CN112000124B - Unmanned aerial vehicle inspection method applied to power grid - Google Patents
Unmanned aerial vehicle inspection method applied to power grid Download PDFInfo
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Abstract
The invention relates to an unmanned aerial vehicle inspection method applied to a power grid. The method is used for solving the problems that the flight line of the unmanned aerial vehicle is unstable, the acquired image is not clear, and the shooting angle does not meet the requirements. The method includes the steps that a 3D map model needs to be established in advance, wherein the 3D map model comprises inspection points, an inspection element set is established for each inspection point, the inspection element set comprises image samples of the inspection points, and index information is preset for the image samples of the inspection points; the 3D map model is loaded in the unmanned aerial vehicle, the unmanned aerial vehicle receives the inspection task, identifies the positions of all inspection points in the 3D map model, and performs inspection route planning; after the unmanned aerial vehicle reaches the inspection point, an image sample corresponding to the inspection point is extracted from the 3D map model, the actual index information of the acquired field image and the index information of the image sample are checked, inspection of the inspection point is completed if the actual index information is matched with the index information of the image sample, and the actual index information is acquired again until the actual index information is matched if the actual index information is not matched with the index information of the image sample. By the method, the effects that the flight line is stable, the quality of the acquired image is high, and the acquired image meets the analysis requirement are achieved.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle inspection, in particular to an unmanned aerial vehicle inspection method applied to a power grid.
Background
When the unmanned aerial vehicle is used for patrolling and examining the line of a power grid in the technology, the unmanned aerial vehicle does not carry a 3D map model, but builds a three-dimensional map at a ground terminal, the unmanned aerial vehicle returns flight information in real time, and then the ground terminal remotely controls the flight of the unmanned aerial vehicle according to the flight information returned by the unmanned aerial vehicle and the position information of an inspection point in the map model, so that the dependence of the unmanned aerial vehicle on remote distance and radar in the flight process is too high in the prior art, and the situations of poor flight stability and information delay exist. Meanwhile, after the unmanned aerial vehicle carries the camera to shoot the inspection point, the unmanned aerial vehicle can not carry out self-inspection on the image acquired on site, so that the quality of the shot image is low, the image is often not in accordance with the analysis requirement, the image cannot be used, and the inspection effect is poor.
Disclosure of Invention
The invention aims to overcome at least one defect (deficiency) of the prior art, provides the unmanned aerial vehicle inspection method applied to the power grid, solves the problems that the flight line of the unmanned aerial vehicle is unstable, the acquired image is not clear enough, and the shooting angle does not meet the requirement, and achieves the effects that the flight line is stable, the acquired image is high in quality and meets the analysis requirement.
The invention adopts the technical scheme that an unmanned aerial vehicle inspection method applied to a power grid comprises the following steps:
step 1, pre-establishing a 3D map model for power grid line inspection, and loading the 3D map model in an unmanned aerial vehicle; the 3D map model is constructed by combining a 3D image of the power grid line, a patrol point and an image sample of the patrol point with a facility layout map of the power grid line; the power grid line 3D image is obtained by carrying a 3D high-definition scanner by an unmanned aerial vehicle and scanning the power grid line in advance, the position information of each inspection point is extracted from a facility layout diagram of the power grid line, and an image sample of the inspection point is extracted from the scanned power grid line 3D image according to the position information of the inspection point; establishing a respective inspection element set for each inspection point in the 3D map model, wherein the inspection element set comprises inspection point image samples, and index information is preset for the inspection point image samples so as to carry out standard comparison after field images are acquired subsequently;
step 2, after receiving the inspection task, the unmanned aerial vehicle loads the inspection task into the 3D map model, plans an inspection line according to the inspection task in the 3D map model, and loads the planned inspection line into the 3D map model;
step 3, the unmanned aerial vehicle performs routing inspection by using a planned routing inspection line in the 3D map model, the 3D map model tracks the position information of the unmanned aerial vehicle in real time, and a routing inspection point arrival prompt is sent according to the position information of the unmanned aerial vehicle;
and 4, after the unmanned aerial vehicle reaches the inspection point, extracting an image sample corresponding to the inspection point from the 3D map model, acquiring a field image according to the index information of the image sample, extracting actual index information of the acquired field image and checking the index information of the image sample, completing inspection of the inspection point if the acquired field image is matched with the actual index information, and acquiring the image again until the acquired field image is matched if the acquired field image is not matched with the actual index information.
The scheme also comprises the following processes: the index information of the image sample comprises one or more index information of image pixel requirements, focusing point, shooting range and shooting angle. By setting index information for the image sample, the image shot on site is convenient to check, which is equivalent to presetting a standard for the image shot on site to ensure that the subsequently collected on-site image meets the requirement.
The scheme also comprises the following processes: the inspection task comprises an inspection point list, and the inspection point list comprises electric network line road sign marks where the inspection points are located and position information of the inspection points on the electric network lines. The inspection point list helps to find the position of the inspection point in the 3D map model and helps to plan the inspection line. Make unmanned aerial vehicle can plan out best flight route according to the concrete position of flight in real time, improve and patrol and examine efficiency.
The scheme also comprises the following processes: the unmanned aerial vehicle receives the inspection task and loads the inspection task into the 3D map model, and the specific steps of performing inspection route planning according to the inspection task in the 3D map model comprise:
loading the inspection task into a 3D map model, and extracting the electric network line landmark marks of the inspection points in the inspection task and the position information of the inspection points on the electric network lines; determining a power grid line where the inspection point is located in the 3D map model according to the power grid line landmark mark where the inspection point is located; determining the position of the inspection point in the 3D map model according to the position information on the power grid line of the inspection point and marking; and planning the routing inspection line in the 3D map model according to the marked routing inspection point.
And setting and sending a patrol task, helping to find the position of a patrol point in the 3D map model, and helping to plan a patrol route. Make unmanned aerial vehicle can plan out best flight route according to the concrete position of flight in real time, improve and patrol and examine efficiency.
The scheme also comprises the following processes: and when the acquired index information of the live image and the index information of the image sample are checked, extracting pixel information from the live image to compare the image pixel requirements. Check the index information of field image and image sample, can ensure to gather that the image is clear and the image shooting angle meets the requirements, unmanned aerial vehicle need not to carry out the inspection to reach standard to the backstage with the picture remote transmission that the scene was shot simultaneously, has guaranteed the high quality and the requirement up to standard of gathering the field image when promoting unmanned aerial vehicle's the efficiency of patrolling and examining.
The scheme also comprises the following processes: and when checking the index information of the acquired field image and the index information of the image sample, acquiring the shooting range and the shooting angle of the field image by extracting the contour information of the inspection point object from the field image, and comparing according to the obtained shooting range and the obtained shooting angle of the field image. Check the index information of field image and image sample, can ensure to gather that the image is clear and the image shooting angle meets the requirements, unmanned aerial vehicle need not to carry out the inspection to reach standard to the backstage with the picture remote transmission that the scene was shot simultaneously, has guaranteed the high quality and the requirement up to standard of gathering the field image when promoting unmanned aerial vehicle's the efficiency of patrolling and examining.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, 3D images, inspection points and image samples of the inspection points are combined with a facility layout map of a power grid line, a 3D map model is constructed in advance and is loaded in an unmanned aerial vehicle in advance, so that a flight line is stable; and acquiring a field image according to the index information of the image sample during inspection, extracting actual index information from the acquired field image and checking the actual index information with the index information of the image sample, completing inspection of the inspection point if the actual index information is matched with the index information of the image sample, and acquiring the image again if the actual index information is not matched with the index information of the image sample, so that the image with high image quality and meeting the analysis requirement is obtained.
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Fig. 1 is a flowchart of an unmanned aerial vehicle inspection method applied to a power grid according to an embodiment of the present invention.
Detailed Description
The drawings are only for purposes of illustration and are not to be construed as limiting the invention. For a better understanding of the following embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
Example 1
As shown in fig. 1, the method for routing inspection by an unmanned aerial vehicle applied to a power grid in the embodiment includes the following specific steps:
s1, before the unmanned aerial vehicle patrols and examines, a 3D map model of power grid line patrols and examines is established, wherein the 3D map model is constructed by combining a 3D image, an inspection point and an image sample of the inspection point with a facility layout map of the power grid line; extracting position information of each inspection point from a facility layout diagram of the power grid line, carrying a 3D high-definition scanner on the 3D image through an unmanned aerial vehicle, scanning the power grid line in advance to obtain the 3D image, and extracting an image sample of the inspection point required by the scanning by using the 3D image obtained by scanning; the specific building method of the 3D map model can be that the high-definition 3D image obtained by scanning is firstly led into modeling software to build the 3D map, then the facility layout of the power grid line is led into the modeling software, the inspection point in the 3D map is found according to the position information of the inspection point in the facility layout of the power grid line, the inspection point in the 3D map and the position of the inspection point in the facility layout of the power grid line are bound, and a specific mark number is set for each power grid line in the facility layout of the power grid line in the modeling software. Meanwhile, establishing a respective inspection element set for each inspection point in the 3D map model, wherein the inspection element set comprises image samples at different angles, and each image sample comprises one or more index information such as image pixel requirements, focus, shooting range and shooting angle; and loading the 3D map model in an unmanned aerial vehicle.
S2, after receiving the inspection task sent by the ground terminal, the unmanned aerial vehicle loads the inspection task into a 3D map model, wherein the inspection task comprises an inspection point list, and the inspection point list comprises electric network line landmark marks where the inspection points are located and position information of the inspection points on a power network line; the unmanned aerial vehicle loads the inspection task into the 3D map model, identifies the positions of all inspection points in the 3D map model, extracts electric network line sign marks of the inspection points in the inspection task and position information of the inspection points on the electric network lines, determines the electric network lines of the inspection points in the 3D map model according to the electric network line sign marks of the inspection points, determines the specific positions of the electric network lines of the inspection points in the 3D map model according to the position information on the electric network lines of the inspection points, marks the specific positions, plans the inspection lines in the 3D map model according to the marked inspection points, and loads the planned lines into the 3D map model.
And S3, the unmanned aerial vehicle patrols and examines by utilizing the planned patrol and examine line in the 3D map model, the 3D map model tracks the position information of the unmanned aerial vehicle in real time, and sends out a patrol and examine point arrival prompt according to the position information of the unmanned aerial vehicle, and the unmanned aerial vehicle starts to execute a patrol and examine task according to the arrival prompt.
S4, after the unmanned aerial vehicle reaches the inspection point, extracting an image sample corresponding to the inspection point from the 3D map model, acquiring a field image according to index information of the image sample, extracting actual index information of the acquired field image and checking the index information of the image sample, completing inspection of the inspection point if the field image is matched with the image sample, and acquiring the image again until the field image is matched if the field image is not matched with the image sample; the checking mode may be directly extracting the pixel information of the live image, or may be to determine the shooting range and angle of the live image by extracting the contour information using the inspection point object. Specifically, when the index information of the acquired live image and the index information of the image sample are checked, the pixel information is extracted from the live image and the pixel information of the image sample is checked according to the image pixel requirement. When the index information of the acquired field image and the index information of the image sample are checked, the contour information of the inspection point object is extracted from the field image to acquire the field image shooting range and the shooting angle, and the index information is checked according to the acquired field image shooting range and the acquired shooting angle and the image sample shooting range and the acquired shooting angle. The index information of the image sample includes other index information such as the focus in addition to the image pixel requirement, the shooting range, and the shooting angle. The index information of the image sample can be increased or reduced according to actual needs, and the checking mode of the image sample can be optimized along with the upgrading of the technology.
In the S1 and the S2, the 3D map model for power grid line inspection is pre-established, the 3D map model is loaded in the unmanned aerial vehicle, and the unmanned aerial vehicle performs the unmanned aerial vehicle inspection method for line planning, so that the dependence of the unmanned aerial vehicle on remote and radar navigation in the flight process is reduced, and the stability of the unmanned aerial vehicle in the flight process is greatly improved.
In the S3 and the S4, the index information of the image sample acquired in advance is checked with the index information of the image actually shot on site, the inspection of the inspection point is finished if the index information is matched, and the image is acquired again until the index information is matched if the index information is not matched, so that the acquired image is clear and the image shooting angle meets the requirements; meanwhile, the unmanned aerial vehicle does not need to remotely transmit the pictures shot on site to the background for standard-reaching inspection, and the high quality and standard-reaching requirements of the collected site images are guaranteed while the inspection efficiency of the unmanned aerial vehicle is improved.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, and are not intended to limit the specific embodiments of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention claims should be included in the protection scope of the present invention claims.
Claims (7)
1. An unmanned aerial vehicle inspection method applied to a power grid is characterized by comprising the following steps:
step 1, pre-establishing a 3D map model for power grid line inspection, and loading the 3D map model in an unmanned aerial vehicle; the 3D map model is constructed by combining a 3D image of the power grid line, a patrol point and an image sample of the patrol point with a facility layout map of the power grid line; carrying a 3D high-definition scanner on the power grid line 3D image through an unmanned aerial vehicle, and scanning the power grid line in advance to obtain the 3D image; establishing a respective inspection element set for each inspection point in the 3D map model, wherein the inspection element sets comprise inspection point image samples, and index information is preset for the inspection point image samples; the index information of the image sample comprises one or more index information of image pixel requirements, focusing point, shooting range and shooting angle;
step 2, the unmanned aerial vehicle receives the routing inspection task and loads the routing inspection task into the 3D map model, routing inspection lines are planned according to the routing inspection task in the 3D map model, and the planned routing inspection lines are loaded into the 3D map model;
step 3, the unmanned aerial vehicle performs inspection by using the planned inspection line in the 3D map model, the 3D map model tracks the position information of the unmanned aerial vehicle in real time, and sends out an inspection point arrival prompt according to the position information of the unmanned aerial vehicle;
and 4, after the unmanned aerial vehicle reaches the inspection point, extracting an image sample corresponding to the inspection point from the 3D map model, acquiring a field image according to index information of the image sample, extracting actual index information of the acquired field image and checking the index information of the image sample, completing inspection of the inspection point if the field image is matched, and acquiring the image again until the field image is matched if the field image is not matched.
2. The unmanned aerial vehicle inspection method according to claim 1, wherein the position information of each inspection point is extracted from a facility layout of a power grid line.
3. The unmanned aerial vehicle inspection method applied to the power grid according to claim 2, wherein the image samples of the inspection points are extracted from the scanned 3D images of the power grid lines according to the position information of the inspection points.
4. The unmanned aerial vehicle inspection method applied to the power grid according to claim 3, wherein the inspection task comprises an inspection point list, and the inspection point list comprises power grid line landmark marks where the inspection points are located and position information of the inspection points on a power grid line.
5. The unmanned aerial vehicle inspection method applied to the power grid according to claim 4, wherein the unmanned aerial vehicle receives the inspection task and loads the inspection task into the 3D map model, and the specific steps of performing inspection route planning according to the inspection task in the 3D map model comprise:
loading the inspection task into a 3D map model, and extracting the electric network line landmark marks of the inspection points in the inspection task and the position information of the inspection points on the electric network lines;
determining a power grid line where the inspection point is located in the 3D map model according to the power grid line landmark mark where the inspection point is located; and planning a routing inspection route in the 3D map model according to the marked routing inspection points.
6. The unmanned aerial vehicle inspection method applied to the power grid according to claim 5, wherein when the acquired index information of the live image and the index information of the image sample are checked, pixel information is extracted from the live image to compare image pixel requirements.
7. The unmanned aerial vehicle inspection method applied to the power grid according to any one of claims 1 to 6, wherein when checking the index information of the acquired live image and the index information of the image sample, the shooting range and the shooting angle of the live image are obtained by extracting the outline information of the inspection point object from the live image, and the comparison is performed according to the obtained shooting range and the obtained shooting angle of the live image.
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| CN112989859B (en) * | 2021-05-08 | 2021-09-10 | 国网江西省电力有限公司电力科学研究院 | Distribution line equipment asset modeling system and method based on unmanned aerial vehicle RFID identification |
| CN113867405A (en) * | 2021-11-09 | 2021-12-31 | 广东电网有限责任公司江门供电局 | Transmission line unmanned aerial vehicle inspection method and system based on 5G network return |
| CN116073520B (en) * | 2023-03-06 | 2024-01-26 | 国网四川省电力公司电力科学研究院 | Power grid inspection method and device, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103941746A (en) * | 2014-03-29 | 2014-07-23 | 国家电网公司 | System and method for processing unmanned aerial vehicle polling image |
| CN103941745A (en) * | 2014-03-07 | 2014-07-23 | 国家电网公司 | Movable substation and working method for unmanned aerial vehicle electric transmission line inspection |
| CN109213189A (en) * | 2018-07-19 | 2019-01-15 | 安徽共生物流科技有限公司 | A kind of unmanned plane inspection system and movement determination method |
| CN110398982A (en) * | 2019-06-21 | 2019-11-01 | 万翼科技有限公司 | A kind of method for inspecting and system of unmanned plane |
| CN111258331A (en) * | 2020-01-20 | 2020-06-09 | 北京拓维思科技有限公司 | Unmanned aerial vehicle power line operation and maintenance system and method |
-
2020
- 2020-07-22 CN CN202010710962.1A patent/CN112000124B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103941745A (en) * | 2014-03-07 | 2014-07-23 | 国家电网公司 | Movable substation and working method for unmanned aerial vehicle electric transmission line inspection |
| CN103941746A (en) * | 2014-03-29 | 2014-07-23 | 国家电网公司 | System and method for processing unmanned aerial vehicle polling image |
| CN109213189A (en) * | 2018-07-19 | 2019-01-15 | 安徽共生物流科技有限公司 | A kind of unmanned plane inspection system and movement determination method |
| CN110398982A (en) * | 2019-06-21 | 2019-11-01 | 万翼科技有限公司 | A kind of method for inspecting and system of unmanned plane |
| CN111258331A (en) * | 2020-01-20 | 2020-06-09 | 北京拓维思科技有限公司 | Unmanned aerial vehicle power line operation and maintenance system and method |
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