Power transmission line sag evaluation method and system based on point cloud data simulation trajectory

Abstract

The invention discloses a power transmission line sag evaluation method and system based on a point cloud data simulation trajectory, and relates to the technical field of conductor sag safety, and the method comprises the steps: S1, obtaining initial point cloud data of a power transmission line region, and carrying out the preprocessing of the initial point cloud data to obtain first point cloud data; s2, establishing an initial meteorological model based on the first point cloud data and an initial meteorological condition, distributing point cloud meteorological attributes, and obtaining second point cloud data; s3, simulating a plurality of meteorological combinations according to a current meteorological condition in combination with historical meteorological data, simulating a spatial form of the power line in the second point cloud data converted from a static point cloud to a dynamic environment, and obtaining third point cloud data; s4, simulating a lead track change state based on the third point cloud data to determine feature changes of the lead under different meteorological conditions, and obtaining fourth point cloud data; and S5, calculating a conductor sag evaluation value based on the fourth point cloud data, and comprehensively evaluating a conductor sag safety state. And the comprehensiveness and the reliability of the safety performance analysis of the conductor sag under the complex environment condition are obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of conductor sag safety technology, and in particular to a transmission line sag assessment method and system based on point cloud data simulation trajectory. Background Art

[0002] As the scale of power grids continues to expand and the requirements for power transmission safety continue to increase, how to accurately evaluate and monitor the operating status of transmission lines in complex geographical areas or special meteorological conditions has become an important issue. However, traditional evaluation methods are usually affected by factors such as the span and the material of the power lines, and it is difficult to accurately simulate various conditions in the actual operating environment. It is impossible to accurately evaluate and analyze the conductor sag in complex weather and complex areas, and thus it is impossible to comprehensively evaluate the safety performance of transmission lines under complex meteorological conditions.

[0003] Chinese patent, publication number: CN111339692B, publication date: September 4, 2020, discloses a method and device for determining power line sag based on laser point cloud data, the method includes: determining the power line point cloud data of the target power line between two adjacent poles in the target area based on the laser point cloud data; applying a preset fitting method to determine the initial sag point and the initial sag value on the target power line; constructing a three-dimensional space range centered on the initial sag point in the power line point cloud data of the target power line; if the three-dimensional space range contains the power line point cloud data, the initial sag point and the initial sag value are corrected using the position information of the point with the smallest elevation value to obtain the actual sag point and the actual sag value. The invention can effectively improve the accuracy of obtaining the power line sag, and can effectively save the time and money cost of data processing, as well as improve the efficiency of obtaining the power line sag. However, the invention ignores the influence of different meteorological conditions on the spatial form of the transmission line and the change of the conductor trajectory, and cannot comprehensively and accurately evaluate the sag safety status of the transmission line. Summary of the invention

[0004] The purpose of the present invention is to address the problem that the prior art lacks consideration of complex meteorological combination conditions, resulting in insufficient conductor sag safety analysis and poor effect; a transmission line sag assessment method and system based on point cloud data simulation trajectory are proposed, by combining the acquired point cloud data with initial meteorological conditions to establish an initial meteorological model, assigning meteorological attributes to the point cloud, and then simulating multiple meteorological combinations according to the current meteorological conditions in combination with historical meteorological data, simulating the spatial form of the power line from a static point cloud to a dynamic environment, and then simulating the trajectory change state of the transmission line, determining the characteristic changes of the conductor relative to different meteorological conditions, so as to calculate the conductor sag assessment value, and comprehensively evaluate the sag safety state of the conductor; the method overcomes the problem that the prior art lacks consideration of complex meteorological combination conditions, ignores the influence of different meteorological conditions on the spatial form of the transmission line and the change of the conductor trajectory, resulting in insufficient conductor sag safety analysis and poor effect, significantly improves the comprehensiveness and reliability of the conductor sag safety performance analysis under complex environmental conditions, and further improves the accuracy and efficiency of the conductor sag safety analysis.

[0005] To solve the above technical problems, according to a first aspect provided by this embodiment, a transmission line sag assessment method based on point cloud data simulation trajectory is proposed, comprising the following steps: S1. Acquire initial point cloud data of the power transmission line area based on an airborne laser radar, and pre-process the initial point cloud data to obtain first point cloud data; S2, establishing an initial meteorological model based on the first point cloud data and the initial meteorological conditions corresponding to the initial point cloud data, assigning meteorological attributes to the point cloud, and obtaining second point cloud data; S3, simulating a plurality of meteorological combinations according to the current meteorological conditions combined with historical meteorological data, and using the meteorological combinations to simulate the spatial form of the power lines in the second point cloud data from the static point cloud to the dynamic environment, to obtain the third point cloud data; S4, simulating the trajectory change state of the transmission line based on the third point cloud data, determining the characteristic change of the conductor relative to different meteorological conditions, and obtaining fourth point cloud data; S5. Calculate the conductor sag evaluation value based on the fourth point cloud data, and comprehensively evaluate the sag safety status of the conductor according to the sag evaluation value.

[0006] In this scheme, by using airborne laser radar equipment, point cloud data of the transmission line area can be acquired in real time, so as to extract the target point cloud object from the acquired point cloud data, obtain the first point cloud data, and combine it with the initial meteorological conditions to construct a basic model reflecting the actual environmental state, which is helpful to assign corresponding meteorological attributes to each point cloud point, and fully consider the different responses of different object categories to meteorological conditions; on the basis of the initial meteorological model, historical meteorological data are combined and various meteorological combinations are simulated to realize the simulation of the spatial form of the conductor from static point cloud to dynamic environment; then the trajectory changes of the transmission line under various meteorological conditions are simulated, and the behavioral characteristics of the transmission line under various meteorological conditions are accurately simulated, including the change of sag, and finally the sag evaluation value of the conductor is calculated, and the sag state of the conductor is comprehensively evaluated according to the sag evaluation value, so as to realize a more comprehensive, reliable and efficient evaluation of the safety performance of the transmission line under complex meteorological conditions, significantly improve the comprehensiveness and reliability of the sag safety performance analysis of the conductor under complex environmental conditions, and further improve the accuracy and efficiency of the sag safety analysis of the conductor.

[0007] Preferably, S1 comprises the following sub-steps: Using an airborne laser radar to collect three-dimensional point cloud data of the power transmission line area in real time, the three-dimensional point cloud data at least includes towers, power lines, the ground and its spatial environment, and using the three-dimensional point cloud data as initial point cloud data; Point cloud data filtering and point cloud data classification are performed on the initial point cloud data to obtain the first point cloud data.

[0008] Preferably, the filtering and classifying of the initial point cloud data specifically includes: filtering, denoising and screening outliers on the initial point cloud data to obtain standard point cloud data with a unified format; Among them, outlier screening specifically includes: Calculate the distance between each data point in the initial point cloud data and its nearest neighbor point, compare the distance with a distance threshold, and if the distance is greater than the distance threshold, mark the current data point as abnormal and then filter it out; The standard point cloud data is classified based on a deep learning model to obtain the first point cloud data.

[0009] Preferably, S2 comprises the following sub-steps: Based on the response characteristics of power equipment to meteorological conditions, an initial meteorological model is constructed to reflect the actual environmental status of the transmission line; the first point cloud data is combined with the initial meteorological conditions, and the initial meteorological model is used to assign meteorological attributes to each point cloud in the first point cloud data to obtain the second point cloud data.

[0010] Preferably, S3 includes the following sub-steps: Acquire historical meteorological data of the transmission line area, wherein the historical meteorological data at least includes time series data of temperature, time series data of humidity and time series data of wind speed; The historical meteorological data is combined with the current meteorological conditions to simulate different meteorological combinations to obtain a number of combined meteorological conditions; The change state quantity of each power equipment under the combined meteorological conditions is calculated according to the response characteristics of the power equipment to the meteorological conditions, and the spatial form of the wire in the second point cloud data is obtained according to the change state quantity to obtain the third point cloud data.

[0011] Preferably, S4 includes the following sub-steps: Extracting the spatial form of the wire based on the third point cloud data, performing time continuity compensation on the spatial form using a Taylor series expansion method, and updating the third point cloud data; Based on the updated third point cloud data, the trajectory change state of the transmission line under different meteorological conditions is simulated to obtain the dynamic behavior characteristics of the conductor relative to the different meteorological conditions, and the fourth point cloud data is obtained according to the behavior characteristics.

[0012] In this scheme, by simulating the trajectory change state of the transmission line under different meteorological conditions, the dynamic behavior characteristics of the conductor relative to different meteorological conditions can be obtained, that is, the trajectory of the conductor under different meteorological conditions and at different times can be obtained, especially for discontinuous or interrupted conductors, to avoid the loss of conductor trajectory leading to inaccurate conductor sag assessment results, misleading the staff and causing safety accidents; to achieve full and complete effective analysis of the conductor sag state. By using the Taylor series expansion method to compensate for the temporal continuity of the spatial form, the conductor trajectory can be completed, so as to better evaluate the safety performance of the transmission line under complex meteorological conditions and other environments.

[0013] Preferably, S5 comprises the following sub-steps: Extract each conductor point based on the fourth point cloud data, and use the conductor point as a sag assessment point; Calculating the sag assessment value of the sag assessment point, comparing the sag assessment value with a standard threshold, and evaluating the sag safety state of the conductor; The sag value at least includes the distance to the ground, the minimum distance of the maximum sag and the sag distance of the conductor support point.

[0014] According to another aspect provided by this embodiment, a transmission line sag assessment system based on point cloud data simulation trajectory is proposed, comprising: A data acquisition module, used to integrate an airborne laser radar to obtain initial point cloud data of the power transmission line area, and send the initial point cloud data to a data analysis module based on a wireless transmission method; A data analysis module, used for preprocessing the initial point cloud data, assigning meteorological attributes to the point cloud, combining meteorological data, simulating the spatial form of power equipment, trajectory changes of transmission lines, and analyzing the sag state of conductors; The data calculation module is used to calculate the conductor sag evaluation value and send the sag evaluation value to the data display module. The data display module is used to visualize the conductor sag evaluation result and generate a conductor sag analysis report.

[0015] Preferably, the data analysis module includes a first data analysis submodule, a second data analysis submodule, a third data analysis submodule and a fourth data analysis submodule; The first data analysis submodule is used to filter, denoise, filter outliers and classify the initial point cloud data; The second data analysis submodule is used to construct an initial meteorological model reflecting the actual environmental status of the transmission line based on the preprocessed point cloud data, and assign meteorological attributes to the point cloud; The third data analysis submodule is used to simulate different meteorological combinations according to the initial meteorological model and the meteorological attributes, and simulate the spatial forms of power equipment under different meteorological combinations; The fourth data analysis submodule is used to analyze the conductor sag safety status according to the sag evaluation value, obtain the conductor sag evaluation result, and send it to the data display module.

[0016] Preferably, the data calculation module includes a first data calculation module and a second data calculation submodule; The first data calculation module is used to perform time continuity compensation on the spatial form and simulate the trajectory change state of the transmission line under different meteorological conditions; The second data calculation submodule is used to calculate the sag evaluation value of the sag evaluation point of the conductor according to the trajectory change state, and send the sag evaluation value to the fourth data analysis submodule.

[0017] In this scheme, the initial point cloud data of the transmission line area can be obtained through the data acquisition module, and the data analysis module can improve the data quality by pre-processing the initial point cloud data, providing strong data support for the subsequent conductor sag safety status analysis; by assigning meteorological attributes and combining meteorological properties to the point cloud, the different responses of different power equipment to different meteorological conditions are fully considered, and the influence of different meteorological conditions on the spatial form of the transmission line and the change of the conductor trajectory is fully considered; through the data calculation module, the conductor sag evaluation value can be accurately calculated, and the conductor sag safety can be comprehensively evaluated based on these sag evaluation values ​​to ensure the reliability of the evaluation results. By sending the sag evaluation value to the data display module, it is convenient to visualize the conductor sag evaluation results and generate a conductor sag analysis report, so that the staff can clearly and intuitively understand the spatial form changes of the conductor under different meteorological conditions, the trajectory change trend, and whether the conductor sag is safe, providing data support for predicting the operation status of the conductor.

[0018] Beneficial effects of the present invention: 1. Build a basic model that reflects the actual environmental state, assign corresponding meteorological attributes to each point cloud point, and fully consider the different responses of different object categories to meteorological conditions; 2. Based on the initial meteorological model, combined with historical meteorological data and simulating various meteorological combinations, the simulation of the spatial form of the conductor in a dynamic environment is realized from static point cloud, and then the trajectory changes of the transmission line under various meteorological conditions are simulated, and the behavioral characteristics of the transmission line under various meteorological conditions are accurately simulated, including the changes in sag; 3. Comprehensively evaluate the sag state of the conductor based on the sag evaluation value to achieve a more comprehensive, reliable and efficient evaluation of the safety performance of the transmission line under complex meteorological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0020] Figure 1 The present invention is a flowchart of a method for evaluating sag of a transmission line based on point cloud data simulation trajectory according to an embodiment of the present invention.

[0021] Figure 2 This is a module diagram of a transmission line sag assessment system based on point cloud data simulation trajectory according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Example 1: Figure 1 As shown, a transmission line sag assessment method based on point cloud data simulation trajectory includes steps S1-S5, wherein: S1. Acquire initial point cloud data of the power transmission line area based on the airborne laser radar, and pre-process the initial point cloud data to obtain first point cloud data.

[0024] Specifically, S1 includes the following sub-steps: Using airborne laser radar to collect three-dimensional point cloud data of the transmission line area in real time, the three-dimensional point cloud data at least includes poles, power lines, ground and its spatial environment, and the three-dimensional point cloud data is used as initial point cloud data; The initial point cloud data is filtered and classified to obtain the first point cloud data.

[0025] Specifically, the initial point cloud data is filtered and classified, including: Filter, denoise and screen outliers on the initial point cloud data to obtain standard point cloud data with a unified format; Among them, outlier screening specifically includes: Calculate the distance between each data point in the initial point cloud data and its nearest neighbor point, compare the distance with the distance threshold, and if the distance is greater than the distance threshold, mark the current data point as an abnormality and then filter it out; The standard point cloud data is classified based on the deep learning model to obtain the first point cloud data.

[0026] Furthermore, the PointNet model can be used to classify point cloud data. PointNet is the first deep learning model that directly processes point cloud data. It processes unordered point sets through symmetric function modules and maximum pooling, achieving SOTA performance in 3D classification and segmentation tasks. It is robust and can cope with missing points, outliers, and noise, and has inspired the subsequent development of point cloud networks. PointNet uses a maximum pooling layer, which can extract the most representative features from any number of points while maintaining invariance to the order of the input points. In addition, PointNet introduces T-Net to learn a transformation matrix, which enhances the model's invariance to spatial transformations of point cloud data by performing an affine transformation on the input data. This design enables PointNet to effectively process 3D point cloud data and stably extract point set features even when there is fluctuation, noise, or missing point clouds. S2. Establish an initial meteorological model based on the first point cloud data and the initial meteorological conditions corresponding to the initial point cloud data, assign meteorological attributes to the point cloud, and obtain second point cloud data.

[0027] Specifically, S2 includes the following sub-steps: Based on the response characteristics of power equipment to meteorological conditions, an initial meteorological model is constructed to reflect the actual environmental status of the transmission line. The first point cloud data is combined with the initial meteorological conditions, and the initial meteorological model is used to assign meteorological attributes to each point cloud in the first point cloud data to obtain the second point cloud data.

[0028] S3. Simulate various meteorological combinations according to current meteorological conditions and historical meteorological data, and use the meteorological combinations to simulate the spatial form of the power lines in the second point cloud data from the static point cloud to the dynamic environment to obtain the third point cloud data.

[0029] Specifically, S3 includes the following sub-steps: Acquire historical meteorological data of the transmission line area, the historical meteorological data at least including time series data of temperature, time series data of humidity and time series data of wind speed; Combine historical meteorological data with current meteorological conditions to simulate different meteorological combinations and obtain several combined meteorological conditions; The change state quantity of each power equipment under the combined meteorological conditions is calculated according to the response characteristics of the power equipment to the meteorological conditions, and the spatial form of the conductor in the second point cloud data is obtained according to the change state quantity to obtain the third point cloud data.

[0030] S4. Simulate the trajectory change state of the transmission line based on the third point cloud data, determine the characteristic changes of the conductor relative to different meteorological conditions, and obtain fourth point cloud data.

[0031] Specifically, S4 includes the following sub-steps: The spatial form of the wire is extracted based on the third point cloud data, and the time continuity compensation of the spatial form is performed using the Taylor series expansion method to update the third point cloud data; Based on the updated third point cloud data, the trajectory change state of the transmission line under different meteorological conditions is simulated to obtain the dynamic behavior characteristics of the conductor relative to the different meteorological conditions, and the fourth point cloud data is obtained according to the behavior characteristics.

[0032] S5. Calculate the conductor sag assessment value based on the fourth point cloud data, and comprehensively assess the conductor sag safety status according to the sag assessment value.

[0033] Specifically, S5 includes the following sub-steps: Extract each conductor point based on the fourth point cloud data, and use the conductor point as a sag assessment point; Calculate the sag assessment value of the sag assessment point, compare the sag assessment value with the standard threshold, and evaluate the sag safety status of the conductor; The sag value includes at least the distance to the ground, the minimum distance of the maximum sag and the sag distance of the conductor support point.

[0034] In this embodiment, by using airborne laser radar equipment, point cloud data of the transmission line area can be acquired in real time, so as to extract the target point cloud object from the acquired point cloud data, obtain the first point cloud data, and combine it with the initial meteorological conditions to construct a basic model reflecting the actual environmental state, which is helpful to assign corresponding meteorological attributes to each point cloud point, and fully consider the different responses of different object categories to meteorological conditions; on the basis of the initial meteorological model, historical meteorological data are combined and various meteorological combinations are simulated to realize the simulation of the spatial form of the conductor from static point cloud to dynamic environment; then the trajectory changes of the transmission line under various meteorological conditions are simulated, and the behavioral characteristics of the transmission line under various meteorological conditions are accurately simulated, including the change of sag, and finally the sag evaluation value of the conductor is calculated, and the sag state of the conductor is comprehensively evaluated according to the sag evaluation value, so as to realize a more comprehensive, reliable and efficient evaluation of the safety performance of the transmission line under complex meteorological conditions, significantly improve the comprehensiveness and reliability of the sag safety performance analysis of the conductor under complex environmental conditions, and further improve the accuracy and efficiency of the sag safety analysis of the conductor.

[0035] Embodiment 2, as Figure 2 As shown, a transmission line sag assessment system based on point cloud data simulation trajectory includes: a data acquisition module, which is used to integrate an airborne laser radar to obtain initial point cloud data of the transmission line area, and send the initial point cloud data to a data analysis module based on a wireless transmission method; Data analysis module, used for preprocessing the initial point cloud data, assigning meteorological attributes to the point cloud, meteorological combination, simulating the spatial form of power equipment, trajectory changes of transmission lines, and conductor sag state analysis; The data calculation module is used to calculate the conductor sag assessment value and send the sag assessment value to the data display module. The data display module is used to visualize the conductor sag assessment results and generate a conductor sag analysis report.

[0036] Specifically, the data analysis module includes a first data analysis submodule, a second data analysis submodule, a third data analysis submodule and a fourth data analysis submodule; The first data analysis submodule is used to filter, denoise, filter outliers and classify the initial point cloud data; the second data analysis submodule is used to construct an initial meteorological model reflecting the actual environmental status of the transmission line based on the preprocessed point cloud data, and assign meteorological attributes to the point cloud; The third data analysis submodule is used to simulate different meteorological combinations according to the initial meteorological model and meteorological attributes, and Simulate the spatial form of power equipment under different combined meteorological conditions; The fourth data analysis submodule is used to analyze the conductor sag safety status according to the sag evaluation value, obtain the conductor sag evaluation result, and send it to the data display module.

[0037] Specifically, the data calculation module includes a first data calculation module and a second data calculation submodule; The first data calculation module is used to compensate for the temporal continuity of the spatial form and simulate the trajectory change state of the transmission line under different meteorological conditions; The second data calculation submodule is used to calculate the sag evaluation value of the sag evaluation point of the conductor according to the track change state, and send the sag evaluation value to the fourth data analysis submodule.

[0038] As an implementation method, the data acquisition module is integrated into the drone equipment, and the laser radar is installed on the drone to collect laser point cloud data and send it to the data analysis module; the data analysis module and the data calculation module are integrated in the electronic device, and the point cloud data obtained by the laser radar is preprocessed and classified, the initial weather generation is performed, the complex weather is simulated, the wire trajectory is simulated, and finally the sag analysis is performed on all wire points to determine whether the wire is safe under complex weather conditions. The data display module is integrated into the mobile terminal or remote control, and is equipped with an application background of the transmission line sag assessment method based on the point cloud data simulation trajectory. The sag analysis process data is visualized and displayed through the application background. At the same time, the application background automatically generates a wire sag analysis report based on the sag assessment results of the received electronic equipment, providing the staff with a basis for wire monitoring decision-making.

[0039] In this embodiment, the initial point cloud data of the transmission line area can be obtained through the data acquisition module, and the data analysis module can improve the data quality by preprocessing the initial point cloud data, providing strong data support for the subsequent conductor sag safety status analysis; by assigning meteorological attributes and combining meteorological properties to the point cloud, the different responses of different power equipment to different meteorological conditions are fully considered, and the influence of different meteorological conditions on the spatial form of the transmission line and the change of the conductor trajectory is fully considered; through the data calculation module, the conductor sag evaluation value can be accurately calculated, and the conductor sag safety is comprehensively evaluated according to these sag evaluation values ​​to ensure the reliability of the evaluation results. By sending the sag evaluation value to the data display module, it is convenient to visualize the conductor sag evaluation results and generate a conductor sag analysis report, so that the staff can clearly and intuitively understand the spatial form changes of the conductor under different meteorological conditions, the trajectory change trend, and whether the conductor sag is safe, providing data support for predicting the operation status of the conductor.

[0040] As an implementation method, for P raw Each point p in (initial point cloud data) i , calculate its nearest neighbor point p j The distance d(p i ,p j ); if d(p i ,p j )>T dist (where T dist is the set distance threshold, which can be set according to actual needs), then p i Mark as an outlier.

[0041] For each point p i , calculate the position mean of the neighboring points around it And update the point position to The data set obtained after the above processing is denoted as P filtered , and then use the deep learning model to classify the point cloud data, distinguish different object categories, and obtain the first point cloud data P sim1 .

[0042] Get the classified point cloud data P sim1 After that, the initial meteorological conditions are obtained, including temperature T, humidity H and wind speed W, etc. The classified point cloud data is combined with the initial meteorological conditions to build an initial meteorological model to assign corresponding meteorological attributes to each point cloud point, and the second point cloud data P containing meteorological attributes is obtained. sim2 Among other things, this process needs to take into account the different responses of different object categories to meteorological conditions, for example: For the tower, the drag coefficient C rSmall, almost unaffected by wind, therefore, temperature T and humidity H are assigned as meteorological attributes; for power lines, the wind resistance coefficient C l It is large, and the influence of wind and gravity needs to be considered. Therefore, temperature T, humidity H and wind speed W are assigned as meteorological attributes; For vegetation, the drag coefficient C v It is relatively large and is significantly affected by wind force. Therefore, temperature T, humidity H, and wind speed W are assigned as meteorological attributes.

[0043] Get the second point cloud data P containing meteorological attributes sim2 Finally, the simulation of the spatial form of the wire in a dynamic environment is realized from static point cloud to simulation of the spatial form of the wire in a dynamic environment by combining historical meteorological data and simulating various meteorological combinations. The specific steps include: Get historical weather data, including temperature T h 、Humidity h and wind speed W h Time series data; Based on historical meteorological data and current meteorological conditions, multiple meteorological combinations are simulated. This process involves different responses of different object categories to meteorological conditions. Taking power lines as an example, assuming that a point in the point cloud data belongs to the power line category, according to the wind resistance coefficient C of the power line l , is p i Assign meteorological attributes temperature T, humidity H and wind speed W, and use the following formula to simulate the displacement Δp of the wire under different meteorological conditions. i : In the formula, C l is the drag coefficient of the power line, A is the cross-sectional area of ​​the power line, W is the wind speed, ρ is the air density, and Δt is the time interval; Through the above steps, the displacement of the conductor under different meteorological conditions is obtained. For each point p i , update its position to (p i +Δp) to simulate the spatial form of the wire under different meteorological conditions and obtain the third point cloud data P sim3 .

[0044] For the third point cloud data P sim3 Each conductor point p in i , using the Taylor series expansion method to simulate the wire trajectory under different meteorological conditions, and update the third point cloud data P sim3 The fourth point cloud data P is obtained by including the simulated trajectory sim4 The formula of Taylor series expansion method is as follows: Where, f(t) is the function of the displacement Δp of the wire with time t, f(t 0) represents the wire at the initial time t 0 The position of f′(t 0 ) represents the wire at the initial time t 0 The speed, f″(t 0 ) represents the wire at the initial time t 0 acceleration.

[0045] For each meteorological condition, points on the conductor are extracted from the result model of the conductor space morphology and time simulation to evaluate the sag of the conductor. sim4 Each conductor point p in i , extract point p on the wire i As the sag assessment point, take the assessment as the calculation target, calculate its distance to the ground, the sag distance of the conductor support (the vertical distance to the connecting line of the two end supports), and the minimum distance of the maximum sag in the conductor section (the minimum safe distance between the maximum sag of the transmission line), and comprehensively evaluate the sag safety status of the conductor based on these distance values. Among them, the conductor support sag distance can obtain the maximum sag; ensure that the safety distance between the maximum sag of the transmission line is large enough to prevent moisture, burning materials, etc. from splashing from the ground to the maximum sag of the transmission line, thereby avoiding dangerous situations such as disconnection and short circuit.

[0046] Beneficial effects of the embodiment: By simulating the trajectory change state of the transmission line under different meteorological conditions, the dynamic behavior characteristics of the conductor relative to different meteorological conditions can be obtained, that is, the trajectory of the conductor under different meteorological conditions and at different times can be obtained, especially for discontinuous or interrupted conductors, to avoid the loss of conductor trajectory leading to inaccurate conductor sag assessment results, misleading the staff and causing safety accidents; to achieve full and complete effective analysis of the conductor sag state. By using the Taylor series expansion method to compensate for the temporal continuity of the spatial form, the conductor trajectory can be completed, so as to better evaluate the safety performance of the transmission line under complex meteorological conditions and other environments.

[0047] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A transmission line sag assessment method based on point cloud data simulation trajectory, characterized by: The steps include: S1. Acquire initial point cloud data of the power transmission line area based on an airborne laser radar, and pre-process the initial point cloud data to obtain first point cloud data; S2, establishing an initial meteorological model based on the first point cloud data and the initial meteorological conditions corresponding to the initial point cloud data, assigning meteorological attributes to the point cloud, and obtaining second point cloud data; S3, simulating a plurality of meteorological combinations according to the current meteorological conditions combined with historical meteorological data, and using the meteorological combinations to simulate the spatial form of the power lines in the second point cloud data from the static point cloud to the dynamic environment, to obtain the third point cloud data; S4, simulating the trajectory change state of the transmission line based on the third point cloud data, determining the characteristic change of the conductor relative to different meteorological conditions, and obtaining fourth point cloud data; S5. Calculate the conductor sag evaluation value based on the fourth point cloud data, and comprehensively evaluate the conductor sag safety status according to the sag evaluation value.

2. The method for evaluating the sag of a power transmission line based on point cloud data simulation trajectory according to claim 1, characterized in that: The S1 comprises the following sub-steps: Using an airborne laser radar to collect three-dimensional point cloud data of the power transmission line area in real time, the three-dimensional point cloud data at least includes towers, power lines, the ground and its spatial environment, and using the three-dimensional point cloud data as initial point cloud data; Point cloud data filtering and point cloud data classification are performed on the initial point cloud data to obtain the first point cloud data.

3. The method for evaluating the sag of a power transmission line based on point cloud data simulation trajectory according to claim 2, characterized in that: The filtering and classifying of the initial point cloud data specifically includes: Filtering, denoising and screening outliers on the initial point cloud data to obtain standard point cloud data with a unified format; Among them, outlier screening specifically includes: Calculate the distance between each data point in the initial point cloud data and its nearest neighbor point, compare the distance with a distance threshold, and if the distance is greater than the distance threshold, mark the current data point as abnormal and then filter it out; The standard point cloud data is classified based on a deep learning model to obtain the first point cloud data.

4. The method for evaluating the sag of a power transmission line based on point cloud data simulation trajectory according to claim 1, characterized in that: The S2 comprises the following sub-steps: Based on the response characteristics of power equipment to meteorological conditions, an initial meteorological model is constructed to reflect the actual environmental status of the transmission line; the first point cloud data is combined with the initial meteorological conditions, and the initial meteorological model is used to assign meteorological attributes to each point cloud in the first point cloud data to obtain the second point cloud data.

5. The method for evaluating the sag of a power transmission line based on point cloud data simulation trajectory according to claim 4, characterized in that: The S3 comprises the following sub-steps: Acquire historical meteorological data of the transmission line area, wherein the historical meteorological data at least includes time series data of temperature, time series data of humidity and time series data of wind speed; The historical meteorological data is combined with the current meteorological conditions to simulate different meteorological combinations to obtain a number of combined meteorological conditions; The change state quantity of each power equipment under the combined meteorological conditions is calculated according to the response characteristics of the power equipment to the meteorological conditions, and the spatial form of the wire in the second point cloud data is obtained according to the change state quantity to obtain the third point cloud data.

6. The method for evaluating the sag of a power transmission line based on point cloud data simulation trajectory according to claim 1, characterized in that: The S4 comprises the following sub-steps: Extracting the spatial form of the wire based on the third point cloud data, performing time continuity compensation on the spatial form using a Taylor series expansion method, and updating the third point cloud data; Based on the updated third point cloud data, the trajectory change state of the transmission line under different meteorological conditions is simulated to obtain the dynamic behavior characteristics of the conductor relative to the different meteorological conditions, and the fourth point cloud data is obtained according to the behavior characteristics.

7. The method for evaluating transmission line sag based on point cloud data simulation trajectory according to claim 1, characterized in that: The S5 comprises the following sub-steps: Extract each conductor point based on the fourth point cloud data, and use the conductor point as a sag assessment point; Calculating the sag assessment value of the sag assessment point, comparing the sag assessment value with a standard threshold, and evaluating the sag safety state of the conductor; The sag value at least includes the distance to the ground, the minimum distance of the maximum sag and the sag distance of the conductor support point.

8. A transmission line sag assessment system based on point cloud data simulation trajectory, applicable to the transmission line sag assessment method based on point cloud data simulation trajectory as claimed in any one of claims 1 to 7, characterized in that: include: A data acquisition module, used to integrate an airborne laser radar to obtain initial point cloud data of the power transmission line area, and send the initial point cloud data to a data analysis module based on a wireless transmission method; A data analysis module, used for preprocessing the initial point cloud data, assigning meteorological attributes to the point cloud, combining meteorological data, simulating the spatial form of power equipment, trajectory changes of transmission lines, and analyzing the sag state of conductors; The data calculation module is used to calculate the conductor sag evaluation value and send the sag evaluation value to the data display module. The data display module is used to visualize the conductor sag evaluation result and generate a conductor sag analysis report.

9. The transmission line sag assessment system based on point cloud data simulation trajectory according to claim 8, characterized in that: The data analysis module includes a first data analysis submodule, a second data analysis submodule, a third data analysis submodule and a fourth data analysis submodule; The first data analysis submodule is used to filter, denoise, filter outliers and classify the initial point cloud data; The second data analysis submodule is used to construct an initial meteorological model reflecting the actual environmental status of the transmission line based on the preprocessed point cloud data, and assign meteorological attributes to the point cloud; The third data analysis submodule is used to simulate different meteorological combinations according to the initial meteorological model and the meteorological attributes, and simulate the spatial forms of power equipment under different meteorological combinations; The fourth data analysis submodule is used to analyze the conductor sag safety status according to the sag evaluation value, obtain the conductor sag evaluation result, and send it to the data display module.

10. The transmission line sag assessment system based on point cloud data simulation trajectory according to claim 9, characterized in that: The data calculation module includes a first data calculation module and a second data calculation submodule; The first data calculation module is used to perform time continuity compensation on the spatial form and simulate the trajectory change state of the transmission line under different meteorological conditions; The second data calculation submodule is used to calculate the sag evaluation value of the sag evaluation point of the conductor according to the trajectory change state, and send the sag evaluation value to the fourth data analysis submodule.

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