CN116906276A - Intelligent inspection method for fan blade - Google Patents
Intelligent inspection method for fan blade Download PDFInfo
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- CN116906276A CN116906276A CN202310685109.2A CN202310685109A CN116906276A CN 116906276 A CN116906276 A CN 116906276A CN 202310685109 A CN202310685109 A CN 202310685109A CN 116906276 A CN116906276 A CN 116906276A
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- 238000000034 method Methods 0.000 title claims abstract description 48
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- 230000007547 defect Effects 0.000 abstract description 4
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Classifications
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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
- F03D17/001—Inspection
- F03D17/004—Inspection by using remote inspection vehicles, e.g. robots or drones
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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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U10/00—Type of UAV
- B64U10/10—Rotorcrafts
- B64U10/13—Flying platforms
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U20/00—Constructional aspects of UAVs
- B64U20/80—Arrangement of on-board electronics, e.g. avionics systems or wiring
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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
- F03D17/001—Inspection
- F03D17/003—Inspection characterised by using optical devices, e.g. lidar or cameras
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
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Abstract
The invention relates to the technical field of fan blade inspection, in particular to an intelligent inspection method for fan blades, which comprises the following steps: step 1, acquiring data information of a fan to be inspected, and determining inspection time; step 2, determining the take-off position of the unmanned aerial vehicle according to the blade orientation of the fan to be inspected, and inspecting the state of the unmanned aerial vehicle; step 3, detecting the fan to be inspected, establishing a model of the fan to be inspected, and determining an inspection path; step 4, automatically inspecting the fan to be inspected according to the inspection path, and monitoring the inspection process by using a remote control device; step 5, uploading the data information acquired by inspection to a cloud data platform, and analyzing the health state of the wind power blade; based on automatic inspection of the unmanned aerial vehicle, the time for stopping and overhauling the fan is reduced by combining the data information of the existing system in the wind power plant, and the electricity generating efficiency of the fan is improved; and judging the health state of the blade in time, finding out the defects to solve the defects in time, and prolonging the service life of the blade.
Description
Technical Field
The invention relates to the technical field of fan blade inspection, in particular to an intelligent inspection method for fan blades.
Background
The blade is a very critical component in a wind power generator set, and its aerodynamic efficiency determines the wind power generator set's ability to utilize wind energy. This requires that the blade not only have optimal mechanical properties and fatigue strength, but also have corrosion resistance, uv irradiation and lightning protection properties. The blade is inevitably rubbed and impacted with sand and dust and particles in the air when rotating at high speed, so that the front edge of the blade is ground, and the front edge bonding is cracked. In addition, with the increase of the service life of the fan, sand holes and cracks can appear after the gel coats on the surfaces of the blades are worn and fall off. The sand holes can cause blade resistance to increase so as to influence the generated energy, and once the generated energy becomes through cavity sand holes, water can be accumulated so as to reduce lightning protection indexes. More and more wind power plants are arranged at sea, and the sea-washing gift with blades facing high salt mist is easily corroded.
In the domestic and foreign wind power industry, the traditional inspection mode of the fan blade is telescope inspection or hanging basket spider man climbing inspection, wherein the telescope inspection has the problems of unclear and incomplete inspection, and estimation and judgment can only be carried out subjectively by personnel. And the mode of hanging flower basket or spider man is adopted, has the problem that the security risk is big, and the cost of labor is high, inefficiency. On the basis, two novel inspection modes of shooting the blade through a ground high-power camera and shooting the blade through an unmanned aerial vehicle are derived. The ground high-power camera inspection mode can be used for clearly and completely shooting the fan blades, but equipment is expensive, the use environment is limited, the blades need to be adjusted to be matched with the ground camera to shoot, the whole working time is long, and the average shooting of a 2MW fan needs to consume about 1 half hour. The unmanned aerial vehicle inspection mode is divided into manual inspection and automatic inspection at present, and the manual inspection has the adverse factors of being greatly influenced by flying hands, uncontrolled shooting quality and the like. Automatic inspection of unmanned aerial vehicle has automatic inspection after the path planning and real-time modeling's automatic inspection at present. The automatic inspection of the advanced path planning has the problems that the workload is increased, the direction of the fan for each shutdown of the motion mechanism is different before each inspection, the modeling is needed again, and the parameters input by people do not necessarily meet the actual conditions.
Therefore, how to quickly and effectively inspect the fan blade is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides an intelligent inspection method for fan blades, which uses an unmanned aerial vehicle to combine data information of the existing system in a wind power plant, builds a model for a wind driven generator, and generates an automatic inspection route, thereby realizing automatic inspection for the wind driven generator and improving inspection efficiency.
In order to achieve the above purpose, the present invention provides the following technical solutions:
preferably, the above-mentioned intelligent inspection method for wind power blade includes:
step 1, acquiring data information of a fan to be inspected, and determining inspection time;
step 2, determining the take-off position of the unmanned aerial vehicle according to the blade orientation of the fan to be inspected, and inspecting the state of the unmanned aerial vehicle;
step 3, detecting the fan to be inspected, establishing a model of the fan to be inspected, and determining an inspection path;
step 4, automatically inspecting the fan to be inspected according to the inspection path, and monitoring the inspection process by using a remote control device;
and 5, uploading the data information acquired by inspection to a cloud data platform, and analyzing the health state of the wind power blade.
Preferably, in the above intelligent inspection method for a wind power blade, the acquiring data information of a fan to be inspected, determining inspection time includes:
step 1-1, acquiring the position of a fan to be patrolled and examined according to an existing wind power plant fan distribution map;
step 1-2, acquiring current and predicted running environment information of a fan to be patrolled and examined through an existing weather prediction system in a wind power plant;
step 1-3, determining the inspection time of the fan to be inspected according to the position and the operation environment information of the fan to be inspected;
and 1-4, stopping the fan to be inspected according to the inspection time by an existing monitoring center in the wind power plant, locking the wind wheel and adjusting the rotation angle of the wind wheel.
Preferably, in the above intelligent inspection method for a wind power blade, the detecting of the fan to be inspected, the establishing of a model of the fan to be inspected, and the determining of the inspection path include:
step 3-1, starting an unmanned aerial vehicle, flying to the horizontal height of a fan hub, collecting the current overall shape of the fan, and transmitting collected data information to a cloud data platform;
step 3-2, the cloud data platform inputs the image information of the current form of the fan into a three-dimensional model of the fan for training to obtain a fan model of the current form;
and 3-3, determining a routing inspection path of the unmanned aerial vehicle according to the fan model, and sending routing inspection path information to the unmanned aerial vehicle.
Preferably, in the above intelligent inspection method for a wind turbine blade, the cloud data platform inputs image information of a current shape of a fan into a three-dimensional model of the fan for training, to obtain a fan model of the current shape, and the method includes:
step 3-21, determining the position of the current blade of the fan according to the image information of the current form of the fan;
step 3-22, obtaining a blade pitch angle when the fan is locked in a halt mode;
and 3-23, inputting the information into an existing fan three-dimensional model for training according to the position and pitch angle information of the fan blades, and obtaining a fan model in the current form.
Preferably, in the above intelligent inspection method for a wind power blade, determining an inspection path of an unmanned aerial vehicle according to a fan model includes:
3-31, establishing a space coordinate system by taking the center of a fan hub as an origin 0, wherein in the space coordinate system, an X axis is parallel to the ground, a Y axis is perpendicular to the ground, and a Z axis is perpendicular to a fan blade;
step 3-32, acquiring the data information of the whole fan and combining the space coordinate system to determine the positions of the points of the fan in the coordinate system;
and 3-33, determining the routing inspection path of the unmanned aerial vehicle in the space coordinate system according to the fan model.
Preferably, in the above intelligent inspection method for a wind power blade, the determining, according to a fan model, an inspection path of the unmanned aerial vehicle in the space coordinate system includes:
step 3-331, obtaining a cross-section graph of the fan blade, and determining a shooting center point and a shooting angle of the fan blade according to graph information;
step 3-332, determining a shooting path on a fan blade according to a shooting center point, and determining a patrol travel path of the unmanned aerial vehicle according to a shooting angle;
and 3-333, determining a hovering point of the unmanned aerial vehicle on the inspection driving path according to the length of the fan blade and the change trend of the fan blade.
Preferably, in the above intelligent inspection method for a wind power blade, the automatically inspecting the fan to be inspected according to the inspection path includes:
step 4-1, starting the unmanned aerial vehicle, flying to a position corresponding to the center of the fan hub, determining the distance between the unmanned aerial vehicle and the center of the fan hub through a laser radar, and determining the position of the unmanned aerial vehicle in the space coordinate system according to the distance;
step 4-2, adjusting along the Z axis of the space coordinate system according to the current position, and entering the initial position of the inspection path;
step 4-3, starting to patrol the fan blade according to the sequence of the patrol path, and acquiring images of the blade when the fan blade reaches the hovering position;
and 4-4, judging the end heads of the fan blades, finishing the current inspection path inspection, and returning the current inspection path to the hub of the fan to perform repositioning, and inspecting the next inspection path.
Preferably, in the above intelligent inspection method for a wind power blade, when reaching a hover position, image acquisition is performed on the blade, including:
step 4-31, adjusting the shooting angle of the cradle head according to the position of the fan blade in the image, so that the fan blade is positioned in the center of the image;
step 4-32, detecting the size of a fan blade in the image, and when the fan blade is smaller than 1/2 of the total size of the image, adjusting the hovering position of the unmanned aerial vehicle, and increasing the duty ratio of the fan blade image;
and 4-33, maintaining the distance and shooting angle between the current hovering position and the fan blade, driving to the next hovering point for shooting, and repeatedly executing the steps 4-31.
Preferably, in the above intelligent inspection method for a wind power blade, the monitoring of the inspection process by using a remote control device includes:
acquiring a shooting image of the unmanned aerial vehicle in real time through a wireless technology, confirming the image, and sending the confirmed image to a cloud data platform;
when the unmanned aerial vehicle gives out an abnormal operation alarm, one-key return or switching is carried out through the remote control device to manually control the unmanned aerial vehicle to land.
Preferably, in the above-mentioned intelligent inspection method for wind turbine blade, the uploading the data information collected by inspection to the cloud data platform analyzes the health status of the wind turbine blade, including:
step 5-1, carrying out front-back background segmentation on the image information of the blades on a patrol path, splicing the image information into a complete fan blade image by combining the original data and using a foreground splicing algorithm, and judging whether missing occurs in blade shooting;
step 5-2, dividing the blade into a non-obstacle area and an obstacle area based on the image after the blade foreground segmentation, and performing fault screening model training;
step 5-3, judging each picture through a fault screening model, filtering out fault-free image information, judging the fault type and severity of the faulty image information, and classifying the faults through the fault type and severity to form a fault report;
and 5-4, assessing the health condition of the fan blade through a fault report.
Compared with the prior art, the invention has the beneficial effects that:
1. based on automatic inspection of the unmanned aerial vehicle, the time for stopping and overhauling the fan is effectively reduced by combining the data information of the existing system in the wind power plant, and the electricity generating efficiency of the fan is improved;
2. based on unmanned aerial vehicle to fan form's on-the-spot collection, adjust through existing three-dimensional model, realized the quick modeling of ready-made, reduced work load, improved the precision of inspection route.
3. Based on modeling, a space coordinate system is established, and a laser radar is used as an aid to accurately determine a patrol path of the unmanned aerial vehicle, so that patrol efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic view of an inspection scene of the unmanned aerial vehicle.
Fig. 3 is a control schematic diagram of the automatic inspection device of the unmanned aerial vehicle.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the present invention, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance; the term "plurality" means two or more, unless expressly defined otherwise. The terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; "coupled" may be directly coupled or indirectly coupled through intermediaries. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present invention, it should be understood that the directions or positional relationships indicated by the terms "upper", "lower", "left", "right", "front", "rear", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or units referred to must have a specific direction, be constructed and operated in a specific direction, and thus should not be construed as limiting the present invention.
In the description of the present specification, the terms "one embodiment," "some embodiments," "particular embodiments," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
As shown in fig. 1, the embodiment of the invention discloses an intelligent inspection method for a wind power blade, which comprises the following steps:
step 1, acquiring data information of a fan to be inspected, and determining inspection time;
step 2, determining the take-off position of the unmanned aerial vehicle according to the blade orientation of the fan to be inspected, and inspecting the state of the unmanned aerial vehicle;
according to the geographical environment near the fan, selecting a position which is closer to the fan, wherein the position is opposite to the fan blade as much as possible; and checking and ensuring the electric quantity of the unmanned aerial vehicle and other equipment between the inspection and the normal operation of the inspection equipment.
Step 3, detecting the fan to be inspected, establishing a model of the fan to be inspected, and determining an inspection path;
step 4, automatically inspecting the fan to be inspected according to the inspection path, and monitoring the inspection process by using a remote control device;
and 5, uploading the data information acquired by inspection to a cloud data platform, and analyzing the health state of the wind power blade.
The beneficial effects of the embodiment are as follows: based on automatic inspection of the unmanned aerial vehicle, the time for stopping and overhauling the fan is effectively reduced by combining the data information of the existing system in the wind power plant, and the electricity generating efficiency of the fan is improved; and judging the health state of the blade in time, finding out the defects to solve the defects in time, and prolonging the service life of the blade.
In one embodiment, an intelligent inspection method for a wind turbine blade acquires data information of a fan to be inspected, and determines inspection time, including:
step 1-1, acquiring the position of a fan to be patrolled and examined according to an existing wind power plant fan distribution map;
step 1-2, acquiring current and predicted running environment information of a fan to be patrolled and examined through an existing weather prediction system in a wind power plant;
step 1-3, determining the inspection time of the fan to be inspected according to the position and the operation environment information of the fan to be inspected;
and 1-4, stopping the fan to be inspected according to the inspection time by an existing monitoring center in the wind power plant, locking the wind wheel and adjusting the rotation angle of the wind wheel.
In the above embodiments, both the map and weather prediction systems are state of the art, as is well known to those skilled in the art, and are conventionally deployed within a wind farm;
the beneficial effects of the embodiment are as follows: through the current system in the wind power plant, combine unmanned aerial vehicle's condition of patrolling and examining, can effectively avoid unmanned aerial vehicle scene unable condition of patrolling and examining to take place, reduce the downtime of fan, improve the power efficiency.
In one embodiment, an intelligent inspection method for a wind power blade detects a fan to be inspected, establishes a model of the fan to be inspected, and determines an inspection path, including:
step 3-1, starting an unmanned aerial vehicle, flying to the horizontal height of a fan hub, collecting the current overall shape of the fan, and transmitting collected data information to a cloud data platform;
step 3-2, the cloud data platform inputs the image information of the current form of the fan into a three-dimensional model of the fan for training to obtain a fan model of the current form;
and 3-3, determining a routing inspection path of the unmanned aerial vehicle according to the fan model, and sending routing inspection path information to the unmanned aerial vehicle.
In the embodiment, the unmanned aerial vehicle shoots the position image of the fan blade, and effective data support can be provided for routing inspection path planning and on-site modeling.
In one embodiment, an intelligent inspection method for a wind power blade, a cloud data platform inputs image information of a current shape of a fan into a three-dimensional model of the fan for training, and obtains the fan model of the current shape, including:
step 3-21, determining the position of the current blade of the fan according to the image information of the current form of the fan;
step 3-22, obtaining a blade pitch angle when the fan is locked in a halt mode;
and 3-23, inputting the information into an existing fan three-dimensional model for training according to the position and pitch angle information of the fan blades, and obtaining a fan model in the current form.
Because the interface of the fan blade is in a salix leaf shape, a windward side and a leeward side exist, and the pitch angle of the blade determines the shooting angle of the unmanned aerial vehicle when the image acquisition is carried out.
In one embodiment, an intelligent inspection method for a wind power blade, determining an inspection path of an unmanned aerial vehicle according to a fan model, includes:
3-31, establishing a space coordinate system by taking the center of a fan hub as an origin 0, wherein in the space coordinate system, an X axis is parallel to the ground, a Y axis is perpendicular to the ground, and a Z axis is perpendicular to the fan blade;
step 3-32, acquiring the data information of the whole fan and combining a space coordinate system, and determining the positions of each point of the fan in the coordinate system;
and 3-33, determining the inspection path of the unmanned aerial vehicle in the space coordinate system according to the fan model.
Wherein, establishing space coordinate axis is unmanned aerial vehicle planning route for prior art.
In one embodiment, an intelligent inspection method for a wind power blade, determining an inspection path of an unmanned aerial vehicle in a space coordinate system according to a fan model, includes:
step 3-331, obtaining a cross-section graph of the fan blade, and determining a shooting center point and a shooting angle of the fan blade according to graph information;
step 3-332, determining a shooting path on a fan blade according to a shooting center point, and determining a patrol travel path of the unmanned aerial vehicle according to a shooting angle;
and 3-333, determining a hovering point of the unmanned aerial vehicle on the inspection driving path according to the length of the fan blade and the change trend of the fan blade.
In the embodiment, 4 inspection paths are planned for one fan blade, wherein 2 fan blades face the wind and 2 fan blades face the lee;
the edges of the fan blades can be shot at the shooting angles, and the shooting images of the windward side and the leeward side are overlapped, so that the shooting integrity of the blades is ensured.
In one embodiment, an intelligent inspection method for a wind power blade automatically inspects a fan to be inspected according to an inspection path, including:
step 4-1, starting the unmanned aerial vehicle, flying to a position corresponding to the center of the fan hub, determining the distance between the unmanned aerial vehicle and the center of the fan hub through a laser radar, and determining the position of the unmanned aerial vehicle in a space coordinate system according to the distance;
step 4-2, adjusting along the Z axis of the space coordinate system according to the current position, and entering the initial position of the inspection path;
step 4-3, starting to patrol the fan blade according to the sequence of the patrol path, and acquiring images of the blade when the fan blade reaches the hovering position;
and 4-4, judging the end heads of the fan blades, finishing the current inspection path inspection, and returning the current inspection path to the hub of the fan to perform repositioning, and inspecting the next inspection path.
Wherein, carry out image acquisition to the blade when reaching the position of hovering, include:
step 4-31, adjusting the shooting angle of the cradle head according to the position of the fan blade in the image, so that the fan blade is positioned in the center of the image;
step 4-32, detecting the size of a fan blade in the image, and when the fan blade is smaller than 1/2 of the total size of the image, adjusting the hovering position of the unmanned aerial vehicle, and increasing the duty ratio of the fan blade image;
and 4-33, maintaining the distance and shooting angle between the current hovering position and the fan blade, driving to the next hovering point for shooting, and repeatedly executing the steps 4-31.
In the above embodiment, the adjustment is performed on the currently photographed image, ensuring the sharpness of the blade image information.
In one embodiment, an intelligent inspection method for a wind turbine blade, which uses a remote control device to monitor an inspection process, includes:
acquiring a shooting image of the unmanned aerial vehicle in real time through a wireless technology, confirming the image, and sending the confirmed image to a cloud data platform;
when the unmanned aerial vehicle gives out an abnormal operation alarm, one-key return or switching is carried out through the remote control device to manually control the unmanned aerial vehicle to land.
In the above embodiment, an auxiliary person is required to determine the image data when the automatic inspection is performed; and meanwhile, emergency treatment is carried out when the unmanned aerial vehicle is abnormal, so that the inspection stability is improved.
In one embodiment, an intelligent inspection method for a wind power blade uploads data information collected by inspection to a cloud data platform to analyze the health status of the wind power blade, including:
step 5-1, carrying out front-back background segmentation on the image information of the blades on a patrol path, splicing the image information into a complete fan blade image by combining the original data and using a foreground splicing algorithm, and judging whether missing occurs in blade shooting;
step 5-2, dividing the blade into a non-obstacle area and an obstacle area based on the image after the blade foreground segmentation, and performing fault screening model training;
step 5-3, judging each picture through a fault screening model, filtering out fault-free image information, judging the fault type and severity of the faulty image information, and classifying the faults through the fault type and severity to form a fault report;
and 5-4, assessing the health condition of the fan blade through a fault report.
Among them, front-back background segmentation, front Jing Pinjie algorithm and fault screening model are all well known prior art to those skilled in the art.
In the embodiment, whether the blade shooting is missing or not can be effectively judged by splicing the graphics; after the faults are judged, a worker analyzes the health state of the fan blade through a fault report.
It should be noted that, in the foregoing embodiment, only the division of the foregoing functional modules is illustrated, and in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the functions described above. The names of the modules and steps related to the embodiments of the present invention are merely for distinguishing the respective modules or steps, and are not to be construed as unduly limiting the present invention.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus/apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus/apparatus.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the appended claims and their equivalents, the present invention is intended to include such modifications and variations as would be included in the above description of the disclosed embodiments, enabling those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An intelligent inspection method for a wind power blade is characterized by comprising the following steps:
step 1, acquiring data information of a fan to be inspected, and determining inspection time;
step 2, determining the take-off position of the unmanned aerial vehicle according to the blade orientation of the fan to be inspected, and inspecting the state of the unmanned aerial vehicle;
step 3, detecting the fan to be inspected, establishing a model of the fan to be inspected, and determining an inspection path;
step 4, automatically inspecting the fan to be inspected according to the inspection path, and monitoring the inspection process by using a remote control device;
and 5, uploading the data information acquired by inspection to a cloud data platform, and analyzing the health state of the wind power blade.
2. The intelligent inspection method for wind power blades according to claim 1, wherein the obtaining data information of the fan to be inspected and determining the inspection time comprise:
step 1-1, acquiring the position of a fan to be patrolled and examined according to an existing wind power plant fan distribution map;
step 1-2, acquiring current and predicted running environment information of a fan to be patrolled and examined through an existing weather prediction system in a wind power plant;
step 1-3, determining the inspection time of the fan to be inspected according to the position and the operation environment information of the fan to be inspected;
and 1-4, stopping the fan to be inspected according to the inspection time by an existing monitoring center in the wind power plant, locking the wind wheel and adjusting the rotation angle of the wind wheel.
3. The intelligent inspection method for wind power blades according to claim 1, wherein the steps of detecting a fan to be inspected, establishing a model of the fan to be inspected, and determining an inspection path include:
step 3-1, starting an unmanned aerial vehicle, flying to the horizontal height of a fan hub, collecting the current overall shape of the fan, and transmitting collected data information to a cloud data platform;
step 3-2, the cloud data platform inputs the image information of the current form of the fan into a three-dimensional model of the fan for training to obtain a fan model of the current form;
and 3-3, determining a routing inspection path of the unmanned aerial vehicle according to the fan model, and sending routing inspection path information to the unmanned aerial vehicle.
4. The intelligent inspection method for wind power blades according to claim 3, wherein the cloud data platform inputs image information of a current shape of a fan into a three-dimensional model of the fan for training, and obtains the fan model of the current shape, and the intelligent inspection method comprises the following steps:
step 3-21, determining the position of the current blade of the fan according to the image information of the current form of the fan;
step 3-22, obtaining a blade pitch angle when the fan is locked in a halt mode;
and 3-23, inputting the information into an existing fan three-dimensional model for training according to the position and pitch angle information of the fan blades, and obtaining a fan model in the current form.
5. The intelligent inspection method for wind power blades according to claim 4, wherein determining the inspection path of the unmanned aerial vehicle according to the fan model comprises:
3-31, establishing a space coordinate system by taking the center of a fan hub as an origin 0, wherein in the space coordinate system, an X axis is parallel to the ground, a Y axis is perpendicular to the ground, and a Z axis is perpendicular to a fan blade;
step 3-32, acquiring the data information of the whole fan and combining the space coordinate system to determine the positions of the points of the fan in the coordinate system;
and 3-33, determining the routing inspection path of the unmanned aerial vehicle in the space coordinate system according to the fan model.
6. The intelligent inspection method for wind power blades according to claim 5, wherein determining an inspection path of the unmanned aerial vehicle in the space coordinate system according to the fan model comprises:
step 3-331, obtaining a cross-section graph of the fan blade, and determining a shooting center point and a shooting angle of the fan blade according to graph information;
step 3-332, determining a shooting path on a fan blade according to a shooting center point, and determining a patrol travel path of the unmanned aerial vehicle according to a shooting angle;
and 3-333, determining a hovering point of the unmanned aerial vehicle on the inspection driving path according to the length of the fan blade and the change trend of the fan blade.
7. The intelligent inspection method for wind power blades according to claim 6, wherein the automatically inspecting the fan to be inspected according to the inspection path comprises:
step 4-1, starting the unmanned aerial vehicle, flying to a position corresponding to the center of the fan hub, determining the distance between the unmanned aerial vehicle and the center of the fan hub through a laser radar, and determining the position of the unmanned aerial vehicle in the space coordinate system according to the distance;
step 4-2, adjusting along the Z axis of the space coordinate system according to the current position, and entering the initial position of the inspection path;
step 4-3, starting to patrol the fan blade according to the sequence of the patrol path, and acquiring images of the blade when the fan blade reaches the hovering position;
and 4-4, judging the end heads of the fan blades, finishing the current inspection path inspection, and returning the current inspection path to the hub of the fan to perform repositioning, and inspecting the next inspection path.
8. The intelligent inspection method for a wind power blade according to claim 7, wherein the image acquisition of the blade when the hovering position is reached comprises:
step 4-31, adjusting the shooting angle of the cradle head according to the position of the fan blade in the image, so that the fan blade is positioned in the center of the image;
step 4-32, detecting the size of a fan blade in the image, and when the fan blade is smaller than 1/2 of the total size of the image, adjusting the hovering position of the unmanned aerial vehicle, and increasing the duty ratio of the fan blade image;
and 4-33, maintaining the distance and shooting angle between the current hovering position and the fan blade, driving to the next hovering point for shooting, and repeatedly executing the steps 4-31.
9. The intelligent inspection method for wind power blades according to claim 1, wherein the monitoring of the inspection process using the remote control device comprises:
acquiring a shooting image of the unmanned aerial vehicle in real time through a wireless technology, confirming the image, and sending the confirmed image to a cloud data platform;
when the unmanned aerial vehicle gives out an abnormal operation alarm, one-key return or switching is carried out through the remote control device to manually control the unmanned aerial vehicle to land.
10. The intelligent inspection method for wind power blades according to claim 1, wherein uploading the data information collected by inspection to a cloud data platform, analyzing the health status of the wind power blades, comprises:
step 5-1, carrying out front-back background segmentation on the image information of the blades on a patrol path, splicing the image information into a complete fan blade image by combining the original data and using a foreground splicing algorithm, and judging whether missing occurs in blade shooting;
step 5-2, dividing the blade into a non-obstacle area and an obstacle area based on the image after the blade foreground segmentation, and performing fault screening model training;
step 5-3, judging each picture through a fault screening model, filtering out fault-free image information, judging the fault type and severity of the faulty image information, and classifying the faults through the fault type and severity to form a fault report;
and 5-4, assessing the health condition of the fan blade through a fault report.
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| CN202310685109.2A CN116906276A (en) | 2023-06-09 | 2023-06-09 | Intelligent inspection method for fan blade |
| LU504712A LU504712B1 (en) | 2023-06-09 | 2023-07-11 | Intelligent inspection method for fan blade |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117536797A (en) * | 2023-10-24 | 2024-02-09 | 华能安徽怀宁风力发电有限责任公司 | Unmanned aerial vehicle-based fan blade inspection system and method |
| CN119572426A (en) * | 2024-11-13 | 2025-03-07 | 中电投东北新能源发展有限公司 | Wind turbine blade drone inspection method and device |
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2023
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- 2023-07-11 LU LU504712A patent/LU504712B1/en active
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117536797A (en) * | 2023-10-24 | 2024-02-09 | 华能安徽怀宁风力发电有限责任公司 | Unmanned aerial vehicle-based fan blade inspection system and method |
| CN117536797B (en) * | 2023-10-24 | 2024-05-31 | 华能安徽怀宁风力发电有限责任公司 | Unmanned aerial vehicle-based fan blade inspection system and method |
| US12276256B1 (en) | 2023-10-24 | 2025-04-15 | Huaneng Anhui Huaining Wind Power Generation Co., Ltd. | Wind turbine blade inspection system and method based on unmanned aerial vehicle |
| CN119572426A (en) * | 2024-11-13 | 2025-03-07 | 中电投东北新能源发展有限公司 | Wind turbine blade drone inspection method and device |
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