CN113205147A - Laser point cloud classification method for overhead transmission line engineering - Google Patents
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Abstract
The invention relates to a classification method in data processing in power transmission line engineering, in particular to a laser point cloud classification method for overhead power transmission line engineering, which is characterized by comprising the following steps: intersecting analysis is carried out on the maximum safety arc vertical plane and the DSM made of the point cloud, the danger range is determined, and errors and omissions in the danger area are avoided through artificial subjective judgment; after the terrain analysis method is used for classifying the terrain of the area, deviation caused by artificial subjectivity can be avoided, meanwhile, point cloud classification is carried out through iterative classification parameters, subjective influence caused by artificial configuration of the classification parameters is reduced, and accuracy of automatic classification results is improved; different point cloud editing methods are adopted for different dangerous areas, accuracy of a key position DEM result is guaranteed, efficiency of point cloud data processing and result quality are improved, and a good technical basis is provided for safety design, construction and operation and maintenance of the power transmission line.
Description
Technical Field
The invention relates to a classification method in data processing in power transmission line engineering, in particular to a laser point cloud classification method for overhead power transmission line engineering.
Background
In the design process of the power transmission line, a Digital Elevation Model (DEM) mainly utilizes an airborne laser scanning technology to collect a line section, a tower footing section and the like, can obtain point cloud data of a power transmission line corridor, obtains ground points after point cloud filtering classification and editing, constructs the DEM and provides important basic Elevation data for the safety design of the power transmission line. In the area with luxuriant vegetation, the problem of vegetation shelter which cannot be avoided by the traditional image-based photogrammetry technology leads to the fact that the ground elevation below the vegetation cannot be accurately measured, so that the manufactured DEM cannot be guaranteed in precision, and the laser point cloud technology has certain vegetation penetration capacity and is the optimal measurement scheme for solving the problem of vegetation shelter at present.
In the existing laser point cloud data processing process, the filtering and classified extraction of the point cloud accounts for about 60-80% of the workload in the whole data processing process, and particularly in areas with luxuriant vegetation and serious shielding, comprehensive manual inspection and editing are needed. However, the manual handling error is large, the efficiency is low, and most importantly, dangerous points in the corridor of the power transmission line are easily missed, which causes that the line construction or operation is difficult to carry out, thereby generating a great line change situation, even a safety accident, and causing economic loss, construction period delay and personal and property loss.
Disclosure of Invention
The invention aims to provide the laser point cloud classification method for the overhead transmission line engineering, which has high processing efficiency, effectively avoids omission of dangerous points, ensures stable operation of construction and operation and improves the safety of line engineering.
The purpose of the invention is realized by the following ways:
the laser point cloud classification method for the overhead transmission line engineering is characterized by comprising the following steps:
1) providing a point cloud data processing system, importing the acquired laser point cloud data of the power transmission line corridor, and filtering the laser point cloud data to remove obvious error points;
2) manufacturing a digital surface model DSM according to the filtered laser point cloud data;
3) acquiring design data of all towers on a power transmission line corridor, wherein the design data comprises three-dimensional coordinates, tower types, elevation values, insulator string lengths and maximum wind deflection angles, and the elevation values are actually measured elevation values;
4) traversing all adjacent towers according to the design data of each tower, simulating each line sag by using a catenary equation, acquiring the maximum sag of the line and calculating the maximum wind drift angle; on the basis of simulating each line sag, uniformly subtracting the maximum safety distance of paired lines from each elevation value to be used as a buffer safety distance, and using the buffer safety distance as a corresponding safety arc perpendicular line;
5) the connecting line of two insulator strings or wire hanging points is used as a rotating shaft, the safety arc perpendicular lines of the central line, the left side line and the right side line of the line and the insulator strings rotate together respectively, the line rotates leftwards and rightwards by 0.5 times of the maximum wind deflection angle, and three curved surfaces formed by the safety arc perpendicular lines of the central line, the left side line and the right side line of the line respectively due to rotation are used as corresponding safety arc vertical surfaces;
6) intersecting the three safety arc vertical surfaces, and acquiring the lowest elevation value at the intersection position to form a maximum safety arc vertical surface;
7) the DSM between adjacent towers is divided into 5 range surfaces according to the sidelines and the range lines: setting a sideline surface in the range of the two sidelines as an a surface; the area of the left sideline and the left range line is a left range surface and is set as a b surface; the area of the right sideline and the right range line is a right range surface which is set as a c surface; fourthly, setting the left range line to the DSM data edge as a left windage yaw surface as a d surface; the right range line to the DSM data edge is a right windage yaw plane which is set as an e plane;
8) traversing all range surfaces of a-e, respectively carrying out 3D intersection analysis with the vertical surface of the maximum safety arc, searching the intersection range of the range surfaces and the maximum safety arc, extracting the closing line of the intersection edge, namely the danger range line, and assigning different colors: intersecting a sideline surface and a maximum safety arc vertical surface to generate a sideline danger range line which is set to be red; intersecting the left range surface and the right range surface with the maximum safety arc vertical surface to generate a plane danger range line which is set to be carmine; thirdly, the left windage yaw plane and the right windage yaw plane are respectively intersected with the vertical plane of the maximum safety arc to generate a windage yaw danger range line which is set to be yellow;
9) according to the voltage grade of the power transmission line, extending the windage yaw danger range line for a specified distance along a direction perpendicular to the line and far away from the line; all danger range lines are used as vector file formats supported by a point cloud data processing system;
10) in the point cloud data processing system, setting ground point classification parameters according to the power transmission line corridor Terrain, wherein the ground point classification parameters comprise side length Max building size of a maximum building, maximum slope Terrain angle allowed by the earth surface and repeated parameters, and generating an initial DEM;
11) carrying out terrain analysis on the initial DEM, extracting factors reflecting the terrain, including gradient, slope direction, elevation banding and terrain correction, grading according to the terrain gradient to divide the factors into different terrain categories, and then dividing the point cloud data into a plurality of sub-areas according to the terrain categories;
12) traversing the sub-regions, iterating the repeated parameters and the maximum gradient of the ground point classification parameters on the basis of the initial ground point classification parameters, restarting automatic classification until the classified ground points are increased by less than 5%, and then re-manufacturing a DEM according to the obtained automatic classification ground points;
13) displaying an elevation model rendered by automatically classifying ground points and a dangerous range line file simultaneously in a point cloud data processing system, further traversing all dangerous range lines, and calculating the ground point density in the dangerous range lines;
14) comparing the image with the field actual measurement elevation points, searching for ground point missing or density insufficient areas in the danger range line according to precision setting, and editing, wherein the steps comprise collecting the elevation points and terrain fitting;
15) and (4) constructing a final DEM (digital elevation model) for making a section map by utilizing the field actual measurement elevation points and the edited point cloud ground points.
In summary, the invention provides a laser point cloud classification method for overhead transmission line engineering, which has the technical key points and the technical effects that:
1. and fitting the power curves under the maximum sag and the maximum wind drift angle, considering the safety distance, manufacturing the maximum safety arc sag, considering the power line position under the extreme condition into the design range, and simulating the position of the real power curve to the maximum extent. And intersecting and analyzing the maximum safety arc vertical plane and the DSM (digital surface model) made of the point cloud to determine the danger range, and avoiding errors and omissions of the danger area judged by manpower subjectively.
2. After the terrain analysis method is used for classifying the terrain of the area, deviation caused by artificial subjectivity can be avoided, meanwhile, point cloud classification is carried out through iterative classification parameters, subjective influence caused by artificial configuration of the classification parameters is reduced, and accuracy of automatic classification results is improved.
3. Different point cloud editing methods are adopted for different dangerous areas, so that the editing work of area point clouds which have no absolute safety influence on lines is eliminated, the pertinence of point cloud processing can be improved, the workload of point cloud editing is reduced, the accuracy of a key position DEM result is ensured, and the special requirements of a power transmission line on DEM data are met.
4. The field actual measurement ground elevation points and the ground points in the point cloud are fused, and the DEM is constructed, so that the utilization efficiency of data and the achievement precision are improved.
5. The invention aims at the special requirements on geographic information data in the process of influencing the engineering safety design of the power transmission line, and performs targeted processing. The method comprises the steps of finding a dangerous area in an overhead transmission line corridor by fitting a transmission line and sag under the maximum working condition, carrying out targeted inspection and key analysis on point cloud in the dangerous area by optimizing a point cloud data processing method, improving the efficiency and the achievement quality of point cloud data processing while avoiding missing dangerous points, and providing a good technical basis for the safety design, construction and operation and maintenance of the transmission line.
Drawings
Fig. 1 is a schematic flow chart of steps of the laser point cloud classification method for the overhead transmission line engineering.
The present invention will be further described with reference to the following examples.
Detailed Description
The best embodiment is as follows:
in order to provide a better understanding of the present invention, the following provides definitions of terms in the power transmission line and point cloud data technology of the present invention:
line center line: and connecting the central points of the transmission line towers.
Line sideline: and (4) a wire sideline of the power transmission line.
A section diagram of the power transmission line: the section lines along the center of the line first mark the terrain, location and elevation of the exaggeration along the center line. The transmission line has three section lines, and a section is respectively cut from the left side line, the right side line and the central line.
Line plan range: and the strip-shaped areas of 20-75m are respectively arranged towards the left and the right along the central line of the line.
DSM: a Digital Surface Model (Digital Surface Model) is a ground elevation Model that includes the height of Surface buildings, bridges, trees, etc.
DEM: a Digital Elevation Model (DEM), which is a solid ground Model that uses a group of ordered numerical arrays to represent ground Elevation, is a branch of a Digital Terrain Model (DTM), from which various other Terrain feature values can be derived.
The terrain category: classifying according to the terrain inclination angle a: leveling land: a < 3 °; in hilly areas: a is more than or equal to 3 degrees and less than 10 degrees; mountain land: a is more than or equal to 10 degrees and less than 25 degrees; high mountain land: a is more than or equal to 25 °
Wind deflection angle: the lead of the power transmission line deviates from the vertical position after being acted by wind, and the lead deviates from the vertical position when being seen along the line direction.
Topographic analysis: and extracting feature elements reflecting the terrain, and finding out the spatial distribution features of the terrain. The various operations of terrain analysis are mainly based on the grid DEM, and various factors reflecting the terrain are extracted: slope, slope direction, elevation banding, terrain correction and the like.
3D intersection analysis: the intersection of polyhedral elements is calculated to generate closed polyhedrons containing overlapping volumes, non-closed polyhedral elements are generated from a common surface area, or line elements are generated from intersecting edges.
Catenary wire: catenary (catenaria) refers to a curve, which is the shape of a uniform, soft (non-extensible) chain with fixed ends (thickness and mass distribution) under the action of gravity.
Point cloud ground point classification parameters: in the algorithm of ground point classification, several parameters need to be set: the length of a side Max building size of a maximum building, the maximum slope Terrain angle allowed by the earth surface, Iteration parameters (Iteration angle, Iteration distance, i.e. the distance and the included angle between the current point and the triangle when the triangle is repeatedly constructed), the condition Edge length of the current point is not added, and the condition Edge length of exiting the triangle in the current cycle is stopped.
The Iteration angle is the maximum included angle value of a plane formed by the connection line of the point and the nearest vertex of the triangle and the triangle, and the smaller the value is, the smaller the fluctuation change in the point cloud is, namely, the points with large fluctuation change are excluded from the ground model.
The Iteration distance ensures that when the triangle is large, there is no large jump in building the triangle repeatedly upwards, helping to exclude short buildings from the model, with values between 0.5 and 1.5 meters.
Tertain angle is the maximum angle allowed for controlling the ground. The angle can be set differently for different terrain and different areas. The maximum angle of the flat land area is smaller, and the larger angle is needed to be set in the places with mountains and hills. When the mountain is high, the maximum can be set to about 85.
Referring to the attached figure 1, the laser point cloud classification method for the overhead transmission line engineering, disclosed by the invention, comprises the following steps of:
1. and importing laser point data to look up by using a point cloud data processing system, filtering and removing obvious error points.
2. And manufacturing the DSM by using the point cloud data.
3. And acquiring all tower design information (including three-dimensional coordinates, tower shapes, breath heights, base dips, insulator string lengths, maximum wind deflection angles, k values under different working conditions and the like), wherein the tower elevation value is an actually measured elevation value.
4. And traversing all adjacent towers, simulating the maximum sag of the line and calculating the maximum wind drift angle by using a catenary equation according to the tower position information and the design parameters.
5. On the basis of simulating the line sag, buffering the safe distance (the maximum safe distance of the pair line is uniformly subtracted from the elevation value of the power sag) to serve as a corresponding safe arc-perpendicular line.
6. The safety arc vertical lines of the central line and the left and right sidelines rotate together with the insulator strings respectively, the rotating shaft is a connecting line of two insulator strings or wire hanging points (if the rotating shaft is a tension tower, the length of the insulator strings does not need to be considered), the rotating shaft rotates left and right by 0.5 times of the maximum wind deflection angle respectively, and the curved surface formed by the rotation of the safety arc vertical lines of the central line and the left and right sidelines is a corresponding safety arc vertical surface.
7. And (6) intersecting the three safety arc vertical surfaces generated in the step (6), and taking the lowest elevation value at the intersection to form the maximum safety arc vertical surface.
8. The DSM between adjacent towers is divided into 5 range surfaces according to the sidelines and the range lines: the method comprises the following steps that firstly, sideline surfaces (a surfaces) are arranged in the range of two sidelines; the area of the left sideline and the left range line is a left range surface (b surface); the area of the right sideline and the right range line is a right range surface (c surface); and fourthly, respectively taking the left and right range lines to the DSM data edge as left and right wind deflection surfaces (d surface and e surface).
9. Traversing all range surfaces (a-e surfaces), respectively carrying out 3D intersection analysis with the vertical surface of the maximum safety arc, searching the intersection range of the two, extracting the range line (closing line) of the intersection edge, namely the danger range line, and assigning different colors: intersecting a sideline surface and a maximum safety arc vertical surface to generate a sideline danger range line which is set to be red; intersecting the left range surface and the right range surface with the maximum safety arc vertical surface to generate a plane danger range line which is set to be carmine; and the left wind deflection surface and the right wind deflection surface are intersected with the vertical surface of the maximum safety arc to generate a wind deflection danger range line which is set to be yellow.
10. According to the grade of the power transmission line, according to the specification requirement, the windage yaw danger range line extends for a specified distance (a specific numerical value is taken according to the voltage grade) along the direction perpendicular to the line and far away from the line.
11. And (3) making all the dangerous range lines as vector file formats supported by point cloud processing software (such as terasolidd supporting dwg and dng).
12. In point cloud processing software, automatic ground point classification parameters are set according to main terrains, and a DEM is generated.
13. And carrying out terrain analysis on the DEM, classifying the DEM into different terrain categories according to a slope angle, and dividing the point cloud data into a plurality of sub-areas according to the terrain.
14. Traversing the sub-regions, iterating ground point classification parameters Iteration and Terrain angle on the basis of the initial classification parameters, restarting automatic classification until the classified ground points are increased by less than 5%, obtaining automatic classification ground points and making a DEM.
16. And displaying the elevation model rendered by automatically classifying ground points and the dangerous range line file simultaneously in the point cloud processing software.
17. And traversing all the danger range lines, and calculating the ground point density (the number of the ground points in the unit area) in the danger range lines.
18. And comparing the image with the field actual measurement points, searching for the area with ground point missing or insufficient density in the dangerous range line according to the precision requirement, and editing, wherein the editing mainly comprises the steps of collecting elevation points and terrain fitting. If the number of surface points in the line of the risk range is sufficient, a simple visual inspection is performed.
19. And uniformly constructing the DEM by utilizing the field actual measurement elevation points and the edited point cloud ground points. Used for making a cross-sectional view.
20. After the editing of the ground points is completed, on the basis of the ground points, the points of the types such as vegetation points, house points, crossing points and the like are extracted, and a thematic elevation model is constructed. The method is used for manufacturing tree height sections and extracting cross-over elevation information.
The parts of the invention not described are the same as the prior art.
Claims (1)
1. The laser point cloud classification method for the overhead transmission line engineering is characterized by comprising the following steps:
1) providing a point cloud data processing system, importing the acquired laser point cloud data of the power transmission line corridor, and filtering the laser point cloud data to remove obvious error points;
2) manufacturing a digital surface model DSM according to the filtered laser point cloud data;
3) acquiring design data of all towers on a power transmission line corridor, wherein the design data comprises three-dimensional coordinates, tower types, elevation values, insulator string lengths and maximum wind deflection angles, and the elevation values are actually measured elevation values;
4) traversing all adjacent towers according to the design data of each tower, simulating each line sag by using a catenary equation, acquiring the maximum sag of the line and calculating the maximum wind drift angle; on the basis of simulating each line sag, uniformly subtracting the maximum safety distance of paired lines from each elevation value to be used as a buffer safety distance, and using the buffer safety distance as a corresponding safety arc perpendicular line;
5) the connecting line of two insulator strings or wire hanging points is used as a rotating shaft, the safety arc perpendicular lines of the central line, the left side line and the right side line of the line and the insulator strings rotate together respectively, the line rotates leftwards and rightwards by 0.5 times of the maximum wind deflection angle, and three curved surfaces formed by the safety arc perpendicular lines of the central line, the left side line and the right side line of the line respectively due to rotation are used as corresponding safety arc vertical surfaces;
6) intersecting the three safety arc vertical surfaces, and acquiring the lowest elevation value at the intersection position to form a maximum safety arc vertical surface;
7) the DSM between adjacent towers is divided into 5 range surfaces according to the sidelines and the range lines: setting a sideline surface in the range of the two sidelines as an a surface; the area of the left sideline and the left range line is a left range surface and is set as a b surface; the area of the right sideline and the right range line is a right range surface which is set as a c surface; fourthly, setting the left range line to the DSM data edge as a left windage yaw surface as a d surface; the right range line to the DSM data edge is a right windage yaw plane which is set as an e plane;
8) traversing all range surfaces of a-e, respectively carrying out 3D intersection analysis with the vertical surface of the maximum safety arc, searching the intersection range of the range surfaces and the maximum safety arc, extracting the closing line of the intersection edge, namely the danger range line, and assigning different colors: intersecting a sideline surface and a maximum safety arc vertical surface to generate a sideline danger range line which is set to be red; intersecting the left range surface and the right range surface with the maximum safety arc vertical surface to generate a plane danger range line which is set to be carmine; thirdly, the left windage yaw plane and the right windage yaw plane are respectively intersected with the vertical plane of the maximum safety arc to generate a windage yaw danger range line which is set to be yellow;
9) according to the voltage grade of the power transmission line, extending the windage yaw danger range line for a specified distance along a direction perpendicular to the line and far away from the line; all danger range lines are used as vector file formats supported by a point cloud data processing system;
10) in the point cloud data processing system, setting ground point classification parameters according to the power transmission line corridor Terrain, wherein the ground point classification parameters comprise side length Max building size of a maximum building, maximum slope Terrain angle allowed by the earth surface and repeated parameters, and generating an initial DEM;
11) carrying out terrain analysis on the initial DEM, extracting factors reflecting the terrain, including gradient, slope direction, elevation banding and terrain correction, grading according to the terrain gradient to divide the factors into different terrain categories, and then dividing the point cloud data into a plurality of sub-areas according to the terrain categories;
12) traversing the sub-regions, iterating the repeated parameters and the maximum gradient of the ground point classification parameters on the basis of the initial ground point classification parameters, restarting automatic classification until the classified ground points are increased by less than 5%, and then re-manufacturing a DEM according to the obtained automatic classification ground points;
13) displaying an elevation model rendered by automatically classifying ground points and a dangerous range line file simultaneously in a point cloud data processing system, further traversing all dangerous range lines, and calculating the ground point density in the dangerous range lines;
14) comparing the image with the field actual measurement elevation points, searching for ground point missing or density insufficient areas in the danger range line according to precision setting, and editing, wherein the steps comprise collecting the elevation points and terrain fitting;
15) and (4) constructing a final DEM (digital elevation model) for making a section map by utilizing the field actual measurement elevation points and the edited point cloud ground points.
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