CN116906277A - Fan yaw variation determining method and device, electronic equipment and storage medium - Google Patents

Fan yaw variation determining method and device, electronic equipment and storage medium Download PDF

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Publication number
CN116906277A
CN116906277A CN202310730876.0A CN202310730876A CN116906277A CN 116906277 A CN116906277 A CN 116906277A CN 202310730876 A CN202310730876 A CN 202310730876A CN 116906277 A CN116906277 A CN 116906277A
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Prior art keywords
fan
moment
point cloud
image
yaw angle
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CN116906277B (en
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严超
刘博�
李志轩
唐东明
刘珂
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Beijing Tuzhi Tianxia Technology Co ltd
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Beijing Tuzhi Tianxia Technology Co ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P13/00—Indicating or recording presence, absence, or direction, of movement
    • G01P13/02—Indicating direction only, e.g. by weather vane
    • G01P13/025—Indicating direction only, e.g. by weather vane indicating air data, i.e. flight variables of an aircraft, e.g. angle of attack, side slip, shear, yaw
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/50—Systems of measurement based on relative movement of target
    • G01S17/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/329—Azimuth or yaw angle
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Radar, Positioning & Navigation (AREA)
  • General Physics & Mathematics (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Sustainable Energy (AREA)
  • Sustainable Development (AREA)
  • Combustion & Propulsion (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Image Analysis (AREA)

Abstract

The application provides a method and a device for determining yaw variation of a fan, electronic equipment and a storage medium. The method comprises the following steps: acquiring a point cloud of a fan at a first moment, and identifying the point cloud of the fan to acquire a first reference yaw angle; obtaining a visible light image of the fan at a second moment, and identifying the visible light image to obtain a second reference yaw angle, wherein the second moment is later than the first moment; determining a difference to the first reference yaw angle and the second reference yaw angle; and under the condition that the difference value is smaller than or equal to a preset angle, judging that the fan does not yaw from the first moment to the second moment, and under the condition that the difference value is larger than or equal to the preset angle, judging that the fan yaw from the first moment to the second moment. The problem of among the prior art manual work look over fan driftage change inefficiency, inaccuracy is solved.

Description

Fan yaw variation determining method and device, electronic equipment and storage medium
Technical Field
The application relates to the field of fan inspection, in particular to a method and a device for determining yaw variation of a fan, electronic equipment and a storage medium.
Background
In the fan field of patrolling and examining, unmanned aerial vehicle technique also is used for the dynamic of fan to patrol and examine, and the dynamic is patrolled and examined and is compared in static to patrol and examine, is under the fan blade keeps pivoted circumstances, and unmanned aerial vehicle carries out and patrol and examine the route, compares traditional static mode of patrolling and examining, unmanned aerial vehicle patrols and examines and has advantages such as high efficiency, safety, accurate. Before dynamic routing inspection, a dynamic routing inspection route is planned according to yaw of the fan. The yaw angle of the fan is often determined by means of image recognition in the prior art.
It should be noted that, in the actual operation of the wind turbine, the yaw angle of the wind turbine is not fixed, for example, in the case that the wind direction changes, the yaw system of the wind turbine can automatically adjust the yaw in a short time according to the change of the wind direction, and in this case, the correct final yaw angle must be measured under the condition that the wind turbine is stable. In the prior art, whether the yaw of the fan is stable is often checked by means of naked eyes, but under the condition that the yaw variation of the fan is small, the manual check cannot be judged. In view of this, the present application has been proposed.
Disclosure of Invention
The application provides a method and a device for determining yaw variation of a fan, electronic equipment and a storage medium. The problem that in the prior art, the yaw change efficiency of a fan is low and inaccurate is manually checked is solved.
According to a first aspect of the present application there is provided a method of determining yaw variation of a wind turbine, the method comprising: acquiring a point cloud of a fan at a first moment, and identifying the point cloud of the fan to acquire a first reference yaw angle; obtaining a visible light image of the fan at a second moment, and identifying the visible light image to obtain a second reference yaw angle, wherein the second moment is later than the first moment; determining a difference to the first reference yaw angle and the second reference yaw angle; and under the condition that the difference value is smaller than or equal to a preset angle, judging that the fan does not yaw from the first moment to the second moment, and under the condition that the difference value is larger than or equal to the preset angle, judging that the fan yaw from the first moment to the second moment.
Further, the method further comprises: determining the second reference yaw angle as a final yaw angle of the wind turbine in case no yaw of the wind turbine occurs; and under the condition that the fan is yawed, re-acquiring a new point cloud of the fan after a preset time period, and determining a third reference yaw angle obtained after the new point cloud is identified as a final yaw angle of the fan.
Further, identifying the point cloud of the wind turbine to obtain a first reference yaw angle includes: screening the point cloud of the fan to obtain the point cloud of the fan cabin; constructing a plane beam S parallel to a Z axis by taking the point cloud of the fan cabin as the center; respectively projecting the point cloud of the fan cabin to each plane of the plane beam S, and counting the number of the point clouds projected to each plane; and performing triangular transformation on the vector of the plane with the largest point cloud number to obtain a first reference yaw angle.
Further, the method comprises the steps of S41, taking a first point cloud as a center, taking Deltax, deltay and Deltaz as side lengths to construct a first cuboid, wherein the point cloud is any one of the point clouds of the fan, deltax=Deltay=0.01 m, and Deltaz is more than or equal to 10m; step S42, centering on the first point cloud, and taking Deltax, deltay and f as centers z -b z Constructing a second cuboid for the side length, f z B, collecting the height of the point cloud for the point cloud equipment z The height of the fan base; step S43, eliminating the first point cloud from the point cloud of the fan when the second cuboid comprises points which are not contained in the first cuboid; and step S44, processing all the point clouds in the point clouds of the fan based on the steps S41 to S43, and determining the point clouds with the rest removed as the point clouds of the fan cabin.
Further, identifying the visible light image to obtain a second reference yaw angle includes: processing the visible light image to obtain a target binarized image of the visible light image, wherein the target binarized image only comprises a fan cabin and an effective area of a fan blade; constructing a straight line bundle by taking the upper left corner of the target binarized image as an original point and taking a preset angle range as a rotation angle interval; projecting the fan cabin and the effective area of the fan blade to the linear beam, and obtaining the shortest projection line; a second reference yaw angle is obtained based on the shortest projection line.
Further, deriving a second reference yaw angle based on the shortest projection line includes: determining a real-time angle of the linear beam when the shortest projection line is obtained; rotating the target binarized image according to the real-time angle to obtain a target image; cutting off the target image according to a preset strategy to obtain a first image and a second image, wherein the first image comprises a fan cabin, and the second image comprises fan blades; obtaining a first ordinate of the center of the effective area of the first image and a second ordinate of the center of the effective area of the second image; comparing the first ordinate with the second ordinate; determining the yaw direction of the fan according to the comparison result; a second reference yaw angle is determined based on the yaw direction of the wind turbine and the real-time angle.
Further, processing the visible light image to obtain a target binarized image of the visible light image, including: performing binarization processing on the visible light image to obtain an initial binarization image and a binarization threshold value; determining the area ratio of the effective area of the initial binary image to the initial binary image; determining an optimal segmentation threshold based on an area duty cycle, a binarization threshold, and pixel units in the initial binarized image; and dividing the initial binary image by using the optimal dividing threshold value, and extracting an effective area of the divided image by using a connected domain analysis algorithm to obtain a target binary image.
According to a second aspect of the present application, there is provided a fan yaw variation determination apparatus, comprising: the first identification unit is used for obtaining the point cloud of the fan at a first moment and identifying the point cloud of the fan to obtain a first reference yaw angle; the second identification unit is used for obtaining a visible light image of the fan at a second moment and identifying the visible light image to obtain a second reference yaw angle, and the second moment is later than the first moment; a determining unit configured to determine a difference to the first reference yaw angle and the second reference yaw angle; the judging unit is used for judging that the fan does not yaw from the first moment to the second moment when the difference value is smaller than or equal to a preset angle, and judging that the fan does yaw from the first moment to the second moment when the difference value is larger than or equal to the preset angle.
According to a third aspect of the present application there is provided a computer device comprising a memory and a processor, the memory having stored thereon computer instructions which, when executed by the processor, cause any of the methods described above to be performed.
According to a fourth aspect of the present application there is provided a non-transitory computer readable storage medium having stored thereon a computer program which when executed by a processor causes any of the methods described above to be performed.
The application provides a method and a device for determining yaw variation of a fan, electronic equipment and a storage medium. The method comprises the following steps: acquiring a point cloud of a fan at a first moment, and identifying the point cloud of the fan to acquire a first reference yaw angle; obtaining a visible light image of the fan at a second moment, and identifying the visible light image to obtain a second reference yaw angle, wherein the second moment is later than the first moment; determining a difference to the first reference yaw angle and the second reference yaw angle; and under the condition that the difference value is smaller than or equal to a preset angle, judging that the fan does not yaw from the first moment to the second moment, and under the condition that the difference value is larger than or equal to the preset angle, judging that the fan yaw from the first moment to the second moment. The problem of among the prior art manual work look over fan driftage change inefficiency, inaccuracy is solved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a method for determining yaw variation of a wind turbine provided by an embodiment of the present application;
FIG. 2 is a schematic diagram of a target binarized image of a visible light image according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a rotated target image according to an embodiment of the present application;
FIG. 4 is a schematic view of a first image obtained after truncation according to an embodiment of the present application;
FIG. 5 is a schematic illustration of a second image obtained after truncation provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of an initial binary image provided by an embodiment of the present application;
fig. 7 is a schematic diagram of an image segmented with an optimal segmentation threshold according to an embodiment of the present application.
Detailed Description
To further clarify the above and other features and advantages of the present application, a further description of the application will be rendered by reference to the appended drawings. It should be understood that the specific embodiments presented herein are for purposes of explanation to those skilled in the art and are intended to be illustrative only and not limiting.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. It will be apparent, however, to one skilled in the art that the specific details need not be employed to practice the present application. In other instances, well-known steps or operations have not been described in detail in order to avoid obscuring the application.
Example 1
The application provides a method for determining yaw variation of a fan, which can be implemented by an intelligent remote controller of an unmanned aerial vehicle, an onboard computer of the unmanned aerial vehicle or other devices with data processing as an execution main body, and is shown in combination with fig. 1, and comprises the following steps:
step S11, obtaining a point cloud of a fan at a first moment, and identifying the point cloud of the fan to obtain a first reference yaw angle.
And step S13, obtaining a visible light image of the fan at a second moment, and identifying the visible light image to obtain a second reference yaw angle, wherein the second moment is later than the first moment.
Specifically, the point cloud and the visible light image of the fan can be used for the unmanned aerial vehicle with the camera and the laser radar to acquire at different moments, for example, the unmanned aerial vehicle can hover right above the fan (wind driven generator), and the pitch angles of the two loads are adjusted for the fan below, the point cloud of the wind driven generator is acquired through the laser radar, and the visible light image of the fan is acquired through the visible light camera. The method for identifying the yaw angle of the fan is suitable for dynamic inspection of the fan, namely, under the condition that the fan is running (namely, the fan blades are rotating), the laser radar collects dynamic fan point clouds, and the visible light camera collects images of the dynamic fan.
It should be further noted that, in the scheme, yaw recognition can be performed on the fan point cloud through a point cloud recognition algorithm, the first reference yaw angle is obtained, the point cloud recognition algorithm can be based on curvature point cloud segmentation, and then a main component analysis method is used for extracting a main direction of the fan. The method can be used for identifying the visible light image through an image identification algorithm to obtain the second reference yaw angle, wherein the image identification algorithm can be a method for detecting the pose of an object through a fast R-CNN.
The following describes the technical details of the unmanned aerial vehicle for controlling to collect the point cloud of the fan:
the solid-state laser radar lens is adjusted to face downwards, the integration time T is set according to the distance L from the unmanned aerial vehicle to the position of the fan cabin, and point cloud data are acquired according to the integration time T:
wherein:
L＝f z -b z -h z
f z elevation, b, when point clouds are acquired for lidar z Is the height of the fan base, h z For windAnd the height of the tower drum.
Step S15, determining the difference between the first reference yaw angle and the second reference yaw angle.
In step S17, when the difference is less than or equal to the preset angle, it is determined that yaw does not occur in the fan from the first moment to the second moment, and when the difference is greater than or equal to the preset angle, it is determined that yaw occurs in the fan from the first moment to the second moment, and it is noted that the preset angle may be 3 degrees to 5 degrees.
Specifically, since the first reference yaw angle of the blower is obtained by identification at the first moment, the second reference yaw angle of the blower is obtained by identification at the second moment, if the blower is subjected to yaw variation from the first moment to the second moment, the difference between the first reference yaw angle and the second reference yaw angle obtained by identification exceeds the preset difference, and under the condition, the change of the yaw of the blower is judged by the scheme. If the difference value between the first reference yaw angle and the second reference yaw angle is smaller than or equal to the preset angle, the yaw of the fan is stable from the first moment to the second moment. Compared with the prior art, the method for judging the yaw variation of the fan does not need manual work, and can be identified under the condition that the yaw variation of the fan is small. Therefore, the problem that the yaw fluctuation efficiency of the fan is low and inaccurate in manual checking in the prior art is solved by the scheme.
The principle of the scheme is that whether the yaw angle of the fan is changed at different moments is identified, and then whether the yaw of the fan is changed is judged through comparison, so that a laser radar is firstly adopted to collect fan point clouds at a first moment, then a first reference yaw angle is obtained through identification, a camera is adopted to collect visible light images at a second moment, then a second reference yaw angle is identified, and the beneficial effects of the first moment point clouds identification and the second moment visible light identification are as follows:
the recognition scheme of visible light has the advantage of high speed, and the disadvantage of insufficient precision to find small yaw variations. The point cloud identification has the advantages of higher precision and longer identification time. Then, for a period of time between the first time and the second time, the method selects to adopt the point cloud identification at the first time, and the period of time between the first time and the second time is enough to complete the point cloud identification to generate the first reference yaw angle. At the second moment, the scheme needs to quickly generate a reference yaw angle so as to finish the identification of yaw variation, and the accuracy of visible light is insufficient but can be used as a reference value for comparison. Therefore, after combining the advantages and disadvantages of the existing identification scheme, the technical scheme of new first-moment point cloud identification and second-moment visible light identification is provided.
Optionally, the method further comprises:
in step S19, in the case that no yaw of the wind turbine occurs, the second reference yaw angle is determined as the final yaw angle of the wind turbine.
Specifically, due to the fact that accuracy of point cloud identification is high, in the case that yaw does not occur in the fan, the second reference yaw angle is selected as a final yaw angle, and a fan routing inspection route is established based on the final yaw angle.
Step S21, under the condition that the fan is yawed, the new point cloud of the fan is collected again after a preset time period, and the third reference yaw angle obtained after the new point cloud is identified is determined to be the final yaw angle of the fan.
Specifically, if the yaw angle of the blower changes, at this time, neither the first yaw angle nor the second yaw angle is suitable as the final yaw angle, because it cannot be determined whether the blower completes the yaw change and is stable at the second moment, the present solution re-collects the new point cloud of the blower after a preset period of time (for example, after 1mi n), and determines the third yaw angle obtained by identifying the new point cloud as the final yaw angle of the blower. It should be noted that, because the yaw angle obtained by the point cloud identification is more accurate than the visible light image identification, the method selects the laser radar to acquire a new point cloud again after a preset time period and then identifies the yaw angle.
Optionally, step S11 identifies a point cloud of the wind turbine to obtain a first reference yaw angle, including:
and step S111, screening the point cloud of the fan cabin from the point cloud of the fan.
And S113, constructing a plane beam S parallel to the Z axis by taking the point cloud of the fan cabin as the center.
Step S115, projecting the point cloud of the fan nacelle to each plane of the plane beam S, and counting the number of the point clouds projected to each plane.
Step S117, performing triangular transformation on the vector of the plane with the largest point cloud number to obtain a first reference yaw angle.
Specifically, the scheme can construct a plane beam projection and solve a yaw angle. And constructing a plane beam S by taking the centroid of the cabin point cloud as the center and parallel to a Z axis, projecting the point cloud of the cabin position to a plane in the plane beam S, counting the number of the projected point clouds, and obtaining a direction vector of the plane with the maximum number of the point clouds, namely a vector perpendicular to the direction of the yaw angle by projection, wherein the first reference yaw angle can be obtained by using triangular transformation.
The coordinate system in which the cabin point cloud is located is defined as follows: the coordinate system is a geodetic coordinate system, the forward eastern direction represents the X axis, the north direction represents the Y axis, and the horizontal direction represents the Z axis.
Optionally, screening the point cloud of the fan cabin from the point clouds of the fan includes:
step S41, a first cuboid is built by taking a first point cloud as a center and taking deltax, deltay and deltaz as side lengths, wherein the point cloud is any one of the point clouds of the fan, deltax=deltay=0.01 m, and deltaz is more than or equal to 10m;
step S42, centering on the first point cloud, and taking Deltax, deltay and f as centers z -b z Constructing a second cuboid for the side length, f z B, collecting the height of the point cloud for the point cloud equipment z The height of the fan base;
step S43, eliminating the first point cloud from the point cloud of the fan when the second cuboid comprises points which are not contained in the first cuboid;
and step S44, processing all the point clouds in the point clouds of the fan based on the steps S41 to S43, and determining the point clouds with the rest removed as the point clouds of the fan cabin.
Specifically, the present solution may filter the obtained point cloud data to remove outliers, and then use the point cloud that is segmented into cabin positions, where a cube with a size of Δx Δy Δz is set in space, and points that include the point cloud outside the interval in the z-axis direction are removed, that is, points (p x ,p y ,p z ) Taking the point as a centroid, taking Deltax, deltay and Deltaz as side lengths, constructing a cuboid A, and taking Deltax, deltay and f z -b z To be a side length, a rectangular parallelepiped B is constructed, and if a point not contained in A is contained in B, then (p x ,p y ,p z ) And removing the point cloud from the original point cloud, and traversing all points in the point cloud to obtain all point clouds of the cabin position.
In the prior art, the method for dividing the cabin point cloud is easily affected by the fan impeller, and the method for dividing the cabin point cloud of the fan can extract the point cloud of the complete cabin position, so that the dividing effect is good.
Optionally, step S13 identifies the visible light image to obtain a second reference yaw angle, including:
step S131, processing the visible light image to obtain a target binarized image of the visible light image, where the target binarized image only includes a fan cabin and an effective area of a fan blade.
Specifically, the target binarized image of the visible light image is shown in fig. 2 in combination with fig. 2, and in fig. 2, the visible light image is processed from an RGB image to an image including only the fan nacelle and the effective area of the fan blade.
And S133, constructing a straight line bundle by taking the upper left corner of the target binarized image as an original point and taking a preset angle range as a rotation angle interval.
And step S135, projecting the effective areas of the fan cabin and the fan blades to the linear beam, and obtaining the shortest projection line.
Step S137, obtaining a second reference yaw angle based on the shortest projection line.
Specifically, the scheme can construct a straight line bundle by taking the upper left corner of the target binarized image as an origin and taking [0 degree, 180 degree ] as a rotation angle interval, then project the fan cabin and the effective area of the fan blade to the straight line bundle, and obtain the shortest projection line, wherein the shortest projection line is the straight line where the yaw angle is located.
Specifically, step S137 obtains a second reference yaw angle based on the shortest projection line, including:
in step S1371, the real-time angle of the line beam is determined when the shortest projection line is obtained.
And step S1372, rotating the target binarized image according to the real-time angle to obtain a target image.
Specifically, the real-time angle (angle corresponding to projection line) of the line beam can be set as alpha, alpha E [0 ] ° ,180 ° ]It should be noted that, the angle α corresponding to the projection line is the value of the second reference yaw angle, but in order to know the yaw angle more precisely, the effective area of the fan needs to be rotated around the center of the image according to the angle α, and the target image obtained after rotation is shown in fig. 3.
Step S1373, truncating the target image according to a preset strategy, to obtain a first image and a second image, where the first image includes a fan cabin, and the second image includes fan blades.
In step S1374, a first ordinate of the first image center and a second ordinate of the second image center are obtained.
Step S1375, comparing the first ordinate with the second ordinate.
And step S1376, determining the yaw direction of the fan according to the comparison result.
Step S1377, determining a second reference yaw angle based on the yaw direction of the wind turbine and the real-time angle.
Specifically, the method can calculate the geometric center of the fan (namely, the centroid of the effective area in the target binarized image), and cut off the fan proportionally according to the geometric center to obtain the segmented images (namely, the first image and the second image) of the position of the engine room and the position of the blade of the fan. The geometric centers of the two graphs are calculated respectively, if the ordinate of the center point of the effective area of the cabin position is larger than that of the effective area of the center point of the blade position, the yaw angle is-alpha, otherwise, the yaw angle is alpha. A schematic view of the first image is shown in fig. 4, and a schematic view of the second image is shown in fig. 5.
Optionally, step S131 processes the visible light image to obtain a target binarized image of the visible light image, including:
step S1311, performing binarization processing on the visible light image to obtain an initial binarized image and a binarization threshold.
Specifically, the RGB visible light image may be reduced, color space converted, and gaussian blurred, and then binarized using the oxford method to obtain an initial binarized image and a binarized threshold. Fig. 6 is a schematic diagram of an initial binarized image.
Step S1312, determining an area ratio of the effective area of the initial binarized image to the initial binarized image.
Step S1313, determining an optimal segmentation threshold based on the area duty, the binarization threshold, and the pixel units in the initial binarized image.
Step S1314, segmenting the initial binary image by using the optimal segmentation threshold, and extracting an effective area of the segmented image by using a connected domain analysis algorithm to obtain a target binary image.
Specifically, the present solution uses the area ratio of the effective area of the binary image in the graph as a constraint condition, uses the binary threshold obtained above as an initial value, uses a pixel unit as a step length, uses the Levenberg-Marquardt method to perform optimization, obtains an optimal segmentation threshold, and obtains a binary image segmented by the threshold, and a schematic diagram of an image segmented by the optimal segmentation threshold is shown in fig. 7. Then, the method uses a connected domain analysis algorithm to extract the fan region of the image segmented by the optimal segmentation threshold, and carries out noise filtration on the effective region according to the position and the area in the image to obtain the target binarized image.
The method for identifying the yaw of the fan optimizes the existing method for identifying the point cloud based on laser radar acquisition, improves the identification precision based on the point cloud identification method, simultaneously changes the yaw of the fan in the process of acquiring the point cloud, provides a visual identification method based on camera image transmission, can mutually verify with the point cloud identification method, and improves the usability and the stability of the system.
Example two
The present application also provides a device for determining yaw variation of a wind turbine, which may be used to perform the method of the first embodiment, and the device includes: the first identification unit is used for obtaining the point cloud of the fan at a first moment and identifying the point cloud of the fan to obtain a first reference yaw angle; the second identification unit is used for obtaining a visible light image of the fan at a second moment and identifying the visible light image to obtain a second reference yaw angle, and the second moment is later than the first moment; a determining unit configured to determine a difference to the first reference yaw angle and the second reference yaw angle; the judging unit is used for judging that the fan does not yaw from the first moment to the second moment when the difference value is smaller than or equal to a preset angle, and judging that the fan does yaw from the first moment to the second moment when the difference value is larger than or equal to the preset angle.
Specifically, since the first reference yaw angle of the blower is obtained by identification at the first moment, the second reference yaw angle of the blower is obtained by identification at the second moment, if the blower is subjected to yaw variation from the first moment to the second moment, the difference between the first reference yaw angle and the second reference yaw angle obtained by identification exceeds the preset difference, and under the condition, the change of the yaw of the blower is judged by the scheme. If the difference value between the first reference yaw angle and the second reference yaw angle is smaller than or equal to the preset angle, the yaw of the fan is stable from the first moment to the second moment. Compared with the prior art, the method for judging the yaw variation of the fan does not need manual work, and can be identified under the condition that the yaw variation of the fan is small. Therefore, the problem that the yaw fluctuation efficiency of the fan is low and inaccurate in manual checking in the prior art is solved by the scheme.
It is to be understood that the specific features, operations and details described herein before with respect to the method of the application may also be similarly applied to the apparatus and system of the application, or vice versa. In addition, each step of the method of the present application described above may be performed by a corresponding component or unit of the apparatus or system of the present application.
It is to be understood that the various modules/units of the apparatus of the application may be implemented in whole or in part by software, hardware, firmware, or a combination thereof. The modules/units may each be embedded in a processor of the computer device in hardware or firmware or separate from the processor, or may be stored in a memory of the computer device in software for invocation by the processor to perform the operations of the modules/units. Each of the modules/units may be implemented as a separate component or module, or two or more modules/units may be implemented as a single component or module.
In one embodiment, a computer device is provided that includes a memory and a processor having stored thereon computer instructions executable by the processor, which when executed by the processor, instruct the processor to perform the steps of the method of embodiments of the present application. The computer device may be broadly a server, a terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc. connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may have an operating system, computer programs, etc. stored therein or thereon. The internal memory may provide an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface and communication interface of the computer device may be used to connect and communicate with external devices via a network. Which when executed by a processor performs the steps of the method of the application.
The present application may be implemented as a computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes steps of a method of an embodiment of the present application to be performed. In one embodiment, the computer program is distributed over a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/operation, or two or more method steps/operations, may be performed by a single computer device or processor, or by two or more computer devices or processors. One or more method steps/operations may be performed by one or more computer devices or processors, and one or more other method steps/operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/operation or two or more method steps/operations.
Those of ordinary skill in the art will appreciate that the method steps of the present application may be implemented by a computer program, which may be stored on a non-transitory computer readable storage medium, to instruct related hardware such as a computer device or a processor, which when executed causes the steps of the present application to be performed. Any reference herein to memory, storage, database, or other medium may include non-volatile and/or volatile memory, as the case may be. Examples of nonvolatile memory include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.
The technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the description provided that such combinations are not inconsistent.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims (10)

1. A method for determining yaw variation of a wind turbine, comprising:
acquiring a point cloud of a fan at a first moment, and identifying the point cloud of the fan to acquire a first reference yaw angle;
obtaining a visible light image of the fan at a second moment, and identifying the visible light image to obtain a second reference yaw angle, wherein the second moment is later than the first moment;
determining a difference to the first reference yaw angle and the second reference yaw angle;
and under the condition that the difference value is smaller than or equal to a preset angle, judging that the fan does not yaw from the first moment to the second moment, and under the condition that the difference value is larger than or equal to the preset angle, judging that the fan yaw from the first moment to the second moment.
2. The method according to claim 1, wherein the method further comprises:
determining the second reference yaw angle as a final yaw angle of the wind turbine in case no yaw of the wind turbine occurs;
and under the condition that the fan is yawed, re-acquiring a new point cloud of the fan after a preset time period, and determining a third reference yaw angle obtained after the new point cloud is identified as a final yaw angle of the fan.
3. The method of claim 1, wherein identifying the point cloud of the wind turbine to obtain the first reference yaw angle comprises:
screening the point cloud of the fan to obtain the point cloud of the fan cabin;
constructing a plane beam S parallel to a Z axis by taking the point cloud of the fan cabin as the center;
respectively projecting the point cloud of the fan cabin to each plane of the plane beam S, and counting the number of the point clouds projected to each plane;
and performing triangular transformation on the vector of the plane with the largest point cloud number to obtain a first reference yaw angle.
4. A method according to claim 3, wherein screening the point cloud of the fan nacelle from the point clouds of the fan comprises:
step S41, a first cuboid is built by taking a first point cloud as a center and taking deltax, deltay and deltaz as side lengths, wherein the point cloud is any one of the point clouds of the fan;
step S42, centering on the first point cloud, and taking Deltax, deltay and f as centers z -b z Constructing a second cuboid for the side length, f z B, collecting the height of the point cloud for the point cloud equipment z The height of the fan base;
step S43, eliminating the first point cloud from the point cloud of the fan when the second cuboid comprises points which are not contained in the first cuboid;
and step S44, processing all the point clouds in the point clouds of the fan based on the steps S41 to S43, and determining the point clouds with the rest removed as the point clouds of the fan cabin.
5. The method of claim 1, wherein identifying the visible light image to obtain a second reference yaw angle comprises:
processing the visible light image to obtain a target binarized image of the visible light image, wherein the target binarized image only comprises a fan cabin and an effective area of a fan blade;
constructing a straight line bundle by taking the upper left corner of the target binarized image as an original point and taking a preset angle range as a rotation angle interval;
projecting the fan cabin and the effective area of the fan blade to the linear beam, and obtaining the shortest projection line;
a second reference yaw angle is obtained based on the shortest projection line.
6. The method of claim 5, wherein deriving a second reference yaw angle based on the shortest projection line comprises:
determining a real-time angle of the line bundle when the shortest projection line is obtained;
rotating the target binarized image according to the real-time angle to obtain a target image;
cutting off the target image according to a preset strategy to obtain a first image and a second image, wherein the first image comprises a fan cabin, and the second image comprises fan blades;
obtaining a first ordinate of the center of the effective area in the first image and a second ordinate of the center of the effective area in the second image;
comparing the first ordinate with the second ordinate;
determining the yaw direction of the fan according to the comparison result;
a second reference yaw angle is determined based on the yaw direction of the wind turbine and the real-time angle.
7. The method of claim 5, wherein processing the visible light image to obtain a target binarized image of the visible light image comprises:
performing binarization processing on the visible light image to obtain an initial binarization image and a binarization threshold value;
determining the area ratio of the effective area of the initial binary image to the initial binary image;
determining an optimal segmentation threshold based on an area duty cycle, a binarization threshold, and pixel units in the initial binarized image;
and dividing the initial binary image by using the optimal dividing threshold value, and extracting an effective area of the divided image by using a connected domain analysis algorithm to obtain a target binary image.
8. A device for determining yaw variation of a wind turbine, comprising:
the first identification unit is used for obtaining the point cloud of the fan at a first moment and identifying the point cloud of the fan to obtain a first reference yaw angle;
the second identification unit is used for obtaining a visible light image of the fan at a second moment and identifying the visible light image to obtain a second reference yaw angle, and the second moment is later than the first moment;
a determining unit configured to determine a difference to the first reference yaw angle and the second reference yaw angle;
the judging unit is used for judging that the fan does not yaw from the first moment to the second moment when the difference value is smaller than or equal to a preset angle, and judging that the fan does yaw from the first moment to the second moment when the difference value is larger than or equal to the preset angle.
9. A computer device comprising a memory and a processor, the memory having stored thereon computer instructions that, when executed by the processor, cause the method of any of claims 1-7 to be performed.
10. A non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes the method of any of claims 1 to 7 to be performed.
CN202310730876.0A 2023-06-20 Fan yaw variation determining method and device, electronic equipment and storage medium Active CN116906277B (en)

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