CN111929698A - Method for identifying hidden danger of tree obstacle in corridor area of power transmission line - Google Patents
Method for identifying hidden danger of tree obstacle in corridor area of power transmission line Download PDFInfo
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- CN111929698A CN111929698A CN202010574415.5A CN202010574415A CN111929698A CN 111929698 A CN111929698 A CN 111929698A CN 202010574415 A CN202010574415 A CN 202010574415A CN 111929698 A CN111929698 A CN 111929698A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
- G01S17/10—Systems determining position data of a target for measuring distance only using transmission of interrupted, pulse-modulated waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
- G06F17/12—Simultaneous equations, e.g. systems of linear equations
Abstract
The invention provides a method for identifying hidden danger of tree obstacles in a corridor area of a power transmission line, which comprises the following steps: calculating sag of the power transmission line between adjacent base towers by using a catenary equation and a sag equation for suspended points in the point cloud data of the corridor area of the power transmission line so as to fit each power transmission line between the adjacent base towers; then, classifying the point cloud data to obtain power transmission line point cloud data, base tower point cloud data and vegetation point cloud data; constructing a columnar exploration space with the adjacent base towers, the power transmission lines between the adjacent base towers and the ground as boundaries on the basis of the point cloud data obtained after classification; and finally, obtaining the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying the trees of which the distance between the vegetation and the power transmission line is smaller than a set value. The method can find the hidden danger of the tree obstacle in the power transmission line in time, prevent the trees from threatening the power transmission line, and has higher identification accuracy compared with the traditional manual measurement elimination.
Description
Technical Field
The invention relates to the technical field of power transmission line protection, in particular to a method for identifying hidden danger of tree obstacles in a corridor area of a power transmission line.
Background
The transmission line is an important component of a national main power grid and an important national infrastructure, and the transmission line faults can cause huge loss to daily production life and national economy of people, so that a power grid operation maintenance department needs to invest a large amount of manpower and material resources to patrol the transmission line every year in order to prevent and stop the occurrence of power grid safety accidents. The power transmission line is mostly located in a mountainous area with dense vegetation, the mountainous area is large, the number of trees is large, and the patrol personnel often encounter the problem of tree obstacles. The tree barrier refers to trees in an offline tree crown or corridor area threatening the safe operation of a power transmission line, and is easy to cause line tripping, even line breakage or pole tower collapse, and large-area power failure and other problems.
The current detection means of the tree obstacle mainly depends on manual naked eye judgment as a main part, and an inspection worker judges the distance between a tree and a power transmission line by holding laser ranging on the ground, but the detection result is large and can have large errors due to the measurement angle and the position relation between the human and the tree obstacle point. In another mode, oblique photography modeling is used for measuring the safety distance, but in the seed detection methods, hardware fittings near a hanging point of the power transmission line and parts, such as insulators, close to a power transmission line corridor area are easily regarded as potential tree obstacle hazards when detection is carried out, so that the potential tree obstacle hazards are not judged accurately.
Disclosure of Invention
The invention aims to provide a method for identifying hidden danger of tree obstacles in a corridor area of a power transmission line, which can improve the accuracy of judgment of hidden danger of tree obstacles in the corridor area of the power transmission line.
In order to achieve the purpose, the invention provides a method for identifying hidden danger of tree obstacles in a corridor area of a power transmission line, which comprises the following steps:
acquiring point cloud data of a laser radar in a power transmission line corridor area, classifying the point cloud data, and extracting the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data;
calculating sag of the power transmission line by using a catenary equation and a sag equation according to the power transmission line point cloud data so as to fit each power transmission line;
constructing a columnar exploration space with a foundation tower, a power transmission line and the ground as boundaries on the basis of the point cloud data obtained after classification;
and acquiring the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying trees of which the distance between the vegetation and the power transmission line is smaller than a set value.
Optionally, the left suspension point of the power transmission line is a coordinate origin, the horizontal direction is an x axis, and the vertical direction is a y axis to establish a coordinate system, where the catenary equation is as follows:
the sag equation is:
wherein σ0The horizontal stress of the power transmission line, gamma is the specific load of the power transmission line, ch is a hyperbolic cosine function, H is the height difference between two suspension points of the power transmission line, L is the span between the two suspension points of the power transmission line, a is the horizontal distance from the suspension point of the origin of coordinates to the lowest point of the power transmission line, and H is the height difference value from the lowest point of the power transmission line to the left suspension point.
Optionally, the catenary equation and the sag equation are fitted and solved by adopting a nonlinear least square confidence domain iterative algorithm, so as to realize the fitting of each transmission line.
Optionally, the step of classifying the point cloud data and extracting the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data includes:
filtering the point cloud data to separate out ground points and non-ground points;
filtering the ground points to obtain the non-ground points, wherein the non-ground points comprise the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data;
separating suspension points in the non-ground points to obtain the point cloud data of the power transmission line;
separating the base tower point cloud data by using the direction characteristics, and separating the vegetation point cloud data and the building point cloud data by using the dimension characteristics;
and respectively separating the vegetation point cloud data and the building point cloud data according to the spherical target or the planar target displayed in the point cloud data space.
Optionally, the step of obtaining the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying the trees in which the distance between the vegetation and the power transmission line is smaller than a set value includes:
performing single-tree segmentation processing on the vegetation point cloud data in the columnar exploration space to obtain point cloud data corresponding to each tree;
and calculating the distance between each tree and the corresponding power transmission line, and identifying the trees of which the distance between each tree and the corresponding power transmission line is less than the set value.
Optionally, the distance between each tree and the corresponding power transmission line is a clearance distance.
Optionally, the clearance D is calculated according to the following formulav：
Dv＝D1-f-D2-Δh-10.2；
Wherein D1 is the height of the left base tower, D2 is the height of the tree, delta h is the construction margin, and f is the sag of any point of the power transmission line.
Optionally, the set value is greater than or equal to 13.5 m.
The method for identifying the hidden danger of the tree obstacle in the corridor area of the power transmission line calculates the sag of the power transmission line between adjacent base towers by using a catenary equation and a sag equation for a suspended point in point cloud data of a laser radar in the corridor area of the power transmission line so as to fit each power transmission line between the adjacent base towers; then, the point cloud data are classified to obtain power transmission line point cloud data, base tower point cloud data and vegetation point cloud data; constructing a columnar exploration space with the adjacent base towers, the power transmission lines between the adjacent base towers and the ground as boundaries on the basis of the point cloud data obtained after classification; and finally, obtaining the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying the trees of which the distance between the vegetation and the power transmission line is smaller than a set value. The method can find the hidden danger of the tree obstacle in the power transmission line in time, prevents trees from threatening the power transmission line, improves the accuracy of identification compared with the traditional manual measurement and elimination, and realizes automatic measurement and calculation of the safety distance and marking of the hidden danger point of the tree obstacle.
Drawings
Fig. 1 is a flowchart of a method for identifying hidden danger of tree obstacle in a corridor area of a power transmission line according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a tree clearance under a power transmission line according to an embodiment of the present invention.
Detailed Description
The following describes in more detail embodiments of the present invention with reference to the schematic drawings. The advantages and features of the present invention will become more apparent from the following description. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
As shown in fig. 1, the present embodiment provides a method for identifying hidden danger of tree obstacle in a corridor area of a power transmission line, including:
step S1: acquiring point cloud data of a laser radar in a power transmission line corridor area, classifying the point cloud data, and extracting the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data;
step S2: calculating sag of the power transmission line by using a catenary equation and a sag equation according to the power transmission line point cloud data so as to fit each power transmission line;
step S3: constructing a columnar exploration space with a foundation tower, a power transmission line and the ground as boundaries on the basis of the point cloud data obtained after classification;
step S4: and acquiring the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying trees of which the distance between the vegetation and the power transmission line is smaller than a set value.
Specifically, step S1 is executed first, the aircraft flies back and forth along the direction parallel to the two sides of the transmission line, the side direction overlapping degree is ensured to be more than 30%, the average point cloud density of the measurement area is not lower than 30 points/square meter, the data coverage takes the center line of the transmission line as the center, and the outer expansion of the two sides is not less than 60 meters. And then carrying out carrier phase difference processing on data acquired by the ground reference station GPS receiver and data received by the aircraft airborne GPS receiver to obtain the three-dimensional coordinates of the flight platform. Then, a laser radar is carried in the traveling device and emits laser pulses to the ground to obtain point cloud data of the power transmission line, reflected pulses reflected by the ground are received, the used time is recorded, the distance from the laser radar to the ground is calculated, and the three-dimensional coordinates of the ground points (point cloud data of the ground points) are calculated by combining with the three-dimensional coordinates of the flight platform. Next, the process is repeated. Denoising the obtained point cloud data of the power transmission line and the generated point cloud data of the ground points, dividing the point cloud data by using three-dimensional grids, counting the number of points falling into each grid, and judging whether points exist in peripheral grids or not; if the number of points in the grid is less than a certain number and no point exists in the peripheral grid, the point is judged to be a noise point.
And then, classifying the point cloud data, and extracting the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data. Specifically, filtering the denoised point cloud data by adopting an irregular triangulation method: firstly, selecting seed points to construct a rough ground triangulation network, gradually selecting the points meeting the requirements from the non-ground points to add the points to the initial rough triangulation network to form a new network, and carrying out iterative calculation until all the points are divided into ground points and non-ground points.
And further, filtering the ground points to obtain the non-ground points, wherein the non-ground points comprise the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data, and at the moment, the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data need to be separated.
And separating suspension points in the non-ground points to obtain the power transmission line point cloud data, then separating the base tower point cloud data by using the direction characteristics, and separating the vegetation point cloud data and the building point cloud data by using the dimension characteristics, wherein at the moment, the vegetation point cloud data and the building point cloud data need to be separated.
And respectively separating the vegetation point cloud data and the building point cloud data according to the spherical target or the planar target displayed in the point cloud data space. Specifically, the vegetation point cloud data is displayed as a spherical target in the space of the point cloud data, and the building point cloud data is displayed as a planar target in the space of the point cloud data, so that the vegetation point cloud data and the building point cloud data can be separated accordingly.
Insulator strings and wires can be identified through the base tower point cloud data and the power transmission line point cloud data, so that suspension points of two adjacent base towers can be determined, and if the left base tower and the right base tower are determined to be two adjacent tower poles, a wire suspension point on the left base tower and a wire suspension point on the right base tower are determined.
Next, step S2 is executed, when the power transmission line is located in the mountainous terrain, the heights of the two adjacent foundation towers are different, and the heights of the suspension points of the two adjacent foundation towers are also different, and the sag of the power transmission line can be calculated by using a catenary equation and a sag equation according to the point cloud data of the power transmission line, so as to fit each power transmission line. Specifically, the position of the maximum elevation value is a base tower position, the power transmission line between two base towers belongs to a natural suspension line and conforms to a hyperbolic cosine function model, and therefore the power transmission line can be fitted according to the characteristics, in this embodiment, a left suspension point of the power transmission line is used as a coordinate origin, a horizontal direction is an x axis, a vertical direction is a y axis to establish a coordinate system, and the catenary equation is as follows:
the sag equation is:
wherein σ0The horizontal stress of the power transmission line, gamma is the specific load of the power transmission line, ch is a hyperbolic cosine function, H is the height difference between two suspension points of the power transmission line, L is the span between the two suspension points of the power transmission line, a is the horizontal distance from the suspension point of the origin of coordinates to the lowest point of the power transmission line, and H is the height difference value from the lowest point of the power transmission line to the left suspension point.
And fitting and solving the catenary equation and the sag equation by adopting a nonlinear least square confidence domain iterative algorithm to realize the fitting of each power transmission line, and obtaining a three-dimensional model of the power transmission line after fitting.
Further, the power transmission line is mostly exposed in the natural environment, and therefore the sag of the power transmission line changes in real time due to the influence of external factors such as meteorological conditions and working conditions, the distance between the power transmission line and ground objects also changes dynamically, and the static laser point cloud data cannot find potential dangerous points in time. According to the conditions, accurate meteorological parameter information of the power transmission line region can be obtained through the online monitoring environment parameter model so as to simulate various operation parameters of the power transmission line under various working conditions, and sag of the power transmission line is calculated according to the parameter information.
Specifically, sag can be calculated by: acquiring input working condition conditions, the model number and parameters of the power transmission line, and calculating specific load and allowable stress of the power transmission line; then selecting possible control conditions, calculating a critical span, and selecting an effective critical span; substituting the specific load and the air temperature under the control meteorological conditions into a state equation to calculate the stress under each meteorological condition; and finally substituting the calculated stress into the sag equation to calculate the sag under different conditions.
Then, step S3 is executed to construct a columnar exploration space with the foundation tower, the power transmission line and the ground as boundaries based on the point cloud data obtained after classification. It can be understood that the two foundation towers, the power transmission line between the foundation towers, vegetation, illegal buildings, crossing lines and the like below the power transmission line form the columnar exploration space together, and because each point of the columnar exploration space has a three-dimensional coordinate, the distance can be calculated in real time. Since the trees should be removed first as the largest obstacle of the transmission line, the present embodiment uses the vegetation data as the target data.
Finally, step S4 is executed: and acquiring the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying trees of which the distance between the vegetation and the power transmission line is smaller than a set value.
Specifically, because the vegetation is a collection of a large number of trees, if a tree threatening the power transmission line needs to be accurately fixed, the vegetation point cloud data in the columnar exploration space needs to be subjected to single-tree segmentation processing to obtain point cloud data corresponding to each tree, then the distance between each tree and the corresponding power transmission line is calculated, and the trees with the distance between the trees and the power transmission line smaller than the set value are identified by colors.
Specifically, because the number of trees in the vegetation is huge, if the distance between each tree and the corresponding power transmission line is calculated, the calculation amount is very large. In this embodiment, before the vegetation point cloud data is subjected to the single-tree segmentation, point cloud data with a distance exceeding a preset buffer distance in the vegetation point cloud data can be acquired, a dangerous vegetation area close to the power transmission line in the vegetation point cloud data is partitioned, then the single-tree segmentation is performed on the point cloud data in the dangerous vegetation area, and the distance between each point and the power transmission line is calculated.
It will be appreciated that the above description describes the manner in which sag is calculated when adjacent pylons differ in height, and should be understood. In a plain area, the heights of adjacent foundation towers are the same, the adjacent foundation towers can be arranged on the flat ground, the suspension points of the two adjacent foundation towers are also equal in height, a simulation connecting straight line between the two foundation towers can be obtained through foundation tower electric cloud data and power transmission line point cloud data, the elevation value of any point on the simulation connecting straight line is respectively equal to the elevation value of the suspension point between the adjacent foundation towers, and at the moment, the sag value can be obtained only by calculating the difference between the elevation value of the lowest point of a wire between the adjacent foundation towers and the elevation value of any suspension point.
Assuming that the elevation value of the wire hanging point A and the wire hanging point B is T, the elevation value of the lowest point of the wire between the first tower 2 and the second tower 3 is P, and calculating the difference between T and P to obtain Zmax, namely the sag value of the line between the first tower 2 and the second tower 3.
As shown in fig. 2, in this embodiment, the distance between each tree and the corresponding transmission line is a clearance, and the clearance D is calculated according to the following formulav：
Dv＝D1-f-D2-Δh-10.2；
Wherein D1 is the height of the left base tower, D2 is the height of the tree, delta h is the construction margin, and f is the sag of any point of the power transmission line.
And then, according to the voltage grade, the ground object type and the geographic environment parameters of the power transmission line, searching for a safety distance threshold value between the tree and the power transmission line in a standard regulation, if the calculated distance between the tree and the corresponding power transmission line is greater than the safety distance threshold value specified by the standard, considering the tree as a dangerous ground object, and giving an early warning through color identification. The patrol personnel can find the tree according to the color identification and fell the tree so as to prevent the tree from threatening the power transmission line and ensure that the power transmission line is in a safe operation and maintenance state. Certainly, as the patrol personnel need a certain preparation time from the confirmation of the trees to be felled to the actual felling of the trees, a certain construction margin needs to be reserved.
It should be understood that the set value may be designed according to the requirement of the overhead transmission line design specification, for example, a dc overhead transmission line of +800V requires that the minimum vertical distance between the transmission line and the tree is less than 13.5m, in this embodiment, the set value is set to be greater than or equal to 13.5 m; the set value may be other values when the power transmission line is a dc overhead power transmission line of other voltage classes, for example, the set value may be set to be greater than or equal to 4.5m when the power transmission line is a dc overhead power transmission line of + 220V.
In conclusion, in the method for identifying the hidden danger of the tree obstacle in the corridor area of the power transmission line, the dangling points in the point cloud data of the laser radar in the corridor area of the power transmission line use the catenary equation and the sag equation to calculate the sag of the power transmission line between adjacent base towers so as to fit each power transmission line between the adjacent base towers; then, the point cloud data are classified to obtain power transmission line point cloud data, base tower point cloud data and vegetation point cloud data; constructing a columnar exploration space with the adjacent base towers, the power transmission lines between the adjacent base towers and the ground as boundaries on the basis of the point cloud data obtained after classification; and finally, obtaining the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying the trees of which the distance between the vegetation and the power transmission line is smaller than a set value. The method can find the hidden danger of the tree obstacle in the power transmission line in time, prevents trees from threatening the power transmission line, improves the accuracy of identification compared with the traditional manual measurement and elimination, and realizes automatic measurement and calculation of the safety distance and marking of the hidden danger point of the tree obstacle.
The above description is only a preferred embodiment of the present invention, and does not limit the present invention in any way. It will be understood by those skilled in the art that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. A method for identifying hidden danger of tree obstacle in a corridor area of a power transmission line is characterized by comprising the following steps:
acquiring point cloud data of a laser radar in a power transmission line corridor area, classifying the point cloud data, and extracting the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data;
calculating sag of the power transmission line by using a catenary equation and a sag equation according to the power transmission line point cloud data so as to fit each power transmission line;
constructing a columnar exploration space with a foundation tower, a power transmission line and the ground as boundaries on the basis of the point cloud data obtained after classification;
and acquiring the distance between the vegetation in the columnar exploration space and the power transmission line, and identifying trees of which the distance between the vegetation and the power transmission line is smaller than a set value.
2. The method for identifying the hidden danger of the tree obstacle in the corridor area of the power transmission line according to claim 1, wherein a coordinate system is established by taking a left suspension point of the power transmission line as a coordinate origin, taking a horizontal direction as an x-axis and taking a vertical direction as a y-axis, and the catenary equation is as follows:
the sag equation is:
wherein σ0The horizontal stress of the power transmission line, gamma is the specific load of the power transmission line, ch is a hyperbolic cosine function, H is the height difference between two suspension points of the power transmission line, L is the span between the two suspension points of the power transmission line, a is the horizontal distance from the suspension point of the origin of coordinates to the lowest point of the power transmission line, and H is the height difference value from the lowest point of the power transmission line to the left suspension point.
3. The method for identifying hidden danger of tree obstacles in the corridor area of the power transmission line according to claim 2, wherein the catenary equation and the sag equation are fitted and solved by adopting a nonlinear least square confidence domain iterative algorithm so as to realize the fitting of each power transmission line.
4. The method for identifying hidden danger of tree obstacles in the corridor area of the power transmission line according to claim 1, wherein the step of classifying the point cloud data and extracting the point cloud data of the power transmission line, the point cloud data of the base tower and the point cloud data of the vegetation comprises the following steps:
filtering the point cloud data to separate out ground points and non-ground points;
filtering the ground points to obtain the non-ground points, wherein the non-ground points comprise the power transmission line point cloud data, the base tower point cloud data and the vegetation point cloud data;
separating suspension points in the non-ground points to obtain the point cloud data of the power transmission line;
separating the base tower point cloud data by using the direction characteristics, and separating the vegetation point cloud data and the building point cloud data by using the dimension characteristics;
and respectively separating the vegetation point cloud data and the building point cloud data according to the spherical target or the planar target displayed in the point cloud data space.
5. The method for identifying hidden danger of tree obstacles in the corridor area of the power transmission line according to claim 1, wherein the step of obtaining the distance between the vegetation in the columnar exploration space and the power transmission line and identifying the trees with the distance between the vegetation and the power transmission line being smaller than a set value comprises the following steps:
performing single-tree segmentation processing on the vegetation point cloud data in the columnar exploration space to obtain point cloud data corresponding to each tree;
and calculating the distance between each tree and the corresponding power transmission line, and identifying the trees of which the distance between each tree and the corresponding power transmission line is less than the set value.
6. The method for identifying potential tree obstacle in the corridor area of the power transmission line according to claim 5, wherein the distance between each tree and the corresponding power transmission line is a clearance distance.
7. The transmission of electricity according to claim 6The method for identifying the hidden danger of the tree obstacle in the area of the route corridor is characterized in that the clearance distance D is calculated according to the following formulav：
Dv＝D1-f-D2-Δh-10.2；
Wherein D1 is the height of the left base tower, D2 is the height of the tree, delta h is the construction margin, and f is the sag of any point of the power transmission line.
8. The method for identifying the hidden danger of tree obstacle in the corridor area of the power transmission line according to claim 6, wherein the set value is greater than or equal to 13.5 m.
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| CN112381041A (en) * | 2020-11-27 | 2021-02-19 | 广东电网有限责任公司肇庆供电局 | Tree identification method and device for power transmission line and terminal equipment |
| CN112558091A (en) * | 2020-11-27 | 2021-03-26 | 广东电网有限责任公司肇庆供电局 | Real-time detection method and device for spatial distance of power transmission line to tree and terminal equipment |
| CN112684449A (en) * | 2021-03-22 | 2021-04-20 | 北京东方至远科技股份有限公司 | Water area power line sag inversion method and device based on SAR technology |
| CN113358033A (en) * | 2021-05-25 | 2021-09-07 | 晋能控股煤业集团有限公司 | Method for judging safe distance of trees under power transmission line based on visual analysis soft measurement |
| CN114431018A (en) * | 2022-03-22 | 2022-05-06 | 南方电网电力科技股份有限公司 | Tree obstacle clearing method, device and system |
| CN116935234A (en) * | 2023-09-18 | 2023-10-24 | 众芯汉创(江苏)科技有限公司 | Automatic classification and tree obstacle early warning system and method for power transmission line corridor point cloud data |
| CN117132915A (en) * | 2023-10-27 | 2023-11-28 | 国网江西省电力有限公司电力科学研究院 | Power transmission line tree obstacle hidden danger analysis method based on automatic classification of point cloud |
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| CN113358033B (en) * | 2021-05-25 | 2022-09-16 | 晋能控股煤业集团有限公司 | Method for judging safe distance of trees under power transmission line based on visual analysis soft measurement |
| CN113358033A (en) * | 2021-05-25 | 2021-09-07 | 晋能控股煤业集团有限公司 | Method for judging safe distance of trees under power transmission line based on visual analysis soft measurement |
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| CN116935234A (en) * | 2023-09-18 | 2023-10-24 | 众芯汉创(江苏)科技有限公司 | Automatic classification and tree obstacle early warning system and method for power transmission line corridor point cloud data |
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| CN117132915B (en) * | 2023-10-27 | 2024-03-12 | 国网江西省电力有限公司电力科学研究院 | Power transmission line tree obstacle hidden danger analysis method based on automatic classification of point cloud |
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