CN109613514A - A kind of shaft tower inclination method for early warning based on airborne lidar point cloud data - Google Patents
A kind of shaft tower inclination method for early warning based on airborne lidar point cloud data Download PDFInfo
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- CN109613514A CN109613514A CN201811638225.4A CN201811638225A CN109613514A CN 109613514 A CN109613514 A CN 109613514A CN 201811638225 A CN201811638225 A CN 201811638225A CN 109613514 A CN109613514 A CN 109613514A
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C9/00—Measuring inclination, e.g. by clinometers, by levels
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Abstract
The invention discloses a kind of, and the shaft tower based on airborne lidar point cloud data tilts method for early warning, is primarily based on Kd-tree cluster and spatial grid growth pre-processes the shaft tower point cloud data that airborne laser radar scans, remove noise point；Secondly based on shaft tower Extraction of Geometrical Features shaft tower trunk region point cloud；It is again based on the angular coordinate that coordinate system spinning solution calculates each layer point cloud data in shaft tower trunk region；It finally calculates every layer of center point coordinate using angular coordinate and is fitted space line equation, obtain inclination radian and the inclination angle of shaft tower, safe early warning finally is carried out to the shaft tower that inclination angle is more than certain secure threshold.The present invention overcomes the defects that traditional artificial detection is not suitable for the efficient detection under complex environment, based on airborne LiDAR shaft tower point cloud data, the automatic gradient for obtaining shaft tower and inclination radian, measurement efficiency and precision are high, early warning can be made to tilting serious shaft tower in time, to prevent causing later period more serious consequence.
Description
Technical field
The present invention relates to remote sensing technology fields, and in particular to a kind of shaft tower inclination based on airborne lidar point cloud data is pre-
Alarm method.
Background technique
Demand of the people to electric energy is growing with the rapid development of the national economy, then causes high pressure, super-pressure
And significantly extending occurs in the large-capacity power route of extra-high voltage.Shaft tower is the basic equipment of transmission line of electricity, is set up
In field, is influenced vulnerable to factors such as strong wind, the unstable, underground minings of geological environment and cause cave-in accident.When transmission line of electricity passes through
When crossing the express zone such as coal mining area, weak soil matter area, hillside, riverbed area, pole and tower foundation can occur sliding, inclination,
Phenomena such as sedimentation, cracking, so as to cause the deformation or inclination of shaft tower；In addition shaft tower in integral hoisting, choose not by hoisting point position
Rationally the deformation of shaft tower can also be caused to tilt.The inclination of shaft tower easily causes transmission line of electricity to occur to fall bar, electrical safety apart from too small
The defects of, especially the shaft tower at dense population areas, important scissors crossing once occur fall tower, caused by consequence it is very tight
Weight.
How high-precision, expeditiously realize shaft tower gradient measurement be engineering site key problem, especially with
Spy/extra high voltage network build up and put into operation, the demand of in-site measurement is growing, and road geographical environment is complex,
Mode manually, which carrys out regular visit, cannot reach the requirement of modern power systems safe and stable operation.In recent years, with
Deep development of the Airborne LiDAR Technology (i.e. airborne laser radar technology) in power-line patrolling, high efficiency, it is high-precision in real time
The characteristics of obtaining three-dimensional data makes it possible Intelligent line patrolling, and shaft tower is the infrastructure of transmission line of electricity, it is ensured that electric power
The energy resource supply of high efficiency of transmission and safety, it is necessary to which the state in real time, accurately grasping and monitoring the facilities such as shaft tower is established complete
Early warning and emergency response mechanism.How it to be based on airborne LiDAR shaft tower point cloud number, early warning is made to the serious shaft tower of inclination in time,
Consequence to prevent causing the later period more serious is one of the difficult point of current research.
Summary of the invention
The purpose of the present invention is to provide a kind of, and the shaft tower based on airborne LiDAR shaft tower point cloud data tilts method for early warning,
The defect of its efficient detection that traditional artificial detection can be overcome not to be suitable under complex environment is based on airborne LiDAR shaft tower
Point cloud data, the automatic gradient for obtaining shaft tower and inclination radian, so that early warning is made to the serious shaft tower of inclination in time, to prevent
Cause the consequence that the later period is more serious.
To achieve the above object, the invention adopts the following technical scheme:
A kind of shaft tower inclination method for early warning based on airborne lidar point cloud data comprising following steps:
S1, the shaft tower point cloud data scanned to airborne laser radar is grown based on Kd-tree cluster and spatial grid
It is pre-processed, removes noise point；
S2, it is based on shaft tower Extraction of Geometrical Features shaft tower trunk region point cloud；
S3, the point cloud data of the obtained shaft tower trunk region step S2 is layered again on Z axis, is then based on coordinate
It is the angular coordinate that spinning solution calculates each layer point cloud data；
S4, every layer of center point coordinate is calculated using the obtained angular coordinate of step S3 and is fitted space line equation,
Inclination radian and the inclination angle of shaft tower are obtained, safe early warning finally is carried out to the shaft tower that inclination angle is more than certain secure threshold.
Further, the realization process of step S2 comprises the steps of:
S21, vertical demixing: the shaft tower point cloud data setting interval height difference Δ H after the denoising obtained to step S1 is carried out
Vertical demixing；
S22, denoising: every layer of a small amount of high-voltage line, bracing wire and drainage thread are rejected using the denoising method based on two-dimentional grid
Etc. noises；
S23, linear relationship is extracted based on RANSAC Algorithm of fitting a straight line: is extracted using RANSAC Algorithm of fitting a straight line transversal
Face diagonal length maxDs separates shaft tower trunk region point cloud data with the linear relationship of cross-sectional height dHs.
Further, in step S3 in coordinate system spinning solution, the step-length for rotating angle is 0.5 °.
Further, the method that space line equation is fitted in step S4 is least square method.
After adopting the above technical scheme, compared with the background technology, the present invention, having the advantages that
(1) it is not suitable for the defect of the efficient detection under complex environment the present invention overcomes traditional artificial detection, is based on
Airborne LiDAR shaft tower point cloud data, the automatic gradient for obtaining shaft tower and inclination radian, measurement efficiency and precision are high, can and
When make early warning to tilting serious shaft tower, to prevent causing later period more serious consequence.
(2) present invention separates shaft tower with the linear relationship of cross-sectional height dHs using cross section diagonal length maxDs
Trunk region point cloud data, rather than traditional linear relationship using cross section side length and cross-sectional height is used, it overcomes transversal
Face side length calculates defect complicated and vulnerable to the influence of high pressure shaft tower point cloud quality, calculates simple, good separating effect.
It (3), can be with the present invention is based on the angular coordinate that coordinate system spinning solution calculates each layer point cloud data in shaft tower trunk region
It is further reduced angular coordinate error, improves accuracy.
Detailed description of the invention
Fig. 1 is overall flow schematic diagram of the present invention；
Fig. 2 is shaft tower trunk region point cloud data, wherein (a) is T-type tower, (b) is V-type tower, (c) is gate tower；
Fig. 3 is shaft tower hierarchical diagram；
Fig. 4 is that T-type tower is layered point cloud data and angle point grid schematic diagram, wherein (a) is point cloud data good working condition, (b)
For point cloud data incompleteness state；
Fig. 5 is rectangle apex envelopes box schematic diagram；
Fig. 6 is the angle point grid of trunk region point cloud data as a result, wherein (a) is T-type tower, (b) is V-type tower, (c) is gate
Tower.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Embodiment
Fig. 1 shows the implementing procedure of the present embodiment, refering to what is shown in Fig. 1, the invention discloses one kind to be based on airborne LiDAR
The shaft tower of point cloud data tilts method for early warning comprising following steps:
S1, the shaft tower point cloud data scanned to airborne laser radar is grown based on Kd-tree cluster and spatial grid
It is pre-processed, removes noise point:
Comprising making an uproar as caused by tail of a comet effect and airborne impurities in the shaft tower point cloud data that airborne laser radar scans
The point of articulation, and due to shaft tower type in transmission of electricity corridor complex geographical environment, vegetation growth fast speed and whole transmission of electricity corridor
With it is not of uniform size, cause shaft tower point cloud data concentrate there are higher topographic(al) points and vegetation point, directly affect subsequent shaft tower trunk
The determination in area, to reduce the gradient counting accuracy of shaft tower.Pass through the original of analysis Kd-tree cluster and spatial grid growth
Reason and feature, pre-process the shaft tower point cloud data that airborne laser radar scans, and remove noise point；
S2, it is based on shaft tower Extraction of Geometrical Features shaft tower trunk region point cloud:
High pressure shaft tower be it is symmetrical about axis, common are T-type tower, V-type tower, gate tower bar, point cloud data is such as
Shown in box inner region in Fig. 2, wherein (a) is T-type tower, (b) it is V-type tower, is (c) gate tower, to the geometry knot of trunk region
Configuration state finds the cross section of the shaft tower trunk region of three types side length and catercorner length after being analyzed is with high pressure stem
The increase of tower height degree remains unchanged, and is a kind of special linear relationship.It, can be according to the height of three classes shaft tower based on the above analysis
Linear relationship between side length or catercorner length separates shaft tower backbone area, but since the calculating of cross section side length is compared
It is complicated and influenced vulnerable to high pressure shaft tower point cloud quality, so the present embodiment is using cross section diagonal length and cross-sectional height
Linear relationship separates shaft tower trunk region point cloud data.
Specific implementation process comprises the steps of:
S21, vertical demixing: the shaft tower point cloud data setting interval height difference Δ H after the denoising obtained to step S1 is carried out
Vertical demixing, Fig. 3 are shaft tower hierarchical diagram；
S22, denoising: every layer of a small amount of high-voltage line, bracing wire and drainage thread are rejected using the denoising method based on two-dimentional grid
Etc. noises；
S23, linear relationship is extracted based on RANSAC Algorithm of fitting a straight line: is extracted using RANSAC Algorithm of fitting a straight line transversal
The linear relationship of face diagonal length maxDs and cross-sectional height dHs find out the layer for meeting linear relationship, to separate shaft tower
Trunk region point cloud data.
S3, the point cloud data of the obtained shaft tower trunk region step S2 is layered again on Z axis, is then based on coordinate
It is the angular coordinate that spinning solution calculates each layer point cloud data；
Fig. 4 shows T-type tower trunk region layer point cloud data (black color dots in grey filled lines frame), and dash-dotted gray line frame is by point
Maximum, minimum value of the cloud data on x and y-axis direction determine that grey filled lines frame is the outsourcing rectangle of point cloud data.Fig. 4 (a) point
Cloud data are relatively complete, and the angular coordinate of dash-dotted gray line frame and solid box determination is almost the same；Fig. 4 (b) is the absence of an angle
Point cloud data, the corner location that dash-dotted gray line frame and solid box determine herein are different (A and A1 point).When due to data scanning
It is mutually blocked between object, every layer of high pressure shaft tower of usual actual extracting is similar to Fig. 4 (b), so if passing through each layer point cloud number
According to the angular coordinate for determining every layer of point cloud data in the maximum in x and y-axis direction, minimum value, large error will lead to, thus shadow
Ring subsequent shaft tower point cloud classification precision.
Difference and three kinds of high pressure shaft tower cross sections for above-mentioned layering point cloud data quality are all rectangular structure
Feature, the present embodiment propose to rotate the method for carrying out demixing point cloud data angular coordinate and extracting based on coordinate system.Its basic principle
Are as follows: as shown in figure 5, rectangle (grey filled lines frame in figure) is rotated around origin O in a coordinate system, vertex (A0, A1,
A2, A3) determined by the area of each side dotted rectangle (dash-dotted gray line frame in figure) for being parallel to x or y-axis be greater than or equal to
Rectangular area, when and only when each side of rectangle is parallel to x or y-axis, dotted rectangle is overlapped with rectangle and area phase
Deng, and dotted rectangle area is minimum at this time.So its dotted line can be sought by rotating to layering point cloud data
Then apex coordinate when rectangular area minimum completes the calculating of angular coordinate by inverse operation again, and these angle points are sat
The dotted rectangle that mark is formed is the practical bounding box for being layered point cloud data, can avoid demixing point cloud to a certain extent in this way
Angular coordinate error caused by the quality of data is poor, further increases accuracy.Its detailed process is as follows:
The determination of S31, rotation formula: due to rectangle be center symmetric figure, around its coordinate origin be rotated by 90 ° within i.e.
The dotted rectangle of minimum area, the i.e. practical bounding box of point cloud data can be found, rotation formula is shown in (1), wherein (x0,y0) and
(x, y) is the coordinate of rotation front and back, and α is the angle rotated counterclockwise；
The determination of S32, rotation parameter: the angular coordinate in order to seek every layer of point cloud data is needed point cloud data around seat
Angular coordinate when mark origin rotate and calculates dotted rectangle area minimum, the step-length for rotating angle at this time are to influence angle point seat
The key factor of precision is marked, but step-length is too small can reduce efficiency of algorithm.In summary it considers, selected angle step-length is 0.5 °；
S33, by seeking maximum, minimum value of the point cloud data on x and y-axis direction, determine the angle point of dotted rectangle
Coordinate, and then its area is calculated, and rotation angle, area and its angular coordinate are respectively stored in storehouse；
S34, point cloud data is rotated by the rotation angle step of setting, calculates postrotational cloud coordinate simultaneously by formula (1)
Dotted rectangle area is calculated, if being less than stored dotted rectangle area in storehouse, replaces the dotted line stored in storehouse
Rectangle rotates angle, area and its angular coordinate.
S35, step S34 is repeated, until rotation angle reaches 90 °；
S36, rotation angle [alpha] when obtaining dotted rectangle area minimum by step S33, S34, S35minAnd its angle point
Coordinate calculates the angular coordinate of the true bounding box of this layer of point cloud data in conjunction with formula (2) are rotated clockwise；
S37, the angular coordinate for calculating separately each practical bounding box of layer point cloud data in shaft tower trunk region according to the method described above, mention
The angle point result that takes (b) is V-type tower, (c) is gate tower as shown in fig. 6, wherein (a) is T-type tower.
S4, every layer of center point coordinate is calculated using the obtained angular coordinate of step S3 and is fitted space line equation,
Inclination radian and the inclination angle of shaft tower are obtained, safe early warning finally is carried out to the shaft tower that inclination angle is more than certain secure threshold.
Every layer of center point coordinate is obtained first with angular coordinate, is sought often using the least square fitting of space line
The coefficient of layer shaft tower central space linear equation.
Space line equation can simplify into:
It is required that parameter be x0, y0, m, n
Space line equation can be with abbreviation are as follows:
Being write as matrix form is:
When having at n, i-th point of equation is:
N equation in parallel obtains:
Least square fitting:
Abbreviation are as follows:
It then can be in the hope of the parameter x in the space line equation of shaft tower by every layer of shaft tower centre coordinate0、y0, m and
N, it is assumed that the space vector of space line isBy space line project on horizontal plane its vector isThe then inclination of shaft tower
Spend θ and radian rad are as follows:
Finally compare shaft tower gradient whether in safety standard indication range, if being more than secure threshold, then will
This shaft tower is labeled as dangerous shaft tower, carries out early warning to it.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
In the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of by anyone skilled in the art,
It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of protection of the claims
Subject to.
Claims (4)
1. a kind of shaft tower based on airborne lidar point cloud data tilts method for early warning, it is characterised in that: the following steps are included:
S1, the shaft tower point cloud data that airborne laser radar scans is carried out based on Kd-tree cluster and spatial grid growth
Pretreatment removes noise point；
S2, it is based on shaft tower Extraction of Geometrical Features shaft tower trunk region point cloud；
S3, the point cloud data of the obtained shaft tower trunk region step S2 is layered again on Z axis, is then based on coordinate system rotation
Shifting method calculates the angular coordinate of each layer point cloud data；
S4, every layer of center point coordinate is calculated using the obtained angular coordinate of step S3 and is fitted space line equation, obtain
The inclination radian of shaft tower and inclination angle finally carry out safe early warning to the shaft tower that inclination angle is more than certain secure threshold.
2. the shaft tower based on airborne lidar point cloud data tilts method for early warning as described in claim 1, it is characterised in that: step
The realization process of rapid S2 comprises the steps of:
S21, vertical demixing: the shaft tower point cloud data setting interval height difference Δ H after the denoising obtained to step S1 carries out vertical
Layering；
S22, denoising: every layer of a small amount of high-voltage line, bracing wire and drainage thread noise are rejected using the denoising method based on two-dimentional grid；
S23, linear relationship is extracted based on RANSAC Algorithm of fitting a straight line: extracts cross section pair using RANSAC Algorithm of fitting a straight line
Diagonal length maxDs separates shaft tower trunk region point cloud data with the linear relationship of cross-sectional height dHs.
3. the shaft tower based on airborne lidar point cloud data tilts method for early warning as described in claim 1, it is characterised in that: step
In rapid S3 in coordinate system spinning solution, the step-length for rotating angle is 0.5 °.
4. the shaft tower based on airborne lidar point cloud data tilts method for early warning as described in claim 1, it is characterised in that: step
The method that space line equation is fitted in rapid S4 is least square method.
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| CN110398231A (en) * | 2019-06-18 | 2019-11-01 | 广东博智林机器人有限公司 | Acquisition methods, device, computer equipment and the storage medium of metope parameter |
| CN111174761A (en) * | 2019-12-31 | 2020-05-19 | 中国电建集团河北省电力勘测设计研究院有限公司 | Circular pole tower inclination deformation rapid calculation method based on laser point cloud |
| CN111583174A (en) * | 2020-03-27 | 2020-08-25 | 武汉地大信息工程股份有限公司 | Method and system for detecting deformation of iron tower based on point cloud data |
| CN111581711A (en) * | 2020-05-19 | 2020-08-25 | 北京数字绿土科技有限公司 | Tower modeling method and device, terminal equipment and computer readable storage medium |
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| CN111583174A (en) * | 2020-03-27 | 2020-08-25 | 武汉地大信息工程股份有限公司 | Method and system for detecting deformation of iron tower based on point cloud data |
| CN111583174B (en) * | 2020-03-27 | 2022-09-06 | 武汉地大信息工程股份有限公司 | Method and system for detecting deformation of iron tower based on point cloud data |
| CN111581711A (en) * | 2020-05-19 | 2020-08-25 | 北京数字绿土科技有限公司 | Tower modeling method and device, terminal equipment and computer readable storage medium |
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| CN112037331A (en) * | 2020-09-14 | 2020-12-04 | 广东电网有限责任公司江门供电局 | Method and system for rapidly judging dangerousness of electric tower |
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| CN112698303A (en) * | 2020-12-23 | 2021-04-23 | 国网电力科学研究院武汉南瑞有限责任公司 | Method and system for measuring point cloud tower inclination parameters based on unmanned aerial vehicle laser radar |
| CN112945198A (en) * | 2021-02-02 | 2021-06-11 | 贵州电网有限责任公司 | Automatic detection method for power transmission line iron tower inclination based on laser LIDAR point cloud |
| CN112945198B (en) * | 2021-02-02 | 2023-01-31 | 贵州电网有限责任公司 | Automatic detection method for inclination of power transmission line iron tower based on laser LIDAR point cloud |
| CN113128579A (en) * | 2021-04-09 | 2021-07-16 | 国网安徽省电力有限公司黄山供电公司 | Method for rapidly and visually measuring ground buried depth of tower pole of power transmission line |
| CN114184166A (en) * | 2021-11-30 | 2022-03-15 | 中冶京诚工程技术有限公司 | High-speed wire P/F wire C-shaped hook inclination detection method and device |
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| CN118500353B (en) * | 2024-07-17 | 2024-11-01 | 中建八局第三建设有限公司 | Hyperbolic cooling tower inclination state identification method |
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