CN112882047A - Laser point cloud based automatic acquisition method and system for power line inter-phase distance - Google Patents
Laser point cloud based automatic acquisition method and system for power line inter-phase distance Download PDFInfo
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- CN112882047A CN112882047A CN202110004342.0A CN202110004342A CN112882047A CN 112882047 A CN112882047 A CN 112882047A CN 202110004342 A CN202110004342 A CN 202110004342A CN 112882047 A CN112882047 A CN 112882047A
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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
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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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
Abstract
The utility model provides a method and a system for automatically acquiring the inter-phase distance of a power line based on laser point cloud, which determine the central plane coordinate of a target tower for extracting the inter-phase distance according to the acquired point cloud data; projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation; extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution; extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position; calculating the space distance between the split point positions corresponding to the upper phase and the middle phase or the middle phase and the lower phase; the method has high operation efficiency, avoids errors possibly caused by manual measurement, and also eliminates errors or mistakes introduced by manual modeling.
Description
Technical Field
The disclosure relates to the technical field of power grid engineering, in particular to a method and a system for automatically acquiring power line inter-phase distance based on laser point cloud.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Under the influence of severe weather such as low temperature, rain, snow, strong wind and the like, the transmission line has the problem of conductor galloping, and a tripping accident can be caused in severe cases. The main measure for solving the conductor galloping is to design and produce an anti-galloping device with a specific specification by measuring the distance between adjacent conductors and additionally install the anti-galloping device on the corresponding conductor of the power transmission line.
The inventor finds that the wire inter-phase distance measurement can adopt methods such as total station prism-free measurement, ground laser scanning or airborne laser radar scanning and the like. The total station instrument needs to invest more manpower and material resources in prism-free measurement, is influenced by various factors such as weather and terrain, and has limited operation time and low working efficiency. Ground laser scanning and airborne laser radar scanning can acquire certain range point cloud data more rapidly, and the operating efficiency is high, and the restriction factor is less relatively.
The conductor spacing distance is obtained based on the classified point cloud, and one method is to measure manually in a three-dimensional scene by means of professional point cloud data processing software, so that the efficiency of the internal operation is low, and meanwhile, the possibility of errors exists in manual interpretation; the other method is to use point cloud data to model or fit the conducting wire, measure or calculate the conducting wire distance between phases in a two-dimensional environment, but the modeling or fitting process needs a certain professional basis, and meanwhile, the conducting wire is not an ideal curve under the actual working condition under the influence of factors such as wind, temperature and the like, and new errors are introduced to the measurement by obtaining the conducting wire distance between phases through modeling or fitting, and even errors are caused in severe cases.
Disclosure of Invention
In order to solve the defects of the prior art, the method and the system for automatically acquiring the interphase distance of the power conductor based on the laser point cloud are provided, the classified laser point cloud data are directly utilized to acquire the three-dimensional coordinates on the conductor of the target position, so that the corresponding interphase distance of the conductor is accurately calculated, any two-three-dimensional measurement work is not needed, the operation efficiency is high, errors possibly caused by manual measurement are avoided, and errors or errors introduced by manual modeling are eliminated.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
the first aspect of the disclosure provides a method for automatically acquiring power conductor phase-to-phase distance based on laser point cloud.
A method for automatically acquiring power line phase-to-phase distance based on laser point cloud comprises the following steps:
acquiring point cloud data of the power transmission line;
determining the central plane coordinates of the target tower from which the inter-phase distances are to be extracted according to the acquired point cloud data, and constructing a line space coordinate system;
projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation;
extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution;
extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position;
the spatial distance between the corresponding split point positions of the upper phase and the middle phase or the middle phase and the lower phase is calculated.
As some possible implementation manners, a line space coordinate system is established by taking the center of a certain tower as an origin of coordinates, taking a connecting line between the centers of two towers as an X direction, taking a perpendicular line of the X direction as a Y direction, and taking a perpendicular line direction as a Z direction.
As some possible implementation manners, the method for acquiring the central plane coordinates of the target tower comprises the following steps:
and (3) extracting the center point of the tower by using the tower characteristic points or performing density-based clustering on the point cloud data by using a field actual measurement method to extract the center of the tower.
As some possible implementations, the power line target location is a location of a power line target accumulated distance.
As some possible implementation manners, 0.5m point cloud data before and after the power line target position are extracted.
As some possible implementations, when the splitting is four-splitting, a method for acquiring conductor point cloud data of a certain phase on a certain side of the power conductor includes:
calculating the average value of point cloud Y coordinates
The point cloud of all the phase wires on one side is larger than
Classifying the point cloud as a left split point cloud, smaller than
Classifying the point cloud into a right split point cloud;
respectively calculating the Z coordinate average value of the classified point clouds
Is greater than
Is an upper split point cloud, smaller than
The point cloud of (a) is a lower split point cloud.
As a further limitation, the inter-phase distances corresponding to the top-left split, the bottom-left split, the top-right split and the bottom-right split are calculated respectively, and the average value of the splits is taken as the final result.
The second aspect of the disclosure provides a power line inter-phase distance automatic acquisition system based on laser point cloud.
A power line inter-phase distance automatic acquisition system based on laser point cloud comprises:
a data acquisition module configured to: acquiring point cloud data of the power transmission line;
a coordinate determination module configured to: determining the central plane coordinates of the target tower from which the inter-phase distances are to be extracted according to the acquired point cloud data, and constructing a line space coordinate system;
a point cloud projection module configured to: projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation;
a point cloud extraction module configured to: extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution;
a point cloud fitting module configured to: extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position;
a distance calculation module configured to: the spatial distance between the corresponding split point positions of the upper phase and the middle phase or the middle phase and the lower phase is calculated.
A third aspect of the present disclosure provides a computer-readable storage medium on which a program is stored, which when executed by a processor, implements the steps in the method for automatically acquiring the inter-phase distance of power conductors based on a laser point cloud according to the first aspect of the present disclosure.
A fourth aspect of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, where the processor executes the program to implement the steps in the method for automatically acquiring the inter-phase distance of the power line based on the laser point cloud according to the first aspect of the present disclosure.
Compared with the prior art, the beneficial effect of this disclosure is:
according to the method, the system, the medium or the electronic equipment, the classified laser point cloud data are directly utilized to obtain the three-dimensional coordinates on the target position wire, so that the corresponding wire inter-phase distance is accurately calculated, any two-three-dimensional measurement work is not needed, the operation efficiency is high, errors possibly caused by manual measurement are avoided, and errors or errors caused by manual modeling are eliminated.
Advantages of additional aspects of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a schematic diagram of calculating a spatial distance of a conducting wire according to embodiment 1 of the present disclosure.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
Example 1:
the embodiment 1 of the disclosure provides a method for automatically acquiring power line inter-phase distance based on laser point cloud, which comprises the following steps:
step 1: acquiring classified power transmission line point cloud data, including power line point cloud data and tower point cloud data;
the method comprises the steps of scanning and collecting point cloud data along the center of a power line through airborne laser radar equipment, resolving through DGPS/IMU combined calculation to obtain original point cloud data, filtering and classifying the point cloud through data processing software, and obtaining power line point cloud data and tower point cloud data.
Considering the influence of wind on the power line, the power line is actually in a swing state, and when laser scanning is performed, point cloud results of reciprocating scanning need to be distinguished.
Step 2: determining center plane coordinates { C of tower1(x,y)，C2(x,y)，…，Cn(x, y) }. The coordinates of the center plane of the tower can be obtained by the following three ways:
1) a field actual measurement method;
2) extracting the center point of the tower by using the characteristic points of the tower, such as an insulator string, the top point of the tower and the like;
3) and performing density-based clustering on the point cloud data, and extracting the center of the tower.
And step 3: determining a target tower position for extracting the inter-phase distance: ci(x,y)，Ci+1And (x, y), wherein i and i +1 are tower numbers, and power line laser point cloud data between two towers are extracted.
And 4, step 4: with Ci(x, y) is the origin of coordinates, Ci(x,y)，Ci+1And (X, Y) connecting lines are in the X direction, the perpendicular line direction is in the Y direction, the plumb line direction is in the Z axis, a line space coordinate system is established, the power line laser point cloud data is projected into the line space coordinate system, the X coordinate is the accumulated distance, the Y coordinate is the offset distance, and the Z coordinate is the elevation.
And 5: extracting power line target position (accumulated distance X)SPosition) and front and back 0.5m point cloud data, respectively extracting upper phase, middle phase and lower phase point cloud data of left/right line according to Y value positive and negative and elevation Z value distribution to obtain
Wherein L represents the left line, i.e., the value of Y is a positive value, and R represents the right line, i.e., the value of Y is a negative value; i is 1,2,3, which represents an upper phase, a middle phase and a lower phase, respectively; j is the point cloud sequence number.
Step 6: each phase of the power conductor can be divided into two-split, three-split, four-split, etc. according to the electrical characteristics of the power transmission line.
Taking a 500kV power transmission line as an example, each phase of wire of the power line is divided into four parts. And respectively extracting the split point cloud data according to the distribution of Y values and Z values in the point cloud data of each phase of conductor.
Taking the phase conductor on the left line as an example, the average value of the Y coordinates of the point cloud is calculated first
The point cloud of all the phase conductors on the left line is traversed to be larger than
Classifying the point cloud as a left split point cloud, smaller than
Classifying the point cloud into a right split point cloud;
secondly, respectively calculating the Z coordinate average value of the classified point clouds
Is greater than
Is an upper split point cloud, smaller than
The point cloud of (a) is a lower split point cloud. Classifying the post-point cloud
Wherein k is 1,2,3,4, respectively representing upper left, lower left, upper right, lower rightAs shown in fig. 1.
And 7: performing curve fitting on the point cloud data of each split of each phase, and calculating a target accumulated distance X by interpolationSAnd (4) three-dimensional coordinates of each point position on the position wire.
And 8: the spatial distance of the corresponding split point location of the superior/middle or middle/lower phase is calculated.
Taking the left line and the upper left split as an example, the coordinates corresponding to the upper phase position are
The coordinates corresponding to the middle phase position are
The coordinate corresponding to the lower phase position is
The distance between the upper phase/middle phase is:
the distance between the middle phase and the lower phase is:
in order to ensure the accuracy of measuring the inter-phase distance and improve the measurement precision, the inter-phase distances corresponding to the upper left, lower left, upper right and lower right splits are respectively calculated, the average value is taken as the final result, and meanwhile, the error is calculated as the measurement precision index:
where n is the number of conductor splits, for this example (500kV transmission line), n is 4.
Example 2:
the embodiment 2 of the present disclosure provides an automatic acquisition system of power line inter-phase distance based on laser point cloud, including:
a data acquisition module configured to: acquiring point cloud data of the power transmission line;
a coordinate determination module configured to: determining the central plane coordinates of the target tower from which the inter-phase distances are to be extracted according to the acquired point cloud data, and constructing a line space coordinate system;
a point cloud projection module configured to: projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation;
a point cloud extraction module configured to: extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution;
a point cloud fitting module configured to: extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position;
a distance calculation module configured to: the spatial distance between the corresponding split point positions of the upper phase and the middle phase or the middle phase and the lower phase is calculated.
The working method of the system is the same as the method for automatically acquiring the inter-phase distance of the power line conductor based on the laser point cloud provided in embodiment 1, and details are not repeated here.
Example 3:
the embodiment 3 of the present disclosure provides a computer-readable storage medium, on which a program is stored, where the program, when executed by a processor, implements the steps in the method for automatically acquiring the inter-phase distance of the power line conductor based on the laser point cloud according to the embodiment 1 of the present disclosure, where the steps are:
step 1: acquiring classified power transmission line point cloud data, including power line point cloud data and tower point cloud data;
the method comprises the steps of scanning and collecting point cloud data along the center of a power line through airborne laser radar equipment, resolving through DGPS/IMU combined calculation to obtain original point cloud data, filtering and classifying the point cloud through data processing software, and obtaining power line point cloud data and tower point cloud data.
Considering the influence of wind on the power line, the power line is actually in a swing state, and when laser scanning is performed, point cloud results of reciprocating scanning need to be distinguished.
Step 2: determining center plane coordinates { C of tower1(x,y)，C2(x,y)，…，Cn(x, y) }. The coordinates of the center plane of the tower can be obtained by the following three ways:
1) a field actual measurement method;
2) extracting the center point of the tower by using the characteristic points of the tower, such as an insulator string, the top point of the tower and the like;
3) and performing density-based clustering on the point cloud data, and extracting the center of the tower.
And step 3: determining a target tower position for extracting the inter-phase distance: ci(x,y)，Ci+1And (x, y), wherein i and i +1 are tower numbers, and power line laser point cloud data between two towers are extracted.
And 4, step 4: with Ci(x, y) is the origin of coordinates, Ci(x,y)，Ci+1And (X, Y) connecting lines are in the X direction, the perpendicular line direction is in the Y direction, the plumb line direction is in the Z axis, a line space coordinate system is established, the power line laser point cloud data is projected into the line space coordinate system, the X coordinate is the accumulated distance, the Y coordinate is the offset distance, and the Z coordinate is the elevation.
And 5: extracting power line target position (accumulated distance X)SPosition) and front and back 0.5m point cloud data, respectively extracting upper phase, middle phase and lower phase point cloud data of left/right line according to Y value positive and negative and elevation Z value distribution to obtain
Wherein L represents the left line, i.e., the value of Y is a positive value, and R represents the right line, i.e., the value of Y is a negative value; i is 1,2,3, which represents an upper phase, a middle phase and a lower phase, respectively; j is the point cloud sequence number.
Step 6: each phase of the power conductor can be divided into two-split, three-split, four-split, etc. according to the electrical characteristics of the power transmission line.
Taking a 500kV power transmission line as an example, each phase of wire of the power line is divided into four parts. And respectively extracting the split point cloud data according to the distribution of Y values and Z values in the point cloud data of each phase of conductor.
Taking the phase conductor on the left line as an example, the average value of the Y coordinates of the point cloud is calculated first
The point cloud of all the phase conductors on the left line is traversed to be larger than
Classifying the point cloud as a left split point cloud, smaller than
Classifying the point cloud into a right split point cloud;
secondly, respectively calculating the Z coordinate average value of the classified point clouds
Is greater than
Is an upper split point cloud, smaller than
The point cloud of (a) is a lower split point cloud. Classifying the post-point cloud
Where k is 1,2,3,4, respectively representing upper left, lower left, upper right, lower right, as shown in fig. 1.
And 7: performing curve fitting on the point cloud data of each split of each phase, and calculating a target accumulated distance X by interpolationSAnd (4) three-dimensional coordinates of each point position on the position wire.
And 8: the spatial distance of the corresponding split point location of the superior/middle or middle/lower phase is calculated.
Taking the left line and the upper left split as an example, the coordinates corresponding to the upper phase position are
The coordinates corresponding to the middle phase position are
The coordinate corresponding to the lower phase position is
The distance between the upper phase/middle phase is:
the distance between the middle phase and the lower phase is:
in order to ensure the accuracy of measuring the inter-phase distance and improve the measurement precision, the inter-phase distances corresponding to the upper left, lower left, upper right and lower right splits are respectively calculated, the average value is taken as the final result, and meanwhile, the error is calculated as the measurement precision index:
where n is the number of conductor splits, for this example (500kV transmission line), n is 4.
Example 4:
the embodiment 4 of the present disclosure provides an electronic device, which includes a memory, a processor, and a program stored in the memory and capable of running on the processor, where the processor executes the program to implement the steps of the method for automatically acquiring the inter-phase distance between power lines based on laser point cloud in the embodiment 1 of the present disclosure, where the steps are as follows:
step 1: acquiring classified power transmission line point cloud data, including power line point cloud data and tower point cloud data;
the method comprises the steps of scanning and collecting point cloud data along the center of a power line through airborne laser radar equipment, resolving through DGPS/IMU combined calculation to obtain original point cloud data, filtering and classifying the point cloud through data processing software, and obtaining power line point cloud data and tower point cloud data.
Considering the influence of wind on the power line, the power line is actually in a swing state, and when laser scanning is performed, point cloud results of reciprocating scanning need to be distinguished.
Step 2: determining center plane coordinates { C of tower1(x,y)，C2(x,y)，…，Cn(x, y) }. The coordinates of the center plane of the tower can be obtained by the following three ways:
1) a field actual measurement method;
2) extracting the center point of the tower by using the characteristic points of the tower, such as an insulator string, the top point of the tower and the like;
3) and performing density-based clustering on the point cloud data, and extracting the center of the tower.
And step 3: determining a target tower position for extracting the inter-phase distance: ci(x,y)，Ci+1And (x, y), wherein i and i +1 are tower numbers, and power line laser point cloud data between two towers are extracted.
And 4, step 4: with Ci(x, y) is the origin of coordinates, Ci(x,y)，Ci+1And (X, Y) connecting lines are in the X direction, the perpendicular line direction is in the Y direction, the plumb line direction is in the Z axis, a line space coordinate system is established, the power line laser point cloud data is projected into the line space coordinate system, the X coordinate is the accumulated distance, the Y coordinate is the offset distance, and the Z coordinate is the elevation.
And 5: extracting power line target position (accumulated distance X)SPosition) and front and back 0.5m point cloud data, respectively extracting upper phase, middle phase and lower phase point cloud data of left/right line according to Y value positive and negative and elevation Z value distribution to obtain
Wherein L represents the left line, i.e., the value of Y is a positive value, and R represents the right line, i.e., the value of Y is a negative value; i is 1,2,3, which represents an upper phase, a middle phase and a lower phase, respectively; j is the point cloud sequence number.
Step 6: each phase of the power conductor can be divided into two-split, three-split, four-split, etc. according to the electrical characteristics of the power transmission line.
Taking a 500kV power transmission line as an example, each phase of wire of the power line is divided into four parts. And respectively extracting the split point cloud data according to the distribution of Y values and Z values in the point cloud data of each phase of conductor.
Taking the phase conductor on the left line as an example, the average value of the Y coordinates of the point cloud is calculated first
The point cloud of all the phase conductors on the left line is traversed to be larger than
Classifying the point cloud as a left split point cloud, smaller than
Classifying the point cloud into a right split point cloud;
secondly, respectively calculating the Z coordinate average value of the classified point clouds
Is greater than
Is an upper split point cloud, smaller than
The point cloud of (a) is a lower split point cloud. Classifying the post-point cloud
Where k is 1,2,3,4, respectively representing upper left, lower left, upper right, lower right, as shown in fig. 1.
And 7: performing curve fitting on the point cloud data of each split of each phase, and calculating a target accumulated distance X by interpolationSAnd (4) three-dimensional coordinates of each point position on the position wire.
And 8: the spatial distance of the corresponding split point location of the superior/middle or middle/lower phase is calculated.
Taking the left line and the upper left split as an example, the coordinates corresponding to the upper phase position are
The coordinates corresponding to the middle phase position are
The coordinate corresponding to the lower phase position is
The distance between the upper phase/middle phase is:
the distance between the middle phase and the lower phase is:
in order to ensure the accuracy of measuring the inter-phase distance and improve the measurement precision, the inter-phase distances corresponding to the upper left, lower left, upper right and lower right splits are respectively calculated, the average value is taken as the final result, and meanwhile, the error is calculated as the measurement precision index:
where n is the number of conductor splits, for this example (500kV transmission line), n is 4.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (10)
1. A method for automatically acquiring power line phase-to-phase distance based on laser point cloud is characterized by comprising the following steps: the method comprises the following steps:
acquiring point cloud data of the power transmission line;
determining the central plane coordinates of the target tower from which the inter-phase distances are to be extracted according to the acquired point cloud data, and constructing a line space coordinate system;
projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation;
extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution;
extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position;
the spatial distance between the corresponding split point positions of the upper phase and the middle phase or the middle phase and the lower phase is calculated.
2. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 1, wherein the method comprises the following steps:
a line space coordinate system is established by taking the center of a certain tower as the origin of coordinates, taking a connecting line between the centers of two towers as the X direction, taking the perpendicular line of the X direction as the Y direction and taking the perpendicular line direction as the Z direction.
3. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 1, wherein the method comprises the following steps:
the method for acquiring the center plane coordinates of the target tower comprises the following steps:
and (3) extracting the center point of the tower by using the tower characteristic points or performing density-based clustering on the point cloud data by using a field actual measurement method to extract the center of the tower.
4. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 1, wherein the method comprises the following steps:
the power line target position is a position of a power line target accumulated distance.
5. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 1, wherein the method comprises the following steps:
and extracting point cloud data of 0.5m before and after the target position of the power line.
6. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 1, wherein the method comprises the following steps:
when the splitting is four-splitting, the method for acquiring the point cloud data of the conductor of a certain phase on a certain side of the power conductor comprises the following steps:
calculating the average value of point cloud Y coordinates
The point cloud of all the phase wires on one side is larger than
Classifying the point cloud as a left split point cloud, smaller than
Classifying the point cloud into a right split point cloud;
respectively calculating the Z coordinate average value of the classified point clouds
Is greater than
Is an upper split point cloud, smaller than
The point cloud of (a) is a lower split point cloud.
7. The method for automatically acquiring the inter-phase distance of the power conductors based on the laser point cloud as claimed in claim 6, wherein the method comprises the following steps:
and respectively calculating the corresponding inter-phase distances of the upper left split, the lower left split, the upper right split and the lower right split, and taking the average value of the splits as a final result.
8. The utility model provides an electric power wire looks distance automatic acquisition system based on laser point cloud which characterized in that: the method comprises the following steps:
a data acquisition module configured to: acquiring point cloud data of the power transmission line;
a coordinate determination module configured to: determining the central plane coordinates of the target tower from which the inter-phase distances are to be extracted according to the acquired point cloud data, and constructing a line space coordinate system;
a point cloud projection module configured to: projecting power line laser point cloud data into a line space coordinate system, wherein an X coordinate is an accumulated distance, a Y coordinate is an offset distance, and a Z coordinate is an elevation;
a point cloud extraction module configured to: extracting point cloud data of preset distances before and after the power line target position, and respectively extracting upper phase point cloud data, middle phase point cloud data and lower phase point cloud data according to Y value positive and negative values and elevation Z value distribution;
a point cloud fitting module configured to: extracting the point cloud data of each split phase according to the distribution of Y values and Z values in the point cloud data of each phase of conductor, and performing curve fitting on the extracted point cloud data of each split phase to obtain three-dimensional coordinates of each point position on the conductor at the target position;
a distance calculation module configured to: the spatial distance between the corresponding split point positions of the upper phase and the middle phase or the middle phase and the lower phase is calculated.
9. A computer-readable storage medium on which a program is stored, the program, when being executed by a processor, implementing the steps of the method for automatically acquiring the inter-phase distance of power conductors based on a cloud of laser points according to any one of claims 1 to 7.
10. An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method for automatically acquiring the distance between the power lines based on the laser point cloud according to any one of claims 1 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102955160A (en) * | 2011-08-19 | 2013-03-06 | 湖北省电力公司电力科学研究院 | Three-dimensional laser radar technology based transmission line tower parameter determination method |
| CN104751481A (en) * | 2015-04-22 | 2015-07-01 | 中国测绘科学研究院 | Stratified random sampling-based LiDAR point-cloud clustering method for single-span power lines |
| CN106157361A (en) * | 2016-05-31 | 2016-11-23 | 中国科学院遥感与数字地球研究所 | A kind of multiple fission conductor full-automatic three-dimensional method for reconstructing based on LiDAR point cloud |
| CN107084676A (en) * | 2017-04-06 | 2017-08-22 | 国核电力规划设计研究院有限公司 | A kind of method of phase spacing at the position for the anti-dancing device for obtaining transmission line of electricity |
| US9869754B1 (en) * | 2017-03-22 | 2018-01-16 | Luminar Technologies, Inc. | Scan patterns for lidar systems |
| CN108663669A (en) * | 2018-08-22 | 2018-10-16 | 上海华测导航技术股份有限公司 | Airborne laser radar system for being applied in power-line patrolling |
| CN111474443A (en) * | 2020-04-13 | 2020-07-31 | 国网山东省电力公司淄博供电公司 | Method and device for measuring power transmission line |
-
2021
- 2021-01-04 CN CN202110004342.0A patent/CN112882047B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102955160A (en) * | 2011-08-19 | 2013-03-06 | 湖北省电力公司电力科学研究院 | Three-dimensional laser radar technology based transmission line tower parameter determination method |
| CN104751481A (en) * | 2015-04-22 | 2015-07-01 | 中国测绘科学研究院 | Stratified random sampling-based LiDAR point-cloud clustering method for single-span power lines |
| CN106157361A (en) * | 2016-05-31 | 2016-11-23 | 中国科学院遥感与数字地球研究所 | A kind of multiple fission conductor full-automatic three-dimensional method for reconstructing based on LiDAR point cloud |
| US9869754B1 (en) * | 2017-03-22 | 2018-01-16 | Luminar Technologies, Inc. | Scan patterns for lidar systems |
| CN107084676A (en) * | 2017-04-06 | 2017-08-22 | 国核电力规划设计研究院有限公司 | A kind of method of phase spacing at the position for the anti-dancing device for obtaining transmission line of electricity |
| CN108663669A (en) * | 2018-08-22 | 2018-10-16 | 上海华测导航技术股份有限公司 | Airborne laser radar system for being applied in power-line patrolling |
| CN111474443A (en) * | 2020-04-13 | 2020-07-31 | 国网山东省电力公司淄博供电公司 | Method and device for measuring power transmission line |
Non-Patent Citations (1)
| Title |
|---|
| 裴育刚等: "LiDAR技术在超高压电力巡线中的应用", 《太原科技》 * |
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