Photovoltaic module inspection method and inspection system based on unmanned aerial vehicle

Abstract

The invention discloses a photovoltaic module inspection method and inspection system based on an unmanned aerial vehicle. The inspection method for the photovoltaic module based on the unmanned aerial vehicle comprises the following steps: performing first inspection on the photovoltaic module to obtain a first coordinate of a fault module; taking the first coordinate as a first inspection point, and planning a first inspection path based on the first inspection point; according to the first inspection path, utilizing the unmanned aerial vehicle to obtain an electroluminescent image set corresponding to the fault component; fault identification is carried out according to the electroluminescent image set, a second fault type of the target fault component is obtained, and the flight height of the unmanned aerial vehicle during first inspection is larger than the flight height of the unmanned aerial vehicle during flying of the first inspection path. According to the photovoltaic module inspection method based on the unmanned aerial vehicle provided by the embodiment of the invention, the blindness of inspection can be reduced, targeted fault type acquisition and fault cause acquisition are performed on the fault module, and the fault identification accuracy is ensured while high-efficiency inspection is ensured.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic power stations, and in particular to an inspection method and inspection system for photovoltaic components based on drones. Background Art

[0002] Photovoltaic energy, as a clean and renewable energy form, has been widely used and developed around the world. Photovoltaic power generation systems convert sunlight into electrical energy, which not only helps reduce greenhouse gas emissions, but also reduces dependence on traditional fossil energy.

[0003] Photovoltaic modules are installed outdoors and are prone to failure under the influence of the outdoor environment. Using drone inspections instead of manual inspections can improve inspection efficiency.

[0004] The current inspection method for photovoltaic modules is to control drones to inspect along a planned route and take infrared or electroluminescent photos. However, the flight altitude is very high when taking infrared photos, and only faulty components can be identified, but the type of fault cannot be identified. The flight altitude is very low when taking electroluminescent photos, and the type of fault can be identified, but the field of view is small, resulting in low efficiency. Summary of the invention

[0005] The present application provides a photovoltaic component inspection method and inspection system based on an unmanned aerial vehicle, which can inspect photovoltaic components with both efficiency and accuracy.

[0006] In a first aspect, an embodiment of the present application provides a method for inspecting photovoltaic components based on a drone, comprising: performing a first inspection on the photovoltaic components to obtain first coordinates of the faulty component; using the first coordinates as a first inspection point, and planning a first inspection path based on the first inspection point; and according to the first inspection path, using a drone to obtain an electroluminescent image set corresponding to the faulty component; performing fault identification according to the electroluminescent image set to obtain a second fault type of the target faulty component, wherein the flight altitude of the drone during the first inspection is greater than the flight altitude for executing the first inspection path.

[0007] According to the aforementioned implementation manner of the first aspect of the present application, the method of obtaining an electroluminescent image set corresponding to a faulty component by using a drone according to the first inspection path includes: performing a second inspection on the faulty component according to the first inspection path through a camera component carried by the drone to obtain a second image set, wherein the second image set includes a second infrared image and a second visible light image; performing fault identification on the faulty component based on the second image set to obtain second coordinates and a first fault type; screening out a target fault point from the second coordinates according to a degree of match between the second coordinates and the first coordinates; obtaining a third coordinate corresponding to the target fault point, and planning a second inspection path based on the third coordinates; obtaining an electroluminescent image set corresponding to the faulty component by using a drone according to the second inspection path, wherein the flight altitude during the execution of the second inspection path is lower than the flight altitude during the second inspection.

[0008] According to any of the aforementioned implementations of the first aspect of the present application, the flight altitude during the second inspection process is less than or equal to the flight altitude during the first inspection.

[0009] According to any of the aforementioned implementations of the first aspect of the present application, the step of screening out the target fault point from the second coordinates based on the degree of matching between the second coordinates and the first coordinates includes: taking the second coordinate that is the same as the first coordinate as the target fault point.

[0010] According to any of the aforementioned embodiments of the first aspect of the present application, the fault identification is performed according to the electroluminescent image set to obtain the second fault type of the target faulty component, including: identifying the faulty component according to the electroluminescent image set to obtain the third coordinates and the second fault type of the faulty component, wherein the second fault type includes: hot spots, hidden cracks, broken fragments, and broken grids.

[0011] According to any of the aforementioned embodiments of the first aspect of the present application, the step of screening out the target fault point from the second coordinates based on the degree of matching between the second coordinates and the first coordinates includes: taking the second coordinates that are the same as the first coordinates and whose first fault type is a hot spot or fragmentation as the target fault point.

[0012] According to any of the aforementioned embodiments of the first aspect of the present application, the fault identification is performed according to the electroluminescent image set to obtain the second fault type of the target faulty component, including: the faulty component is identified according to the electroluminescent image set to obtain the third coordinates and the second fault type of the faulty component, wherein the second fault type includes: hot spots and hidden cracks.

[0013] According to any of the aforementioned implementations of the first aspect of the present application, the method further includes: obtaining a corresponding fault cause based on a corresponding relationship between the second fault type and the first fault type.

[0014] According to any of the aforementioned implementations of the first aspect of the present application, the corresponding fault cause is obtained according to the correspondence between the second fault type and the first fault type, including: for the target fault component, when the first fault type is a hot spot and the second fault type is a hidden crack, the photovoltaic component corresponding to the third coordinate is used as the target fault component, and the corresponding fault type is hidden crack; when the first fault type is a hot spot and the second fault type is no fault, the photovoltaic component corresponding to the third coordinate is used as the target fault component, and the corresponding fault type is an external cause.

[0015] According to any of the aforementioned embodiments of the first aspect of the present application, the corresponding fault cause is obtained according to the correspondence between the second fault type and the first fault type, including: for the target faulty component, when the first fault type is fragmentation and the second fault type is hot spot, it is determined that the target faulty component is slightly fragmented; when the first fault type is fragmentation and the second fault type is fragmentation, it is determined that the target faulty component is severely fragmented.

[0016] In a second aspect, an embodiment of the present application provides a photovoltaic component inspection system, comprising: a drone, used to perform a first inspection on the photovoltaic component to obtain a first coordinate of a faulty component, and used to obtain an electroluminescent image set corresponding to the faulty component according to a first inspection path, wherein the flight altitude of the drone when performing the first inspection is greater than the flight altitude of the first inspection path;

[0017] An image processing device is communicatively connected to the drone, and the image processing device is configured to use the first coordinate as a first inspection point, plan the first inspection path based on the first inspection point, perform fault identification based on the electroluminescent image set, and obtain a second fault type of the target faulty component.

[0018] According to the inspection method of photovoltaic components based on drones in the embodiment of the present application, the photovoltaic components are successively inspected for the first time and the inspection of the first inspection path is performed. The flight altitude of the drone during the first inspection is greater than the flight altitude of the first inspection path. Therefore, the flight altitude is high when the first inspection is performed, the field of view is large, and the first coordinates of the faulty component can be efficiently obtained. When the first inspection path is executed, the flight altitude is low, and the electroluminescent image set corresponding to the faulty component can be obtained at this time. The fault identification based on the electroluminescent image set has a high recognition accuracy, and the fault type and cause can be identified. When planning the first inspection path, the first coordinate is used as the first inspection point, and the first inspection path is planned based on the first inspection point. Therefore, when performing fault identification based on the electroluminescent image set, the blindness of the inspection can be reduced, and the fault type and cause of the fault component can be obtained in a targeted manner, thereby ensuring the accuracy of fault identification while ensuring high-efficiency inspection, efficiently and accurately discovering the cause of the faulty component, improving the efficiency of photovoltaic component operation and maintenance, and facilitating the improvement of the power generation of photovoltaic components. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0020] Figure 1 This is a flow chart of an embodiment of a photovoltaic module fault detection method of the present application;

[0021] Figure 2 A flowchart of using a drone to obtain an electroluminescent image set corresponding to a faulty component according to a first inspection path in an alternative embodiment of a fault detection method for a photovoltaic component of the present application;

[0022] Figure 3 This is a schematic structural diagram of an embodiment of a photovoltaic module inspection system of the present application;

[0023] Figure 4 This is a schematic diagram of the hardware structure of an image processing device according to an embodiment of the present application.

[0024] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0026] It should be noted that all directional indications in the embodiments of the present application (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0027] In addition, the descriptions of "first", "second", etc. in this application are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0028] Photovoltaic modules refer to the basic components of photovoltaic power generation systems. Photovoltaic modules include multiple cells (solar cells). These cells are connected together in a specific way and connected to other components through current leads and junction boxes to form independent photovoltaic power generation modules.

[0029] An embodiment of the present application provides a method for inspecting photovoltaic components based on a drone. Figure 1 This is a flow chart of an embodiment of a photovoltaic module fault detection method of the present application. The photovoltaic module fault detection method includes steps S110 to S130.

[0030] In step S110, a first inspection is performed on the photovoltaic components to obtain the first coordinates of the faulty components.

[0031] In some embodiments, a camera assembly carried by a drone is used to perform a first inspection of a photovoltaic assembly to obtain a first image set, wherein the first image set includes a first infrared image and a first visible light image. A fault of the photovoltaic assembly is identified based on the first image set to obtain a faulty assembly and a first coordinate of the faulty assembly.

[0032] The camera assembly is, for example, a pan-tilt camera assembly. The camera assembly may include an infrared image acquisition device and a visible light image acquisition device. The infrared image acquisition device is used to acquire infrared images, and the visible light image acquisition device is used to acquire visible light images.

[0033] In one example, the first inspection is for photovoltaic components of the entire photovoltaic power station. In other optional embodiments, the first inspection may be for photovoltaic components of a target area in the photovoltaic power station.

[0034] In step S120, the first coordinate is used as a first inspection point, and a first inspection path is planned based on the first inspection point; and according to the first inspection path, a drone is used to obtain an electroluminescent image set corresponding to the faulty component.

[0035] In step S130, fault identification is performed based on the electroluminescent image set to obtain a second fault type of the target faulty component, wherein the flight altitude of the drone during the first inspection is greater than the flight altitude of the drone during the first inspection path.

[0036] According to the fault detection method of the photovoltaic component of the embodiment of the present application, the photovoltaic component is successively inspected for the first time and the inspection of the first inspection path is performed. The flying altitude of the drone during the first inspection is greater than the flying altitude of the first inspection path. Therefore, the flying altitude is high when the first inspection is performed, the field of vision is large, and the first coordinates of the faulty component can be efficiently obtained. When flying the first inspection path, the flying altitude is low, and the electroluminescent image set corresponding to the faulty component can be obtained at this time. The fault identification based on the electroluminescent image set has a high recognition accuracy, and the fault type and cause can be identified. When planning the first inspection path, the first coordinate is used as the first inspection point, and the first inspection path is planned based on the first inspection point. Therefore, when performing fault identification based on the electroluminescent image set, the blindness of the inspection can be reduced, and the fault type and cause of the fault can be obtained in a targeted manner for the faulty component, thereby ensuring the accuracy of fault identification while ensuring high-efficiency inspection, efficiently and accurately discovering the cause of the faulty component, improving the efficiency of photovoltaic component operation and maintenance, and facilitating the improvement of the power generation of photovoltaic components.

[0037] In some embodiments, according to the first inspection path, the drone is directly used to obtain the electroluminescent image set corresponding to the faulty component. In some other embodiments, according to the first inspection path, the drone can be further used to obtain the electroluminescent image set corresponding to the faulty component after at least one inspection.

[0038] Figure 2A flowchart of using a drone to obtain an electroluminescent image set corresponding to a faulty component according to a first inspection path in an alternative embodiment of a fault detection method for a photovoltaic component of the present application. In some embodiments, the step of using a drone to obtain an electroluminescent image set corresponding to a faulty component according to the first inspection path further includes steps S121 to S125.

[0039] In step S121, a second inspection is performed on the faulty component according to the first inspection path by using the camera component carried by the drone to obtain a second image set, wherein the second image set includes a second infrared image and a second visible light image.

[0040] In step S122, fault identification is performed on the faulty component based on the second image set to obtain second coordinates and the first fault type.

[0041] In step S123, the target fault point is screened out from the second coordinates according to the matching degree between the second coordinates and the first coordinates.

[0042] In step S124, the third coordinates corresponding to the target fault point are obtained, and a second inspection path is planned based on the third coordinates.

[0043] In step S125, according to the second inspection path, the UAV is used to obtain the electroluminescent image set corresponding to the faulty component, wherein the flight altitude during the execution of the second inspection path is lower than the flight altitude during the second inspection.

[0044] In some embodiments, the flight height during the second inspection is less than or equal to the flight height during the first inspection.

[0045] In some embodiments, the above-mentioned step S123 of screening out the target fault point from the second coordinate according to the matching degree between the second coordinate and the first coordinate includes: taking the second coordinate identical to the first coordinate as the target fault point. At this time, the faulty components having the same coordinates as the first inspection and the second inspection are screened out as the target fault point, and then after fault identification is performed according to the electroluminescent image set, multiple fault types of the target fault point can be identified, such as hot spots, hidden cracks, broken pieces, broken grids and other faults. That is, at this time, the step S130 of performing fault identification according to the electroluminescent image set to obtain the second fault type of the target faulty component may include: performing faulty component identification according to the electroluminescent image set to obtain the third coordinates and the second fault type of the faulty component, wherein the second fault type includes: hot spots, hidden cracks, broken pieces, broken grids.

[0046] In some other embodiments, the step S123 of selecting the target fault point from the second coordinate according to the matching degree between the second coordinate and the first coordinate includes: taking the second coordinate that is the same as the first coordinate and the first fault type is a hot spot or a fragmentation as the target fault point. That is, at this time, the specific hot spot and fragmentation target fault points are selected as the fault points that need to be further detected. At this time, the step S130 of performing fault identification according to the electroluminescent image set to obtain the second fault type of the target fault component may include: performing fault component identification according to the electroluminescent image set to obtain the third coordinate and the second fault type of the fault component, wherein the second fault type includes: hot spot and hidden crack.

[0047] In some embodiments, the inspection method of photovoltaic components based on a drone further includes: obtaining a corresponding fault cause according to a corresponding relationship between the second fault type and the first fault type.

[0048] When the first fault type obtained in the second inspection is a hot spot, the cause of the fault can be further known based on the correspondence between the second fault type and the first fault type obtained later.

[0049] In one example, the step of obtaining the corresponding fault cause according to the corresponding relationship between the second fault type and the first fault type includes: for the target fault component, when the first fault type is a hot spot and the second fault type is a hidden crack, the photovoltaic component corresponding to the third coordinate is used as the target fault component, and the corresponding fault type is hidden crack; when the first fault type is a hot spot and the second fault type is no fault, the photovoltaic component corresponding to the third coordinate is used as the target fault component, and the corresponding fault type is an external cause. The external cause is, for example, obstruction caused by external causes such as dust accumulation and bird droppings.

[0050] When the first fault type obtained in the second inspection is fragmentation, the cause of the fault can be further known according to the correspondence between the second fault type and the first fault type obtained later. In this embodiment, the fragmentation fault is the fragmentation of the battery cell.

[0051] In one example, the step of obtaining the corresponding fault cause based on the correspondence between the second fault type and the first fault type includes: for the target faulty component, when the first fault type is fragmentation and the second fault type is hot spot, determining that the target faulty component is slightly fragmented; when the first fault type is fragmentation and the second fault type is fragmentation, determining that the target faulty component is severely fragmented.

[0052] According to the fault detection method of the photovoltaic module in the above embodiment, the corresponding fault cause is obtained according to the corresponding relationship between the second fault type and the first fault type, so that when the photovoltaic module is found to have hot spots, fragmentation and other faults, the specific fault cause can be further known, so that the operation and maintenance personnel can eliminate the fault according to the specific fault cause, thereby further improving the efficiency of the operation and maintenance of the photovoltaic module and facilitating the improvement of the power generation of the photovoltaic module.

[0053] The present application also provides a photovoltaic module inspection system. Figure 3 1 is a schematic diagram of a photovoltaic module inspection system according to an embodiment of the present invention. The photovoltaic module inspection system includes a drone 110 and an image processing device 120. The image processing device 120 is in communication connection with the drone 110.

[0054] The drone 110 is used to perform a first inspection on the photovoltaic components, obtain the first coordinates of the faulty components, and acquire a set of electroluminescent images corresponding to the faulty components according to a first inspection path, wherein the flight altitude of the drone during the first inspection is greater than the flight altitude of the first inspection path.

[0055] The image processing device 120 is configured to use the first coordinate as a first inspection point, plan a first inspection path based on the first inspection point, perform fault identification according to the electroluminescent image set, and obtain a second fault type of the target faulty component.

[0056] The inspection system of photovoltaic components according to the embodiment of the present application includes a communication-connected drone 110 and an image processing device 120. The drone 110 performs a first inspection on the photovoltaic components and an inspection along the first inspection path. The flight altitude of the drone 110 during the first inspection is greater than the flight altitude of the first inspection path. Therefore, the flight altitude is high when performing the first inspection, and the field of view is large, so the first coordinates of the faulty component can be efficiently acquired. When flying the first inspection path, the flight altitude is low, and the electroluminescent image set corresponding to the faulty component can be acquired at this time. The fault identification based on the electroluminescent image set has a high recognition accuracy, and the fault type and cause can be identified. When planning the first inspection path, the image processing device 120 uses the first coordinate as the first inspection point, and plans the first inspection path based on the first inspection point. Therefore, when performing fault identification based on electroluminescent image sets, the blindness of the inspection can be reduced, and the fault type and cause of the faulty component can be obtained in a targeted manner, thereby ensuring the accuracy of fault identification while ensuring high-efficiency inspections, efficiently and accurately discovering the causes of faulty components, improving the efficiency of photovoltaic component operation and maintenance, and facilitating the improvement of photovoltaic component power generation.

[0057] Figure 4The hardware structure diagram of an embodiment of the image processing device of the present application is shown in FIG. In some embodiments, the image processing device 120 includes a memory 121 and at least one processor 122, the memory 121 stores instructions, and the at least one processor 122 calls the instructions in the memory 121, so that the image processing device 120 executes an image processing method to realize fault detection of photovoltaic modules.

[0058] The image processing method comprises: taking the first coordinate as a first inspection point, planning a first inspection path based on the first inspection point, performing fault identification according to an electroluminescent image set, and obtaining a second fault type of a target fault component.

[0059] Specifically, the processor 122 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0060] The memory 121 may include a large capacity memory 121 for data or instructions. By way of example and not limitation, the memory 121 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 121 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 121 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 121 is a non-volatile solid-state memory. In a specific embodiment, the memory 121 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0061] In one example, the image processing device 120 may further include a communication interface 123 and a bus 124. The processor 122, the memory 121, and the communication interface 123 are connected via the bus 124 and communicate with each other.

[0062] The communication interface 123 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0063] Bus 124 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory 121 bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 124 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0064] In addition, in combination with the image processing method in the above embodiment, the present application embodiment may provide a computer-readable storage medium for implementation. The computer-readable storage medium stores instructions, and when the instructions are executed by a processor, the image processing method in the above embodiment is implemented.

[0065] The image processing method comprises: taking the first coordinate as a first inspection point, planning a first inspection path based on the first inspection point, performing fault identification according to an electroluminescent image set, and obtaining a second fault type of a target fault component.

[0066] The present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0067] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0068] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0069] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for inspecting photovoltaic components based on drones, characterized in that: include: Perform a first inspection on the photovoltaic components to obtain the first coordinates of the faulty components; Taking the first coordinate as a first inspection point, and planning a first inspection path based on the first inspection point; and according to the first inspection route, using a drone to obtain an electroluminescent image set corresponding to the faulty component; Fault identification is performed based on the electroluminescent image set to obtain a second fault type of the target faulty component, wherein the flight altitude of the drone during the first inspection is greater than the flight altitude of the drone during the first inspection path.

2. The photovoltaic module fault detection method according to claim 1, characterized in that: The method of acquiring an electroluminescent image set corresponding to the faulty component by using a drone according to the first inspection path includes: Using the camera component carried by the drone, a second inspection is performed on the faulty component according to the first inspection path to obtain a second image set, wherein the second image set includes a second infrared image and a second visible light image; Performing fault identification on the faulty component based on the second image set to obtain second coordinates and a first fault type; According to the matching degree between the second coordinate and the first coordinate, the target fault point is selected from the second coordinate; Acquire a third coordinate corresponding to the target fault point, and plan a second inspection path based on the third coordinate; According to the second inspection path, a drone is used to obtain an electroluminescent image set corresponding to the faulty component, wherein the flight altitude during the execution of the second inspection path is lower than the flight altitude during the second inspection.

3. The photovoltaic module fault detection method according to claim 2, characterized in that: The flight altitude during the second inspection is less than or equal to the flight altitude during the first inspection.

4. The photovoltaic module fault detection method according to claim 2, characterized in that: The step of selecting the target fault point from the second coordinate according to the matching degree between the second coordinate and the first coordinate includes: A second coordinate that is the same as the first coordinate is used as a target fault point.

5. The photovoltaic module fault detection method according to claim 4, characterized in that: The performing fault identification according to the electroluminescent image set to obtain a second fault type of the target faulty component includes: The faulty component is identified according to the electroluminescent image set to obtain the third coordinates and the second fault type of the faulty component, wherein the second fault type includes: hot spot, hidden crack, broken fragment, and broken grid.

6. The photovoltaic module fault detection method according to claim 2, characterized in that: The step of selecting the target fault point from the second coordinate according to the matching degree between the second coordinate and the first coordinate includes: A second coordinate that is the same as the first coordinate and whose first fault type is a hot spot or a fragmentation is used as a target fault point.

7. The photovoltaic module fault detection method according to claim 6, characterized in that: The performing fault identification according to the electroluminescent image set to obtain a second fault type of the target faulty component includes: The faulty component is identified according to the electroluminescent image set to obtain the third coordinates and the second fault type of the faulty component, wherein the second fault type includes: hot spots and hidden cracks.

8. The photovoltaic module fault detection method according to claim 5 or 7, characterized in that: The method further includes: acquiring a corresponding fault cause according to a corresponding relationship between the second fault type and the first fault type.

9. The photovoltaic module fault detection method according to claim 8, characterized in that: The obtaining a corresponding fault cause according to a corresponding relationship between the second fault type and the first fault type includes: For the target faulty component, when the first fault type is a hot spot and the second fault type is a hidden crack, the photovoltaic component corresponding to the third coordinate is used as the target faulty component, and the corresponding fault type is hidden crack; When the first fault type is a hot spot and the second fault type is no fault, the photovoltaic component corresponding to the third coordinate is used as the target fault component, and the corresponding fault type is an external cause.

10. The photovoltaic module fault detection method according to claim 8, characterized in that: The obtaining a corresponding fault cause according to a corresponding relationship between the second fault type and the first fault type includes: For the target faulty component, when the first fault type is fragmentation and the second fault type is hot spot, it is determined that the target faulty component is slightly fragmented; When the first fault type is fragmentation and the second fault type is breakage, it is determined that the target faulty component is severely fragmented.

11. A photovoltaic module inspection system, characterized in that: include: A drone, used to perform a first inspection on a photovoltaic component to obtain a first coordinate of a faulty component, and to acquire a set of electroluminescent images corresponding to the faulty component according to a first inspection path, wherein the flying altitude of the drone during the first inspection is greater than the flying altitude of the first inspection path; An image processing device is communicatively connected to the drone, and the image processing device is configured to use the first coordinate as a first inspection point, plan the first inspection path based on the first inspection point, perform fault identification based on the electroluminescent image set, and obtain a second fault type of the target faulty component.

Images