CN107103599A - A kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR - Google Patents
A kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR Download PDFInfo
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- 230000005540 biological transmission Effects 0.000 title claims abstract description 50
- 230000005611 electricity Effects 0.000 title claims abstract description 35
- 238000004458 analytical method Methods 0.000 title claims abstract description 17
- 238000007689 inspection Methods 0.000 claims description 5
- 238000012423 maintenance Methods 0.000 claims description 5
- 238000010835 comparative analysis Methods 0.000 claims description 3
- VMXUWOKSQNHOCA-UKTHLTGXSA-N ranitidine Chemical compound [O-][N+](=O)\C=C(/NC)NCCSCC1=CC=C(CN(C)C)O1 VMXUWOKSQNHOCA-UKTHLTGXSA-N 0.000 claims description 3
- 238000000034 method Methods 0.000 description 4
- 238000004140 cleaning Methods 0.000 description 2
- 235000017166 Bambusa arundinacea Nutrition 0.000 description 1
- 235000017491 Bambusa tulda Nutrition 0.000 description 1
- 241001330002 Bambuseae Species 0.000 description 1
- 235000015334 Phyllostachys viridis Nutrition 0.000 description 1
- 239000011425 bamboo Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0008—Industrial image inspection checking presence/absence
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- G06Q50/06—Energy or water supply
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
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Abstract
The present invention relates to a kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR, step is：A, laser point cloud data and high definition image data using laser radar apparatus collection electric transmission line channel and periphery trees；B, according to laser point cloud data judge whether trees meet the regulation of the safe O＆M code of current transmission line of electricity to the distance of transmission line of electricity, be such as unsatisfactory for, then this trees be disposed；C, according to the empirical value of the speed of growth of different trees judge that trees grow into the timing node of hidden danger；The speed of growth of d, multi collect laser radar data and high definition image data, the constantly different trees in amendment different regions, and thus update the timing node that trees grow into hidden danger.
Description
Technical field
The present invention relates to transmission of electricity O＆M field, electric power disaster analysis field, more particularly it relates to which one kind is based on
LiDAR transmission line of electricity trees hidden danger prediction analysis method.
Background technology
The reliability of transmission line of electricity is influenceed by many internal and external factors, and the contradiction between its center line and tree is pacified to transmission line of electricity
Row for the national games has constituted a serious threat, and cleaning trees hidden danger has turned into the important work that O＆M unit ensures power transmission facility safe operation
Make.Trees, bamboo in electric transmission line channel etc. are cut every year, year is older, every year the line caused by screen of trees in power transmission line corridor
Road trip event happens occasionally, it is found that screen of trees, the manpower and materials of cleaning screen of trees consumption turn into the burden of O＆M working unit.Pin
To the screen of trees problem in the seriousness and complexity of screen of trees problem, particularly mountain area, the present invention utilizes laser radar apparatus, carries out
The forecast analysis research of electric transmission line channel trees hidden danger, to improve transmission line of electricity O＆M unit screen of trees hidden danger anticipation, is protected
Hinder the safe and stable operation of transmission line of electricity.
The content of the invention
The purpose of the present invention is to rely primarily on manual patrol to break through conventional transmission lines paths trees hidden danger, disaster
A kind of pattern investigated, it is proposed that transmission line of electricity trees hidden danger prediction analysis method based on LiDAR, gathers transmission line of electricity
Passage and its laser point cloud data and high definition image data of neighbouring trees, the on this basis current transmission line of electricity of Accurate Analysis
With the presence or absence of trees hidden danger, and analysis predicts when that trees hidden danger will likely occur in where.
The present invention meets the technical schemes of above-mentioned requirements, and to be to provide a kind of transmission line of electricity trees hidden danger based on LiDAR pre-
Analysis method is surveyed, is comprised the following steps：
A. laser point cloud data and the visible shadow of high definition are carried out to transmission line of electricity and periphery atural object using laser radar apparatus
As collection；
B. laser point cloud data is classified, marks the trees that influence is likely to cause on transmission line of electricity, including it is defeated
The trees of eminence beyond trees and electric transmission line channel in electric wire paths；
C. the current state of trees is determined according to laser point cloud data, judges whether the distance of current trees and power line is small
In the safe distance of current transmission line safety O＆M code, if it is, judging current trees for hidden danger point, and start follow-up
Disposal process；
D. for not being judged as the trees of hidden danger, with reference to high definition image data, tree families are determined；
E. the timing node that trees grow into hidden danger is calculated according to the empirical value of different arboreal growth speed, in the time
Transmission line of electricity operation maintenance personnel is reminded to carry out the inspection of the scene of a crime and processing before node；
F. by the comparative analysis of the laser point cloud data of different time sections multi collect, constantly amendment different regions are various
The speed of growth of trees, and thus constantly update the timing node that trees grow up into hidden danger.
The beneficial effects of the invention are as follows break through conventional transmission lines paths trees hidden danger, disaster and rely primarily on manual patrol
The pattern investigated, it is proposed that a kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR, relative to manually patrolling
Depending on mode, this method can accurately judge the distance of trees and transmission line of electricity, reduce the tour of transmission line of electricity operation maintenance personnel
Workload, effective improve makes an inspection tour efficiency and reduces personal safety risk, final to reduce the O＆M cost of transmission line of electricity.
Brief description of the drawings
Fig. 1 is the transmission line of electricity trees hidden danger prediction analysis method flow chart of the invention based on LiDAR.
Embodiment
See Fig. 1, a kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR comprises the following steps：
A. laser point cloud data and the visible shadow of high definition are carried out to transmission line of electricity and periphery atural object using laser radar apparatus
As collection；
B. laser point cloud data is classified, marks the trees that influence is likely to cause on transmission line of electricity, including it is defeated
The trees of eminence beyond trees and electric transmission line channel in electric wire paths；
C. the current state of trees is determined according to laser point cloud data, judges whether the distance of current trees and power line is small
In the safe distance of current transmission line safety O＆M code, if it is, judging current trees for hidden danger point, and start follow-up
Disposal process；
D. for not being judged as the trees of hidden danger, with reference to high definition image data, tree families are determined；
E. the timing node that trees grow into hidden danger is calculated according to the empirical value of different arboreal growth speed, in the time
Transmission line of electricity operation maintenance personnel is reminded to carry out the inspection of the scene of a crime and processing before node；
F. by the comparative analysis of the laser point cloud data of different time sections multi collect, constantly amendment different regions are various
The speed of growth of trees, and thus constantly update the timing node that trees grow up into hidden danger.
The inventive method is mainly used in transmission line of electricity trees hidden danger forecast analysis, and power transmission line is gathered using laser radar apparatus
It is accurate to judge that transmission line of electricity is hidden with the presence or absence of trees after the laser point cloud data and high definition image data of paths, analyzing and processing
Suffer from, and according to the speed of growth of trees, analysis prediction trees are likely to form the timing node of hidden danger, can so greatly reduced defeated
The tour workload of electric line operation maintenance personnel, effective improve makes an inspection tour efficiency and reduces personal safety risk, final to reduce transmission of electricity
The O＆M cost of circuit.
Transmission line of electricity trees hidden danger prediction analysis method based on LiDAR is as shown in Figure 1；
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change or replacement that can be readily occurred in,
It should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims
It is defined.
Claims (1)
1. a kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR, it is characterised in that comprise the following steps：
A, laser point cloud data is carried out to transmission line of electricity and periphery atural object using laser radar apparatus and high definition visible image is adopted
Collection；
B, laser point cloud data is classified, mark the trees that influence is likely to cause on transmission line of electricity, including power transmission line
The trees of eminence beyond trees and electric transmission line channel in paths；
C, the current state for determining according to laser point cloud data trees, judge whether the distance of current trees and power line is less than and work as
The safe distance of preceding transmission line safety O＆M code, if it is, judging current trees for hidden danger point, and starts follow-up place
Put flow；
D, the trees for not being judged as hidden danger, with reference to high definition image data, determine tree families；
E, trees are calculated according to the empirical value of different arboreal growth speed grow into the timing node of hidden danger, in the timing node
Preceding prompting transmission line of electricity operation maintenance personnel carries out the inspection of the scene of a crime and disposal；
F, the comparative analysis by the laser point cloud data of different time sections multi collect, constantly the amendment various trees in different regions
The speed of growth, and thus constantly update trees and grow up into the timing node of hidden danger.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710221254.XA CN107103599A (en) | 2017-04-06 | 2017-04-06 | A kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR |
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| CN201710221254.XA CN107103599A (en) | 2017-04-06 | 2017-04-06 | A kind of transmission line of electricity trees hidden danger prediction analysis method based on LiDAR |
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Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108037770A (en) * | 2017-11-22 | 2018-05-15 | 国网山东省电力公司济宁供电公司 | Unmanned plane power transmission line polling system and method based on artificial intelligence |
| CN108226894A (en) * | 2017-11-29 | 2018-06-29 | 北京数字绿土科技有限公司 | A kind of Processing Method of Point-clouds and device |
| CN108986165A (en) * | 2018-07-11 | 2018-12-11 | 云南电网有限责任公司电力科学研究院 | The monitoring method and device of a kind of high-voltage line to tree electric discharge safe spacing |
| CN109146177A (en) * | 2018-08-23 | 2019-01-04 | 云南电网有限责任公司普洱供电局 | A kind of electric line screen of trees prediction technique and device |
| CN109215065A (en) * | 2018-09-07 | 2019-01-15 | 北京数字绿土科技有限公司 | Screen of trees hidden danger prediction technique, device and the realization device of transmission line of electricity |
| CN109214573A (en) * | 2018-09-07 | 2019-01-15 | 北京数字绿土科技有限公司 | Transmission line of electricity arboreal growth or lodging dangerous point prediction technique and device |
| CN109390873A (en) * | 2018-11-30 | 2019-02-26 | 贵州电网有限责任公司 | A method of predicting that screen of trees is threatened using point cloud data in electric transmission line channel |
| CN109461142A (en) * | 2018-10-11 | 2019-03-12 | 广东电网有限责任公司 | Route Analysis of Potential method, apparatus and electric terminal |
| CN109785352A (en) * | 2018-12-21 | 2019-05-21 | 广东工业大学 | A kind of intelligent and high-efficiency airborne radar point cloud analysis method |
| CN110189311A (en) * | 2019-05-24 | 2019-08-30 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | A kind of calculation method of transmission line of electricity screen of trees hidden danger region trees felling area |
| CN111082360A (en) * | 2019-12-23 | 2020-04-28 | 深圳供电局有限公司 | Power transmission line mobile monitoring device, system and method |
| CN111931976A (en) * | 2020-06-22 | 2020-11-13 | 云南电网有限责任公司带电作业分公司 | Prediction method for tree growth hidden danger in power transmission line corridor area |
| CN112016396A (en) * | 2020-07-22 | 2020-12-01 | 国网通用航空有限公司 | Line channel safety analysis method based on tree growth prediction |
| CN112558091A (en) * | 2020-11-27 | 2021-03-26 | 广东电网有限责任公司肇庆供电局 | Real-time detection method and device for spatial distance of power transmission line to tree and terminal equipment |
| CN113470017A (en) * | 2021-08-31 | 2021-10-01 | 海门裕隆光电科技有限公司 | Power transmission line safety early warning detection method, device and equipment based on artificial intelligence |
| CN113569914A (en) * | 2021-06-29 | 2021-10-29 | 山东信通电子股份有限公司 | Power transmission line inspection method and system fusing point cloud data |
| CN114119606A (en) * | 2022-01-20 | 2022-03-01 | 国网江西省电力有限公司电力科学研究院 | Intelligent tree obstacle hidden danger analysis method based on visible light photo power line coloring |
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Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108037770A (en) * | 2017-11-22 | 2018-05-15 | 国网山东省电力公司济宁供电公司 | Unmanned plane power transmission line polling system and method based on artificial intelligence |
| CN108037770B (en) * | 2017-11-22 | 2021-05-28 | 国网山东省电力公司济宁供电公司 | Unmanned aerial vehicle power transmission line inspection system and method based on artificial intelligence |
| CN108226894A (en) * | 2017-11-29 | 2018-06-29 | 北京数字绿土科技有限公司 | A kind of Processing Method of Point-clouds and device |
| US11544511B2 (en) | 2017-11-29 | 2023-01-03 | Beijing Greenvalley Technology Co., Ltd. | Method, apparatus, and electronic device for processing point cloud data, and computer readable storage medium |
| CN108986165A (en) * | 2018-07-11 | 2018-12-11 | 云南电网有限责任公司电力科学研究院 | The monitoring method and device of a kind of high-voltage line to tree electric discharge safe spacing |
| CN109146177A (en) * | 2018-08-23 | 2019-01-04 | 云南电网有限责任公司普洱供电局 | A kind of electric line screen of trees prediction technique and device |
| CN109146177B (en) * | 2018-08-23 | 2022-02-11 | 云南电网有限责任公司普洱供电局 | Power transmission and distribution line tree fault prediction method and device |
| CN109215065A (en) * | 2018-09-07 | 2019-01-15 | 北京数字绿土科技有限公司 | Screen of trees hidden danger prediction technique, device and the realization device of transmission line of electricity |
| CN109214573A (en) * | 2018-09-07 | 2019-01-15 | 北京数字绿土科技有限公司 | Transmission line of electricity arboreal growth or lodging dangerous point prediction technique and device |
| CN109461142A (en) * | 2018-10-11 | 2019-03-12 | 广东电网有限责任公司 | Route Analysis of Potential method, apparatus and electric terminal |
| CN112884745A (en) * | 2018-10-11 | 2021-06-01 | 广东电网有限责任公司 | Line hidden danger analysis method and device and electronic terminal |
| CN109390873A (en) * | 2018-11-30 | 2019-02-26 | 贵州电网有限责任公司 | A method of predicting that screen of trees is threatened using point cloud data in electric transmission line channel |
| CN109785352A (en) * | 2018-12-21 | 2019-05-21 | 广东工业大学 | A kind of intelligent and high-efficiency airborne radar point cloud analysis method |
| CN109785352B (en) * | 2018-12-21 | 2022-11-22 | 广东工业大学 | Intelligent efficient airborne radar point cloud analysis method |
| CN110189311A (en) * | 2019-05-24 | 2019-08-30 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | A kind of calculation method of transmission line of electricity screen of trees hidden danger region trees felling area |
| CN111082360A (en) * | 2019-12-23 | 2020-04-28 | 深圳供电局有限公司 | Power transmission line mobile monitoring device, system and method |
| CN111931976A (en) * | 2020-06-22 | 2020-11-13 | 云南电网有限责任公司带电作业分公司 | Prediction method for tree growth hidden danger in power transmission line corridor area |
| CN112016396A (en) * | 2020-07-22 | 2020-12-01 | 国网通用航空有限公司 | Line channel safety analysis method based on tree growth prediction |
| CN112016396B (en) * | 2020-07-22 | 2024-01-26 | 国网电力空间技术有限公司 | Line channel safety analysis method based on tree growth prediction |
| CN112558091A (en) * | 2020-11-27 | 2021-03-26 | 广东电网有限责任公司肇庆供电局 | Real-time detection method and device for spatial distance of power transmission line to tree and terminal equipment |
| CN112558091B (en) * | 2020-11-27 | 2023-08-01 | 广东电网有限责任公司肇庆供电局 | Real-time detection method and device for tree space distance of transmission line and terminal equipment |
| CN113569914A (en) * | 2021-06-29 | 2021-10-29 | 山东信通电子股份有限公司 | Power transmission line inspection method and system fusing point cloud data |
| CN113569914B (en) * | 2021-06-29 | 2024-02-09 | 山东信通电子股份有限公司 | Point cloud data fusion type power transmission line inspection method and system |
| CN113470017B (en) * | 2021-08-31 | 2021-11-16 | 海门裕隆光电科技有限公司 | Power transmission line safety early warning detection method, device and equipment based on artificial intelligence |
| CN113470017A (en) * | 2021-08-31 | 2021-10-01 | 海门裕隆光电科技有限公司 | Power transmission line safety early warning detection method, device and equipment based on artificial intelligence |
| CN114119606A (en) * | 2022-01-20 | 2022-03-01 | 国网江西省电力有限公司电力科学研究院 | Intelligent tree obstacle hidden danger analysis method based on visible light photo power line coloring |
| CN114119606B (en) * | 2022-01-20 | 2022-05-10 | 国网江西省电力有限公司电力科学研究院 | Intelligent tree obstacle hidden danger analysis method based on visible light photo power line coloring |
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