implemented in hardware, software, firmware or combinations thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and as in another embodiment, can be implemented using any or a combination of the following technologies, which are well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0094] Embodiment 5, reference Figure 1 and Figure 2 As a fifth embodiment of the present application, a power distribution equipment point cloud data modeling processing method is provided. In order to verify the beneficial effects of the present application, scientific demonstration is carried out through experiments.

[0095] In order to verify the effectiveness of the power distribution equipment point cloud data modeling processing method, the present study selects high-voltage transmission lines as the research object, real-time collects temperature, humidity and wind speed meteorological data through the meteorological station installed near the power distribution equipment, and uses high-precision laser radar system to obtain point cloud data of the section of transmission line. The point cloud data is preprocessed to ensure the accuracy of subsequent modeling;

[0096] After the data preparation stage is completed, the meteorological data is aligned with the preprocessed point cloud data, and imported into a three-dimensional modeling software to build a three-dimensional model. Based on the influence of temperature, humidity and wind speed on the performance of the conductor, the thermal expansion coefficient, elastic modulus and wind load of the conductor are adjusted respectively. By combining these adjusted parameters, a state equation is established to calculate the stress distribution of the conductor under different weather conditions. The sag of the wind deflected conductor is calculated using a parabolic equation, and finally the stress distribution and sag data of the conductor under various weather conditions are generated;

[0097] In order to intuitively show the overall structure of the power distribution equipment, point cloud data and vector modeling technology are adopted, a macro three-dimensional model is generated, micro modeling is carried out for the conductor and insulator, the model can accurately reflect the actual state of the equipment, the macro model and the micro model are fused to form a multi-scale comprehensive model, and the model is fine simulated by using a physical engine to simulate the equipment state under different working conditions;

[0098] The experimental data are shown in Table 1 as follows:

[0099] Table 1 Experimental data table

[0100]

[0101] From the above table, it can be seen that the power distribution equipment point cloud data modeling processing method proposed in the application shows significant advantages under different meteorological conditions. The specific analysis is as follows:

[0102] Under the conditions of temperature 20 DEG C, humidity 60%, and wind speed 5 m / s, the conductor stress of the application case is 146000 N / m 2 , and the conductor stress of the comparative case is 152000 N / m 2 , reduced by 3.9%;

[0103] Under the conditions of temperature 30 DEG C, humidity 70%, and wind speed 10 m / s, the conductor stress of the application case is 168000 N / m 2 , and the conductor stress of the comparative case is 185000 N / m 2 , reduced by 9.2%;

[0104] Under the conditions of temperature 10 DEG C, humidity 50%, and wind speed 3 m / s, the conductor stress of the application case is 126000 N / m 2 , and the conductor stress of the comparative case is 132000 N / m 2 , reduced by 4.5%;

[0105] Under the conditions of temperature 20 DEG C, humidity 60%, and wind speed 5 m / s, the conductor sag of the application case is 0.76 m, and the conductor sag of the comparative case is 0.82 m, reduced by 7.3%;

[0106] Under the conditions of temperature 30 DEG C, humidity 70%, and wind speed 10 m / s, the conductor sag of the application case is 1.08 m, and the conductor sag of the comparative case is 1.25 m, reduced by 13.6%;

[0107] Under the condition of temperature 10℃, humidity 50%, and wind speed 3m / s, the wire sag of the case of the application is 0.67m, while the wire sag of the comparative case is 0.72m, reduced by 7.0%;

[0108] Under the condition of temperature 20℃, humidity 60%, and wind speed 5m / s, the modeling error of the case of the application is 1.2%, while the modeling error of the comparative case is 5.2%, reduced by 76.9%;

[0109] Under the condition of temperature 30℃, humidity 70%, and wind speed 10m / s, the modeling error of the case of the application is 1.9%, while the modeling error of the comparative case is 8.1%, reduced by 76.5%;

[0110] Under the condition of temperature 10℃, humidity 50%, and wind speed 3m / s, the modeling error of the case of the application is 1.1%, while the modeling error of the comparative case is 4.5%, reduced by 75.6%.

[0111] As can be seen from the comparison, compared with the existing power distribution equipment modeling method, the method proposed by the application not only comprehensively considers the influence of multiple meteorological factors, but also significantly improves the accuracy and reliability of the model through high-precision point cloud data and advanced modeling technology.

[0112] It should be noted that the above examples are only used to illustrate the technical solutions of the application and are not limiting. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the application, and they should be covered in the scope of the claims of the application.

Claims

1. A power distribution equipment point cloud data modeling processing method, characterized in that: The method comprises the following steps: obtaining meteorological data and point cloud data, and constructing a three-dimensional model, and adjusting modeling parameters of the three-dimensional model through the meteorological data; establishing a state equation according to the adjusted modeling parameters, and calculating stress distribution data; generating sag distribution data by combining the stress distribution data with sag data and introducing a wind deviation influence parameter through the stress distribution data; combining the stress distribution data, the sag distribution data, and the point cloud data to establish a macro three-dimensional model and a micro three-dimensional model; fusing the macro three-dimensional model and the micro three-dimensional model to generate a multi-scale comprehensive model, and performing simulation analysis on the comprehensive model.

2. The power distribution equipment point cloud data modeling processing method of claim 1, wherein, obtaining meteorological data and point cloud data, modeling according to the meteorological data, and adjusting modeling parameters through the meteorological data, comprising the following steps: obtaining the meteorological data of the area where the power distribution equipment is located; obtaining the point cloud data and performing noise reduction processing on the point cloud data; modeling the meteorological data and the point cloud data after noise reduction processing to obtain a three-dimensional model, and adjusting parameters in the three-dimensional model according to changes in the obtained meteorological data.

3. The power distribution equipment point cloud data modeling processing method of claim 2, wherein, establishing a state equation according to the modeling parameters, and calculating stress distribution data, comprising: establishing a state equation according to the modeling parameters, calculating stress values through the modeling parameters, arranging the stress values according to the spatial position distribution of the conductor to obtain stress distribution data.

4. The power distribution equipment point cloud data modeling processing method of claim 3, wherein, generating sag distribution data by combining the stress distribution data with sag data and introducing a wind deviation influence parameter through the stress distribution data, comprising the following steps: calculating tension parameters from the stress distribution data through a stress distribution formula; introducing the tension parameters and sag data into a slant parabolic equation by introducing a wind deviation influence parameter to generate a wind deviation sag calculation model; applying the wind deviation sag calculation model to the spatial coordinate system of the three-dimensional model to calculate three-dimensional coordinates and generate sag distribution data; the sag data is calculated from the stress distribution data of the conductor under different meteorological conditions, combined with the conductor sag without wind deviation, and calculated by using a slant parabolic equation to obtain sag distribution data.

5. The power distribution equipment point cloud data modeling processing method of claim 4, wherein, combining the stress distribution data, the sag distribution data, and the point cloud data to generate a macro three-dimensional model and a micro three-dimensional model through modeling technology, comprising: using the point cloud data as the basis, combining the stress distribution data and the sag data, and constructing a whole structure model of the power transmission line through vectorization modeling technology to generate a macro three-dimensional model.

6. The power distribution equipment point cloud data modeling processing method of claim 5, wherein, combining the stress distribution data, the sag distribution data, and the point cloud data to generate a macro three-dimensional model and a micro three-dimensional model through modeling technology, comprising: using the details of the point cloud data to model the power distribution line components through geometric modeling technology to generate a micro three-dimensional model.

7. The power distribution equipment point cloud data modeling processing method of claim 6, wherein, fusing the macro three-dimensional model and the micro three-dimensional model to generate a multi-scale comprehensive model, and performing simulation analysis on the comprehensive model, comprising: unifying the spatial coordinates of the macro three-dimensional model and the micro three-dimensional model, fusing them through model fusion technology to generate a multi-scale comprehensive model; performing simulation on the physical scene of the multi-scale comprehensive model to obtain the changes of stress and sag parameters in the three-dimensional model; The meteorological data includes temperature, humidity and wind speed; The sag data is stress distribution data of the conductor, combined with the conductor sag when there is no wind deviation, the sag of the wind deviation conductor is calculated by using a slanted parabolic equation The wind deviation influence parameter is wind pressure specific load and wind deviation angle data.

8. A power distribution equipment point cloud data modeling processing system, applying a power distribution equipment point cloud data modeling processing method according to any one of claims 1-7, characterized in that, It comprises: A data collection and meteorological model establishment module, which acquires meteorological data and point cloud data, models according to the meteorological data, and adjusts modeling parameters through the meteorological data; A stress distribution data calculation and analysis module, which establishes a state equation by using the modeling parameters, and calculates stress distribution data; A sag distribution data calculation module, which generates sag distribution data by using a slanted parabolic equation, combining the stress distribution data and the sag data, and introducing the wind deviation influence parameter; A three-dimensional model construction module, which combines the stress distribution data, the sag distribution data and the point cloud data, and generates macroscopic and microscopic three-dimensional models by using modeling technology; A model fusion and simulation analysis module, which fuses the macroscopic and microscopic three-dimensional models to generate a multi-scale comprehensive model, and performs simulation analysis on the comprehensive model. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the power distribution equipment point cloud data modeling processing method in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the power distribution equipment point cloud data modeling processing method in any one of claims 1 to 7.

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