CN111504195A - Laser point cloud based electric power infrastructure acceptance method and device - Google Patents
Laser point cloud based electric power infrastructure acceptance method and device Download PDFInfo
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- CN111504195A CN111504195A CN202010422628.6A CN202010422628A CN111504195A CN 111504195 A CN111504195 A CN 111504195A CN 202010422628 A CN202010422628 A CN 202010422628A CN 111504195 A CN111504195 A CN 111504195A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C9/00—Measuring inclination, e.g. by clinometers, by levels
Abstract
The embodiment of the application provides a laser point cloud-based electric power capital construction acceptance method and device, wherein the method comprises the following steps: the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area; acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure; based on the point cloud data of the target component, applying a preset measurement rule of the target component to determine a value of a measurement parameter of the target component; and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component. The method and the device can effectively improve the automation degree and efficiency of tower footing acceptance check, and can effectively improve the accuracy and reliability of tower footing acceptance check result acquisition.
Description
Technical Field
The application relates to the technical field of power transmission line operation, in particular to a laser point cloud-based power infrastructure acceptance method and device.
Background
Acceptance of infrastructure projects in the power industry is always an important part in the construction of power infrastructures in China, and the acceptance results directly influence the subsequent production, use and maintenance work of the power infrastructures. At present, the acceptance of capital construction in the power industry relates to the acceptance of hidden projects, foundation projects, tower projects, stringing projects, grounding projects, line protection facilities and the like. For acceptance of pole tower engineering and overhead line engineering, the traditional acceptance mode is basically manual measurement, the existing tools are utilized for measurement such as satellite measurement, theodolite measurement and total station measurement, and some fixed measurement modes such as a gear side method and a gear end method are applied to the measurement of sag, so that the following problems are usually encountered in the measurement which is difficult to avoid:
1. there are a large number of power facilities located in mountainous areas for which field-erected instrumentation is difficult to operate practically;
2. measuring time and labor consumption by an erection instrument for field construction;
3. it is inconvenient to record, share, etc. data in real time.
Disclosure of Invention
In view of at least one of the above problems in the prior art, the present application provides a method and an apparatus for checking and accepting a power infrastructure based on a laser point cloud, which can effectively improve the automation degree and efficiency of tower footing checking and accepting, and can effectively improve the accuracy and reliability of tower footing checking and accepting result acquisition.
In order to solve the technical problem, the application provides the following technical scheme:
in a first aspect, the application provides a laser point cloud-based electric power capital construction acceptance method, which includes:
the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area;
acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure;
based on the point cloud data of the target component, applying a preset measurement rule of the target component to determine a value of a measurement parameter of the target component;
and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component.
Further, the acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure includes:
sending a point cloud data selection request aiming at a target component of the target power infrastructure by a client device, so that the client device sets a rectangular frame with a mouse point as a center according to the point cloud data selection request, and selecting the rectangular frame nearby the target component in a preset screen coordinate system to form a projection matrix of the laser point cloud relative to a screen; outputting the current window camera position corresponding to the rectangular frame, the coordinate value of the mouse point in a screen coordinate system, the size of the rectangular frame and a projection matrix of the laser point cloud relative to the screen to a server;
the server receives a current window camera position, a coordinate value of a mouse point in a screen coordinate system and the size of the rectangular frame, which are sent by the client device, and based on the coordinate value of the mouse point in the screen coordinate system and the size of the rectangular frame, the server filters the coordinate value of the point cloud data established by the target power according to a projection matrix of the laser point cloud relative to a screen, filters out the point cloud data of the target component, and then selects and outputs a point closest to the current window camera position and a mouse click position;
receiving a point which is sent by the server and is closest to the current window camera position and the mouse click position;
and selecting point cloud data of the target component from the point cloud data of the target power infrastructure based on a point closest to the current window camera position and the mouse click position.
Further, the target component comprises a tower;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting any point on a base of the tower and a top cross arm point of the tower based on the point cloud data of the tower;
determining a base horizontal plane normal vector of the tower according to any point on the base of the tower;
determining a top end cross arm plane of the tower according to the top end cross arm point of the tower by using a least square method, and determining a top end cross arm plane normal vector of the tower based on the top end cross arm plane;
and determining the value of the tower inclination angle of one of the measurement parameters based on the base horizontal plane normal vector and the top cross arm plane normal vector of the tower.
Further, the target component includes a cross arm;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting any point on cross arms at two ends of a tower in the target power infrastructure as a cross arm point based on the point cloud data of the cross arms;
determining a top end cross arm plane of the tower according to the cross arm points by using a least square method;
and taking the diagonal height difference corresponding to the top end cross arm plane as the value of the cross arm height difference of one of the measurement parameters.
Further, the target component includes a jumper;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting two end points and any middle point of the jumper wire based on the point cloud data of the jumper wire;
fitting the jumper wire based on a preset parabolic equation by using two end points and any one intermediate point of the jumper wire, and solving a constant of the parabolic equation;
determining the height difference of a connecting line segment between the jumper and a jumper endpoint based on a preset line segment equation, and solving a constant of the line segment equation;
determining a coordinate value of a maximum sag point of a jumper as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation;
and determining the coordinate value of the nearest point of the jumper and the tower as one of the measurement parameters by applying a k-d tree structure.
Further, the target component includes a wire;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting two end points and any middle point of the wire based on the point cloud data of the wire;
fitting the wire based on a preset parabolic equation by using two end points and any one intermediate point of the wire, and solving a constant of the parabolic equation;
determining the height difference of a connecting line segment between the lead and the lead end point based on a preset line segment equation, and solving a constant of the line segment equation;
and determining the coordinate value of the maximum sag point of the wire as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation.
Further, the determining a value of a measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component further includes:
selecting any point on the wire as a target wire point based on the point cloud data of the wire; acquiring other lead points on the cross section within a circular range taking the target lead point as the center of a circle and taking a preset distance as the radius;
a cross section point obtaining step: fitting the wire based on the target wire point and other wire points by using a least square method, and acquiring a tangent of the wire at the target wire point and a projection of the tangent; determining a cross-sectional point of the wire on the cross-section based on the projection of the tangent;
and updating the target lead points, and repeatedly executing the cross section point acquisition step based on the updated target lead points until cross section points corresponding to all lead points on the cross section are acquired, and determining a value of a phase-to-phase distance between leads serving as one of the measurement parameters by using the cross section points corresponding to each lead point.
Further, the acquiring of the laser point cloud data of the target area where the target power transmission line is located includes:
controlling a three-dimensional laser scanning device to acquire point cloud data of an overhead transmission line area;
receiving point cloud data of the overhead transmission line area, and denoising the point cloud data;
classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
In a second aspect, the present application provides an electric power capital construction acceptance apparatus based on laser point cloud, including:
the power infrastructure point cloud data acquisition module is used for acquiring laser point cloud data of a target area where a target power transmission line is located and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area;
the target component point cloud data acquisition module is used for acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure;
the measurement parameter determining module is used for determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component;
and the acceptance result generating module is used for generating an acceptance result of the corresponding target power infrastructure according to the value of the measurement parameter of the target component.
Further, the electric power infrastructure point cloud data acquisition module is specifically configured to execute the following:
controlling a three-dimensional laser scanning device to acquire point cloud data of an overhead transmission line area;
receiving point cloud data of the overhead transmission line area, and denoising the point cloud data;
classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
According to the technical scheme, the laser point cloud-based power infrastructure acceptance method and device provided by the application comprise the following steps: the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area; acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure; based on the point cloud data of the target component, applying a preset measurement rule of the target component to determine a value of a measurement parameter of the target component; the acceptance result of the corresponding target power infrastructure is generated according to the value of the measurement parameter of the target component, so that the automation degree and efficiency of tower footing acceptance can be effectively improved, the accuracy and reliability of the acquisition of the tower footing acceptance result can be effectively improved, the problem of difficulty in field equipment erection is solved, and the field operation is changed into the interior operation; by utilizing the laser point cloud measurement, the precision can be controlled to be in the centimeter level, and the measurement precision is greatly improved compared with the field measurement; the measurement result can be visually checked on the laser point cloud, so that the place which does not meet the standard in the acceptance positioning and acceptance result can be conveniently found out; data are convenient to arrange and classify, and therefore the use reliability of the tower footing of the overhead transmission line can be effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a power infrastructure acceptance method based on laser point cloud according to an embodiment of the present application.
Fig. 2 is a schematic flow chart of a laser point cloud-based power infrastructure acceptance method provided in an application example of the present application.
Fig. 3 is a schematic structural diagram of an electric power capital construction and acceptance device based on laser point cloud according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In order to effectively improve the automation degree and efficiency of tower footing acceptance check and can effectively improve the accuracy and reliability of the acquisition of the tower footing acceptance check result, the embodiment of the application provides an embodiment of a laser point cloud-based electric power infrastructure acceptance check method, and referring to fig. 1, the laser point cloud-based electric power infrastructure acceptance check method specifically includes the following contents:
step 100: the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area.
Step 200: and acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure.
Step 300: and determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component.
Step 400: and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component.
In order to effectively improve the accuracy and pertinence of point cloud data acquisition of a target component, in an embodiment of the laser point cloud-based power infrastructure acceptance method provided in the present application, step 200 of the laser point cloud-based power infrastructure acceptance method specifically includes the following contents:
step 210: sending a point cloud data selection request aiming at a target component of the target power infrastructure by a client device, so that the client device sets a rectangular frame with a mouse point as a center according to the point cloud data selection request, and selecting the rectangular frame nearby the target component in a preset screen coordinate system to form a projection matrix of the laser point cloud relative to a screen; and outputting the current window camera position corresponding to the rectangular frame, the coordinate value of the mouse point in a screen coordinate system, the size of the rectangular frame and a projection matrix of the laser point cloud relative to the screen to a server.
The server receives the current window camera position, the coordinate value of the mouse point in the screen coordinate system and the size of the rectangular frame which are sent by the client device, filters out the point cloud data of the target component according to the coordinate value of the laser point cloud relative to the projection matrix of the screen and the coordinate value of the point cloud data established by the target power based on the coordinate value of the mouse point in the screen coordinate system and the size of the rectangular frame, and then selects and outputs the point closest to the current window camera position and the mouse click position.
Step 220: and receiving a point which is sent by the server and is closest to the current window camera position and the mouse click position.
Step 230: and selecting point cloud data of the target component from the point cloud data of the target power infrastructure based on a point closest to the current window camera position and the mouse click position.
In order to effectively and accurately obtain the value of the tower inclination angle, which is one of the measurement parameters, in one embodiment of the laser point cloud-based power infrastructure acceptance method provided by the application, the target component comprises a tower; the first embodiment of step 300 of the laser point cloud based power infrastructure acceptance method specifically includes the following steps:
step 311: and respectively selecting any point on the base of the tower and the top cross arm point of the tower based on the point cloud data of the tower.
Step 312: and determining the horizontal plane normal vector of the base of the tower according to any point on the base of the tower.
Step 313: and determining a top cross arm plane of the tower according to the top cross arm point of the tower by using a least square method, and determining a top cross arm plane normal vector of the tower based on the top cross arm plane.
Step 314: and determining the value of the tower inclination angle of one of the measurement parameters based on the base horizontal plane normal vector and the top cross arm plane normal vector of the tower.
In order to effectively and accurately acquire the value of the cross arm height difference of one of the measurement parameters, in one embodiment of the laser point cloud-based power infrastructure acceptance method provided by the application, the target component comprises a cross arm; the second embodiment of step 300 of the laser point cloud based power infrastructure acceptance method specifically includes the following steps:
step 321: and respectively selecting any point on cross arms at two ends of the tower in the target power infrastructure as a cross arm point based on the point cloud data of the cross arms.
Step 322: and determining the top end cross arm plane of the tower according to the cross arm points by using a least square method.
Step 323: and taking the diagonal height difference corresponding to the top end cross arm plane as the value of the cross arm height difference of one of the measurement parameters.
In order to effectively and accurately acquire the value of the maximum sag point of the jumper wire of one of the measurement parameters, in one embodiment of the laser point cloud-based electric power infrastructure acceptance method provided by the application, the target component comprises the jumper wire; the third embodiment of the step 300 of the laser point cloud based power infrastructure acceptance method specifically includes the following steps:
step 331: and respectively selecting two end points and any middle point of the jumper wire based on the point cloud data of the jumper wire.
Step 332: and fitting the jumper wire based on a preset parabolic equation by using two end points and any middle point of the jumper wire, and solving a constant of the parabolic equation.
Step 333: and determining the height difference of a connecting line segment between the jumper and the end point of the jumper based on a preset line segment equation, and solving a constant of the line segment equation.
Step 334: and determining the coordinate value of the maximum sag point of the jumper as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation.
Step 335: and determining the coordinate value of the nearest point of the jumper and the tower as one of the measurement parameters by applying a k-d tree structure.
In order to effectively and accurately acquire the value of the maximum sag point of the wire of one of the measurement parameters, in one embodiment of the laser point cloud-based electric power infrastructure acceptance method provided by the application, the target component comprises a wire; the fourth embodiment of the step 300 of the laser point cloud based power infrastructure acceptance method specifically includes the following steps:
step 341: and respectively selecting two end points and any middle point of the wire based on the point cloud data of the wire.
Step 342: and fitting the wire based on a preset parabolic equation by using two end points and any middle point of the wire, and solving a constant of the parabolic equation.
Step 343: determining the height difference of a connecting line segment between the lead and the lead end point based on a preset line segment equation, and solving a constant of the line segment equation.
Step 344: and determining the coordinate value of the maximum sag point of the wire as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation.
In order to effectively and accurately acquire the value of the phase-to-phase data distance between the wires of one of the measurement parameters, in one embodiment of the laser point cloud-based power infrastructure acceptance method provided by the application, the target component comprises a wire; the fifth embodiment of the step 300 of the laser point cloud based power infrastructure acceptance method specifically includes the following steps:
step 351: selecting any point on the wire as a target wire point based on the point cloud data of the wire; and acquiring other lead points on the cross section within the circular range taking the target lead point as the center of a circle and taking the preset distance as the radius.
Step 352: a cross section point obtaining step: fitting the wire based on the target wire point and other wire points by using a least square method, and acquiring a tangent of the wire at the target wire point and a projection of the tangent; determining a cross-sectional point of the wire on the cross-section based on the projection of the tangent.
Step 353: and updating the target lead points, and repeatedly executing the cross section point acquisition step based on the updated target lead points until the values of the phase-to-phase distance between the leads, which are one of the measurement parameters, are determined according to the cross section points corresponding to all the lead points on the cross section after the cross section points corresponding to all the lead points on the cross section are acquired.
In order to effectively improve the accuracy of obtaining laser point cloud data of a target area where a target power transmission line is located and the application reliability, in an embodiment of the laser point cloud-based power infrastructure acceptance method, step 100 in the laser point cloud-based power infrastructure acceptance method specifically includes the following steps:
step 110: and controlling a three-dimensional laser scanning device to acquire point cloud data of the overhead transmission line area.
Step 120: and receiving point cloud data of the overhead transmission line area, and denoising the point cloud data.
Step 130: classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
That is, the laser point cloud data can be automatically or manually classified, and the classification can filter useless noise points to obtain tower point cloud, power line point cloud, jumper point cloud, hardware point cloud and other ground vegetation point clouds.
In order to further explain the scheme, the application example of the method is suitable for the measurement acceptance of tower projects and overhead line projects which are difficult to accept through a manual instrument. The method specifically comprises the steps of pole tower measurement, cross arm height difference, jumper wire measurement, lead sag measurement and phase distance measurement. Referring to fig. 2, the method specifically includes the following steps:
s101, laser point cloud data of a target area are collected through three-dimensional laser scanning.
Preferably, the step S101 further includes:
(1) scanning the surrounding environment through a laser radar, and collecting point cloud data of the surrounding environment;
(2) and classifying the collected laser point cloud data of the surrounding environment, and extracting the laser point cloud data of the target area.
Specifically, the laser point cloud technology is to describe an actual object by using points distributed in space, that is, to describe an absolute spatial position of the object on the earth by using laser point cloud; the points include all objects in the scanning area, including usable and unusable parts, even noise points (i.e. original laser point cloud data), and after the original laser point cloud data is obtained, the laser point cloud data needs to be classified, that is, the contents represented by the point cloud blocks or areas are marked, according to the classification, useless points can be filtered, and the usable parts are extracted and segmented, so that usable point cloud data is obtained. For example, the power transmission line point cloud classification in the power industry can classify towers, power lines, related hardware and ground environments.
The classification method can be manual classification, or automatic classification according to a point cloud clustering mode or a point cloud block shape, and manual repair can be performed after classification.
And S102, matching simple and convenient human-computer interaction, namely point cloud picking.
Specifically, interactive point picking:
1) a mouse buffer (i.e., a square centered on the mouse and having the buffer size as a side length) is set.
2) And clicking the mouse near the target point, and sending the coordinate value uv, the buffer size, the current window camera position and the projection matrix of the laser point cloud relative to the screen of the current mouse in the screen coordinate system to the server.
3) And the server calculates the coordinate values of the actual laser point cloud data according to the mouse coordinate values uv and the size of the buffer, filters out points in the corresponding buffer, and returns the points closest to the current window camera position and the mouse click position to the webpage end after selecting the points.
4) And the front end picks up the selected laser point cloud according to the coordinate point returned by the server.
And S103, calculating a target measurement value according to a corresponding formula.
Specifically, for the following measurement items:
tower measurement:
1) and S102 is used for selecting a tower base point (any point on the base) and a tower top cross arm point respectively.
2) And obtaining a tower base and calculating a base horizontal plane normal vector a according to the base point, and obtaining a top cross arm plane and calculating a normal vector b by using a least square method according to the tower top cross arm point.
3) Calculating the angle between normal vectors a, b
Calculating the inclination angle of the tower
。
(II) cross arm height difference:
1) and S102 is used for selecting any point on cross arms at two ends of the tower respectively.
2) And (4) obtaining a top end cross arm plane by using a least square method according to the cross arm points, and calculating the height difference of the diagonal line of the plane.
And (III) jumper wire measurement:
1) and S102 is used for selecting two end points and any middle point of the jumper respectively.
2) Using parabolic equations based on three points
And fitting the jumper point cloud. And obtaining a, b and c.
3) Calculating the line segment (equation is
) Height difference of
D, e can be determined from the wire ends.
4) Derivation to obtain the lowest point of the equation
The position is the maximum sag point of the jumper.
5) And (3) solving the nearest point of the jumper wire on the tower by using a kd tree (a binary tree structure, and the nearest point of two point clouds can be calculated).
(IV) measuring the conductor sag:
1) and S102 is used for selecting two end points and any middle point of the wire respectively.
2) Using parabolic equations based on three points
And fitting a wire point cloud. To obtain a，b，c。
3) Calculating the line segment (equation is
) Height difference of
D, e can be determined from the wire ends.
4) Derivation to obtain the lowest point of the equation
The point is the maximum sag point of the wire.
(V) phase spacing measurement:
1) a point a is arbitrarily selected on the arrival line using S102.
2) And (3) obtaining a point A and lead points around the point A, fitting the leads by using a least square method, obtaining a tangent line b of the lead at the point A, recording the projection of the b on an xOy plane as b ', and obtaining the position information of the lead at the cross section point by using a plane phi parallel to a z axis and vertical to b' to intersect with all the leads.
3) And classifying the points according to rows and columns, and calculating the distance to obtain the distance between the phases.
And S104, counting the measurement results and deriving a table.
From the above description, the laser point cloud-based power infrastructure acceptance method provided by the embodiment of the application solves the problem of difficulty in field equipment erection, and changes field operation into internal operation; by utilizing the laser point cloud measurement, the precision can be controlled to be in the centimeter level, and the measurement precision is greatly improved compared with the field measurement; the measurement result can be visually checked on the laser point cloud, so that the place which does not meet the standard in the acceptance positioning and acceptance result can be conveniently found out; the data is convenient to sort and classify.
From the software aspect, in order to effectively improve the automation degree and efficiency of tower footing acceptance check and can effectively improve the accuracy and reliability of the acquisition of the tower footing acceptance check result, the application provides an embodiment of the laser point cloud-based electric power infrastructure acceptance device for implementing all or part of the contents in the laser point cloud-based electric power infrastructure acceptance method, referring to fig. 3, the laser point cloud-based electric power infrastructure acceptance device includes the following contents:
the power infrastructure point cloud data acquisition module 10 is configured to acquire laser point cloud data of a target area where a target power transmission line is located, and select point cloud data of a target power infrastructure from the laser point cloud data, where the point cloud data of the target power infrastructure includes point cloud data of towers, power lines, hardware fittings and a ground environment in the target area.
And the target component point cloud data acquisition module 20 is used for acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure.
And the measurement parameter determining module 30 is configured to apply a preset measurement rule of the target component based on the point cloud data of the target component to determine a value of a measurement parameter of the target component.
And the acceptance result generating module 40 is configured to generate an acceptance result of the corresponding target power infrastructure according to the value of the measurement parameter of the target component.
In order to effectively improve the accuracy and the application reliability of the laser point cloud data acquisition of the target area where the target power transmission line is located, in an embodiment of the laser point cloud-based power infrastructure acceptance apparatus according to the present application, the power infrastructure point cloud data acquisition module 10 in the laser point cloud-based power infrastructure acceptance apparatus is specifically configured to execute the following contents:
controlling a three-dimensional laser scanning device to acquire point cloud data of an overhead transmission line area;
receiving point cloud data of the overhead transmission line area, and denoising the point cloud data;
classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
The specific implementation content of the laser point cloud-based electric power infrastructure acceptance device provided in the embodiment of the application is referred to the embodiment of the laser point cloud-based electric power infrastructure acceptance method, and is not repeated here.
From the above description, the laser point cloud-based power infrastructure acceptance inspection device provided by the embodiment of the application can effectively improve the automation degree and efficiency of tower footing acceptance inspection, can effectively improve the accuracy and reliability of tower footing acceptance result acquisition, solves the problem of difficulty in field equipment erection, and changes field operation into internal operation; by utilizing the laser point cloud measurement, the precision can be controlled to be in the centimeter level, and the measurement precision is greatly improved compared with the field measurement; the measurement result can be visually checked on the laser point cloud, so that the place which does not meet the standard in the acceptance positioning and acceptance result can be conveniently found out; data are convenient to arrange and classify, and therefore the use reliability of the tower footing of the overhead transmission line can be effectively improved.
In order to effectively improve the automation degree and efficiency of tower footing acceptance check and can effectively improve the accuracy and reliability of tower footing acceptance check result acquisition, the application provides an embodiment of an electronic device for realizing all or part of contents in the laser point cloud-based power foundation acceptance check method, and the electronic device specifically includes the following contents:
a processor, a memory, a communication interface, and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the electronic equipment and the user terminal and relevant equipment such as a relevant database and the like; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the electronic device may refer to the embodiment of the laser point cloud-based power infrastructure acceptance method and the embodiment of the laser point cloud-based power infrastructure acceptance apparatus in the embodiment, and the contents thereof are incorporated herein, and repeated details are not repeated.
In an embodiment, the laser point cloud based power infrastructure acceptance function may be integrated into the central processor. Wherein the central processor may be configured to control:
step 100: the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area.
Step 200: and acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure.
Step 300: and determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component.
Step 400: and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component.
From the above description, the electronic device provided by the embodiment of the application can effectively improve the automation degree and efficiency of tower footing acceptance check, can effectively improve the accuracy and reliability of tower footing acceptance check result acquisition, solves the problem of difficulty in field equipment erection, and changes field operation into internal operation; by utilizing the laser point cloud measurement, the precision can be controlled to be in the centimeter level, and the measurement precision is greatly improved compared with the field measurement; the measurement result can be visually checked on the laser point cloud, so that the place which does not meet the standard in the acceptance positioning and acceptance result can be conveniently found out; data are convenient to arrange and classify, and therefore the use reliability of the tower footing of the overhead transmission line can be effectively improved.
Embodiments of the present application further provide a computer-readable storage medium capable of implementing all steps in the laser point cloud based power infrastructure acceptance method in the above embodiments, where the computer-readable storage medium stores thereon a computer program, and when the computer program is executed by a processor, the computer program implements all steps of the laser point cloud based power infrastructure acceptance method in the above embodiments, where the execution subject is a server or a client, for example, the processor implements the following steps when executing the computer program:
step 100: the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area.
Step 200: and acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure.
Step 300: and determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component.
Step 400: and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component.
As can be seen from the above description, the computer-readable storage medium provided in the embodiment of the present application can effectively improve the automation degree and efficiency of tower footing acceptance check, and can effectively improve the accuracy and reliability of tower footing acceptance check result acquisition, thereby solving the problem of difficulty in field equipment erection and turning field operation into interior operation; by utilizing the laser point cloud measurement, the precision can be controlled to be in the centimeter level, and the measurement precision is greatly improved compared with the field measurement; the measurement result can be visually checked on the laser point cloud, so that the place which does not meet the standard in the acceptance positioning and acceptance result can be conveniently found out; data are convenient to arrange and classify, and therefore the use reliability of the tower footing of the overhead transmission line can be effectively improved.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. 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.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A power infrastructure acceptance method based on laser point cloud is characterized by comprising the following steps:
the method comprises the steps of obtaining laser point cloud data of a target area where a target power transmission line is located, and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area;
acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure;
based on the point cloud data of the target component, applying a preset measurement rule of the target component to determine a value of a measurement parameter of the target component;
and generating a corresponding acceptance result of the target power infrastructure according to the value of the measurement parameter of the target component.
2. The laser point cloud based power infrastructure acceptance method of claim 1, wherein the obtaining point cloud data of at least one target component in the point cloud data of the target power infrastructure comprises:
sending a point cloud data selection request aiming at a target component of the target power infrastructure by a client device, so that the client device sets a rectangular frame with a mouse point as a center according to the point cloud data selection request, and selecting the rectangular frame nearby the target component in a preset screen coordinate system to form a projection matrix of the laser point cloud relative to a screen; outputting the current window camera position corresponding to the rectangular frame, the coordinate value of the mouse point in a screen coordinate system, the size of the rectangular frame and a projection matrix of the laser point cloud relative to the screen to a server;
the server receives a current window camera position, a coordinate value of a mouse point in a screen coordinate system and the size of the rectangular frame, which are sent by the client device, and based on the coordinate value of the mouse point in the screen coordinate system and the size of the rectangular frame, the server filters the coordinate value of the point cloud data established by the target power according to a projection matrix of the laser point cloud relative to a screen, filters out the point cloud data of the target component, and then selects and outputs a point closest to the current window camera position and a mouse click position;
receiving a point which is sent by the server and is closest to the current window camera position and the mouse click position;
and selecting point cloud data of the target component from the point cloud data of the target power infrastructure based on a point closest to the current window camera position and the mouse click position.
3. The laser point cloud-based power infrastructure acceptance method of claim 1, wherein the target component comprises a tower;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting any point on a base of the tower and a top cross arm point of the tower based on the point cloud data of the tower;
determining a base horizontal plane normal vector of the tower according to any point on the base of the tower;
determining a top end cross arm plane of the tower according to the top end cross arm point of the tower by using a least square method, and determining a top end cross arm plane normal vector of the tower based on the top end cross arm plane;
and determining the value of the tower inclination angle of one of the measurement parameters based on the base horizontal plane normal vector and the top cross arm plane normal vector of the tower.
4. The laser point cloud-based power infrastructure acceptance method of claim 1, wherein the target component comprises a cross arm;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting any point on cross arms at two ends of a tower in the target power infrastructure as a cross arm point based on the point cloud data of the cross arms;
determining a top end cross arm plane of the tower according to the cross arm points by using a least square method;
and taking the diagonal height difference corresponding to the top end cross arm plane as the value of the cross arm height difference of one of the measurement parameters.
5. The laser point cloud based power infrastructure acceptance method of claim 1, wherein the target component comprises a jumper;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting two end points and any middle point of the jumper wire based on the point cloud data of the jumper wire;
fitting the jumper wire based on a preset parabolic equation by using two end points and any one intermediate point of the jumper wire, and solving a constant of the parabolic equation;
determining the height difference of a connecting line segment between the jumper and a jumper endpoint based on a preset line segment equation, and solving a constant of the line segment equation;
determining a coordinate value of a maximum sag point of a jumper as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation;
and determining the coordinate value of the nearest point of the jumper and the tower as one of the measurement parameters by applying a k-d tree structure.
6. The laser point cloud based power infrastructure acceptance method of claim 1, wherein the target component comprises a wire;
correspondingly, the determining the value of the measurement parameter of the target component by applying the preset measurement rule of the target component based on the point cloud data of the target component includes:
respectively selecting two end points and any middle point of the wire based on the point cloud data of the wire;
fitting the wire based on a preset parabolic equation by using two end points and any one intermediate point of the wire, and solving a constant of the parabolic equation;
determining the height difference of a connecting line segment between the lead and the lead end point based on a preset line segment equation, and solving a constant of the line segment equation;
and determining the coordinate value of the maximum sag point of the wire as one of the measurement parameters according to the constant of the parabolic equation and the constant of the line segment equation.
7. The laser point cloud-based power infrastructure acceptance method according to claim 6, wherein the determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component further comprises:
selecting any point on the wire as a target wire point based on the point cloud data of the wire; acquiring other lead points on the cross section within a circular range taking the target lead point as the center of a circle and taking a preset distance as the radius;
a cross section point obtaining step: fitting the wire based on the target wire point and other wire points by using a least square method, and acquiring a tangent of the wire at the target wire point and a projection of the tangent; determining a cross-sectional point of the wire on the cross-section based on the projection of the tangent;
and updating the target lead points, and repeatedly executing the cross section point acquisition step based on the updated target lead points until cross section points corresponding to all lead points on the cross section are acquired, and determining a value of a phase-to-phase distance between leads serving as one of the measurement parameters by using the cross section points corresponding to each lead point.
8. The laser point cloud-based power infrastructure acceptance method according to claim 1, wherein the obtaining of the laser point cloud data of the target area where the target power transmission line is located comprises:
controlling a three-dimensional laser scanning device to acquire point cloud data of an overhead transmission line area;
receiving point cloud data of the overhead transmission line area, and denoising the point cloud data;
classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
9. The utility model provides an electric power capital construction acceptance device based on laser point cloud which characterized in that includes:
the power infrastructure point cloud data acquisition module is used for acquiring laser point cloud data of a target area where a target power transmission line is located and selecting point cloud data of target power infrastructure from the laser point cloud data, wherein the point cloud data of the target power infrastructure comprises point cloud data of towers, power lines, hardware fittings and ground environment in the target area;
the target component point cloud data acquisition module is used for acquiring point cloud data of at least one target component in the point cloud data of the target power infrastructure;
the measurement parameter determining module is used for determining the value of the measurement parameter of the target component by applying a preset measurement rule of the target component based on the point cloud data of the target component;
and the acceptance result generating module is used for generating an acceptance result of the corresponding target power infrastructure according to the value of the measurement parameter of the target component.
10. The laser point cloud-based power infrastructure acceptance apparatus according to claim 9, wherein the power infrastructure point cloud data obtaining module is specifically configured to perform the following:
controlling a three-dimensional laser scanning device to acquire point cloud data of an overhead transmission line area;
receiving point cloud data of the overhead transmission line area, and denoising the point cloud data;
classifying the point cloud data after denoising processing based on a preset point cloud clustering mode or a point cloud block shape to obtain the point cloud data of the tower, the power line, the hardware fitting and the ground environment in the target area.
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