WO2020108088A1 - 确定风力发电机组的塔架净空的方法和装置 - Google Patents
确定风力发电机组的塔架净空的方法和装置 Download PDFInfo
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- WO2020108088A1 WO2020108088A1 PCT/CN2019/109391 CN2019109391W WO2020108088A1 WO 2020108088 A1 WO2020108088 A1 WO 2020108088A1 CN 2019109391 W CN2019109391 W CN 2019109391W WO 2020108088 A1 WO2020108088 A1 WO 2020108088A1
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- tower
- tip
- blade
- image
- edge
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
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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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- 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
- F05B2260/00—Function
- F05B2260/80—Diagnostics
-
- 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
- F05B2270/33—Proximity of blade to tower
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- 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
- F05B2270/80—Devices generating input signals, e.g. transducers, sensors, cameras or strain gauges
- F05B2270/804—Optical devices
- F05B2270/8041—Cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- 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
Definitions
- the present disclosure generally relates to the field of wind power technology, and more particularly, to a method and apparatus for determining the tower headroom of a wind turbine.
- the clearance of the tower of the wind turbine refers to the distance from the tip of the blade to the surface of the tower during the rotation of the impeller.
- the blade For wind turbines, if the blade sweeping occurs, the blade needs to be replaced, and the cost of a single blade is higher, which will increase the maintenance cost. At the same time, the unit needs to be shut down during the blade replacement, and the power generation will also be lost during the unit shutdown. Therefore, once the blade sweep tower occurs, it will bring greater economic losses to the wind farm.
- the tower headroom of the wind turbine cannot be measured by a measuring tool, which results in the fact that the tower headroom of the wind turbine cannot be obtained in real time.
- Exemplary embodiments of the present disclosure provide a method and apparatus for determining the tower headroom of a wind turbine to solve the technical problem that the tower headroom of a wind turbine cannot be measured in the prior art.
- a method for determining the tower headroom of a wind turbine comprising: acquiring an image of the wind turbine during operation, the image including the tips of the blades of the wind turbine and the tower Barrel; determine the position of the tip of the blade of the wind turbine from the acquired image; identify the edge of the tower from the acquired image; calculate the tip of the blade to the determined position of the tip of the blade and the identified edge of the tower The distance of the edge of the tower to obtain the clearance of the tower.
- an apparatus for determining the tower headroom of a wind turbine includes: an image acquisition module that acquires an image of the wind turbine during operation, the image including the wind turbine The tip of the blade and the tower; the tip detection module to determine the position of the tip of the blade of the wind turbine from the acquired image; the tower edge recognition module to identify the edge of the tower from the acquired image; the tower clearance determination module Based on the determined position of the tip of the blade and the identified edge of the tower, the distance from the tip of the blade to the edge of the tower is calculated to obtain the clearance of the tower.
- a tower headroom monitoring system includes: an image capturer for capturing images of blades of a wind turbine during operation; and a processor configured to: Acquiring images including the tips of the blades of the wind turbine and the tower from the captured images; determining the positions of the tips of the blades of the wind turbine from the acquired images; identifying the edges of the tower from the acquired images; Based on the determined position of the tip of the blade and the identified edge of the tower, the distance from the tip of the blade to the edge of the tower is calculated to obtain the tower clearance.
- a computer-readable storage medium storing a computer program, which when executed by a processor implements the above method for determining the tower headroom of a wind turbine.
- the tower headroom of the wind power generator set can be determined in real time, so as to effectively avoid the occurrence of blade sweeping.
- FIG. 1 shows a block diagram of a tower clearance monitoring system according to an exemplary embodiment of the present disclosure
- FIG. 2 shows a flowchart of a method for determining a tower headroom of a wind turbine according to an exemplary embodiment of the present disclosure
- FIG. 3 shows a schematic diagram of the installation position of the image capturer according to the first exemplary embodiment of the present disclosure
- FIG. 4 shows a schematic diagram of an image captured by the image capturer according to the first exemplary embodiment of the present disclosure
- FIG. 5 shows a schematic diagram of the installation position of the image capturer according to the second exemplary embodiment of the present disclosure
- FIG. 6 shows a schematic diagram of a protection device for protecting an image capturer according to a second exemplary embodiment of the present disclosure
- FIG. 7 shows a schematic diagram of an image captured by an image capturer according to a second exemplary embodiment of the present disclosure
- FIG. 8 shows a flowchart of a step of detecting the position of the tip of a blade according to an exemplary embodiment of the present disclosure
- FIG. 9 shows a flowchart of the step of identifying the edge of the tower according to an exemplary embodiment of the present disclosure
- FIG. 10 shows a block diagram of a device for determining the tower headroom of a wind turbine according to an exemplary embodiment of the present disclosure
- FIG. 11 shows a block diagram of a tower edge recognition module according to an exemplary embodiment of the present disclosure.
- FIG. 1 shows a block diagram of a tower clearance monitoring system according to an exemplary embodiment of the present disclosure.
- FIG. 2 shows a flowchart of a method for determining a tower headroom of a wind turbine according to an exemplary embodiment of the present disclosure.
- the tower clearance monitoring system includes an image capturer 100 and a processor 200.
- the image capturer 100 is used to capture images of the blades of the wind turbine during operation.
- the processor 200 is configured to perform the method shown in FIG. 2 for determining the tower clearance of the wind turbine.
- step S10 an image of the wind generating set during operation is acquired.
- the acquired images include the tips of the blades of the wind turbine and the tower.
- the image capturer 100 captures images of the blades of the wind turbine during operation, and the images captured by the image capturer 100 include images of the tips of the blades of the wind turbine and the tower tube for tower clearance analysis. Image, and then the blade tip and tower are identified for the image used for tower clearance analysis.
- the image used for the tower clearance analysis is an image in which the tip of the blade of the wind turbine and the tower tube are included in the captured image.
- the tower clearance refers to the distance between the tip of the blade and the surface of the tower during the rotation of the impeller, in order to determine the value of the tower clearance, it is necessary to pass the image of the tip of the blade and the tower containing the wind turbine Only through analysis can the tower clearance be determined.
- the image capturer 100 may include, but is not limited to, a camera or a laser 2D (two-dimensional) scanner for capturing images of the blades of the wind turbine during operation.
- the video camera can record the video of the blades of the wind turbine during the operation, and then identify each frame of the captured video, from each frame of the image Identify images used for tower clearance analysis.
- images of the blades of a continuous multi-frame wind turbine during operation can be obtained by shooting video, and then for each frame of image, the image including the tip of the blade and the tower barrel can be identified for performing the subsequent tower Overhead clearance analysis. In this way, real-time monitoring of the tower headroom through video means is realized.
- image recognition methods can be used to recognize the images captured by the image capturer 100 to identify the images including the tips of the blades of the wind turbine and the tower from the captured images, and to recognize Is determined as the image used for the tower clearance analysis.
- the captured image may be identified through template matching. For example, multiple template images marked with the tips of the blades of the wind turbine and the tower can be established in advance, and the captured images are compared with the multiple template images, respectively.
- multiple template images marked with the tip of the blade and the tower can be stacked on the image captured by the image capturer 100 for template matching, when any one of the multiple template images exists in the captured image
- the matched image is determined as the image including the tip of the blade of the wind turbine and the tower, that is, the matched image is determined as the image used for the tower clearance analysis.
- the above method of performing image recognition through template matching is only an example, and the present disclosure is not limited thereto, and other image recognition methods are also feasible.
- the installation position of the image capturer 100 can be reasonably set to enable the image capturer 100 to capture images including the tips of the blades of the wind turbine and the tower. Two installation examples of the image capturer 100 are described below.
- the image capturer 100 may be installed at the bottom of the nacelle of the wind turbine to capture images including the tips of the blades of the wind turbine and the tower.
- FIG. 3 shows a schematic diagram of the installation position of the image capturer according to the first exemplary embodiment of the present disclosure.
- the image capture device 100 may be provided at the bottom of the nacelle 3 of the wind turbine, that is, the image capture device 100 may be provided at the bottom of the nacelle 3 shell between the tower 1 and the hub, to When the blade 2 is rotated to an angle range that effectively measures the clearance, an image including the tip of the blade 2 and the tower 1 is captured.
- the above-mentioned effective angular range for measuring the headroom may be a predetermined angular range.
- the angle range of the effective measurement clearance may refer to a predetermined angle range near the azimuth angle of the impeller when the tip of the blade is perpendicular to the ground, in other words, it refers to the tower as the line of symmetry and radius and the center angle is predetermined Angled fan.
- a bracket may be provided at the bottom of the nacelle 3 of the wind turbine to fix the image capturer 100 on the bracket.
- the present disclosure is not limited to this, and the image capturer 100 may be directly installed on the bottom of the casing of the nacelle 3 without providing a bracket.
- a focal length of more than 20 millimeters (mm) may be selected Camera.
- the tip of the blade 2 and the tower 1 can be within the shooting range of the camera by adjusting the installation position of the camera and/or selecting a camera with a proper focal length, so as to capture a high-quality headroom for the tower Analyze the image.
- the blade tip speed exceeds 80 seconds/meter (m/s) when the wind turbine is in full power. Therefore, the tip of the blade will appear in the shooting range of the camera for about 300 milliseconds (ms). You can capture images containing the tip of the blade, and you can select a camera with a frame rate of more than 20Hz.
- the camera should also have a night vision function.
- the camera's infrared fill light irradiation distance should reach 200 meters.
- FIG. 4 shows a schematic diagram of an image captured by the image capturer 100 according to the first exemplary embodiment of the present disclosure.
- FIG. 4 shows that when the image capturer 100 is set at the bottom of the nacelle 3, the image captured by the image capturer 100 including the tip A of the blade 2 and the tower 1 can be identified by recognizing the image shown in FIG. 4
- the tower headroom S is determined, and the detailed process of tower headroom analysis for the image shown in FIG. 4 will be described later.
- the image capturer 100 may be disposed in a designated area on the side of the wind turbine and at a predetermined distance from the wind turbine to capture the tip and tower of the blade that contains the wind turbine Image.
- FIG. 5 shows a schematic diagram of an installation position of an image capturer according to a second exemplary embodiment of the present disclosure.
- the image capturer 100 may be provided in a designated area on the side of the wind turbine, preferably, a bracket may be provided in the specified area to adjust the height and capture angle of the image capturer 100 to enable image capture
- the imager 100 can capture images including the tip of the blade 2 and the tower 1.
- a protection device may be provided in a designated area on the side of the wind turbine to reduce image capture in a harsh environment 100 captures the impact of the image process.
- FIG. 6 shows a schematic diagram of a protection device for protecting an image capturer according to a second exemplary embodiment of the present disclosure.
- the protection device may include a support plate 11 and a baffle 22.
- the support plate 11 is used to fix the image collector 100, and the shooting height of the image capturer 100 can be adjusted by adjusting the height of the support plate 11 from the ground.
- the baffle 22 is a three-sided baffle used to protect the image capturer 100 on three sides, so that the image capturer 100 is not easily affected by severe windy weather.
- the baffle 22 may be a trapezoidal three-sided baffle.
- protection device shown in FIG. 6 is only an example, and the present disclosure is not limited to this, and those skilled in the art may determine the shape and size of the support plate and the baffle plate according to needs.
- those skilled in the art can also select other types of protection devices to protect the image capture device 100.
- a shielding plate can be added above the image capture device 100, or a transparent protective cover can be provided around the image capture device 100. Wait.
- FIG. 7 shows a schematic diagram of an image captured by an image capturer according to a second exemplary embodiment of the present disclosure.
- FIG. 7 shows that when the image capturer 100 is disposed in a designated area on the side of the wind turbine, the image captured by the image capturer 100 includes the tip A of the blade and the tower tube.
- the image recognition can determine the tower headroom S. The detailed process of tower headroom analysis for the image shown in FIG. 7 will be introduced later.
- the image capturer is provided on the tower, so that the image capturer can be shot from top to bottom in the tower direction or from bottom to top in the tower direction to obtain an image that can be used for tower clearance analysis.
- the processor 200 may be provided in the nacelle of the wind turbine generator for processing the image captured by the image capturer 100.
- the processor 200 may also be located in the monitoring center (or dispatch center) of the wind farm.
- the image capturer 100 may directly send the captured image to the processor 200, or the image capturer 100 may also The captured image is sent to the controller of the wind turbine, and the controller transmits the received image to the processor 200 for tower clearance analysis.
- data transmission can be performed between the image capturer 100 and the processor 200 in a wired manner.
- the image capturer 100 can send the captured image to the processor 200 in a bus manner.
- the present disclosure is not limited to this, and data transmission between the image capturer 100 and the processor 200 may also be performed in a wireless manner.
- the relative positional relationship between the image capturer 100 and the wind turbine is also fixed, so which area in the image captured by the image capturer 100 may be With the tower, which area may contain blades is also relatively fixed.
- the method for determining the tower headroom of a wind turbine may further include: extracting the blade detection head from the acquired image for tower headroom analysis
- the first sensitive area at the tip and the second sensitive area for identifying the edge of the tower can be subjected to tower clearance analysis for the extracted first and second sensitive areas.
- step S20 the position of the tip of the blade of the wind turbine is determined from the acquired image.
- the position of the tip of the blade of the wind turbine can be detected from the first sensitive area.
- the blade tip feature points can be detected from the image used for tower clearance analysis (or in the first sensitive area), and the coordinates corresponding to the detected blade tip feature points can be used as the position of the blade tip.
- various methods can be used to detect leaf tip feature points from the image, which is not limited in this disclosure.
- those skilled in the art may also adopt other methods to detect the position of the tip of the blade from the first sensitive area.
- the leaf tip feature point may be a pixel point in the image that satisfies any of the following cases: the pixel point with the largest gray gradient value in the image, the intersection of any two or more non-parallel straight lines, and the image Pixels where the gradient value of the gray scale is greater than the first set value and the change rate of the gradient direction is greater than the second set value.
- a predetermined window may be used to traverse the first sensitive area to detect the position of the tip of the blade of the wind turbine from the first sensitive area.
- traversing the first sensitive area refers to moving the predetermined window along a preset search route to implement leaf tip feature point detection on the entire first sensitive area.
- the window size of the predetermined window may be set according to actual accuracy requirements.
- the images contained in the predetermined window before and after the movement may not overlap at all, or may partially overlap, which is not limited in this disclosure, and those skilled in the art can select according to actual needs. That is to say, those skilled in the art can determine the size of the predetermined window and the size of the sliding displacement according to requirements, which is not limited in this disclosure.
- step S201 using the current position of the predetermined window as a starting point, the predetermined window is slid in any direction on the first sensitive area.
- step S202 for the sliding in each direction, the degree of gradation change of the pixels in the predetermined window before and after sliding is determined.
- the degree of gradation change of the pixel point may refer to the gradient change speed of the gradation of the pixel point.
- (u, v) represents the offset along the first predetermined direction and the second predetermined direction when the predetermined window slides
- (x, y) represents the coordinate position of the corresponding pixel in the predetermined window
- w (x, y) is the window function.
- the window function can be set to a binary normal distribution with the center of the predetermined window as the origin.
- I(x, y) represents the brightness (intensity) of the pixel
- I(x+u, y+v) represents the brightness of the pixel after sliding (u, v) offset.
- M is a 2 ⁇ 2 matrix
- the expression of matrix M is:
- the formula (2) can be used to determine the degree of gradation change of the pixels in the predetermined window before and after sliding.
- the present disclosure is not limited to this, and those skilled in the art may also use other methods to determine the degree of gradation change.
- step S203 it is judged whether the degree of gradation change satisfies the set condition when sliding in all directions.
- the degree of gradation change of the pixels in the predetermined window before and after sliding meets the set condition means that the degree of gradation change corresponding to sliding in each direction is greater than the set change value (for example, sliding in each direction (The gradient speed of the gray scale of the corresponding pixel point is greater than the set change value).
- step S204 is performed: changing the position of the predetermined window on the first sensitive area, and returning to step S201.
- step S205 it is determined that there is a leaf tip feature in the image contained in the predetermined window at the current position point.
- step S206 the leaf tip feature points are detected from the image included in the current position of the predetermined window, and the coordinates corresponding to the detected leaf tip feature points are determined as the position of the tip of the blade.
- the blade tip feature points can be detected in the manner shown in steps S201 to S205 described above, and the coordinates corresponding to the detected blade tip feature points can be used as the position of the blade tip.
- the position A of the tip of the blade can be detected from the first sensitive area in the above manner.
- the step of detecting the leaf tip feature point from the image included in the current position of the predetermined window may include: maximizing the gradient value of the grayscale and/or the rate of change of the gradient direction in the image included in the image included in the predetermined window at the current position Of pixels are determined as leaf tip feature points.
- blade tip feature point response function (blade tip feature point measurement function) R can be defined according to the following formula:
- ⁇ 1 is the degree of gradient change in the first predetermined direction
- ⁇ 2 is the degree of gradient change in the second predetermined direction
- h is the response coefficient
- the value of the leaf tip feature point response function R can be compared with a predetermined threshold, and when the value of R is greater than or equal to the predetermined threshold, the pixel corresponding to the local maximum of R is determined as the leaf tip Feature points.
- detecting the position of the tip of the blade is to determine the degree of gray change of each pixel in the first sensitive area, preferably, it may be based on the gray change of each sub-pixel in the first sensitive area Degree to detect the position of the tip of the blade, which can improve the accuracy of detecting the position of the tip of the blade.
- a sub-pixel is a pixel between two physical pixels (that is, the pixel mentioned above), and the sub-pixel exists within a gap from the physical pixel. That is to say, it is possible to perform leaf tip feature point detection based on sub-pixel points in the first sensitive area.
- the step of detecting the leaf tip feature points from the first sensitive area may include: detecting a plurality of candidate leaf tip feature points from the first sensitive area; To determine the final leaf tip feature point.
- the tip of the blade is close to the ground, and the tip of the blade is located at the bottom of the blade, so when multiple candidate blade tip feature points are detected, the candidate leaf closest to the ground The sharp feature point is most likely the tip of the blade.
- the candidate closest to the ground can be selected from a plurality of candidate blade tip feature points based on the relative positional relationship between the image capturer 100 used to capture the image for tower clearance analysis and the wind turbine
- the leaf tip feature point serves as the final leaf tip feature point (ie, the tip of the blade).
- the point with the largest Y-axis coordinate value among the plurality of candidate blade tip feature points is determined as the final Characteristic point of the leaf tip.
- the point with the smallest Y-axis coordinate value among the plurality of candidate leaf tip feature points (that is, the lowest candidate leaf tip feature point in the first sensitive area) is determined It is the final leaf tip feature point.
- points A, A1, and A2 shown in FIG. 7 represent a plurality of points obtained when performing leaf tip feature point detection based on sub-pixel points in the first sensitive area.
- the point A with the smallest Y-axis coordinate value may be determined as the final leaf tip feature point, that is, the coordinates corresponding to point A may be determined as the position of the tip of the blade.
- FIG. 8 illustrates the steps of detecting the position of the tip of the blade from the first sensitive area by taking the example of extracting the first sensitive area from the image used for the tower clearance analysis.
- the present disclosure is not limited to this, and the method of detecting the position of the tip of the blade shown in FIG. 8 is also applicable to the case of detecting the position of the tip of the blade from the image used for tower clearance analysis (from the captured image). In this case, it is necessary to use the predetermined window to traverse the entire image for tower clearance analysis. When the predetermined window is at any position on the image for tower clearance analysis, you can use the method shown in Figure 8 to The position of the tip of the blade is detected in the image contained in the window.
- a straight line can be identified from an image through a straight line detection method to determine the intersection of two or more straight lines as a leaf tip feature point.
- step S30 the edge of the tower is identified from the acquired image.
- the designated point in the image can be used as the edge of the tower.
- the designated point may be a pixel point in the image corresponding to a point on the tower used for determining the tower clearance determined on the basis of the relative relationship between the image capturer and the tower of the wind turbine. That is to say, the designated point may be a pixel point corresponding to the image in the position where the blade is most likely to contact the tower during operation.
- point B is a designated point that is the edge of the tower in the image.
- the edge of the tower can be identified by performing edge detection (or straight line detection) on the image.
- the edge of the tower can be identified from the second sensitive area.
- various straight line detection methods may be used to detect a straight line from the second sensitive area, and use the detected straight line as the edge of the tower, but the present disclosure is not limited to this, and other methods may be used to identify from the second sensitive area
- the edge of the tower is determined by, for example, identifying the preset mark for indicating the edge of the tower from the second sensitive area.
- FIG. 9 shows a flowchart of the step of identifying the edge of the tower according to an exemplary embodiment of the present disclosure.
- step S301 multiple edge feature points are extracted from the second sensitive area.
- the image corresponding to the second sensitive area may be converted into a grayscale image, and edge feature points may be extracted from the converted grayscale image.
- edge feature points can also be extracted in other ways.
- step S302 the extracted multiple edge feature points are mapped into the parameter space, and corresponding straight lines are drawn in the parameter space based on the multiple edge feature points.
- these three straight lines intersect at the same point (1,0)
- the horizontal and vertical coordinates of this point are the slope and intercept of the straight line in the image space. That is to say, when the intersection point of multiple straight lines is found in the parameter space, the straight line in the image space can be determined.
- step S303 at least one aggregation point in the parameter space is determined.
- the at least one gathering point is a point where a straight line exceeds a predetermined number.
- step S304 at least one straight line in the second sensitive area is determined according to the coordinate value of the at least one gathering point, and the edge of the tower barrel is determined based on the at least one straight line.
- the step of determining at least one straight line in the second sensitive area according to the coordinate value of at least one gathering point may include: for each gathering point, use the abscissa of the gathering point as the slope of the straight line, and the longitudinal of the gathering point The coordinates are used as the intercept of the straight line to obtain a straight line corresponding to the gathering point in the second sensitive area. That is to say, the edge feature points can be extracted from the second sensitive area (ie, the image space) based on the predetermined coordinate system of the image space, and after determining the aggregation point, the corresponding straight line can be drawn under the predetermined coordinate system.
- the step of determining the edge of the tower barrel based on at least one straight line may include: determining the edge of the tower barrel based on the fitted straight line obtained after the fitting by fitting the determined at least one straight line.
- a straight line with a relative distance less than a specified distance can be selected from at least one straight line for fitting.
- the obtained fitted straight line is used as the edge of the tower, and two pieces are obtained after fitting.
- fitting a straight line use the line connecting the midpoints of the two fitted straight lines as the edge of the tower.
- the line connecting the midpoints of the two straight lines may be determined as the edge of the tower.
- a straight line L in the second sensitive area is obtained by fitting, and the straight line L is determined as the edge of the tower barrel.
- the distance from the point to the straight line can be used to determine the distance from the tip of the blade to the edge of the tower.
- the above manner of determining the tower edge by fitting at least one straight line is only an example, and the present disclosure is not limited thereto, and other ways of determining the tower edge are also feasible.
- the length of each straight line can be calculated, and the longest straight line is selected as the edge of the tower.
- FIG. 9 takes the example of extracting the second sensitive area from the image used for the tower headroom analysis as an example to introduce the steps of identifying the edge of the tower barrel from the second sensitive area.
- the present disclosure is not limited to this, and the method of identifying the edge of the tower shown in FIG. 9 is also applicable to the case of identifying the edge of the tower from the image used for the tower clearance analysis.
- multiple edge feature points can be extracted from the image used for tower headroom analysis to identify the edge of the tower.
- edge information can be extracted from the second sensitive area, such as extracting multiple edge points, and fitting the multiple edge points to obtain an edge straight line as the edge of the tower.
- step S40 according to the determined position of the tip of the blade and the identified cylinder edge of the tower, the distance from the blade tip to the edge of the tower cylinder is calculated to obtain the tower headroom.
- the vertical distance from the position of the tip of the blade (such as the coordinate position) to the straight line corresponding to the edge of the tower can be calculated as the tower clearance.
- the step of calculating the distance from the tip of the blade to the edge of the tower to obtain tower clearance may include: according to the determined position and identification of the tip of the blade Calculate the pixel distance from the tip of the blade to the edge of the tower; based on the correspondence between the predetermined pixel distance between any two pixels and the actual distance, use the tip of the blade to the edge of the tower The pixel distance calculates the actual distance from the tip of the blade to the edge of the tower, and determines the actual distance as the tower clearance.
- any two pixels may be two adjacent pixels or two pixels specified on the image.
- FIG. 10 shows a block diagram of an apparatus for determining a tower headroom of a wind turbine according to an exemplary embodiment of the present disclosure.
- the apparatus for determining the tower headroom of a wind turbine includes an image acquisition module 10, a blade tip detection module 20, a tower edge recognition module 30 and a tower headroom determination module 40.
- the image acquisition module 10 acquires images of the wind turbine during operation.
- the acquired images include the tips of the blades of the wind turbine and the tower.
- the image acquisition module 10 may acquire images of the blades of the wind turbine during operation, and determine that the images of the blades during the operation include the tips of the blades of the wind turbine and the tower tube for tower clearance analysis Image.
- an image capturer can be used to capture images of the blades of the wind turbine during operation, and then the image capturer sends the captured images to the image acquisition module 10.
- the installation position of the image capturer can be reasonably set so that the image capturer can capture images including the tips of the blades of the wind turbine and the tower.
- the following describes two installation examples of the image capturer.
- the image capturer may be arranged at the bottom of the nacelle of the wind turbine to capture images including the tips of the blades of the wind turbine and the tower.
- the image capture device can be located on the side of the wind turbine and the distance between the wind turbine and the wind turbine is a predetermined distance in a specified area to capture the tip of the wind turbine blade and tower image.
- the device for determining the tower headroom of a wind turbine may further include: a sensitive area extraction module (not shown in the figure), which is used to detect blades from the acquired image The first sensitive area at the tip of the and the second sensitive area used to identify the edge of the tower, the tower headroom analysis can be performed on the extracted first and second sensitive areas later.
- a sensitive area extraction module (not shown in the figure), which is used to detect blades from the acquired image The first sensitive area at the tip of the and the second sensitive area used to identify the edge of the tower, the tower headroom analysis can be performed on the extracted first and second sensitive areas later.
- the blade tip detection module 20 determines the position of the tip of the blade of the wind turbine from the acquired image.
- the blade tip detection module 20 may determine the position of the tip of the blade of the wind turbine from the first sensitive area.
- the blade tip detection module 20 can use a predetermined window to traverse the first sensitive area.
- the predetermined window is at any position on the first sensitive area, the blade tip detection module 20 can be included from the predetermined window in the following manner The position of the tip of the blade is detected in the image:
- the blade tip detection module 20 may determine the pixel point with the largest gradient value of grayscale and/or the highest rate of change in gradient direction in the image contained when the predetermined window is at any position as the blade tip feature point.
- the present disclosure is not limited to this, and the intersection point of any two or more non-parallel straight lines may also be determined as the blade tip characteristic point.
- the blade tip detection module 20 may detect multiple candidate leaf tip feature points from the first sensitive area, and determine the final leaf tip feature point from the multiple candidate leaf tip feature points according to a preset condition.
- the blade tip detection module 20 selects the candidate blade tip feature closest to the ground from a plurality of candidate blade tip feature points based on the relative positional relationship between the image capturer used to capture the image for tower clearance analysis and the wind turbine The point is used as the final leaf tip characteristic point.
- the blade tip detection module 20 may determine the point with the largest Y-axis coordinate value among the plurality of candidate blade tip feature points as the final blade tip feature point.
- the blade tip detection module 20 may determine the point with the smallest Y-axis coordinate value among the plurality of candidate blade tip feature points as the final blade tip feature point.
- the tower edge recognition module 30 recognizes the edge of the tower from the acquired image.
- the tower edge identification module 30 may identify the edge of the tower from the second sensitive area.
- the tower edge recognition module 30 may use the designated point in the image as the edge of the tower.
- the designated point may be a pixel point in the image corresponding to a point on the tower used for determining the tower clearance determined on the basis of the relative relationship between the image capturer and the tower of the wind turbine. That is to say, the designated point may be a pixel point corresponding to the image in the position where the blade is most likely to contact the tower during operation.
- the tower edge recognition module 30 may identify the edge of the tower by performing edge detection on the image.
- the tower edge identification module 30 may use various image recognition methods to identify the edge of the tower from the second sensitive area. The function of the tower edge recognition module 30 will be described below with reference to FIG. 11. It should be understood that the method for identifying the edge of the tower shown in FIG. 11 is only a preferred example, and other image recognition methods for identifying the edge of the tower are also feasible.
- FIG. 11 shows a block diagram of a tower edge recognition module 30 according to an exemplary embodiment of the present disclosure.
- the tower edge recognition module 30 may include a feature extraction submodule 301, a conversion submodule 302, an aggregation point determination submodule 303 and an edge determination submodule 304.
- the feature extraction submodule 301 extracts multiple edge feature points from the second sensitive area.
- the feature extraction submodule 301 may convert the image corresponding to the second sensitive area into a grayscale image, and extract edge feature points from the converted grayscale image.
- the conversion sub-module 302 maps the extracted multiple edge feature points into the parameter space, and draws corresponding straight lines in the parameter space based on the multiple edge feature points.
- the aggregation point determination submodule 303 determines at least one aggregation point in the parameter space.
- the at least one gathering point is a point where a straight line exceeds a predetermined number.
- step 303 of FIG. 9 Since the detailed process of the aggregation point determination sub-module 303 determining at least one aggregation point has been described in step 303 of FIG. 9, the content of this part of the present disclosure will not be repeated here.
- the edge determination submodule 304 determines at least one straight line in the second sensitive area according to the coordinate value of the at least one gathering point, and determines the edge of the tower barrel based on the at least one straight line.
- the edge determination submodule 304 may use the horizontal coordinate of the aggregation point as the slope of the straight line, and the vertical coordinate of the aggregation point as the intercept of the straight line to obtain the aggregation point in the second sensitive area. Corresponding straight line.
- the edge determination submodule 304 may select a straight line with a relative distance less than a specified distance from at least one straight line to perform fitting.
- a fitted straight line is obtained after fitting, the obtained fitted straight line is used as the edge of the tower.
- two fitted straight lines are obtained after closing, the line connecting the midpoints of the two fitted straight lines is taken as the edge of the tower.
- the tower clearance determination module 40 calculates the distance from the tip of the blade to the edge of the tower based on the determined position of the tip of the blade and the identified edge of the tower to obtain the tower clearance. For example, the tower headroom determination module 40 may calculate the vertical distance from the position of the tip of the blade to the straight line corresponding to the edge of the tower barrel as the tower headroom.
- the tower clearance determination module 40 may calculate the pixel distance from the tip of the blade to the edge of the tower according to the determined position of the blade tip and the identified edge of the tower, based on the predetermined pixel distance between any two pixels and The corresponding relationship of the actual distance is used to calculate the actual distance from the tip of the blade to the edge of the tower using the pixel distance from the tip of the blade to the edge of the tower, and the actual distance is determined as the tower headroom.
- Exemplary embodiments according to the present disclosure also provide a computer-readable storage medium storing a computer program.
- the computer-readable storage medium stores a computer program that, when executed by the processor, causes the processor to execute the above method for determining the tower headroom of the wind turbine.
- the computer-readable recording medium is any data storage device that can store data read by a computer system. Examples of computer-readable recording media include read-only memory, random-access memory, read-only optical disks, magnetic tapes, floppy disks, optical data storage devices, and carrier waves (such as data transmission through the Internet via wired or wireless transmission paths).
- the tower headroom of the wind power generator can be monitored in real time to effectively avoid the losses caused by the blade sweeping tower.
- the method and device for determining the tower headroom of the wind power generator set according to the exemplary embodiments of the present disclosure can not only fully realize the tower by properly designing the bracket for supporting the image capture device and selecting the installation position of the image capture device
- the function of headroom video monitoring can also ensure the safe operation of wind turbines.
- the tower headroom of the wind power generator can be obtained relatively simply, without manual measurement, and is convenient and quick.
- the tip of the blade is detected based on the blade tip feature point detection method, and the edge of the tower barrel can also be identified by a straight line detection method, thereby The distance between the tip of the blade and the edge of the tower.
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Abstract
Description
Claims (13)
- 一种确定风力发电机组的塔架净空的方法,所述方法包括:获取风力发电机组在运行过程中的图像,所述图像包括所述风力发电机组的叶片的尖端以及塔筒;从获取的图像中确定所述风力发电机组的叶片的尖端的位置;从获取的图像中识别所述塔筒的边缘;根据确定的叶片的尖端的位置和识别的塔筒的边缘,计算叶片的尖端到塔筒的边缘的距离以获得塔架净空。
- 如权利要求1所述的方法,其中,所述方法还包括:从获取的图像中提取用于检测叶片的尖端的第一敏感区域和用于识别塔筒的边缘的第二敏感区域,其中,从第一敏感区域中确定所述风力发电机组的叶片的尖端的位置,从第二敏感区域中识别所述塔筒的边缘。
- 如权利要求2所述的方法,其中,从第一敏感区域中确定所述风力发电机组的叶片的尖端的位置包括:使用一预定窗口遍历第一敏感区域,当所述预定窗口处于第一敏感区域上的任一位置时,通过以下方式从所述预定窗口内包含的图像中检测叶片的尖端的位置:以所述任一位置为起点,在第一敏感区域上沿任意方向滑动所述预定窗口;针对沿每个方向的滑动,确定滑动前与滑动后所述预定窗口内的像素点的灰度变化程度,并判断所述灰度变化程度是否满足设定条件;如果针对沿所有方向的滑动,滑动前与滑动后所述预定窗口内的像素点的灰度变化程度均满足设定条件,则确定所述预定窗口在所述任一位置时包含的图像中存在叶尖特征点;从所述预定窗口在所述任一位置时包含的图像中检测叶尖特征点,并将检测到的叶尖特征点对应的坐标确定为叶片的尖端的位置。
- 如权利要求3所述的方法,其中,从所述预定窗口在所述任一位置时包含的图像中检测叶尖特征点包括:将所述预定窗口在所述任一位置时包含的图像中灰度的梯度值和/或梯 度方向的变化速率最高的像素点确定为叶尖特征点。
- 如权利要求2所述的方法,其中,从第一敏感区域中确定所述风力发电机组的叶片的尖端的位置包括:从第一敏感区域中检测出多个候选叶尖特征点;根据预设条件从所述多个候选叶尖特征点中确定最终的叶尖特征点。
- 如权利要求5所述的方法,其中,用于捕获风力发电机组在运行过程中的图像的图像捕获器被设置在风力发电机组的机舱底部,或者所述图像捕获器被设置在位于风力发电机组侧面且与风力发电机组之间的距离为预定距离的指定区域内,其中,根据预设条件从所述多个候选叶尖特征点中确定最终的叶尖特征点包括:当所述图像捕获器被设置在机舱底部时,将所述多个候选叶尖特征点中的Y轴坐标值最大的点确定为最终的叶尖特征点;当所述图像捕获器被设置在所述指定区域内时,将所述多个候选叶尖特征点中的Y轴坐标值最小的点确定为最终的叶尖特征点。
- 如权利要求2所述的方法,其中,从第二敏感区域中识别所述塔筒的边缘包括:从第二敏感区域中提取多个边缘特征点;将所述多个边缘特征点映射到参数空间中,并基于所述多个边缘特征点在参数空间绘制对应的多条直线;确定参数空间中的至少一个聚集点,所述至少一个聚集点为超过预定数量直线通过的点;根据所述至少一个聚集点的坐标值确定在第二敏感区域中的至少一条直线,基于所述至少一条直线确定塔筒的边缘。
- 如权利要求7所述的方法,其中,根据所述至少一个聚集点的坐标值确定在第二敏感区域中的至少一条直线包括:针对每个聚集点,将该聚集点的横坐标作为直线的斜率,将该聚集点的纵坐标作为直线的截距,得到在第二敏感区域中的与该聚集点对应的直线。
- 如权利要求7所述的方法,其中,基于所述至少一条直线确定塔筒的边缘包括:当对所述至少一条直线进行拟合获得一条拟合直线时,将得到的拟合直 线作为塔筒的边缘;或者,当对所述至少一条直线进行拟合获得两条拟合直线时,将连接所述两条拟合直线的中点的连线作为塔筒的边缘。
- 如权利要求1所述的方法,其中,根据确定的叶片的尖端的位置和识别的塔筒的边缘,计算叶片的尖端到塔筒的边缘的距离以获得塔架净空包括:根据确定的叶片的尖端的位置和识别的塔筒的边缘,计算叶片的尖端到塔筒的边缘的像素距离;基于预先确定的任意两个像素之间的像素距离与实际距离的对应关系,来利用叶片的尖端到塔筒的边缘的像素距离计算叶片的尖端到塔筒的边缘的实际距离,将所述实际距离确定为塔架净空。
- 一种确定风力发电机组的塔架净空的装置,所述装置包括:图像获取模块,被配置为获取风力发电机组在运行过程中的图像,所述图像包括所述风力发电机组的叶片的尖端以及塔筒;叶尖检测模块,被配置为从获取的图像中确定所述风力发电机组的叶片的尖端的位置;塔筒边缘识别模块,被配置为从获取的图像中识别所述塔筒的边缘;塔架净空确定模块,被配置为根据确定的叶片的尖端的位置和识别的塔筒的边缘,计算叶片的尖端到塔筒的边缘的距离以获得塔架净空。
- 一种塔架净空监测系统,所述塔架净空监测系统包括:图像捕获器,用于捕获风力发电机组的叶片在运行过程中的图像;处理器,被配置为:从所捕获的图像中获取包括所述风力发电机组的叶片的尖端以及塔筒的图像;从获取的图像中确定所述风力发电机组的叶片的尖端的位置;从获取的图像中识别所述塔筒的边缘;根据确定的叶片的尖端的位置和识别的塔筒的边缘,计算叶片的尖端到塔筒的边缘的距离以获得塔架净空。
- 一种存储有计算机程序的计算机可读存储介质,当所述计算机程序在被处理器执行时实现如权利要求1至10中任意一项所述的确定风力发电机组的塔架净空的方法。
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