CN110879601A - Unmanned aerial vehicle inspection method for unknown fan structure - Google Patents
Unmanned aerial vehicle inspection method for unknown fan structure Download PDFInfo
- Publication number
- CN110879601A CN110879601A CN201911240805.2A CN201911240805A CN110879601A CN 110879601 A CN110879601 A CN 110879601A CN 201911240805 A CN201911240805 A CN 201911240805A CN 110879601 A CN110879601 A CN 110879601A
- Authority
- CN
- China
- Prior art keywords
- point
- aerial vehicle
- unmanned aerial
- inspection
- coordinate
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000007689 inspection Methods 0.000 title claims abstract description 109
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 8
- 230000003287 optical effect Effects 0.000 claims description 12
- 239000011159 matrix material Substances 0.000 claims description 6
- 238000002372 labelling Methods 0.000 claims description 3
- 238000013519 translation Methods 0.000 claims description 3
- 230000036544 posture Effects 0.000 description 6
- 230000007547 defect Effects 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000004576 sand Substances 0.000 description 2
- 208000025274 Lightning injury Diseases 0.000 description 1
- 238000005299 abrasion Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Automation & Control Theory (AREA)
- Multimedia (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses an unmanned aerial vehicle inspection method for an unknown fan structure, which comprises the following steps: s1, remotely shooting the whole fan at multiple angles, wherein the fan is contained in the picture and close to the central part of the picture, and processing the picture to acquire coordinate information of a key inspection point; s2, calculating coordinate information of routing inspection points for equally dividing the blades by using the acquired coordinate information of the key routing inspection points; s3, calculating the coordinate information of the required cruise point by using the coordinate information of the patrol point to generate a flight path; s4, the unmanned aerial vehicle takes off and arrives at the cruise point, and the position and the attitude of the unmanned aerial vehicle are adjusted by utilizing coordinate information of the cruise point so as to enable the unmanned aerial vehicle to be over against a target point; and S5, carrying out target recognition on the inspection point before the inspection point is photographed, adjusting the posture of the holder again, and enabling the inspection point to be close to the center of the photo as much as possible. The invention can enable the inspection point to be close to the center of the photo as much as possible, and the reliability of autonomous inspection of the unmanned aerial vehicle is higher while the efficiency is improved.
Description
Technical Field
The invention relates to blade inspection of a fan, in particular to an unmanned aerial vehicle inspection method for unknown structural information of the fan.
Background
The blade is an important component of the wind generating set, and because the environment of the fan is severe, the blade is damaged by natural factors such as wind, sand, rain, snow, thunder and lightning when running in the severe environment, so that the defects of surface shedding, sand holes, lightning stroke, blade edge abrasion and the like are formed, and the blade needs to be periodically checked and maintained to prevent accidents caused by the defects. The traditional blade inspection means is manual detection by utilizing a telescope and a rope to vertically drop, and has the defects of large danger coefficient, low efficiency, high cost and the like. With the gradual development of the wind power market and the successive appearance of large wind turbines, the length of the blades is also increased from the original 30-40m to 60-70m, generally, the service life of the wind turbines is 20 years, and the increase of the weight of the blades and the increase of the length of the blades bring challenges to the maintenance of the blades.
Along with the development of the technology, the unmanned aerial vehicle is increasingly widely applied to inspection work. The unmanned aerial vehicle has the characteristics of hovering, low-speed flying, simplicity and convenience in operation, convenience in maintenance, high cost performance and the like, so that the unmanned aerial vehicle is applied to blade detection, and the working efficiency is greatly improved. In the existing method, an operator observes the surface state of the blade through a real-time image displayed by a ground station, and remotely operates the unmanned aerial vehicle to acquire pictures of all angles for further detailed examination when a suspicious point is found, so that the unmanned aerial vehicle needs to be continuously controlled and adjusted to be convenient to shoot, great manpower needs to be invested, the control error is large, and the manpower cost is high. And under the condition that the structure of the fan is known, the method for realizing autonomous inspection of the unmanned aerial vehicle by using the fan structure information to perform algorithm optimization can reduce the labor cost to a great extent, has higher efficiency, but does not have an efficient inspection method under the condition that the structure of the fan is unknown.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides the unmanned aerial vehicle inspection method with unknown fan structure information, so that the unmanned aerial vehicle autonomous inspection reliability is higher while the efficiency is improved.
The purpose of the invention is realized by the following technical scheme: an unmanned aerial vehicle inspection method for an unknown fan structure comprises the following steps:
s1, remotely shooting the whole fan at multiple angles, wherein the fan is contained in the picture and close to the central part of the picture, and processing the picture to acquire coordinate information of a key inspection point;
s2, calculating coordinate information of routing inspection points for equally dividing the blades by using the acquired coordinate information of the key routing inspection points;
s3, calculating the coordinate information of the required cruise point by using the coordinate information of the patrol point to generate a flight path;
s4, the unmanned aerial vehicle takes off and arrives at the cruise point, and the position and the attitude of the unmanned aerial vehicle are adjusted by utilizing coordinate information of the cruise point so as to enable the unmanned aerial vehicle to be over against a target point;
and S5, carrying out target recognition on the inspection point before the inspection point is photographed, adjusting the posture of the holder again, and enabling the inspection point to be close to the center of the photo as much as possible.
Further, the key inspection point comprises three blade tips and a hub center of the fan.
Further, the step S1 includes the following sub-steps:
s101, remotely shooting the whole fan at multiple angles to obtain multiple pictures, wherein the fan in each picture is completely contained in the picture and is close to the center of the picture;
s102, for each shot photo image, acquiring a pixel point coordinate P of a key inspection point in the imageuv(u, v), the camera's internal reference matrix K; recording longitude and latitude information of the airplane and attitude angle information of the camera during photographing, and determining a rotation matrix R from a camera coordinate system to a geodetic coordinate systemcw(ii) a Setting a reference origin of a northeast coordinate system, and calculating the coordinate t (X) of the photographing point in the coordinate system0,Y0,Z0) Recording the coordinates of the cameraDepth Z between the distance of the lower shooting point and the inspection pointc；
S103, for any key inspection point, deriving a normalized coordinate P of the inspection point in a camera coordinate systemcAnd calculating the theoretical three-dimensional coordinate P of the key inspection pointw(Xw,Yw,Zw)：
Pc＝K-1ZcPuv
Further, in step S102, obtaining the coordinates of the pixel points of the key inspection point in the image includes the following two ways:
firstly, after the image is shot, exporting the image from a memory card for labeling to acquire pixel coordinates;
and secondly, marking the real-time returned video image to acquire pixel coordinates.
Further, the step S2 includes:
the number of the subsection sections of the line segment between the center of the hub and each blade tip point is preset, and after the coordinate of the key routing inspection point of the fan is obtained, the coordinate of the routing inspection point is obtained by equally dividing the line segment between the blade tip point and the center of the hub.
Further, the step S3 includes:
according to the routing inspection requirement, presetting constraint conditions between a routing inspection point and a routing inspection point, wherein the constraint conditions comprise the distance between a cruise point and the routing inspection point and the direction of the cruise point relative to the routing inspection point; the inspection point refers to a target point needing inspection on the electric power tower, and the cruising point is the position of the unmanned aerial vehicle when the unmanned aerial vehicle takes a picture;
and calculating the coordinate information of the required cruise point according to the patrol point and the constraint condition, and generating the flight path.
Further, the step S4 includes:
control unmanned aerial vehicle flies to patrolling and examining near the point, according to unmanned aerial vehicle's the gesture and the position this moment, adjusts the gesture to unmanned aerial vehicle just to patrolling and examining the direction of point, utilizes the position at unmanned aerial vehicle place in the space and the coordinate information who patrols and examines the point to obtain a direction vector in the space, wherein, need adjust corresponding driftage and every single move angle when adjusting the gesture.
Further, the step S5 includes the following sub-steps:
s501, carrying out target identification on the inspection point before photographing at the inspection point;
s502, carrying out online image processing on a photo obtained by photographing at a cruising point, identifying a blade part needing to be inspected, and adjusting the posture of a camera holder to enable the camera holder to be positioned at the center of the photo;
s503, setting PwIs the actual target point geographic coordinate position, O is the optical center, PoIs that the optical center is to P along the Z axis of the camera coordinate systemwThe foot of the plane is vertical, P is PwAnd PoIntersecting the u-axis and the v-axis along the camera coordinate system; zcIs PwThe perpendicular distance from the plane to the optical center, u' being PwAnd PoActual geographical distance in the direction of the u-axis in the camera coordinate system, v' being PwAnd PoActual geographic distance along the v-axis direction under the camera coordinate system; d is PwDistance from O; d is the distance between P and O;
calculated in the front PwThereafter, the geographic coordinates t and R of the optical center OcwWhen known, then:
D＝|t-Pw|，
Pc＝Rcw(Pw-t)
calculated as ZcWherein f isxIs combined by α f, fyIs combined by β f, f is the focal length of the camera, α is the zoom factor of the pixel coordinate on the u and v coordinate axes, [ c ]x,cy]TIs the amount of translation of the origin;
then according to the following steps:
obtaining the transverse length under the u 'actual camera coordinate system and the length and the longitudinal length under the v' actual camera coordinate system;
from ZcPythagorean theorem with u' to obtain
Obtain the required yaw angle
Obtaining the required pitch angle from D, v' and D
And adjusting the attitude information of the cruise point in the track according to the calculated yaw and pitch angles.
The invention has the beneficial effects that: the invention can adjust the pose of the unmanned aerial vehicle to ensure that the unmanned aerial vehicle is over against a target point under the condition of unknown fan structure; target identification is once carried out to the point of patrolling and examining before the place is patrolled and navigated the navigation point and is taken a picture, and the cloud platform gesture is adjusted once more, will patrol and examine the point and be close to the photo center as far as possible, in the lifting efficiency, make unmanned aerial vehicle independently patrol and examine the reliability stronger.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a schematic diagram of attitude adjustment of the drone;
fig. 3 is a schematic diagram of the adjustment of the posture of the pan/tilt head.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in fig. 1, an unmanned aerial vehicle inspection method for an unknown fan structure includes the following steps:
s1, remotely shooting the whole fan at multiple angles, wherein the fan is contained in the picture and close to the central part of the picture, and processing the picture to acquire coordinate information of a key inspection point;
s2, calculating coordinate information of routing inspection points for equally dividing the blades by using the acquired coordinate information of the key routing inspection points;
s3, calculating the coordinate information of the required cruise point by using the coordinate information of the patrol point to generate a flight path;
s4, the unmanned aerial vehicle takes off and arrives at the cruise point, and the position and the attitude of the unmanned aerial vehicle are adjusted by utilizing coordinate information of the cruise point so as to enable the unmanned aerial vehicle to be over against a target point;
and S5, carrying out primary target identification on the inspection points before the inspection points are photographed, adjusting the posture of the holder again, enabling the inspection points to be close to the center of the photo as much as possible, and carrying out unmanned aerial vehicle autonomous inspection according to the adjusted flight path and the postures of the holders of the inspection points in the flight path so as to improve inspection precision.
In the embodiment of the application, the key routing inspection points comprise three blade tips and a hub center of the fan; the step S1 includes the following sub-steps:
s101, remotely shooting the whole fan at multiple angles to obtain multiple pictures, wherein the fan in each picture is completely contained in the picture and is close to the center of the picture;
s102, for each shot photo image, acquiring a pixel point coordinate P of a key inspection point in the imageuv(u, v), the camera's internal reference matrix K; recording longitude and latitude information of the airplane and attitude angle information of the camera during photographing, and determining a rotation matrix R from a camera coordinate system to a geodetic coordinate systemcw(ii) a Setting a reference origin of a northeast coordinate system, and calculating the coordinate t (X) of the photographing point in the coordinate system0,Y0,Z0) Recording the depth Z between the shooting point and the inspection point under the coordinate system of the camerac；
S103, for any key inspection point, deriving a normalized coordinate P of the inspection point in a camera coordinate systemcAnd calculating the theoretical three-dimensional coordinate P of the key inspection pointw(Xw,Yw,Zw)：
Pc＝K-1ZcPuv
Further, in step S102, obtaining the coordinates of the pixel points of the key inspection point in the image includes the following two ways:
firstly, after the image is shot, exporting the image from a memory card for labeling to acquire pixel coordinates;
and secondly, marking the real-time returned video image to acquire pixel coordinates.
In an embodiment of the present application, the step S2 includes:
presetting the number of segmentation segments of a line segment between the center of the hub and each blade tip point, obtaining the coordinates of a key routing inspection point of the fan, and then obtaining the coordinates of the routing inspection point by equally dividing the line segment between the blade tip point and the center of the hub; during specific implementation, the contact ratio of the two photos can be adjusted according to the scene, and the corresponding flight distance can be adjusted.
Further, the step S3 includes:
according to the routing inspection requirement, presetting constraint conditions between a routing inspection point and a routing inspection point, wherein the constraint conditions comprise the distance between a cruise point and the routing inspection point and the direction of the cruise point relative to the routing inspection point; the inspection point refers to a target point needing inspection on the electric power tower, and the cruising point is the position of the unmanned aerial vehicle when the unmanned aerial vehicle takes a picture;
and calculating the coordinate information of the required cruise point according to the patrol point and the constraint condition, and generating the flight path.
In an embodiment of the present application, the step S4 includes:
controlling the unmanned aerial vehicle to fly to the vicinity of the inspection point, adjusting the attitude to the direction in which the unmanned aerial vehicle is over against the inspection point according to the attitude and the position of the unmanned aerial vehicle at the moment, and acquiring a direction vector in the space by using the position of the unmanned aerial vehicle in the space and the coordinate information of the inspection point, wherein corresponding yaw and pitch angles need to be adjusted when the attitude is adjusted; as shown in fig. 2, in this embodiment,
is the direction vector of the drone at the moment,
the direction vector of the connecting line of the unmanned aerial vehicle point and the patrol point.
The step S5 includes the following sub-steps:
s501, carrying out target identification on the inspection point before photographing at the inspection point; because the first time a picture is used to include all the patrol inspection points, corresponding errors exist, and because the operation is performed by using the points, the last picture taken may not completely include the object to be shot, and because the leaves are wide and long, an operation similar to object recognition is feasible;
s502, carrying out online image processing on a photo obtained by photographing at a cruising point, identifying a blade part needing to be inspected, and adjusting the posture of a camera holder to enable the camera holder to be positioned at the center of the photo; therefore, the method is beneficial to the post-inspection photo processing and the inspection stability;
s503. As shown in figure 3, set PwIs the actual target point geographic coordinate position, O is the optical center, PoIs that the optical center is to P along the Z axis of the camera coordinate systemwThe foot of the plane is vertical, P is PwAnd PoIntersecting the u-axis and the v-axis along the camera coordinate system; zcIs PwThe perpendicular distance from the plane to the optical center, u' being PwAnd PoActual geographical distance in the direction of the u-axis in the camera coordinate system, v' being PwAnd PoActual geographic distance along the v-axis direction under the camera coordinate system; d is PwDistance from O; d is the distance between P and O;
calculated in the front PwThereafter, the geographic coordinates t and R of the optical center OcwWhen known, then:
D＝|t-Pw|，
Pc＝Rcw(Pw-t)
calculated as ZcWherein f isxIs combined by α f, fyIs combined by β f, f is the focal length of the camera, α is the zoom factor of the pixel coordinate on the u and v coordinate axes, [ c ]x,cy]TIs the amount of translation of the origin;
then according to the following steps:
obtaining the transverse length under the u 'actual camera coordinate system and the length and the longitudinal length under the v' actual camera coordinate system;
from ZcPythagorean theorem with u' to obtain
Obtain the required yaw angle
Obtaining the required pitch angle from D, v' and D
And adjusting the attitude information of the cruise point in the track according to the calculated yaw and pitch angles.
The invention can adjust the pose of the unmanned aerial vehicle to ensure that the unmanned aerial vehicle is over against a target point under the condition of unknown fan structure; target identification is once carried out to the point of patrolling and examining before the place is patrolled and navigated the navigation point and is taken a picture, and the cloud platform gesture is adjusted once more, will patrol and examine the point and be close to the photo center as far as possible, in the lifting efficiency, make unmanned aerial vehicle independently patrol and examine the reliability stronger.
The foregoing is a preferred embodiment of the present invention, it is to be understood that the invention is not limited to the form disclosed herein, but is not to be construed as excluding other embodiments, and is capable of other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. The utility model provides an unmanned aerial vehicle method of patrolling and examining to unknown fan structure which characterized in that: the method comprises the following steps:
s1, remotely shooting the whole fan at multiple angles, wherein the fan is contained in the picture and close to the central part of the picture, and processing the picture to acquire coordinate information of a key inspection point;
s2, calculating coordinate information of routing inspection points for equally dividing the blades by using the acquired coordinate information of the key routing inspection points;
s3, calculating the coordinate information of the required cruise point by using the coordinate information of the patrol point to generate a flight path;
s4, the unmanned aerial vehicle takes off and arrives at the cruise point, and the position and the attitude of the unmanned aerial vehicle are adjusted by utilizing coordinate information of the cruise point so as to enable the unmanned aerial vehicle to be over against a target point;
and S5, carrying out target recognition on the inspection point before the inspection point is photographed, adjusting the posture of the holder again, and enabling the inspection point to be close to the center of the photo as much as possible.
2. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the key inspection point comprises three blade tips of the fan and a hub center.
3. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the step S1 includes the following sub-steps:
s101, remotely shooting the whole fan at multiple angles to obtain multiple pictures, wherein the fan in each picture is completely contained in the picture and is close to the center of the picture;
s102, for each shot photo image, acquiring a key patrolCoordinate P of pixel point of inspection point in imageuv(u, v), the camera's internal reference matrix K; recording longitude and latitude information of the airplane and attitude angle information of the camera during photographing, and determining a rotation matrix R from a camera coordinate system to a geodetic coordinate systemcw(ii) a Setting a reference origin of a northeast coordinate system, and calculating the coordinate t (X) of the photographing point in the coordinate system0,Y0,Z0) Recording the depth Z between the shooting point and the inspection point under the coordinate system of the camerac；
S103, for any key inspection point, deriving a normalized coordinate P of the inspection point in a camera coordinate systemcAnd calculating the theoretical three-dimensional coordinate P of the key inspection pointw(Xw,Yw,Zw)：
Pc＝K-1ZcPuv
4. The unmanned aerial vehicle inspection method for unknown fan structures of claim 3, wherein: in step S102, obtaining the coordinates of the pixel points of the key inspection point in the image includes the following two ways:
firstly, after the image is shot, exporting the image from a memory card for labeling to acquire pixel coordinates;
and secondly, marking the real-time returned video image to acquire pixel coordinates.
5. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the step S2 includes:
the number of the subsection sections of the line segment between the center of the hub and each blade tip point is preset, and after the coordinate of the key routing inspection point of the fan is obtained, the coordinate of the routing inspection point is obtained by equally dividing the line segment between the blade tip point and the center of the hub.
6. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the step S3 includes:
according to the routing inspection requirement, presetting constraint conditions between a routing inspection point and a routing inspection point, wherein the constraint conditions comprise the distance between a cruise point and the routing inspection point and the direction of the cruise point relative to the routing inspection point; the inspection point refers to a target point needing inspection on the electric power tower, and the cruising point is the position of the unmanned aerial vehicle when the unmanned aerial vehicle takes a picture;
and calculating the coordinate information of the required cruise point according to the patrol point and the constraint condition, and generating the flight path.
7. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the step S4 includes:
control unmanned aerial vehicle flies to patrolling and examining near the point, according to unmanned aerial vehicle's the gesture and the position this moment, adjusts the gesture to unmanned aerial vehicle just to patrolling and examining the direction of point, utilizes the position at unmanned aerial vehicle place in the space and the coordinate information who patrols and examines the point to obtain a direction vector in the space, wherein, need adjust corresponding driftage and every single move angle when adjusting the gesture.
8. The unmanned aerial vehicle inspection method for unknown fan structures of claim 1, wherein: the step S5 includes the following sub-steps:
s501, carrying out target identification on the inspection point before photographing at the inspection point;
s502, carrying out online image processing on a photo obtained by photographing at a cruising point, identifying a blade part needing to be inspected, and adjusting the posture of a camera holder to enable the camera holder to be positioned at the center of the photo;
s503, setting PwIs the actual target point geographic coordinate position, O is the optical center, PoIs that the optical center is to P along the Z axis of the camera coordinate systemwThe foot of the plane is vertical, P is PwAnd PoIntersecting the u-axis and the v-axis along the camera coordinate system; zcIs PwThe perpendicular distance from the plane to the optical center, u' being PwAnd PoAlong the direction of the u axis under the camera coordinate systemV' is PwAnd PoActual geographic distance along the v-axis direction under the camera coordinate system; d is PwDistance from O; d is the distance between P and O;
calculated in the front PwThereafter, the geographic coordinates t and R of the optical center OcwWhen known, then:
calculated as ZcWherein f isxIs combined by α f, fyIs combined by β f, f is the focal length of the camera, α is the zoom factor of the pixel coordinate on the u and v coordinate axes, [ c ]x,cy]TIs the amount of translation of the origin;
then according to the following steps:
obtaining the transverse length under the u 'actual camera coordinate system and the length and the longitudinal length under the v' actual camera coordinate system;
from ZcPythagorean theorem with u' to obtain
Obtain the required yaw angle
Obtaining the required pitch angle from D, v' and D
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911240805.2A CN110879601B (en) | 2019-12-06 | 2019-12-06 | Unmanned aerial vehicle inspection method for unknown fan structure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911240805.2A CN110879601B (en) | 2019-12-06 | 2019-12-06 | Unmanned aerial vehicle inspection method for unknown fan structure |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110879601A true CN110879601A (en) | 2020-03-13 |
| CN110879601B CN110879601B (en) | 2021-05-18 |
Family
ID=69730450
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911240805.2A Active CN110879601B (en) | 2019-12-06 | 2019-12-06 | Unmanned aerial vehicle inspection method for unknown fan structure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110879601B (en) |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112102395A (en) * | 2020-11-09 | 2020-12-18 | 广东科凯达智能机器人有限公司 | Autonomous inspection method based on machine vision |
| CN112164015A (en) * | 2020-11-30 | 2021-01-01 | 中国电力科学研究院有限公司 | Monocular vision autonomous inspection image acquisition method and device and power inspection unmanned aerial vehicle |
| CN112230235A (en) * | 2020-09-24 | 2021-01-15 | 北京京能能源技术研究有限责任公司 | Fan blade positioning method and system, computer equipment and readable storage medium |
| CN112711267A (en) * | 2020-04-24 | 2021-04-27 | 江苏方天电力技术有限公司 | Unmanned aerial vehicle autonomous inspection method based on RTK high-precision positioning and machine vision fusion |
| CN112905955A (en) * | 2021-01-27 | 2021-06-04 | 天津航天中为数据***科技有限公司 | Fan front and back autonomous inspection planning method |
| CN112947511A (en) * | 2021-01-25 | 2021-06-11 | 北京京能能源技术研究有限责任公司 | Method for inspecting fan blade by unmanned aerial vehicle |
| CN113050693A (en) * | 2021-03-26 | 2021-06-29 | 厦门理工学院 | Unmanned aerial vehicle inspection method, device and equipment for wind power blade detection |
| CN113177918A (en) * | 2021-04-28 | 2021-07-27 | 上海大学 | Intelligent and accurate inspection method and system for electric power tower by unmanned aerial vehicle |
| CN113885580A (en) * | 2021-11-17 | 2022-01-04 | 国能定边新能源有限公司 | Route planning method and system for realizing automatic inspection of fan based on unmanned aerial vehicle |
| CN114217641A (en) * | 2021-10-29 | 2022-03-22 | 国网河南省电力公司中牟县供电公司 | Unmanned aerial vehicle power transmission and transformation equipment inspection method and system in non-structural environment |
| CN114661062A (en) * | 2022-02-22 | 2022-06-24 | 广州中科云图智能科技有限公司 | Unmanned aerial vehicle-based power transmission line inspection method, device and equipment |
| CN115097867A (en) * | 2022-08-23 | 2022-09-23 | 无锡海纳智能科技有限公司 | Method for determining unmanned aerial vehicle shooting attitude under fan inspection route |
| CN115480589A (en) * | 2022-09-06 | 2022-12-16 | 中科云尚(南京)智能技术有限公司 | Method and system for generating fan inspection route based on unmanned aerial vehicle |
| CN115951718A (en) * | 2023-03-14 | 2023-04-11 | 风脉能源（武汉）股份有限公司 | Fan blade inspection local dynamic path planning method and system based on unmanned aerial vehicle |
| CN116206094A (en) * | 2023-04-28 | 2023-06-02 | 尚特杰电力科技有限公司 | Fan blade angle measuring method, device and system and electronic equipment |
| CN116839595A (en) * | 2023-09-01 | 2023-10-03 | 北京宝隆泓瑞科技有限公司 | Method for creating unmanned aerial vehicle route |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104406762A (en) * | 2014-11-28 | 2015-03-11 | 国家电网公司 | Method for testing wind loading rating of unmanned helicopter inspection system for inspecting overhead transmission lines |
| CN206035727U (en) * | 2016-07-18 | 2017-03-22 | 中能电力科技开发有限公司 | Fan blade unmanned aerial vehicle intelligence system of patrolling and examining |
| CN109213197A (en) * | 2018-09-11 | 2019-01-15 | 成都优艾维智能科技有限责任公司 | A kind of autonomous method for inspecting of unmanned plane for single time tangent tower of direct current |
| US20190049962A1 (en) * | 2017-08-10 | 2019-02-14 | RavenOPS, Inc. | Autonomous robotic technologies for industrial inspection |
| CN109466785A (en) * | 2018-09-11 | 2019-03-15 | 成都优艾维智能科技有限责任公司 | A kind of autonomous method for inspecting of unmanned plane for exchange double back tangent tower |
| CN110007690A (en) * | 2019-05-08 | 2019-07-12 | 北京天龙智控科技有限公司 | A kind of unmanned plane cruising inspection system and method |
| CN110134143A (en) * | 2019-05-30 | 2019-08-16 | 广东电网有限责任公司 | A kind of electric inspection process method, system and electronic equipment and storage medium |
| US20190256208A1 (en) * | 2017-03-13 | 2019-08-22 | General Electric Company | System and method for integrating flight path and site operating data |
| KR20190108832A (en) * | 2018-03-15 | 2019-09-25 | (주)니어스랩 | Apparatus and Method for Detecting/Analyzing Defect of Windturbine Blade |
| CN110282143A (en) * | 2019-06-14 | 2019-09-27 | 中国能源建设集团广东省电力设计研究院有限公司 | A kind of marine wind electric field unmanned plane method for inspecting |
-
2019
- 2019-12-06 CN CN201911240805.2A patent/CN110879601B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104406762A (en) * | 2014-11-28 | 2015-03-11 | 国家电网公司 | Method for testing wind loading rating of unmanned helicopter inspection system for inspecting overhead transmission lines |
| CN206035727U (en) * | 2016-07-18 | 2017-03-22 | 中能电力科技开发有限公司 | Fan blade unmanned aerial vehicle intelligence system of patrolling and examining |
| US20190256208A1 (en) * | 2017-03-13 | 2019-08-22 | General Electric Company | System and method for integrating flight path and site operating data |
| US20190049962A1 (en) * | 2017-08-10 | 2019-02-14 | RavenOPS, Inc. | Autonomous robotic technologies for industrial inspection |
| KR20190108832A (en) * | 2018-03-15 | 2019-09-25 | (주)니어스랩 | Apparatus and Method for Detecting/Analyzing Defect of Windturbine Blade |
| CN109213197A (en) * | 2018-09-11 | 2019-01-15 | 成都优艾维智能科技有限责任公司 | A kind of autonomous method for inspecting of unmanned plane for single time tangent tower of direct current |
| CN109466785A (en) * | 2018-09-11 | 2019-03-15 | 成都优艾维智能科技有限责任公司 | A kind of autonomous method for inspecting of unmanned plane for exchange double back tangent tower |
| CN110007690A (en) * | 2019-05-08 | 2019-07-12 | 北京天龙智控科技有限公司 | A kind of unmanned plane cruising inspection system and method |
| CN110134143A (en) * | 2019-05-30 | 2019-08-16 | 广东电网有限责任公司 | A kind of electric inspection process method, system and electronic equipment and storage medium |
| CN110282143A (en) * | 2019-06-14 | 2019-09-27 | 中国能源建设集团广东省电力设计研究院有限公司 | A kind of marine wind electric field unmanned plane method for inspecting |
Non-Patent Citations (1)
| Title |
|---|
| LONG WANG: "Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-Taken Images", 《 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》 * |
Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112711267A (en) * | 2020-04-24 | 2021-04-27 | 江苏方天电力技术有限公司 | Unmanned aerial vehicle autonomous inspection method based on RTK high-precision positioning and machine vision fusion |
| CN112230235A (en) * | 2020-09-24 | 2021-01-15 | 北京京能能源技术研究有限责任公司 | Fan blade positioning method and system, computer equipment and readable storage medium |
| CN112230235B (en) * | 2020-09-24 | 2021-12-10 | 北京京能能源技术研究有限责任公司 | Fan blade positioning method and system, computer equipment and readable storage medium |
| CN112102395A (en) * | 2020-11-09 | 2020-12-18 | 广东科凯达智能机器人有限公司 | Autonomous inspection method based on machine vision |
| CN112164015A (en) * | 2020-11-30 | 2021-01-01 | 中国电力科学研究院有限公司 | Monocular vision autonomous inspection image acquisition method and device and power inspection unmanned aerial vehicle |
| CN112164015B (en) * | 2020-11-30 | 2021-04-23 | 中国电力科学研究院有限公司 | Monocular vision autonomous inspection image acquisition method and device and power inspection unmanned aerial vehicle |
| CN112947511A (en) * | 2021-01-25 | 2021-06-11 | 北京京能能源技术研究有限责任公司 | Method for inspecting fan blade by unmanned aerial vehicle |
| CN112905955A (en) * | 2021-01-27 | 2021-06-04 | 天津航天中为数据***科技有限公司 | Fan front and back autonomous inspection planning method |
| CN113050693A (en) * | 2021-03-26 | 2021-06-29 | 厦门理工学院 | Unmanned aerial vehicle inspection method, device and equipment for wind power blade detection |
| CN113050693B (en) * | 2021-03-26 | 2022-04-19 | 厦门理工学院 | Unmanned aerial vehicle inspection method, device and equipment for wind power blade detection |
| CN113177918B (en) * | 2021-04-28 | 2022-04-19 | 上海大学 | Intelligent and accurate inspection method and system for electric power tower by unmanned aerial vehicle |
| CN113177918A (en) * | 2021-04-28 | 2021-07-27 | 上海大学 | Intelligent and accurate inspection method and system for electric power tower by unmanned aerial vehicle |
| CN114217641A (en) * | 2021-10-29 | 2022-03-22 | 国网河南省电力公司中牟县供电公司 | Unmanned aerial vehicle power transmission and transformation equipment inspection method and system in non-structural environment |
| CN114217641B (en) * | 2021-10-29 | 2024-05-07 | 国网河南省电力公司中牟县供电公司 | Unmanned aerial vehicle power transmission and transformation equipment inspection method and system in non-structural environment |
| CN113885580A (en) * | 2021-11-17 | 2022-01-04 | 国能定边新能源有限公司 | Route planning method and system for realizing automatic inspection of fan based on unmanned aerial vehicle |
| CN114661062B (en) * | 2022-02-22 | 2023-11-28 | 广州中科云图智能科技有限公司 | Inspection method, device and equipment for power transmission line based on unmanned aerial vehicle |
| CN114661062A (en) * | 2022-02-22 | 2022-06-24 | 广州中科云图智能科技有限公司 | Unmanned aerial vehicle-based power transmission line inspection method, device and equipment |
| CN115097867A (en) * | 2022-08-23 | 2022-09-23 | 无锡海纳智能科技有限公司 | Method for determining unmanned aerial vehicle shooting attitude under fan inspection route |
| CN115480589A (en) * | 2022-09-06 | 2022-12-16 | 中科云尚(南京)智能技术有限公司 | Method and system for generating fan inspection route based on unmanned aerial vehicle |
| CN115951718A (en) * | 2023-03-14 | 2023-04-11 | 风脉能源（武汉）股份有限公司 | Fan blade inspection local dynamic path planning method and system based on unmanned aerial vehicle |
| CN115951718B (en) * | 2023-03-14 | 2023-05-09 | 风脉能源（武汉）股份有限公司 | Unmanned aerial vehicle-based fan blade inspection local dynamic path planning method and system |
| CN116206094B (en) * | 2023-04-28 | 2023-07-21 | 尚特杰电力科技有限公司 | Fan blade angle measuring method, device and system and electronic equipment |
| CN116206094A (en) * | 2023-04-28 | 2023-06-02 | 尚特杰电力科技有限公司 | Fan blade angle measuring method, device and system and electronic equipment |
| CN116839595A (en) * | 2023-09-01 | 2023-10-03 | 北京宝隆泓瑞科技有限公司 | Method for creating unmanned aerial vehicle route |
| CN116839595B (en) * | 2023-09-01 | 2023-11-28 | 北京宝隆泓瑞科技有限公司 | Method for creating unmanned aerial vehicle route |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110879601B (en) | 2021-05-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110879601B (en) | Unmanned aerial vehicle inspection method for unknown fan structure | |
| CN110554704B (en) | Unmanned aerial vehicle-based fan blade autonomous inspection method | |
| CN110908401B (en) | Unmanned aerial vehicle autonomous inspection method for unknown tower structure | |
| CN112904877A (en) | Automatic fan blade inspection system and method based on unmanned aerial vehicle | |
| CN110580717B (en) | Unmanned aerial vehicle autonomous inspection route generation method for electric power tower | |
| CN109911231B (en) | Unmanned aerial vehicle autonomous carrier landing method and system based on GPS and image recognition hybrid navigation | |
| CN107729808B (en) | Intelligent image acquisition system and method for unmanned aerial vehicle inspection of power transmission line | |
| CN108894933B (en) | Method and system for tracking, losing and re-capturing fan blade tips during tracking detection of fan blade tips through unmanned aerial vehicle | |
| US9346544B2 (en) | Unmanned aerial vehicle and methods for controlling same | |
| CN106762451A (en) | Fan blade damage detection method, device and system based on unmanned aerial vehicle | |
| CN111038721B (en) | Unmanned aerial vehicle for inspecting wind turbine blade based on image recognition and inspection method | |
| CN114296483B (en) | Intelligent inspection method and electronic equipment for wind driven generator in non-stop state | |
| CN111596693A (en) | Ground target tracking control method and system of unmanned aerial vehicle based on pan-tilt camera | |
| CN112068539A (en) | Unmanned aerial vehicle automatic driving inspection method for blades of wind turbine generator | |
| CN113759960A (en) | Unmanned aerial vehicle-based fan blade and tower barrel inspection identification system and method | |
| CN109190186B (en) | Automatic reconstruction method and system for fan model through unmanned aerial vehicle | |
| CN115145314B (en) | Fan blade inspection path planning method based on unmanned aerial vehicle | |
| CN109660721B (en) | Unmanned aerial vehicle flight shooting quality optimization method, system, equipment and storage medium | |
| CN108869196B (en) | Method and system for detecting rear side blade root area of fan through unmanned aerial vehicle | |
| CN110825110A (en) | Acquisition flight method for power line visible light point cloud resolving photo | |
| CN110001945A (en) | One kind facade that falls precipice finely tilts boat and takes the photograph device and method for imaging | |
| CN114326771A (en) | Unmanned aerial vehicle shooting route generation method and system based on image recognition | |
| EP4097354A1 (en) | Method of imaging a wind turbine rotor blade | |
| CN113359815A (en) | Fan blade unmanned aerial vehicle autonomous obstacle avoidance inspection method and system based on RTK positioning | |
| CN110825098B (en) | Unmanned aerial vehicle distribution network intelligent inspection system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |