CN104050715A - High-precision three-dimensional reconstruction method for power transmission line and corridor - Google Patents
High-precision three-dimensional reconstruction method for power transmission line and corridor Download PDFInfo
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- CN104050715A CN104050715A CN201410283175.8A CN201410283175A CN104050715A CN 104050715 A CN104050715 A CN 104050715A CN 201410283175 A CN201410283175 A CN 201410283175A CN 104050715 A CN104050715 A CN 104050715A
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Abstract
The invention discloses a high-precision three-dimensional reconstruction method for a power transmission line and a corridor, and belongs to the technical field of power transmission line patrolling. The method includes the steps of firstly, collecting three-dimensional point cloud data of the power transmission line and the corridor through an airborne laser radar; secondly, verifying the three-dimensional point cloud data to remove wrong points and height anomaly points; thirdly, automatically classifying the three-dimensional point cloud data based on a voxel classification method; fourthly, conducting automatic three-dimensional reconstruction on the power transmission line and the corridor. The method has the advantages that three-dimensional information of the power transmission line and the corridor can be rapidly and accurately generated through the laser point cloud data where data processing and classifying are conducted, and therefore data accuracy can be ensured, and the workloads for daily operation and maintenance can be greatly reduced; by means of a three-dimensional scene obtained on the basis of the laser scanning three-dimensional imaging technology, the three-dimensional space of the line and the corridor are truly displayed on a computer, and the power transmission line and the corridor can be overall controlled and can also be examined by focusing on parts.
Description
Technical field
The invention belongs to polling transmission line technical field, particularly the high-precision three-dimensional method for reconstructing in a kind of transmission line of electricity and corridor.
Background technology
No matter current helicopter line walking adopts multispectral technology or thermal infrared technology, and sterically defined measurement accuracy is all not high, and the multi-source data obtaining separately processes mostly, does not have integrated as a wholely, deals with also cumbersome.Correlative study both domestic and external shows, utilizes laser radar system to address these problems preferably.Current, domestic this technology of also having introduced, in Transmission Line Design, obtained application, but in Maintenance of Electric Transmission Line also in starting the exploratory stage, and current research both domestic and external has certain limitation, the transmission line of electricity data post-processed that laser radar is gathered is still rare with comprehensive analysis.
Summary of the invention
The deficiency existing for prior art, the present invention proposes the high-precision three-dimensional method for reconstructing in a kind of transmission line of electricity and corridor, it is characterized in that, and the concrete steps of the method are:
1) by airborne laser radar, gather the three dimensional point cloud in transmission line of electricity and corridor;
2) three dimensional point cloud is tested, reject wrong point and the point of height anomaly;
3) based on voxel classification method, three dimensional point cloud is carried out to automatic classification;
4) transmission line of electricity and corridor are carried out to automatic three-dimensional reconstruction.
Described step 1) be specially:
11) the information layout data with reference to Geographic Information System GIS gathers path, gathers the three dimensional point cloud in transmission line of electricity and corridor by airborne laser radar;
12) by Unscented kalman filtering method, High Accuracy Inertial information and differential Global Positioning System information are carried out to information fusion, realize the preresearch estimates of three dimensional point cloud;
13) by data correlation, Registration of Measuring Data and filtering and noise reduction, obtain high accuracy three-dimensional cloud data.
The concrete formula of rejecting the point of height anomaly described step 2) is:
Dh
i＝H
i-h′；
Wherein, Dh
irepresent the poor of the actual measurement elevation of i three-dimensional point and Fitting height; H
ithe actual measurement elevation that represents i three-dimensional point; H ' expression Fitting height;
Work as Dh
iwhile being greater than spot elevation threshold value, be judged to be the point of height anomaly, otherwise be judged as normal point.
Described step 3) in, by three dimensional point cloud automatic classification, be transmission line of electricity candidate point and corridor candidate point; Concrete formula is:
P
powerline＝{p
i|C(p
i)＝0}；
Wherein, P
powerlinerepresent the transmission line of electricity candidate point set filtering out, p
irepresent i three-dimensional point, C (p
i) be transmission line of electricity curvilinear function.
Described step 4) be specially:
41) for transmission line of electricity candidate point, adopt particle filter algorithm to detect transmission line of electricity direction, adopt exterior point removal and segmentation method to carry out transmission line of electricity and just extract, obtain the segment data of transmission line of electricity;
42) for corridor candidate point, adopt exterior point filtering to filter, then carry out environmental scenery extraction, obtain corridor segment data;
43) to the segment data of transmission line of electricity, the line segment detecting method based on voxel connects into line, then carries out the automatic three-dimensional reconstruction of transmission line of electricity; Line segment detecting method to corridor segment data based on voxel connects into line, carries out the automatic three-dimensional reconstruction in corridor.
Described employing particle filter algorithm detects and comprises transmission line of electricity direction:
Transmission line of electricity candidate point is divided into several set at random;
Using each set as a particle collection, adopt particle filter algorithm to extract the key point in each set;
The formula that extracts key point is:
Wherein, p (x
k| z
k) expression probability density function; Key point is the point that particle set makes probability density function maximum; N represents the number of transmission line of electricity candidate point; x
kthe volume coordinate that represents k transmission line of electricity candidate point; ω
kx
kweight, z
kwith respect to x
kthe aircraft that records of airborne laser radar to the distance of transmission line of electricity candidate point;
Key point in each set is connected, and the circuit obtaining is transmission line of electricity.
Described step 41) computing formula that adopts exterior point removal and segmentation method to obtain the segment data of transmission line of electricity in is:
Wherein, C
tthe segment data that represents transmission line of electricity, Kd is the set that the point on transmission line of electricity forms,
a step function, when x > φ,
when x=φ,
when x < φ,
φ is a threshold value, and t is constantly.
The beneficial effect of the invention: compare with traditional manual type, the inventive method has following characteristics:
(1) through data processing, sorted laser point cloud data, can generate quickly and accurately the three-dimensional information in transmission line of electricity and corridor, as landform, landforms, each type objects of earth's surface, lead wire and earth wire, shaft tower etc., the accuracy of data can be guaranteed, the workload of daily O&M can be greatly reduced again.
(2) three-dimensional scenic obtaining based on scanning three-dimensional imaging laser technology, shows on computers circuit corridor three dimensions is true, not only can the overall situation control but also can check at local emphasis.
Accompanying drawing explanation
Fig. 1 is the three-dimensional rebuilding method process flow diagram that the present invention proposes;
Fig. 2 is the high-acruracy survey process flow diagram to transmission line of electricity by LiDAR.
Embodiment
Below in conjunction with accompanying drawing, the inventive method is further described.
The present invention mainly adopts airborne laser radar (Light Detection And Ranging, LiDAR) to carry out high-precision three-dimensional reconstruction to transmission line of electricity and corridor.The range finding of LiDAR integrated laser, computing machine, Inertial Measurement Unit (Inertial Measurement Unit, IMU), differential Global Positioning System (Differential Global Positioning System, DGPS) etc. technology is in one, can obtain the meticulous three-dimensional coordinate of ground object, the geospatial information that possesses high-spatial and temporal resolution for obtaining provides a kind of brand-new technological means.
If Fig. 1 is the three-dimensional rebuilding method process flow diagram that the present invention proposes, step is as follows:
1) by LiDAR, gather the three dimensional point cloud in transmission line of electricity and corridor, step is as Fig. 2:
11) the information layout data with reference to Geographic Information System (Geographic Information System, GIS) gathers path, gathers the three dimensional point cloud in transmission line of electricity and corridor by LiDAR.
12) by Unscented kalman filtering method, High Accuracy Inertial information and differential Global Positioning System information are carried out to information fusion, realize the preresearch estimates of three dimensional point cloud.
13) by data correlation, Registration of Measuring Data and filtering and noise reduction, obtain high accuracy three-dimensional cloud data.
Pendulum angle data to aircraft GPS track data, aspect data, laser ranging data and laser scanning mirror are carried out Combined Treatment, finally obtain high accuracy three-dimensional cloud data.
2) three dimensional point cloud is tested, reject wrong point and the point of height anomaly.
The point of mistake refers to that apparent point, such as the indivedual points that have serious distance to depart from other point.
The point of height anomaly, as low especially point (point of below ground) or extra high point (cloud or aloft bird), the computing formula of the point of height anomaly is as follows:
Dh
i＝H
i-h′；
Wherein, Dh
irepresent the poor of the actual measurement elevation of i transmission line of electricity candidate point and Fitting height; H
ithe actual measurement elevation that represents i transmission line of electricity candidate point; H ' expression Fitting height.Work as Dh
iwhile being greater than spot elevation threshold value, be judged to be the point of height anomaly, otherwise be judged as normal point.This threshold value need to be summed up out through many experiments, can set voluntarily.
3) based on voxel classification method, three dimensional point cloud is classified.
The all types of data that three dimensional point cloud has after treatment comprised pickup area, possessed three dimensions display function, but because the dissimilar three dimensional point clouds such as wire, shaft tower, vegetation merge, the visual extreme difference of the 3-D view of formation.So three dimensional point cloud need to be classified, the method of taking is the sorting technique based on voxel, three dimensional point cloud is divided into transmission line of electricity candidate point and corridor candidate point automatically, and the laser data of sophisticated category can clearly be differentiated the key elements such as power circuit, shaft tower, vegetation and ground.Concrete formula is:
P
powerline＝{p
i|C(p
i)＝0}
Wherein, P
powerlinerepresent the transmission line of electricity candidate point set filtering out, pi represents i LiDAR point, C (p
i) be transmission line of electricity curvilinear function; Remaining LiDAR point (three dimensional point cloud) is corridor candidate point.
4) transmission line of electricity and corridor are carried out to three-dimensional reconstruction, are specially:
41) for transmission line of electricity candidate point, adopt particle filter algorithm to carry out the detection of transmission line of electricity direction, it comprises:
Transmission line of electricity candidate point is divided into several set at random;
Using each set as a particle collection, adopt particle filter algorithm to extract the key point in each set;
The formula that extracts key point is:
Wherein, p (x
k| z
k) expression probability density function; Key point is the point that particle set makes probability density function maximum; N represents the number of transmission line of electricity candidate point; x
kthe volume coordinate that represents k transmission line of electricity candidate point; ω
kx
kweight, z
kwith respect to x
kthe aircraft that records of airborne laser radar to the distance of transmission line of electricity candidate point;
Key point in each set is connected, and the circuit obtaining is transmission line of electricity.
Then, then adopt exterior point to remove and segmentation method carries out transmission line of electricity and just extracts, its computing formula is:
Wherein, C
tthe segment data that represents transmission line of electricity, Kd is the set that the point on transmission line of electricity forms,
a step function, when x > φ,
these points may be some wrong points; When x=φ,
when x < φ,
these points may be other noise spots such as trees; φ is a threshold value, and its value is determined by the cloud data of transmission line of electricity; T is constantly.
42) for corridor candidate point, because causing data, physics, environmental factor produce noise spot, need carry out filtering and noise reduction, adopt exterior point filtering to filter, then carry out environmental scenery extraction, obtain corridor segment data;
43) to the segment data of transmission line of electricity, the line segment detecting method based on voxel connects into line, then carries out the automatic three-dimensional reconstruction of transmission line of electricity; Line segment detecting method to corridor segment data based on voxel connects into line, carries out the automatic three-dimensional reconstruction in corridor.
The above; be only the present invention's embodiment preferably, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.
Claims (7)
1. the high-precision three-dimensional method for reconstructing in transmission line of electricity and corridor, is characterized in that, the concrete steps of the method are:
1) by airborne laser radar, gather the three dimensional point cloud in transmission line of electricity and corridor;
2) three dimensional point cloud is tested, reject wrong point and the point of height anomaly;
3) based on voxel classification method, three dimensional point cloud is carried out to automatic classification;
4) transmission line of electricity and corridor are carried out to automatic three-dimensional reconstruction.
2. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 1 and corridor, is characterized in that, described step 1) be specially:
11) the information layout data with reference to Geographic Information System GIS gathers path, gathers the three dimensional point cloud in transmission line of electricity and corridor by airborne laser radar;
12) by Unscented kalman filtering method, High Accuracy Inertial information and differential Global Positioning System information are carried out to information fusion, realize the preresearch estimates of three dimensional point cloud;
13) by data correlation, Registration of Measuring Data and filtering and noise reduction, obtain high accuracy three-dimensional cloud data.
3. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 2 and corridor, is characterized in that, described step 2) in reject the point of height anomaly concrete formula be:
Dh
i＝H
i-h′；
Wherein, Dh
irepresent the poor of the actual measurement elevation of i three-dimensional point and Fitting height; H
ithe actual measurement elevation that represents i three-dimensional point; H ' expression Fitting height;
Work as Dh
iwhile being greater than spot elevation threshold value, be judged to be the point of height anomaly, otherwise be judged as normal point.
4. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 3 and corridor, is characterized in that, described step 3) in by three dimensional point cloud automatic classification, be transmission line of electricity candidate point and corridor candidate point; Concrete formula is:
P
powerline＝{p
i|C(p
i)＝0}；
Wherein, P
powerlinerepresent the transmission line of electricity candidate point set filtering out, p
irepresent i three-dimensional point, C (p
i) be transmission line of electricity curvilinear function.
5. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 4 and corridor, is characterized in that, described step 4) be specially:
41) for transmission line of electricity candidate point, adopt particle filter algorithm to detect transmission line of electricity direction, adopt exterior point removal and segmentation method to carry out transmission line of electricity and just extract, obtain the segment data of transmission line of electricity;
42) for corridor candidate point, adopt exterior point filtering to filter, then carry out environmental scenery extraction, obtain corridor segment data;
43) to the segment data of transmission line of electricity, the line segment detecting method based on voxel connects into line, then carries out the automatic three-dimensional reconstruction of transmission line of electricity; Line segment detecting method to corridor segment data based on voxel connects into line, carries out the automatic three-dimensional reconstruction in corridor.
6. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 5 and corridor, is characterized in that, described employing particle filter algorithm detects and comprises transmission line of electricity direction:
Transmission line of electricity candidate point is divided into several set at random;
Using each set as a particle collection, adopt particle filter algorithm to extract the key point in each set;
The formula that extracts key point is:
Wherein, p (x
k| z
k) expression probability density function; Key point is the point that particle set makes probability density function maximum; N represents the number of transmission line of electricity candidate point; x
kthe volume coordinate that represents k transmission line of electricity candidate point; ω
kx
kweight, z
kwith respect to x
kthe aircraft that records of airborne laser radar to the distance of transmission line of electricity candidate point;
Key point in each set is connected, and the circuit obtaining is transmission line of electricity.
7. the high-precision three-dimensional method for reconstructing in transmission line of electricity according to claim 6 and corridor, is characterized in that, described step 41) in adopt the computing formula that exterior point is removed and segmentation method obtains the segment data of transmission line of electricity to be:
Wherein, C
tthe segment data that represents transmission line of electricity, Kd is the set that the point on transmission line of electricity forms,
a step function, when x > φ,
when x=φ,
when x < φ,
φ is a threshold value, and t is constantly.
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| CN201410283175.8A CN104050715A (en) | 2014-06-23 | 2014-06-23 | High-precision three-dimensional reconstruction method for power transmission line and corridor |
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ID=51503483
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Cited By (18)
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| CN104392486A (en) * | 2014-11-25 | 2015-03-04 | 西安理工大学 | Point-cloud scene rebuilding method |
| CN106056563A (en) * | 2016-05-20 | 2016-10-26 | 首都师范大学 | Airborne laser point cloud data and vehicle laser point cloud data fusion method |
| CN106504362A (en) * | 2016-10-18 | 2017-03-15 | 国网湖北省电力公司检修公司 | Power transmission and transformation system method for inspecting based on unmanned plane |
| CN106503060A (en) * | 2016-09-28 | 2017-03-15 | 山东东电电气工程技术有限公司 | A kind of transmission line of electricity three dimensional point cloud is processed and hands over across thing acquisition methods |
| CN106657882A (en) * | 2016-10-18 | 2017-05-10 | 国网湖北省电力公司检修公司 | Real-time monitoring method for power transmission and transformation system based on unmanned aerial vehicle |
| CN107238845A (en) * | 2017-05-19 | 2017-10-10 | 云南电网有限责任公司电力科学研究院 | A kind of power transmission line unmanned machine flight path detection method based on 3 D laser scanning |
| CN107393004A (en) * | 2017-07-17 | 2017-11-24 | 北京数字绿土科技有限公司 | A kind of method and device for obtaining building amount of demolition in power transmission line corridor |
| CN107564111A (en) * | 2017-05-31 | 2018-01-09 | 武汉圆桌智慧科技有限公司 | Power line space safety analysis method based on computer vision |
| CN107680102A (en) * | 2017-08-28 | 2018-02-09 | 国网甘肃省电力公司电力科学研究院 | A kind of airborne cloud data electric force pole tower extraction method based on space constraint |
| CN107704629A (en) * | 2017-10-31 | 2018-02-16 | 广东电网有限责任公司电力科学研究院 | A kind of power transmission line unmanned machine inspection visual management method and device |
| CN107817504A (en) * | 2017-10-27 | 2018-03-20 | 广东电网有限责任公司机巡作业中心 | A kind of airborne laser radar point cloud data processing method |
| CN108764012A (en) * | 2018-03-27 | 2018-11-06 | 国网辽宁省电力有限公司电力科学研究院 | The urban road shaft recognizer of mobile lidar data based on multi-frame joint |
| CN108986234A (en) * | 2018-06-19 | 2018-12-11 | 广东电网有限责任公司 | terrain data fusion method and device |
| CN109033696A (en) * | 2018-08-20 | 2018-12-18 | 贵州电网有限责任公司 | A kind of transmission line of electricity share split calculation method based on laser point cloud |
| CN109063369A (en) * | 2018-08-22 | 2018-12-21 | 广州供电局有限公司 | Cable trace planing method and cable trace device for planning |
| CN109100703A (en) * | 2018-09-07 | 2018-12-28 | 北京数字绿土科技有限公司 | A kind of transmission line of electricity dangerous point detection method and device |
| CN112836352A (en) * | 2021-01-12 | 2021-05-25 | 中国电建集团贵州电力设计研究院有限公司 | Power transmission line model generation method integrating three-dimensional design and laser point cloud |
| CN114332415A (en) * | 2022-03-09 | 2022-04-12 | 南方电网数字电网研究院有限公司 | Three-dimensional reconstruction method and device of power transmission line corridor based on multi-view technology |
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| CN104392486A (en) * | 2014-11-25 | 2015-03-04 | 西安理工大学 | Point-cloud scene rebuilding method |
| CN104392486B (en) * | 2014-11-25 | 2017-07-28 | 西安理工大学 | One kind point cloud scene reconstruction method |
| CN106056563A (en) * | 2016-05-20 | 2016-10-26 | 首都师范大学 | Airborne laser point cloud data and vehicle laser point cloud data fusion method |
| CN106503060A (en) * | 2016-09-28 | 2017-03-15 | 山东东电电气工程技术有限公司 | A kind of transmission line of electricity three dimensional point cloud is processed and hands over across thing acquisition methods |
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| CN107817504B (en) * | 2017-10-27 | 2021-05-28 | 广东电网有限责任公司机巡作业中心 | Airborne laser radar point cloud data processing method |
| CN107704629A (en) * | 2017-10-31 | 2018-02-16 | 广东电网有限责任公司电力科学研究院 | A kind of power transmission line unmanned machine inspection visual management method and device |
| CN107704629B (en) * | 2017-10-31 | 2021-07-02 | 广东电网有限责任公司电力科学研究院 | Transmission line unmanned aerial vehicle routing inspection visual management method and device |
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| CN108986234A (en) * | 2018-06-19 | 2018-12-11 | 广东电网有限责任公司 | terrain data fusion method and device |
| CN108986234B (en) * | 2018-06-19 | 2023-09-29 | 广东电网有限责任公司 | Terrain data fusion method and device |
| CN109033696B (en) * | 2018-08-20 | 2021-04-23 | 贵州电网有限责任公司 | Laser point cloud-based power transmission line stranding calculation method |
| CN109033696A (en) * | 2018-08-20 | 2018-12-18 | 贵州电网有限责任公司 | A kind of transmission line of electricity share split calculation method based on laser point cloud |
| CN109063369A (en) * | 2018-08-22 | 2018-12-21 | 广州供电局有限公司 | Cable trace planing method and cable trace device for planning |
| CN109100703A (en) * | 2018-09-07 | 2018-12-28 | 北京数字绿土科技有限公司 | A kind of transmission line of electricity dangerous point detection method and device |
| CN112836352A (en) * | 2021-01-12 | 2021-05-25 | 中国电建集团贵州电力设计研究院有限公司 | Power transmission line model generation method integrating three-dimensional design and laser point cloud |
| CN114332415A (en) * | 2022-03-09 | 2022-04-12 | 南方电网数字电网研究院有限公司 | Three-dimensional reconstruction method and device of power transmission line corridor based on multi-view technology |
| CN114332415B (en) * | 2022-03-09 | 2022-07-29 | 南方电网数字电网研究院有限公司 | Three-dimensional reconstruction method and device of power transmission line corridor based on multi-view technology |
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