Method and device for detecting a state of a fan blade

Abstract

The application discloses a detection method and device for the state of a fan blade. The detection method comprises the following steps: receiving fan state data via the communication connection between a UAV and a fan by the controller of the UAV; controlling the UAV to fly according to a first flight route to shoot the fan blade to obtain a first image to detect the state of the fan blade through the first image in response to the fan state data indicating that the fan is in a running state; and controlling the UAV to fly according to a second flight route to shoot the fan blade to obtain a second image to detect the state of the fan blade through the second image in response to the fan state data indicating that the fan is in a shutdown state. The first image comprises images of all the fan blades shot at preset time intervals when the UAV is in a hovering state, and the second image comprises images of all the fan blades shot in real time when the UAV is in a non-hoovering state.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of wind power generation in general, and more particularly, to a method and device for detecting a state of a wind turbine blade. BACKGROUND

[0002] In the wind power industry, as the demand for wind energy utilization becomes stronger to achieve greater power benefits, the capacity of wind turbine generators (which can be referred to as "generators") and the length of wind turbine blades also tend to increase. However, under this development trend, as the length of the blades of wind turbine generators (e.g., megawatt generators) increases, the load asymmetry effects caused by factors such as wind shear, tower shadow, and turbulence on the generators can be exacerbated.

[0003] As a main component for converting wind energy into mechanical energy, the wind turbine blade is affected by high-speed centrifugal force and alternating airflow force while driving the impeller to rotate, and the working environment of the wind turbine is relatively harsh, which can all cause the state of the wind turbine blade to deteriorate after the wind turbine has been in operation for a period of time, for example, cracks can occur. The deterioration of the state of the blade can not only affect the power generation performance of the wind turbine, but even the situation of blade rupture can occur. In this case, due to the high rotational speed of the impeller, the broken blade has a large amount of energy, which can cause serious accidents and even the safety risk of sweeping the tower. Therefore, timely detection of the state of the blade is of great significance and plays an important role in the safe operation of the wind turbine. SUMMARY

[0004] Embodiments of the present disclosure provide a method and device for detecting a state of a wind turbine blade, so that an unmanned aerial vehicle (UAV) performs automatic image shooting according to the actual operating state of the wind turbine to detect the state of the wind turbine blade.

[0005] In one general aspect, a method for detecting a state of a wind turbine blade is provided, which is applied to a controller of an unmanned aerial vehicle (UAV), and the method comprises: receiving, by the controller of the UAV via a communication connection between the UAV and the wind turbine, wind turbine state data; in response to the wind turbine state data indicating that the wind turbine is in an operating state, controlling, by the controller of the UAV, the UAV to fly according to a first flight route to shoot the wind turbine blade to obtain a first image, so as to detect the state of the wind turbine blade through the first image; and in response to the wind turbine state data indicating that the wind turbine is in a shutdown state, controlling, by the controller of the UAV, the UAV to fly according to a second flight route to shoot the wind turbine blade to obtain a second image, so as to detect the state of the wind turbine blade through the second image, wherein the first image comprises images of all wind turbine blades shot at preset time intervals when the UAV is in a hovering state, and the second image comprises images of all wind turbine blades shot in real time when the UAV is in a non-hoovering state.

[0006] Optionally, the step of controlling the UAV to fly along the first flight path to capture the wind turbine to obtain a first image for detecting the wind turbine blade state based on the wind turbine state data can comprise: in response to the wind turbine state data indicating that the wind turbine is in operation, performing the following processing: controlling the UAV to fly to a preset hovering position based on the wind turbine hub height in the wind turbine state data, and then hovering; and capturing the wind turbine blades to obtain a first image for detecting the wind turbine blade state based on the first image after the UAV hovers, wherein the first flight path comprises a flight path from the UAV taking off to hovering, and the preset hovering position is a position at a first preset distance from the wind turbine hub plane and a second preset distance from the wind turbine hub center axis.

[0007] Optionally, the step of capturing the wind turbine blades to obtain a first image for detecting the wind turbine blade state based on the first image after the UAV hovers can comprise: after the UAV hovers, performing the following processing: detecting a first time point at which a first wind turbine blade passes through an effective shooting area of the UAV and a second time point at which a second wind turbine blade passes through the effective shooting area of the UAV by a ranging device located in the UAV; after a preset time interval elapses from the second time point, controlling the UAV to automatically capture a third wind turbine blade image, wherein the preset time interval is equal to a difference between the second time point and the first time point minus a preset shooting time of the UAV; detecting a third time point at which a third wind turbine blade passes through the effective shooting area of the UAV by the ranging device; in response to a difference between the third time point and the second time point minus the preset time interval being less than or equal to a preset threshold, performing the following processing: after the preset time interval elapses from the third time point, controlling the UAV to automatically capture a first wind turbine blade image; detecting a fourth time point at which the first wind turbine blade passes through the effective shooting area of the UAV again by the ranging device; and after the preset time interval elapses from the fourth time point, controlling the UAV to automatically capture a second wind turbine blade image, thereby obtaining the first image comprising the third wind turbine blade image, the first wind turbine blade image, and the second wind turbine blade image for detecting the wind turbine blade state based on the first image.

[0008] Optionally, after the step of detecting a third time point at which a third wind turbine blade passes through the effective shooting area of the UAV by the ranging device, in response to a difference between the third time point and the second time point minus the preset time interval being greater than the preset threshold, the step of detecting a first time point at which a first wind turbine blade passes through the effective shooting area of the UAV and a second time point at which a second wind turbine blade passes through the effective shooting area of the UAV is performed again to obtain a first updated image after the wind turbine speed changes, thereby detecting the wind turbine blade state based on the first updated image.

[0009] Optionally, the preset hovering position can include at least one preset hovering position, and the step of taking an image of the wind turbine blades after the UAV hovers can include: taking a set of blade partial images corresponding to the current hovering position after the UAV hovers at each of the at least one preset hovering position, to obtain a first image, wherein the first image includes at least one set of blade partial images corresponding to the at least one hovering position taken by the UAV at the at least one hovering position, and the at least one set of blade partial images constitute a complete image of all the wind turbine blades.

[0010] Optionally, the step of controlling the UAV to fly along a second flight path to take an image of the wind turbine to obtain a second image to detect the state of the wind turbine blades through the second image can include: in response to the wind turbine state data indicating that the wind turbine is in a shutdown state, performing the following processing: determining a first included angle between a first wind turbine blade and a vertical direction based on the wind turbine state data; controlling the UAV to take an image of the wind turbine in real time along the second flight path corresponding to the first included angle to obtain a second image to detect the state of the wind turbine blades through the second image.

[0011] Optionally, the step of controlling the UAV to take an image of the wind turbine along the second flight path corresponding to the first included angle to obtain a second image to detect the state of the wind turbine blades through the second image can include: controlling the UAV to take a first wind turbine blade image, a second wind turbine blade image, and a third wind turbine blade image in real time along a flight path corresponding to the first included angle, a flight path corresponding to a second included angle, and a flight path corresponding to a third included angle, respectively, to obtain the second image including the first wind turbine blade image, the second wind turbine blade image, and the third wind turbine blade image to detect the state of the wind turbine blades through the second image, wherein the second included angle is an angle with a horizontal direction included angle being the sum of the first included angle and 30 degrees, and the third included angle is an angle with a horizontal direction included angle being the difference between 30 degrees and the first included angle.

[0012] Optionally, the step of controlling the unmanned aerial vehicle to respectively fly along a flight path corresponding to the first angle, along a flight path corresponding to the second angle, and along a flight path corresponding to the third angle to capture the first wind turbine blade image, the second wind turbine blade image, and the third wind turbine blade image in real time can include: in response to a ranging device located in the unmanned aerial vehicle detecting that the unmanned aerial vehicle has flown to a position corresponding to a tip of the first wind turbine blade, controlling the unmanned aerial vehicle to fly upward and to the left at the first angle and capture the first wind turbine blade image in real time until the ranging device detects that the unmanned aerial vehicle has flown beyond a position corresponding to a hub of the wind turbine; in response to the ranging device detecting that the unmanned aerial vehicle has flown beyond the position corresponding to the hub of the wind turbine, controlling the unmanned aerial vehicle to fly upward and to the right at the second angle and capture the second wind turbine blade image in real time until the ranging device detects that the unmanned aerial vehicle has flown beyond a position corresponding to a tip of the second wind turbine blade; in response to the ranging device detecting that the unmanned aerial vehicle has flown beyond the position corresponding to the tip of the second wind turbine blade, controlling the unmanned aerial vehicle to fly downward and to the left at the second angle for a preset time period, wherein the preset time period is a time period corresponding to capturing the second wind turbine blade in real time; controlling the unmanned aerial vehicle to fly horizontally to the left until the ranging device detects that the unmanned aerial vehicle has flown to a position corresponding to a root of the third wind turbine blade; in response to the ranging device detecting that the unmanned aerial vehicle has flown to the position corresponding to the root of the third wind turbine blade, controlling the unmanned aerial vehicle to fly upward and to the left at the third angle and capture the third wind turbine blade image in real time until the ranging device detects that the unmanned aerial vehicle has flown beyond a position corresponding to a tip of the third wind turbine blade.

[0013] In another general aspect, there is provided a device for detecting a state of wind turbine blades, the device comprising: a communication module configured to receive wind turbine state data via a communication connection between an unmanned aerial vehicle and a wind turbine; and a control module configured to: in response to the wind turbine state data indicating that the wind turbine is in an operating state, control the unmanned aerial vehicle to fly along a first flight path to capture images of the wind turbine blades to obtain a first image to detect a state of the wind turbine blades from the first image; and in response to the wind turbine state data indicating that the wind turbine is in a shutdown state, control the unmanned aerial vehicle to fly along a second flight path to capture images of the wind turbine blades to obtain a second image to detect the state of the wind turbine blades from the second image, wherein the first image comprises images of all the wind turbine blades captured at preset time intervals while the unmanned aerial vehicle is in a hovering state, and the second image comprises images of all the wind turbine blades captured in real time while the unmanned aerial vehicle is in a non-hoovering state.

[0014] Optionally, the operation of the control module, in response to the wind turbine state data indicating that the wind turbine is in the running state, controlling the UAV to fly along the first flight path to shoot the wind turbine to obtain a first image, to detect the wind turbine blade state through the first image, can include: in response to the wind turbine state data indicating that the wind turbine is in the running state, performing the following processing: based on the wind turbine hub height in the wind turbine state data, controlling the UAV to fly to a preset hovering position along the first flight path and then hovering; after the UAV hovers, shooting the wind turbine blade to obtain a first image to detect the wind turbine blade state through the first image, wherein the first flight path includes a flight path from the UAV taking off to hovering, and the preset hovering position is a position at a first preset distance from the wind turbine hub plane and a second preset distance from the wind turbine hub center axis.

[0015] Optionally, the operation of the control module, after the UAV hovers, shooting the wind turbine blade to obtain a first image to detect the wind turbine blade state through the first image, can include: after the UAV hovers, performing the following processing: detecting, by a ranging device located in the UAV, a first time point at which a first wind turbine blade passes through an effective shooting area of the UAV and a second time point at which a second wind turbine blade passes through the effective shooting area of the UAV; after a preset time interval elapses from the second time point, controlling the UAV to automatically shoot a third wind turbine blade image, wherein the preset time interval is equal to the difference between the second time point and the first time point minus a preset shooting time of the UAV; detecting, by the ranging device, a third time point at which a third wind turbine blade passes through the effective shooting area of the UAV; in response to the difference between the third time point and the second time point minus the preset time interval being less than or equal to a preset threshold, performing the following processing: after the preset time interval elapses from the third time point, controlling the UAV to automatically shoot a first wind turbine blade image; detecting, by the ranging device, a fourth time point at which the first wind turbine blade passes through the effective shooting area of the UAV again; after the preset time interval elapses from the fourth time point, controlling the UAV to automatically shoot a second wind turbine blade image, thereby obtaining the first image including the third wind turbine blade image, the first wind turbine blade image and the second wind turbine blade image to detect the wind turbine blade state through the first image.

[0016] Optionally, the control module can be further configured to, after the step of detecting a third time point at which the third fan blade passes through the effective shooting area of the UAV by the ranging device, in response to a difference between the third time point and the second time point minus the preset time interval being greater than the preset threshold, return to execute the steps of detecting the first time point at which the first fan blade passes through the effective shooting area of the UAV and the second time point at which the second fan blade passes through the effective shooting area of the UAV to reacquire a first updated image after the fan speed changes, so as to detect the fan blade state through the first updated image.

[0017] Optionally, the preset hovering position can include at least one preset hovering position, and the operation of the control module to shoot the fan blades after the UAV hovers to obtain a first image can include: shooting a set of blade local images corresponding to the current hovering position after the UAV hovers at each of the at least one preset hovering position to obtain a first image, wherein the first image includes at least one set of blade local images corresponding to the at least one hovering position shot by the UAV at the at least one hovering position, and the at least one set of blade local images constitute a complete image of all fan blades.

[0018] Optionally, in response to the fan state data indicating that the fan is in a shutdown state, the control module controls the UAV to fly according to a second flight path to shoot the fan to obtain a second image to detect the fan blade state through the second image, which can include: in response to the fan state data indicating that the fan is in a shutdown state, performing the following processing: determining a first included angle between the first fan blade and the vertical direction based on the fan state data; controlling the UAV to shoot the fan in real time to obtain a second image according to the second flight path corresponding to the first included angle to detect the fan blade state through the second image.

[0019] Optionally, the operation of the control module to control the UAV to shoot the fan in real time to obtain a second image according to the second flight path corresponding to the first included angle to detect the fan blade state through the second image can include: controlling the UAV to shoot a first fan blade image, a second fan blade image and a third fan blade image in real time according to a flight path corresponding to the first included angle, a flight path corresponding to a second included angle and a flight path corresponding to a third included angle respectively, so as to obtain the second image including the first fan blade image, the second fan blade image and the third fan blade image to detect the fan blade state through the second image, wherein the second included angle is an angle with a horizontal direction included angle being the sum of the first included angle and 30 degrees, and the third included angle is an angle with a horizontal direction included angle being the difference between 30 degrees and the first included angle.

[0020] Optionally, the operation of the control module controlling the UAV to fly at a flight path corresponding to the first angle, to fly at a flight path corresponding to the second angle, and to fly at a flight path corresponding to the third angle to capture the first wind turbine blade image, the second wind turbine blade image, and the third wind turbine blade image in real time can include: in response to a ranging device located in the UAV detecting that the UAV flies to a position corresponding to a tip of the first wind turbine blade, controlling the UAV to fly to the left upper side at the first angle and capture the first wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond a hub of the wind turbine; in response to the ranging device detecting that the UAV flies to the position beyond the hub of the wind turbine, controlling the UAV to fly to the right upper side at the second angle and capture the second wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond a tip of the second wind turbine blade; in response to the ranging device detecting that the UAV flies to the position beyond the tip of the second wind turbine blade, controlling the UAV to fly to the left lower side at the second angle for a preset time period, wherein the preset time period is a time period corresponding to capturing the second wind turbine blade in real time; controlling the UAV to fly to the left along a horizontal direction until the ranging device detects that the UAV flies to a position corresponding to a root of the third wind turbine blade; in response to the ranging device detecting that the UAV flies to the position corresponding to the root of the third wind turbine blade, controlling the UAV to fly to the left upper side at the third angle and capture the third wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond a tip of the third wind turbine blade.

[0021] In another general aspect, there is provided a computer program product including computer programs / instructions that, when executed by a processor, implement the method of detecting a state of a wind turbine blade as described above.

[0022] In another general aspect, there is provided a computer-readable storage medium that, when instructions in the computer-readable storage medium are executed by a processor of an electronic device / server, enables the electronic device / server to perform the method of detecting a state of a wind turbine blade as described above.

[0023] In another general aspect, there is provided a computing device for a UAV, the computing device comprising: at least one processor; at least one memory storing computer executable instructions, wherein the computer executable instructions, when executed by the at least one processor, cause the at least one processor to perform the method of detecting a state of a wind turbine blade as described above.

[0024] The method and device for detecting the state of the fan blade according to the embodiments of the present disclosure can timely and efficiently detect the state of the fan blade under various fan operating states by proposing to use the unmanned aerial vehicle to perform automatic image shooting according to the actual operating state of the fan. In addition, by not limiting the operating state of the fan when performing detection by using the unmanned aerial vehicle, for example, not limiting that the operating state of the fan must be the shutdown state, the loss of the power generation capacity of the wind farm is effectively reduced. By using the unmanned aerial vehicle to shoot images to detect the state of the blade, only image analysis is required, the difficulty of material identification is reduced, and the development workload is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0025] The above and other objects and features of the embodiments of the present disclosure will become more apparent from the following description made with reference to the accompanying drawings, in which:

[0026] Figure 1 is a flowchart illustrating a method for detecting the state of a fan blade according to an embodiment of the present disclosure;

[0027] Figure 2 is an example flowchart illustrating a method for detecting the state of a fan blade according to an embodiment of the present disclosure;

[0028] Figure 3 is a schematic diagram illustrating the positional relationship between an unmanned aerial vehicle and a fan in a method for detecting the state of a fan blade according to an embodiment of the present disclosure;

[0029] Figure 4 is a schematic diagram illustrating an automatic shooting time point according to an embodiment of the present disclosure;

[0030] Figure 5 is an example flowchart illustrating a method for detecting the state of a fan blade according to an embodiment of the present disclosure;

[0031] Figures 6A to 6C is a schematic diagram illustrating the positional relationship between an unmanned aerial vehicle and a fan in a method for detecting the state of a fan blade according to another embodiment of the present disclosure;

[0032] Figure 7 is a schematic diagram illustrating a detection indicator light of an unmanned aerial vehicle according to an embodiment of the present disclosure;

[0033] Figure 8 is a structural block diagram of a device for detecting the state of a fan blade according to an embodiment of the present disclosure;

[0034] Figure 9A and Figure 9B are schematic diagrams of a system for detecting the state of a fan blade according to an embodiment of the present disclosure, respectively;

[0035] Figure 10is an example flow diagram illustrating a communication address matching according to an embodiment of the disclosure;

[0036] Figure 11 is a block diagram illustrating a computing device for a drone according to an embodiment of the disclosure. DETAILED DESCRIPTION

[0037] The following detailed description is provided to help the reader obtain a thorough understanding of the methods, devices, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, devices, and / or systems described herein will be clear to those skilled in the art after understanding the disclosure provided herein. For example, the order of the operations described herein is merely an example, and is not limited to those set forth herein, but can be changed as will be clear to one of ordinary skill in the art after understanding the disclosure provided herein, except for operations that must occur in a specific order. Also, descriptions of features known in the art can be omitted for the sake of clarity and conciseness.

[0038] The features described herein can be implemented in different forms and should not be construed as limited to the examples described herein. Rather, these examples have been provided so that this disclosure will be thorough and complete, and will fully convey the scope of the methods, devices, and / or systems to be implemented as understood after understanding the disclosure provided herein.

[0039] As used herein, the term "and / or" includes any one of the associated listed items, as well as any combination of any two or more of the associated listed items.

[0040] The terms used herein are merely used to describe various examples, and are not intended to limit the disclosure. The singular forms are intended to include the plural forms unless the context clearly indicates otherwise. The terms "comprise", "include" and "have" indicate the presence of the described features, numbers, operations, components, elements, and / or combinations thereof, but do not exclude the presence or addition of one or more other features, numbers, operations, components, elements, and / or combinations thereof.

[0041] Unless otherwise defined, all terms used herein (including technical terms and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosure belongs after understanding the disclosure. Unless explicitly defined otherwise herein, terms such as those defined in a general dictionary should be interpreted as having a meaning consistent with their meanings in the context of the relevant art and the disclosure, and should not be interpreted ideally or overly formally.

[0042] In addition, in the description of the examples, detailed descriptions of related structures or functions considered to cause obscuring of the disclosure will be omitted.

[0043] Reference will now be made in detail embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout. The embodiments will be explained by referring to the drawings in order to explain the present disclosure.

[0044] In the related art, the blade state caused by blade deterioration is generally small, so that it can be difficult to find by artificial observation with the aid of a telescope or the like. In addition, since the wind speed and the wind direction are both transient, it is difficult to detect, for example, a blade crack and a cracking condition by means of existing wind turbine operation data and a blade vibration method.

[0045] In the present disclosure, the wind turbine blade state can include at least one of the following: a dimple, paint peeling, a scratch, a crack, icing, and contamination. Hereinafter, for the convenience of description, some related descriptions can be made by taking a blade crack as an example.

[0046] For example, the deficiencies of the existing methods will be described by taking the detection of a blade crack as an example. Specifically, the existing methods for detecting a blade crack include a blade detection trolley method, an ultrasonic flaw detection method, a color recognition detection method, and a blade vibration detection method.

[0047] For the blade detection trolley method, the disadvantages include a high cost, inconvenience for installation, and inconvenience for high-altitude online operation. In addition, since the three blades of the wind turbine are located in different directions, it is more difficult to install when detecting the blade with the direction upward when the wind turbine is stopped. In addition, in the case where the blade needs to be rotated to change the azimuth angle, not only does the relevant personnel need to enter the warehouse for operation, but also the following problems exist: if the wind speed is low when the detection is performed, the impeller can be difficult to rotate, which causes adverse effects on the timeliness of the detection; and if the wind speed is large when the detection is performed, the blade's whipping can affect the stability of the device. In addition, since the time for installing and dismounting the blade detection trolley is long, it can indirectly cause the extension of the wind turbine downtime, so that with the increase in the number of units / wind turbines, it can greatly affect the power generation of the entire wind farm.

[0048] For the ultrasonic flaw detection method, this method uses ultrasonic echoes to detect blade cracks, and the disadvantages are: this method can only detect cracks with a large width when the cracks penetrate, but since the depth and width of the blade cracks are random, it is difficult to detect the surface cracking of the blade and the cracks with a small width generated thereby. In addition, since the surface of the wind turbine blade (especially the windward surface) is a curved structure, this method can cause false detection due to the existence of the curved surface.

[0049] For the color recognition detection method, the method needs to set different color paints on the bottom layer and surface of the blade first, and then detect whether the blade has cracks by detecting different colors. The disadvantage is that since the fan is exposed to the external natural environment for a long time, factors such as light and dust will cause the color to change or be unable to be detected due to being covered, which makes the detection effect of the method deteriorate. In addition, the method also needs to improve the production process of the blade and process the blade, which will lead to an increase in design cost and the inability to detect the previously installed blades. Therefore, the method has great limitations.

[0050] For the blade vibration detection method, the method realizes detection by collecting data of the vibration sensor installed on the blade. The disadvantage is that the algorithm is complex, and it is difficult to effectively distinguish the data corresponding to the cracks from the data generated by wind gusts, wind shear, turbulence, control factors (for example, given speed jitter), and the like.

[0051] In view of the related problems in the above blade crack detection, the present application proposes a fan blade state detection method and device to solve the above problems related to blade state detection.

[0052] The following refers to Figures 1 to 11 The fan blade state detection method and device according to the embodiments of the present disclosure are described in detail.

[0053] Figure 1 is a flow chart showing a fan blade state detection method 100 according to an embodiment of the present disclosure. Here, the fan blade state detection method 100 according to the embodiments of the present disclosure can be applied to the controller of the unmanned aerial vehicle, so that the unmanned aerial vehicle automatically performs the detection method 100 via the control of the controller.

[0054] Referring to Figure 1 In step S101, the fan state data is received via the communication connection between the unmanned aerial vehicle and the fan.

[0055] In step S102, in response to the fan state data indicating that the fan is in a running state, the unmanned aerial vehicle is controlled to fly according to a first flight route to shoot the fan blades to obtain a first image, so as to detect the fan blade state through the first image. Hereinafter, the scheme corresponding to this step can be referred to as the first scheme and the corresponding detection mode can be referred to as the first detection mode.

[0056] Here, the first image includes images of all the fan blades shot at a preset time interval when the unmanned aerial vehicle is in a hovering state.

[0057] According to the embodiments of the present disclosure, step S102 can further include: in response to the fan state data indicating that the fan is in a running state, steps S1021 to S1022 are executed:

[0058] At step S1021, based on the wind turbine hub height in the wind turbine state data, the unmanned aerial vehicle is controlled to fly to a preset hovering position according to a first flight route and then hover.

[0059] At step S1022, after the unmanned aerial vehicle hovers, the wind turbine blade is photographed to obtain a first image, so as to detect the wind turbine blade state through the first image.

[0060] For example, the first flight route includes a flight route from the start of takeoff of the unmanned aerial vehicle to hovering, and the preset hovering position is a position at a first preset distance from the wind turbine hub plane and a second preset distance from the wind turbine hub center axis. For example, the preset hovering position can include at least one preset hovering position.

[0061] According to the embodiment of the present disclosure, by automatically photographing the blade image based on the preset hovering position, it is not necessary to limit that the wind turbine operating state must be the shutdown state, thereby effectively reducing the loss of power generation of the wind farm. In addition, by using the unmanned aerial vehicle to photograph the image to detect the blade state, only the image needs to be analyzed, the material recognition difficulty is reduced, and the development workload is reduced.

[0062] According to the embodiment of the present disclosure, step S1022 can further include the following steps S21 to S25 after the unmanned aerial vehicle hovers:

[0063] At step S21, by a ranging device located in the unmanned aerial vehicle, a first time point at which the first wind turbine blade passes through an effective photographing area of the unmanned aerial vehicle and a second time point at which the second wind turbine blade passes through the effective photographing area of the unmanned aerial vehicle are detected.

[0064] In the present disclosure, as for the ranging device, the present disclosure can use, for example but not limited to, an ultrasonic and / or infrared range finder, an ultrasonic and / or infrared material level meter, etc. as the ranging device, and for the convenience of description, the present disclosure mainly takes the ultrasonic range finder as the ranging device (hereinafter, can be referred to as an ultrasonic ranging device) as an example for specific description. For example, the characteristics of the ultrasonic ranging device are simply described here: the ultrasonic directivity is strong, the ultrasonic energy consumption is slow, and the distance of propagation in the medium is far.

[0065] At step S22, when a preset time interval elapses after the second time point, the unmanned aerial vehicle is controlled to automatically photograph a third wind turbine blade image. Here, the preset time interval is equal to the difference between the second time point and the first time point minus the difference of the preset photographing time of the unmanned aerial vehicle.

[0066] At step S23, by the ranging device, a third time point at which the third wind turbine blade passes through the effective photographing area of the unmanned aerial vehicle is detected.

[0067] At step S24, in response to the difference between the third time point and the second time point minus the preset time interval being less than or equal to the preset threshold value, the following steps S241-S243 are performed:

[0068] At step S241, when the preset time interval has elapsed after the third time point, the unmanned aerial vehicle is controlled to automatically capture the first fan blade image.

[0069] At step S242, a fourth time point at which the first fan blade again passes through the effective shooting area of the unmanned aerial vehicle is detected by the ranging device.

[0070] At step S243, when the preset time interval has elapsed after the fourth time point, the unmanned aerial vehicle is controlled to automatically capture the second fan blade image, thereby obtaining a first image including the third fan blade image, the first fan blade image, and the second fan blade image, to detect the fan blade state through the first image.

[0071] According to embodiments of the present disclosure, by detecting and recording the time at which the blade passes through using the ultrasonic ranging device, the time interval at which the two blades pass through the blade can be obtained, and then the time point at which the next automatic photographing of the blade is obtained according to the photographing delay time, so that accurate photographing is achieved when the blade arrives (photographing is started in advance and accurately completed), and the situation of empty photographing or image blur is avoided.

[0072] After step S23, at step S25, in response to the difference between the third time point and the second time point minus the preset time interval being greater than the preset threshold value, the step of detecting the first time point at which the first fan blade passes through the effective shooting area of the unmanned aerial vehicle and the second time point at which the second fan blade passes through the effective shooting area of the unmanned aerial vehicle is returned to be performed, so as to reacquire a first updated image after the fan speed changes, thereby detecting the fan blade state through the first updated image.

[0073] According to embodiments of the present disclosure, through the above step S25, the shooting position of the unmanned aerial vehicle can be adjusted in time in the case that the fan operating parameters change during shooting and detection, so that the detection result is more accurate and the safety of the unmanned aerial vehicle is ensured by adjusting the shooting position of the unmanned aerial vehicle.

[0074] As an example, in the case that the preset hovering position includes at least one preset hovering position, step S1022 can further include: capturing a set of blade local images corresponding to the current hovering position after the unmanned aerial vehicle hovers at each of the at least one preset hovering position, to obtain the first image.

[0075] For example, the first image includes at least one set of blade local images corresponding to the at least one hovering position, which are captured by the unmanned aerial vehicle at the at least one hovering position, and the at least one set of blade local images constitute a complete image of all fan blades.

[0076] According to an embodiment of the present disclosure, by performing automatic shooting at multiple hovering positions, the integrity of the shot image, i.e., the image containing all the regions of the blades, can be ensured.

[0077] According to an embodiment of the present disclosure, by using the method of ultrasonic ranging and image recognition, it can be automatically detected whether the shooting of the current blade is completed, thereby improving the timeliness of shooting and detection, and improving the accuracy of blade state judgment.

[0078] In step S103, in response to the wind turbine state data indicating that the wind turbine is in a shutdown state, the unmanned aerial vehicle is controlled to fly along a second flight path to shoot the wind turbine blade to obtain a second image, so as to detect the wind turbine blade state through the second image. Hereinafter, the scheme corresponding to this step can be referred to as a second scheme, and the corresponding detection mode can be referred to as a second detection mode.

[0079] Here, the second image includes images of all the wind turbine blades shot in real time when the unmanned aerial vehicle is in a non-hovering state.

[0080] According to an embodiment of the present disclosure, step S103 can further include, in response to the wind turbine state data indicating that the wind turbine is in a shutdown state, performing steps S1031 and S1032:

[0081] In step S1031, a first included angle between the first wind turbine blade and the vertical direction is determined based on the wind turbine state data.

[0082] In step S1032, the unmanned aerial vehicle is controlled to shoot the wind turbine in real time along a second flight path corresponding to the first included angle to obtain a second image, so as to detect the wind turbine blade state through the second image.

[0083] As an example, step S1032 can further include controlling the unmanned aerial vehicle to shoot a first wind turbine blade image, a second wind turbine blade image and a third wind turbine blade image in real time along a flight path corresponding to the first included angle, a flight path corresponding to a second included angle and a flight path corresponding to a third included angle respectively, so as to obtain a second image including the first wind turbine blade image, the second wind turbine blade image and the third wind turbine blade image, and detect the wind turbine blade state through the second image. Here, the second included angle is an angle with a horizontal direction included angle being the sum of the first included angle and 30 degrees, and the third included angle is an angle with a horizontal direction included angle being the difference between 30 degrees and the first included angle.

[0084] According to an embodiment of the present disclosure, by presetting the azimuth angle and / or the included angle a, the automatic shooting and detection of the blade image by the unmanned aerial vehicle in the shutdown state of the wind turbine can be realized without human operation control, thereby effectively avoiding a series of problems such as the unmanned aerial vehicle flying out of the blade detection range, the unmanned aerial vehicle colliding with the blade, and operation errors due to various reasons such as too far distance and poor line of sight when human control.

[0085] As an example, step S1032 can further include steps S31-S35:

[0086] In step S31, in response to the ranging device located in the UAV detecting that the UAV flies to a position corresponding to the tip of the first wind turbine blade, the UAV is controlled to fly left-upward at a first angle and take a first wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond the wind turbine hub.

[0087] In step S32, in response to the ranging device detecting that the UAV flies to a position beyond the wind turbine hub, the UAV is controlled to fly right-upward at a second angle and take a second wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond the tip of the second wind turbine blade.

[0088] In step S33, in response to the ranging device detecting that the UAV flies to a position beyond the tip of the second wind turbine blade, the UAV is controlled to fly left-downward at the second angle for a preset time period. Here, the preset time period is a time period corresponding to taking the second wind turbine blade in real time.

[0089] In step S34, the UAV is controlled to fly leftward along the horizontal direction until the ranging device detects that the UAV flies to a position corresponding to the root of the third wind turbine blade.

[0090] In step S35, in response to the ranging device detecting that the UAV flies to a position corresponding to the root of the third wind turbine blade, the UAV is controlled to fly left-upward at a third angle and take a third wind turbine blade image in real time until the ranging device detects that the UAV flies to a position beyond the tip of the third wind turbine blade.

[0091] According to embodiments of the present disclosure, by utilizing the ultrasonic ranging device to synchronously trigger the photographing function of the UAV while playing a safety guarantee role, the UAV can automatically take a blade image and detect the blade deterioration state such as cracks based on the automatic detection of the relevant parts of the hub and the blade by the ultrasonic ranging device, and the entire process does not require the operation of relevant personnel.

[0092] As an example, the following illustrates an example of the detection method 100 with reference to Figure 2 . Figure 2 is an example flowchart illustrating a detection method of a wind turbine blade state according to embodiments of the present disclosure.

[0093] With reference to Figure 2 , in step S201, it is determined whether the communication connection between the UAV and the current wind turbine is successful.

[0094] In step S202, if the communication connection is successfully established, the wind turbine status data received from the wind turbine via the communication connection is used to determine whether the wind turbine is currently in operation.

[0095] In step S203, in response to the fan being in operation, the first solution is automatically executed. In step S204, in response to the fan being in shutdown, the second solution is automatically executed.

[0096] During the execution of the first scheme, in step S205, if the impeller speed changes during the detection process, the time for the drone to take pictures of the blades is calculated in real time based on the real-time impeller speed value.

[0097] In step S206, it is determined whether the wind direction has changed and / or whether the wind turbine has started yaw control. If so, in step S207, the direction of the UAV and the distance between the UAV and the blades are automatically adjusted according to the changes in the operating status of the wind turbine blades.

[0098] By using drones to automatically select the appropriate detection mode based on the wind turbine's status (running or stopped), the automation of the detection is improved. Furthermore, it is not necessary to start the wind turbine to cooperate with the detection when it is stopped, nor is it necessary to stop the wind turbine to cooperate with the detection when it is running.

[0099] The following will refer to Figures 3 to 6C To specifically explain the first solution corresponding to step S102 (e.g.) Figures 3 to 5 (as shown) and the second scheme corresponding to step S103 (such as) Figures 6A to 6C (As shown).

[0100] Specifically, Figure 3 This is a schematic diagram illustrating the positional relationship between a drone and a wind turbine in a wind turbine blade state detection method according to an embodiment of the present disclosure. Figure 4 This is a schematic diagram illustrating the automatic shooting time point according to an embodiment of the present disclosure, and Figure 5 This is an example flowchart illustrating the detection of the condition of wind turbine blades according to an embodiment of the present disclosure. Figures 6A to 6C This is a schematic diagram illustrating the positional relationship between a drone and a wind turbine in a method for detecting the state of wind turbine blades according to another embodiment of the present disclosure.

[0101] In an embodiment, such as Figure 3 , Figures 6A to 6C As shown, the blades of the wind turbine are shown as blade 101, blade 102 and blade 103, and the drone is shown as drone 104.

[0102] As an example, refer to Figure 3 and Figure 5At block S501, it is judged whether the UAV has flown to a preset height and is at a preset distance from the hub plane of the wind turbine. For example, the preset height can be the hub height of the wind turbine. In addition, the UAV can fly to the preset height by means of a height sensor provided in the UAV, and the distance judgment described below can be realized by means of a distance measuring device provided in the UAV.

[0103] After it is judged that the UAV has flown to the preset height, block S502 is executed, at which the UAV is controlled to move a distance S to the left or to the right.

[0104] It should be noted that, in the case where the preset height is the hub height of the wind turbine, at block S502, the UAV can also be controlled to move a distance S to other directions around the hub, instead of being limited to moving a distance S to the left or to the right. Moreover, in the case of this example, the first flight route of the UAV includes a route from takeoff to a position reached by flying to the hub height of the wind turbine and a route from the position to a position reached by moving a distance S thereafter.

[0105] In addition, in the case of this example, the hub height of the wind turbine can be pre-stored in the controller of the UAV, or it can also be received from the outside, for example, from the wind turbine via a communication connection with the wind turbine.

[0106] As another example, the preset height described above is not limited to the hub height of the wind turbine, i.e., is not equal to the hub height of the wind turbine, in which case blocks S501 and S502 can be combined into one step, in which the UAV is controlled to fly to a position at a first preset distance from the hub plane of the wind turbine and at a second preset distance from the central axis of the hub of the wind turbine. Here, the second preset distance can be the distance S described above, and the first preset distance is used to ensure the safety of the operation of the UAV.

[0107] For example, the safety of the UAV in the above operation can be ensured by means of an ultrasonic distance measuring device, and there is no special requirement for the accuracy of the ultrasonic distance measuring device, i.e., the ultrasonic distance measuring device can detect the distance between the UAV and the blades in real time, thereby preventing the UAV from being too close to the blades, for example, preventing the UAV from colliding with the blades, etc. In addition, after the position of the UAV exceeds the position corresponding to the hub, the ultrasonic distance measuring device can automatically start direction adjustment and automatically detect the next blade.

[0108] In addition, in the present disclosure, all situations involving the use of an ultrasonic distance measuring device to ensure a safe distance between the UAV and the wind turbine also apply to the above description herein, which will not be described again.

[0109] After block S502, the UAV hovers and block S503 is performed, in which the first blade time T1 that the blade 101 passes through the effective shooting area of the UAV is detected by the ultrasonic ranging device, and the second blade time T2 that the blade 102 passes through the effective shooting area of the UAV is detected by the ultrasonic ranging device, so as to calculate the automatic shooting time T0 according to the shutter time Tp, T1 and T2 (as shown in block S504).

[0110] Then, in block S505, the third blade time T3 that the blade 103 passes through the effective shooting area of the UAV is detected by the ultrasonic ranging device. In block S506, it is judged whether the difference between T3 and T2 is close to T0, if yes, block S507 is performed, otherwise, block S303 is returned to re-perform the related operation.

[0111] In block S507, the three blades are prepared to be shot in the next cycle (i.e. the next round) of the fan blade rotation according to the time parameter T0 obtained before, so as to complete the shooting of the three blades in the current cycle in S508.

[0112] In this example, due to the long length of the blades and the limited effective shooting area of the UAV, it is likely that only the partial images of each of the three blades can be shot and the complete images of all the blades cannot be shot through hovering only once based on the distance S, so in this case, it is necessary to hover several times (i.e. each distance corresponds to one hovering) based on distances different from the distance S (the distance corresponds to the number of hovers) and perform the above operation to obtain the complete images of all the blades.

[0113] By detecting and recording the time that the blades pass through by using the ultrasonic ranging device, the time interval of the two blades passing through the blades can be obtained, and then according to the delay time of the shooting shutter, the time point of the next automatic shooting of the blades can be obtained, so as to accurately shoot when the blades arrive, and the situation that the blades cannot be shot cannot occur. Hereinafter, with reference to Figure 4 The above effects are exemplified.

[0114] With reference to Figure 4 , Figure 4 is a statistical diagram of the automatic shooting time. In Figure 4In the above example, t1 represents the time at which the ultrasonic ranging device detects that the blade 101 reaches a position directly opposite the UAV (here, it can be understood as the position at which the position coordinates of the UAV are mapped to the hub plane or the position reached by the blade when the distance between the UAV and the blade is the shortest), t2 represents the time at which the ultrasonic ranging device detects that the blade 102 reaches a position directly opposite the UAV, and t3 represents the time at which the ultrasonic ranging device detects that the blade 103 reaches a position directly opposite the UAV. Assuming that the shutter speed of the camera arranged on the UAV is Tp, when the blade 102 reaches the position of the UAV, the photographing is started in advance at the time t2+(t2-t1)-Tp, and the effect of this is that when the blade 103 reaches, the photographing operation of the blade 103 is started, so that the photographing at the time when the blade reaches is realized accurately.

[0115] Further, when the blade 103 is photographed, the ultrasonic ranging is performed again, and the difference between the time at which the ranging succeeds and the calculated photographing time is detected. If the difference is too large, it indicates that the rotating speed of the impeller changes (for example, the rotating speed of the impeller changes from 10 rpm to 20 rpm, and the time interval between t4, t5, t6 in FIG. 6 indicates the change of the rotating speed of the impeller), and in this case, the automatic photographing time interval for the blade is recalculated. Figure 4

[0116] According to the above example of the present disclosure, by automatically calculating the photographing time interval, the accuracy of photographing each region of the blade is ensured, and the cases of photographing empty (no region of the blade is photographed but only the gap region between the blades is photographed) or image blur are avoided, so that the workload of screening and cleaning of image data is reduced, and by using image data instead of video data, the workload of data analysis can be reduced. In addition, by automatically adjusting the photographing time interval according to the rotating speed of the impeller, the present scheme is more suitable for the actual operating environment of the wind turbine and is more suitable for a long-time automatic detection process.

[0117] As another example, in the case of shutdown of the wind turbine, the detection method according to the example includes automatically photographing the images of the blades 101, 102, and 103, respectively.

[0118] Referring to Figures 6A to 6C The detection method according to the example includes steps (1) to (6):

[0119] In step (1), the UAV determines the included angle a of the blade 101 with the vertical direction based on the blade azimuth angle.

[0120] Here, the blade azimuth angle can be pre-stored in the controller of the UAV, or can also be received from the outside, for example, from the wind turbine via a communication connection with the wind turbine. In addition, the included angle a can also be pre-stored in the controller of the UAV, or can also be received from the outside, for example, from the wind turbine via a communication connection with the wind turbine. In addition, the blade azimuth angle and / or the included angle a can be used for the UAV to automatically correct its orientation.​

[0121] In addition, regarding the blade azimuth angle, it is defined as: when the blade tip of a blade is upward, the corresponding blade azimuth angle is 0 degree, and after the blade rotates one round and turns to the position where the blade tip is upward again, the corresponding blade azimuth angle is 360 degrees, that is, the blade azimuth angle is a continuously and periodically changing angle value as the blade rotates from 0 degree to 360 degrees.

[0122] As an example, the azimuth angles of the three blades of the fan can be calculated by the impeller azimuth angle. For example, assuming that the three blades of the fan are respectively denoted as blade 1, blade 2 and blade 3, and the angle when the blade tip of the blade 1 is upward is 0 degree of the impeller azimuth angle, then in this case, the azimuth angle of the blade 1 is 0 degree, the azimuth angle of the blade 2 is 120 degrees, and the azimuth angle of the blade 3 is 240 degrees.

[0123] In step (2), after the included angle a is determined, the unmanned aerial vehicle can start and fly to the position corresponding to the blade tip of the blade 101 through the distance detection of the ultrasonic ranging device, in order to prepare to start photographing the blade 101.

[0124] In step (3), the unmanned aerial vehicle is automatically controlled to fly obliquely to the upper left at an angle a and perform photographing, so as to ensure that the image of the entire blade is photographed, until the ultrasonic ranging device cannot detect the ultrasonic echo (which can also be referred to as: detecting that the unmanned aerial vehicle has passed the position corresponding to the hub), at which time it can be determined that the photographing of the blade 101 has been completed. Then the unmanned aerial vehicle automatically adjusts the direction, preparing to photograph the next blade.

[0125] In step (4), the unmanned aerial vehicle is automatically controlled to fly obliquely to the upper right at an angle of 30+a and perform photographing, so as to ensure that the image of the entire blade is photographed, until the ultrasonic ranging device cannot detect the ultrasonic echo, at which time it can be determined that the photographing of the blade 102 has been completed. Then the unmanned aerial vehicle automatically adjusts the direction, preparing to photograph the next blade.

[0126] In step (5), the unmanned aerial vehicle is automatically controlled to fly at an angle of (30+a) to the lower left for a preset time period, which is the flight time period recorded by the unmanned aerial vehicle in step (4) from the blade root of the blade 102 to the blade tip.

[0127] In step (6), then the unmanned aerial vehicle is automatically controlled to fly horizontally to the left, and when the blade (for example, the blade root of the blade 103) is detected again through the ultrasonic ranging device, the unmanned aerial vehicle is controlled to fly obliquely to the upper left at an angle of 30-a and perform photographing, until the ultrasonic ranging sensor cannot detect the ultrasonic echo, at which time it is judged that the photographing of the blade 103 has been completed.

[0128] At this step (6), the UAV has completed the photographing operation of all the blades, and then the UAV can return to the preset position (for example, the preset coordinates on the ground).

[0129] In the present disclosure, during the flight of the UAV, the blade contour line and the center line can be detected, and if it is detected that the position of the UAV deviates, the position of the UAV is automatically corrected, for example, if it is detected that the position deviates to the left, the position of the UAV is automatically corrected to the right; or if it is detected that the position deviates to the right, the position of the UAV is automatically corrected to the left; or if it is detected that the position deviates upward, the position of the UAV is automatically corrected downward; or if it is detected that the position deviates downward, the position of the UAV is automatically corrected upward.

[0130] In the present disclosure, after the UAV completes the image shooting and storage of all the blades, the controller (which can include a processor (for example, a central processing unit (CPU)) and an image processing device (referred to as GPU)) of the UAV can process all the image data to analyze the blade state data, for example, the specific situation of the existence of cracks. For example, such blade state data can be displayed on the UAV through different color indicator lights (for example, the detection indicator light in Figure 7 For each blade, the indicator light can be set as a three-color indicator light, which respectively represents three states of normal blade (green), slightly abnormal blade (yellow), and severely abnormal blade (red).

[0131] In addition, in the present disclosure, the UAV is also provided with an automatic direction adjusting device and a camera device. The automatic direction adjusting device is configured to control the flight of the UAV in the direction control to automatically complete the shooting of all the blades without the need for human operation control by the relevant personnel. The camera device is configured to obtain a graph, so that the GPU can identify the features of the graph through, for example but not limited to, a contour line detection algorithm.

[0132] Figure 8 is a structural block diagram showing a detection device for the state of a fan blade according to an embodiment of the present disclosure. Figure 9A and Figure 9B are respectively schematic diagrams showing a detection system for the state of a fan blade according to an embodiment of the present disclosure.

[0133] Referring to Figure 8 , the detection device 800 for the state of a fan blade according to an embodiment of the present disclosure can include a communication module 810 and a control module 820.

[0134] According to an embodiment of the present disclosure, the communication module 810 is configured to receive fan state data via a communication connection between the UAV and the fan.

[0135] For example, in one example, the function of the communication module 810 can be implemented byFigure 9A In another example, if it has been determined that the detection is to be performed in the situation of the shutdown of the wind turbine before the shutdown of the wind turbine, the function of the communication module 810 can also be implemented without the wireless communication module as shown in FIG. 8B. Figure 9B The function of the communication module 810 can also be implemented without the wireless communication module as shown in FIG. 8B.

[0136] According to an embodiment of the present disclosure, the control module 820 is configured to perform the following operations 1) and 2):

[0137] In operation 1), in response to the wind turbine state data indicating that the wind turbine is in the running state, the unmanned aerial vehicle is controlled to fly along a first flight path to take images of the wind turbine blades to obtain first images, so as to detect the wind turbine blade state through the first images. Here, the first images include images of all the wind turbine blades taken at preset time intervals when the unmanned aerial vehicle is in a hovering state.

[0138] As an example, operation 1) can further include: in response to the wind turbine state data indicating that the wind turbine is in the running state, performing the following processes 11) and 12):

[0139] In process 11), based on the wind turbine hub height in the wind turbine state data, the unmanned aerial vehicle is controlled to hover after flying to a preset hovering position along the first flight path.

[0140] In process 12), after the unmanned aerial vehicle hovers, the wind turbine blades are taken to obtain first images, so as to detect the wind turbine blade state through the first images.

[0141] For example, the first flight path includes a flight path from the start of takeoff of the unmanned aerial vehicle to hovering, and the preset hovering position is a position at a first preset distance from the plane of the wind turbine hub and a second preset distance from the center axis of the wind turbine hub. In addition, as an example, the preset hovering position can include at least one preset hovering position.

[0142] As an example, process 12) can further include: after the unmanned aerial vehicle hovers, performing the following processes 121) to 125):

[0143] In process 121), by a ranging device located in the unmanned aerial vehicle, a first time point at which a first wind turbine blade passes through an effective shooting area of the unmanned aerial vehicle and a second time point at which a second wind turbine blade passes through the effective shooting area of the unmanned aerial vehicle are detected.

[0144] In process 122), when a preset time interval has elapsed after the second time point, the unmanned aerial vehicle is controlled to automatically take an image of a third wind turbine blade. Here, the preset time interval is equal to the difference between the second time point and the first time point minus the difference of the preset shooting time of the unmanned aerial vehicle.

[0145] In process 123), by the ranging device, a third time point at which the third wind turbine blade passes through the effective shooting area of the unmanned aerial vehicle is detected.

[0146] In the processing 124), in response to the difference between the third time point and the second time point minus the preset time interval being less than or equal to the preset threshold value, the following processing 1241) to 1243) are performed:

[0147] In the processing 1241), when the preset time interval has elapsed after the third time point, the unmanned aerial vehicle is controlled to automatically capture the first fan blade image.

[0148] In the processing 1242), the fourth time point at which the first fan blade passes through the effective shooting area of the unmanned aerial vehicle again is detected by the ranging device.

[0149] In the processing 1243), when the preset time interval has elapsed after the fourth time point, the unmanned aerial vehicle is controlled to automatically capture the second fan blade image, thereby obtaining a first image including the third fan blade image, the first fan blade image, and the second fan blade image, to detect the fan blade state through the first image.

[0150] In addition, after the processing 123), in the processing 125), in response to the difference between the third time point and the second time point minus the preset time interval being greater than the preset threshold value, the step of detecting the first time point at which the first fan blade passes through the effective shooting area of the unmanned aerial vehicle and the second time point at which the second fan blade passes through the effective shooting area of the unmanned aerial vehicle is returned to perform, to reacquire a first updated image after the fan speed changes, thereby detecting the fan blade state through the first updated image.

[0151] As an example, in the case where the preset hovering position includes at least one preset hovering position, the processing 12) can further include: capturing a set of blade partial images corresponding to the current hovering position after the unmanned aerial vehicle hovers at each of the at least one preset hovering position, to obtain a first image. Here, the first image includes at least one set of blade partial images corresponding to at least one hovering position captured by the unmanned aerial vehicle at the at least one hovering position, and the at least one set of blade partial images constitutes a complete image of all fan blades.

[0152] In operation 2), in response to the fan state data indicating that the fan is in a shutdown state, the unmanned aerial vehicle is controlled to fly according to a second flight path to capture fan blades to obtain a second image, to detect the fan blade state through the second image. Here, the second image includes an image of all fan blades captured in real time when the unmanned aerial vehicle is in a non-hovering state.

[0153] As an example, operation 2) can further include: in response to the fan state data indicating that the fan is in a shutdown state, the following processing 21) and 22) are performed:

[0154] In the process 21), a first included angle between the first wind turbine blade and a vertical direction is determined based on the wind turbine state data.

[0155] In the process 22), the UAV is controlled to take real-time images of the wind turbine along a second flight path corresponding to the first included angle to detect the wind turbine blade state through the second images.

[0156] As an example, the process 22) can further include controlling the UAV to take real-time images of the first wind turbine blade image, the second wind turbine blade image and the third wind turbine blade image along a flight path corresponding to the first included angle, a flight path corresponding to the second included angle and a flight path corresponding to the third included angle, respectively, to obtain the second images including the first wind turbine blade image, the second wind turbine blade image and the third wind turbine blade image, to detect the wind turbine blade state through the second images.

[0157] Here, the second included angle is an angle having an included angle of 30 degrees with the horizontal direction and a sum of the first included angle and 30 degrees, and the third included angle is an angle having an included angle of 30 degrees with the horizontal direction and a difference between the first included angle and 30 degrees.

[0158] For example, the process 22) can further include processes 221) to 225):

[0159] In the process 221), in response to a ranging device located in the UAV detecting that the UAV flies to a position corresponding to a tip of the first wind turbine blade, the UAV is controlled to fly upward to the left at the first included angle and take real-time images of the first wind turbine blade until the ranging device detects that the UAV flies to a position beyond a hub of the wind turbine.

[0160] In the process 222), in response to the ranging device detecting that the UAV flies to a position beyond the hub of the wind turbine, the UAV is controlled to fly upward to the right at the second included angle and take real-time images of the second wind turbine blade until the ranging device detects that the UAV flies to a position beyond a tip of the second wind turbine blade.

[0161] In the process 223), in response to the ranging device detecting that the UAV flies to a position beyond the tip of the second wind turbine blade, the UAV is controlled to fly downward to the left at the second included angle for a preset time period. Here, the preset time period is a time period corresponding to taking real-time images of the second wind turbine blade.

[0162] In the process 224), the UAV is controlled to fly leftward along the horizontal direction until the ranging device detects that the UAV flies to a position corresponding to a root of the third wind turbine blade.

[0163] In the processing 225), in response to the ranging device detecting that the UAV flies to a position corresponding to the root of the third fan blade, the UAV is controlled to fly left up at a third included angle and take a third fan blade image in real time until the ranging device detects that the UAV flies to a position beyond the tip of the third fan blade.

[0164] Referring to Figure 9A , the detection system of the fan blade state according to the embodiments of the present disclosure can include: a UAV controller (including a processor), a ranging device (including a control circuit, a transmitter and a receiver), an image processing device (which can be referred to as GPU for short) (here, although the GPU is shown as being independent of the UAV controller, it can be included in the UAV controller) and a wireless communication module.

[0165] According to the embodiments of the present disclosure, the wireless communication module can be configured to receive data transmitted by a ground controller of the UAV, and / or communicate data with a fan controller. For example, the communication data includes but is not limited to impeller speed, fan state, impeller azimuth angle, wind speed value, wind direction value, etc. In addition, the wireless communication module supports various communication protocols, such as WiFi, Bluetooth (here, the distance of Bluetooth communication can reach 300m under preset conditions), various generations of mobile communication technology protocols.

[0166] As an example, the wireless communication module can communicate with the fan controller or the ground controller and obtain the state data of the fan in real time, so as to automatically execute the detection method of the present disclosure according to the actual running state of the fan.

[0167] For example, Figure 10 A flowchart showing that the wireless communication module is in communication connection with the fan controller is shown. Referring to Figure 10 , Figure 10 is an example flowchart for communication address matching according to the embodiments of the present disclosure, the overall process includes: setting the corresponding communication address in the controller of the UAV according to the fan number in the wind farm, and establishing connection with the corresponding fan. The specific steps S1001 to S1007 can be shown as Figure 10 , which will not be described here again.

[0168] It is worth noting that in step S1004, if the fan is not powered on, the second scheme is directly executed. Here, the wireless communication module can judge that the fan is not powered on through communication connection failure, but the present disclosure is not limited thereto, but also can judge that the fan is not powered on through other ways, for example, receiving information corresponding to the fan not being powered on from the ground controller, etc. In addition, after step S1007, the specific detection operation to be executed can be judged according to the execution conditions of the first scheme and the second scheme.

[0169] According to an embodiment of the present disclosure, the control circuit works as follows: the control circuit first sends a generating pulse signal to the transmitter (e.g., an ultrasonic probe), and then the transmitter emits an ultrasonic signal to the outside; the ultrasonic signal encounters the blocking of the blade to generate a return pulse signal, which is received by the receiver; the control circuit calculates the time difference (e.g., T as shown in Figure 9A and 9B ) between the generating pulse signal and the return pulse signal, and then multiplies the time difference by the speed of sound to obtain the distance (e.g., L as shown in Figure 9A and 9B ) between the UAV and the blade, and transmits the distance to the controller of the UAV for controlling the flight of the UAV.

[0170] In addition, a display screen can also be provided in the UAV and / or in the ground controller corresponding to the UAV for displaying the automatically saved abnormal image of the blade for identification and confirmation by relevant personnel.

[0171] It should be noted that the operations performed by each of the above structural blocks can be similar to those described with reference to Figure 1 , which will not be described here again.

[0172] Figure 11 is a block diagram illustrating a computing device 1100 for a UAV according to an embodiment of the present disclosure.

[0173] Referring to Figure 11 , the computing device 1100 for a UAV according to an embodiment of the present disclosure can include a processor 1110 and a memory 1120. The processor 1110 can include, but is not limited to, a central processing unit (CPU), a digital signal processor (DSP), a microcomputer, a field programmable gate array (FPGA), a system on chip (SoC), a microprocessor, an application specific integrated circuit (ASIC), etc. The memory 1120 can store computer executable instructions to be executed by the processor 1110. When the processor 1110 executes the computer executable instructions stored in the memory 1120, the detection method as described above can be implemented.

[0174] The detection method according to embodiments of the disclosure can be written as computer programs / instructions to form a computer program product and stored on a computer readable storage medium. When the computer programs / instructions are executed by a processor, the detection method as described above can be implemented. When the instructions in the computer readable storage medium are executed by the processor of the electronic device / server, the electronic device / server is enabled to perform the detection method as described above. Examples of the computer readable storage medium include read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disc memory, hard disk drive (HDD), solid state drive (SSD), card memory such as a multimedia card, secure digital (SD) card or extreme digital (XD) card, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, and any other device configured to store a computer program and any associated data, data files and data structures in a non-transitory manner and provide the computer program and any associated data, data files and data structures to a processor or computer so that the processor or computer can execute the computer program. In one example, the computer program and any associated data, data files and data structures are distributed over a networked computer system so that the computer program and any associated data, data files and data structures are stored, accessed and executed in a distributed manner by one or more processors or computers.

[0175] The detection method and device for the state of the fan blade according to embodiments of the disclosure can timely and efficiently detect the state of the fan blade under various fan operating states by proposing to use the unmanned aerial vehicle to automatically capture images according to the actual operating state of the fan, so as to realize the detection of the blade crack and the like, reduce the workload of the relevant personnel and the complexity of the operation, and reduce the maintenance downtime of the wind turbine.

[0176] On the other hand, by not limiting the operating state of the fan when performing detection by using the unmanned aerial vehicle, for example, it is not necessary to limit that the operating state of the fan must be the shutdown state, so that the loss of the power generation capacity of the wind farm is effectively reduced.

[0177] On the other hand, by using the unmanned aerial vehicle to shoot images, only image analysis is required, the difficulty of material identification is reduced, and the development workload is reduced.

[0178] On the other hand, by presetting the azimuth angle value and using the fixed included angle relationship between the blades, the unmanned aerial vehicle can automatically shoot and detect the blade images without manual operation control, thereby effectively avoiding a series of problems such as the unmanned aerial vehicle flying out of the blade detection range, the unmanned aerial vehicle colliding with the blade, and operation errors due to various reasons such as too far distance and poor line of sight when manually controlling.

[0179] On the other hand, the ultrasonic ranging device used in the present disclosure has the advantages of preventing the unmanned aerial vehicle from colliding with the blade and being used to synchronously trigger the photographing function of the unmanned aerial vehicle, so that the unmanned aerial vehicle can automatically shoot the blade images and detect them without the operation of relevant personnel. Since the ultrasonic ranging device is mainly used to detect the safety distance from the fan blade, there is no special requirement for the detection accuracy of the device, thereby reducing the equipment cost of the ultrasonic ranging device to reduce the overall cost of detection.

[0180] On the other hand, since the detection method of the present disclosure belongs to a non-contact detection method, it does not need to install any equipment on the fan, and the difficulty of implementation is greatly reduced compared with the existing detection method.

[0181] Although some embodiments of the present disclosure have been disclosed and described, those skilled in the art should understand that modifications and variations can be made to these embodiments without departing from the concept and spirit of the present disclosure, which is defined by the claims and their equivalents.

Claims

1. A method for detecting the condition of wind turbine blades, characterized in that, The detection method is applied to the controller of a drone, and the detection method includes: The drone's controller receives wind turbine status data via a communication connection between the drone and the wind turbine. In response to the wind turbine status data indicating that the wind turbine is in operation, the UAV controller performs the following processing: Based on the wind turbine hub height in the wind turbine status data, the UAV is controlled to fly along a first route to a preset hovering position and then hover. After the UAV hovers, the following processing is performed: The first time point when the first wind turbine blade passes through the effective shooting area of ​​the drone, and the second time point when the second wind turbine blade passes through the effective shooting area of ​​the drone, are detected using a ranging device located in the drone. After the preset time interval has elapsed since the second time point, the drone is controlled to automatically capture images of the third wind turbine blades. The preset time interval is equal to the difference between the second time point and the first time point minus the preset image capture time of the drone. The ranging device detects the third time point at which the third wind turbine blade passes through the effective shooting area of ​​the drone. In response to the fact that the difference between the third time point and the second time point minus the preset time interval is less than or equal to a preset threshold, the following processing is performed: After the preset time interval has elapsed after the third time point, the drone is controlled to automatically capture images of the first wind turbine blades. The ranging device detects the fourth time point at which the first wind turbine blades pass through the effective shooting area of ​​the drone again. When the preset time interval has elapsed after the fourth time point, the drone is controlled to automatically capture images of the second wind turbine blades, thereby obtaining a first image including the third wind turbine blade image, the first wind turbine blade image, and the second wind turbine blade image, so as to detect the wind turbine blade status through the first image. The drone's controller, responding to the wind turbine status data indicating that the wind turbine is in a stopped state, controls the drone to fly along a second route to capture images of the wind turbine blades, thereby detecting the wind turbine blade status through these images. The first image includes images of all wind turbine blades taken at preset time intervals while the drone is hovering, and the second image includes images of all wind turbine blades taken in real time while the drone is not hovering.

2. The detection method according to claim 1, characterized in that, The first flight path includes the flight path from the start of the drone's takeoff to its hovering position, and the preset hovering position is a position at a first preset distance from the wind turbine hub plane and a second preset distance from the central axis of the wind turbine hub.

3. The detection method according to claim 1, characterized in that, After the step of detecting the third time point when the third wind turbine blade passes through the effective shooting area of ​​the UAV through the ranging device, in response to the difference between the third time point and the second time point minus the preset time interval being greater than the preset threshold, the step of detecting the first time point when the first wind turbine blade passes through the effective shooting area of ​​the UAV and the second time point when the second wind turbine blade passes through the effective shooting area of ​​the UAV is returned to be executed, so as to re-acquire the first updated image after the wind turbine speed change, thereby detecting the wind turbine blade status through the first updated image.

4. The detection method according to claim 1, characterized in that, The preset hovering position includes at least one preset hovering position, and the step of taking a picture of the wind turbine blades after the drone hovers to obtain the first image includes: After the drone hovers at each of the at least one preset hovering positions, it captures a set of partial images of the blades corresponding to the current hovering position to obtain a first image. The first image includes at least one set of partial images of the blades taken by the UAV at the at least one hovering position, corresponding to the at least one hovering position, and the at least one set of partial images of the blades constitutes a complete image of all wind turbine blades.

5. The detection method according to claim 1, characterized in that, The step of controlling a drone to fly along a second flight path to capture a second image of the wind turbine in response to the wind turbine status data indicating that the wind turbine is in a shutdown state, and thereby detecting the wind turbine blade status through the second image, includes: In response to the fan status data indicating that the fan is in a stopped state, the following processing is performed: Based on the fan status data, determine the first angle between the first fan blade and the vertical direction; The drone is controlled to take real-time pictures of the wind turbine along the second flight path corresponding to the first included angle to obtain a second image, so as to detect the state of the wind turbine blades through the second image.

6. The detection method according to claim 5, characterized in that, The step of controlling the drone to take real-time photos of the wind turbine to obtain a second image, along a second flight path corresponding to the first included angle, and to detect the state of the wind turbine blades through the second image includes: The drone is controlled to take real-time images of the first, second, and third wind turbine blades along routes corresponding to the first, second, and third included angles, respectively. This results in a second image comprising the images of the first, second, and third wind turbine blades, which is used to detect the state of the wind turbine blades. Wherein, the second included angle is the angle with the horizontal direction that is the sum of the first included angle and 30 degrees, and the third included angle is the angle with the horizontal direction that is the difference between 30 degrees and the first included angle.

7. The detection method according to claim 6, characterized in that, The steps of controlling the drone to capture real-time images of the first wind turbine blade, the second wind turbine blade, and the third wind turbine blade using flight paths corresponding to the first angle, the second angle, and the third angle, respectively, include: In response to the ranging device located in the drone detecting that the drone has flown to a position corresponding to the tip of the first wind turbine blade, the drone is controlled to fly to the upper left at the first included angle and take real-time images of the first wind turbine blade until the ranging device detects that the drone has flown past the position corresponding to the wind turbine hub. In response to the ranging device detecting that the UAV has flown past the position corresponding to the wind turbine hub, the UAV is controlled to fly to the upper right at the second included angle and take real-time images of the second wind turbine blade until the ranging device detects that the UAV has flown past the position corresponding to the tip of the second wind turbine blade. In response to the ranging device detecting that the UAV has flown past the position corresponding to the tip of the second wind turbine blade, the UAV is controlled to fly downward to the left at the second included angle for a preset time period, wherein the preset time period is the time period corresponding to the real-time shooting of the second wind turbine blade; Control the drone to fly horizontally to the left until the ranging device detects that the drone has flown to a position corresponding to the root of the third wind turbine blade; In response to the ranging device detecting that the UAV has flown to a position corresponding to the root of the third wind turbine blade, the UAV is controlled to fly to the upper left at the third included angle and take real-time images of the third wind turbine blade until the ranging device detects that the UAV has flown past the position corresponding to the tip of the third wind turbine blade.

8. A device for detecting the condition of wind turbine blades, characterized in that, The device includes: The communication module is configured to receive wind turbine status data via a communication connection between the drone and the wind turbine. The control module is configured as follows: In response to the wind turbine status data indicating that the wind turbine is in operation, the following processing is performed: based on the wind turbine hub height in the wind turbine status data, the UAV is controlled to fly along the first route to a preset hovering position and then hover. After the UAV hovers, it takes pictures of the wind turbine blades to obtain a first image, so as to detect the wind turbine blade status through the first image. In response to the wind turbine status data indicating that the wind turbine is in a stopped state, the drone is controlled to fly along a second route to capture images of the wind turbine blades to obtain a second image, which is then used to detect the status of the wind turbine blades. The first image includes images of all wind turbine blades taken at preset time intervals while the drone is hovering, and the second image includes images of all wind turbine blades taken in real time while the drone is not hovering. The operation of taking a picture of the wind turbine blades after the drone hovers to obtain a first image, and then detecting the state of the wind turbine blades through the first image, includes: After the drone hovers, perform the following steps: The first time point when the first wind turbine blade passes through the effective shooting area of ​​the drone and the second time point when the second wind turbine blade passes through the effective shooting area of ​​the drone are detected by the ranging device located in the drone. When the preset time interval has elapsed after the second time point, the drone is controlled to automatically capture an image of the third wind turbine blade, wherein the preset time interval is equal to the difference between the second time point and the first time point minus the preset photo capture time of the drone. The ranging device is used to detect the third time point when the third wind turbine blade passes through the effective shooting area of ​​the UAV. In response to the fact that the difference between the third time point and the second time point minus the preset time interval is less than or equal to a preset threshold, the following processing is performed: After the preset time interval has elapsed after the third time point, the drone is controlled to automatically capture images of the first wind turbine blades; The ranging device is used to detect the fourth time point at which the first wind turbine blade passes through the effective shooting area of ​​the drone again. After the preset time interval has elapsed after the fourth time point, the drone is controlled to automatically capture images of the second wind turbine blades, thereby obtaining the first image, which includes the third wind turbine blade image, the first wind turbine blade image, and the second wind turbine blade image, so as to detect the wind turbine blade status through the first image.

9. A computer program product, characterized in that, The computer program product includes a computer program / instruction that, when executed by a processor, implements the method for detecting the state of wind turbine blades as described in any one of claims 1 to 7.

10. A computing device for an unmanned aerial vehicle (UAV), characterized in that, include: At least one processor; At least one memory that stores computer-executable instructions. The computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the wind turbine blade state detection method as described in any one of claims 1 to 7.

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