Photovoltaic module shielding identification method, device, equipment, medium and program product

Abstract

The embodiment of the invention provides a photovoltaic module shielding identification method. The method comprises the following steps: acquiring an optical acquisition image of a photovoltaic module; performing channel separation on the optical acquisition image to obtain a blue channel image and a green channel image after channel separation; determining a shadow rate and a component coverage rate of the optical acquisition image according to the blue channel image and the green channel image; and determining the shielding rate of the photovoltaic module according to the shadow rate and the module coverage rate. According to the technical scheme of the embodiment of the invention, the efficiency and accuracy of shielding rate identification of the photovoltaic module can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of solar cells, and in particular to a photovoltaic module shading recognition method, device, computer equipment, storage medium and program product. Background Art

[0002] During the operation of photovoltaic panels, the rear-row components in the photovoltaic panel array may be blocked by the front-row components due to the change in the incident angle of sunlight during the day. These obstructions will affect the light reception of the photovoltaic panels and reduce the power generation efficiency. In order to reduce the impact of photovoltaic components being blocked, engineers need to obtain the obstruction status of the components at the incident angle of sunlight in each period, and then calculate and configure the operating parameters of the tracking bracket according to the obstruction status to achieve the optimization of the bracket rotation angle. Therefore, how to efficiently and accurately obtain the obstruction status of photovoltaic components in each period is very important.

[0003] However, the relevant technology uses drone inspections to collect videos, and then engineers manually observe the collected videos and count the obscured cells in the videos one by one to determine the obstruction rate of the photovoltaic modules. This method is time-consuming and labor-intensive, has low efficiency, and its accuracy is difficult to guarantee.

[0004] It should be noted that the above content is not necessarily prior art, nor is it intended to limit the scope of patent protection of this application. Summary of the invention

[0005] The embodiments of the present application provide a photovoltaic module shading identification method, device, computer equipment, storage medium and program product to solve or alleviate one or more technical problems raised above.

[0006] A first aspect of an embodiment of the present application provides a photovoltaic module shielding recognition method, comprising: Acquire optical acquisition images of photovoltaic modules; Performing channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation; determining a shadow rate and a component coverage rate of the optically collected image according to the blue channel image and the green channel image; The shielding rate of the photovoltaic component is determined according to the shadow rate and the component coverage rate.

[0007] Optionally, determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image includes: The shadow rate of each pixel in the optical acquisition image is determined by using a shadow rate calculation formula according to the blue channel image and the green channel image. The shadow rate calculation formula is:

[0008] Among them, the shadow ratio is the shadow ratio, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the shadow ratio is currently calculated.

[0009] Optionally, determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image includes: The component coverage of each pixel in the optical acquisition image is determined by using a coverage calculation formula according to the blue channel image and the green channel image. The coverage calculation formula is:

[0010] Among them, the module ratio is the component coverage, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the coverage is currently calculated.

[0011] Optionally, determining the shielding rate of the photovoltaic assembly according to the shadow rate and the assembly coverage rate includes: Determining a shadow area of ​​the optically collected image according to the shadow ratio; Determining a component coverage area of ​​the optically collected image according to the component coverage rate; The shielding rate of the photovoltaic component is determined according to the shadow area and the component coverage area.

[0012] Optionally, determining the shadow area of ​​the optically collected image according to the shadow ratio includes: Binarizing each pixel in the optically collected image according to the shadow rate to obtain a first binarization result of the optically collected image; generating a first mask image according to the first binarization result; The first mask image is applied to the optically collected image to determine a shadow area of ​​the optically collected image.

[0013] Optionally, determining the component coverage area of ​​the optically collected image according to the component coverage rate includes: Binarizing each pixel in the optically collected image according to the component coverage to obtain a second binarization result of the optically collected image; generating a second mask image according to the second binarization result; The second mask image is applied to the optically collected image to determine a component coverage area of ​​the optically collected image.

[0014] Optionally, determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image includes: Performing median filtering on the blue channel image and the green channel image respectively to obtain a processed blue channel image and a processed green channel image; A shadow rate and a component coverage rate of the optically collected image are determined according to the processed blue channel image and the processed green channel image.

[0015] A second aspect of an embodiment of the present application provides a photovoltaic assembly shielding recognition device, comprising: An acquisition module, used for acquiring an optical acquisition image of a photovoltaic module; A separation module, used to perform channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation; A first determination module, configured to determine a shadow rate and a component coverage rate of the optically collected image according to the blue channel image and the green channel image; The second determination module is used to determine the shielding rate of the photovoltaic component according to the shadow rate and the component coverage rate.

[0016] A third aspect of an embodiment of the present application provides a computer device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein: the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described above.

[0017] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method described above is implemented.

[0018] A fifth aspect of an embodiment of the present application provides a computer program product, including a computer program, which implements the method described above when executed by a processor.

[0019] The above technical solution adopted in the embodiment of the present application may have the following advantages: By acquiring an optical acquisition image of a photovoltaic module, performing channel separation on the optical acquisition image, acquiring a blue channel image and a green channel image after channel separation, determining the shadow rate and module coverage rate of the optical acquisition image according to the blue channel image and the green channel image, and determining the occlusion rate of the photovoltaic module according to the shadow rate and the module coverage rate, the automatic recognition and calculation of the occlusion rate of the photovoltaic module can be achieved, thereby improving the efficiency of identifying the occlusion rate of the photovoltaic module, and also improving the accuracy of identifying the occlusion rate of the photovoltaic module. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0021] Figure 1 is a flow chart of a photovoltaic module shading identification method provided in an embodiment of the present application; Figure 2 yes Figure 1 Flow chart of sub-steps of step S106; Figure 3 yes Figure 2 Flow chart of sub-steps of step S200; Figure 4 is the optical acquisition image of the photovoltaic module; Figure 5 is the binary shadow ratio image of the photovoltaic module; Figure 6 yes Figure 2 Flow chart of sub-steps of step S202; Figure 7 is the binary coverage image of photovoltaic modules; Figure 8 is a flowchart of a photovoltaic module shading identification method provided in an embodiment of the present application; Fig. 9 yes Figure 2 Flow chart of sub-steps of step S104; Fig.10 is a block diagram of a photovoltaic module shading identification device provided in an embodiment of the present application; and Fig.11 It is a schematic diagram of the hardware architecture of the computer device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings. In the accompanying drawings, for clarity, the sizes of layers, regions, elements and their relative sizes may be exaggerated. The same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limitations on the present application. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present application.

[0023] It should be noted that the descriptions involving "first", "second", etc. in the embodiments of the present application are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. 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 the 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.

[0024] In the description of the present application, it should be understood that the numerical labels before the steps do not indicate the order in which the steps are executed, but are only used to facilitate the description of the present application and to distinguish each step, and therefore should not be understood as a limitation on the present application.

[0025] In the present application, when it comes to a numerical interval (i.e., a numerical range), unless otherwise specified, the distribution of the optional numerical values ​​in the numerical interval is considered to be continuous, and includes the two numerical endpoints (i.e., the minimum and maximum values) of the numerical interval, and each numerical value between the two numerical endpoints. Unless otherwise specified, when the numerical interval only refers to an integer in the numerical interval, it includes the two endpoint integers of the numerical range, and each integer between the two endpoints, which is equivalent to directly listing each integer. When multiple numerical ranges are provided to describe features or characteristics, these numerical ranges can be merged. In other words, unless otherwise specified, the numerical range disclosed in the present application should be understood to include any and all sub-ranges included therein. The "numerical value" in the numerical interval can be any quantitative value, such as a number, a percentage, a ratio, etc. "Numerical interval" allows for broadly including quantitative intervals such as percentage intervals, ratio intervals, and ratio intervals.

[0026] The embodiment of the present application provides a photovoltaic module shading recognition technology solution. Based on this, the efficiency of photovoltaic module shading rate recognition can be improved, and the accuracy of photovoltaic module shading rate recognition can also be improved. See below for details.

[0027] Hereinafter, exemplary embodiments according to the present application will be described in more detail with reference to the accompanying drawings. It should be noted that these exemplary embodiments can be implemented in many different forms and should not be construed as being limited to the embodiments described herein.

[0028] like Figure 1 As shown, the embodiment of the present application provides a photovoltaic component shading identification method. The photovoltaic component shading identification method may include steps S100 to S106, wherein: Step S100, acquiring an optical collection image of a photovoltaic module.

[0029] Specifically, a drone may be used to take aerial photos of the photovoltaic components to be identified, thereby obtaining optical acquisition images of the photovoltaic components. Alternatively, a drone may be used to take aerial photos regularly (e.g., every hour) to obtain optical acquisition images of the photovoltaic components, thereby obtaining the component shading rate of the photovoltaic components at various time periods.

[0030] Step S102, performing channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation.

[0031] Specifically, after the optical collection image of the photovoltaic component is collected, the optical collection image can be separated into red, blue and green (RGB) channels to obtain a red channel image, a blue channel image and a green channel image respectively, and the blue channel image and the green channel image are obtained.

[0032] Step S104, determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image.

[0033] Since the shaded photovoltaic module has a stronger light reflectivity in the blue channel and a lower reflectivity in the green channel, a function or formula can be constructed based on this characteristic of the photovoltaic module so that the calculation result can reflect the degree of shade of the photovoltaic module. For example, a function or formula can be constructed so that when the shaded area of ​​the photovoltaic module is large, the calculation result is large, and when the shaded area of ​​the photovoltaic module is small, the calculation result is small.

[0034] In an optional embodiment, step S104 may include: determining the shadow rate of each pixel in the optically collected image by using a shadow rate calculation formula according to the blue channel image and the green channel image, wherein the shadow rate calculation formula is:

[0035] Among them, shadow ratio is the shadow ratio of the optically collected image, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the shadow ratio is currently calculated. In the above formula, arctan(x, y) means to calculate the angle between the ray from the origin to the point (x, y) and the X-axis, and its value range is (-π, π). Since (bg) may be a non-negative number or a negative number, and (b+g) is a non-negative number, the value range of arctan((bg), (b+g)) is a non-negative number of (0, π), which can better normalize the exponent.

[0036] In this optional embodiment, through the shadow rate calculation formula, the characteristics of the blocked photovoltaic component with strong light reflection ability in the blue channel and low reflectivity in the green channel can be effectively utilized to determine the shadow rate of the optically collected image, so that the calculation result of the shadow rate truly reflects the shadow situation in the optically collected image of the photovoltaic component, thereby improving the accuracy of the calculation result.

[0037] Accordingly, a function or formula can be constructed so that the calculated result can reflect the coverage of the photovoltaic module in the optical acquisition image. For example, a function or formula can be constructed so that when the area covered by the photovoltaic module is large, the calculated result is large, and when the area covered by the photovoltaic module is small, the calculated result is small.

[0038] In an optional embodiment, in step S104, determining the shadow rate and component coverage of the optically collected image according to the blue channel image and the green channel image includes determining the component coverage of the optically collected image according to the blue channel image and the green channel image, which may specifically include: determining the component coverage of each pixel in the optically collected image using a coverage calculation formula according to the blue channel image and the green channel image, wherein the coverage calculation formula is:

[0039] Among them, module ratio is the component coverage, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the coverage is currently calculated.

[0040] In this optional embodiment, through the coverage calculation formula, the component coverage of the photovoltaic component can be determined by effectively utilizing the characteristics of the blocked photovoltaic component, that is, its strong light reflection ability in the blue channel and its low reflectivity in the green channel. Therefore, the calculation result of the component coverage can truly reflect the component coverage in the optical acquisition image of the photovoltaic component, thereby improving the accuracy of the calculation result.

[0041] Step S106, determining the shielding rate of the photovoltaic module according to the shadow rate and the module coverage rate.

[0042] It can be understood that what is obtained by the above-mentioned shadow rate calculation formula is the shadow rate of each pixel of the optical collection image, while what is obtained by the above-mentioned coverage rate calculation formula is the component coverage rate of each pixel of the optical collection image. Therefore, when determining the occlusion rate of the photovoltaic component based on the shadow rate and the component coverage rate, the shadow rate of the optical collection image can be obtained by summarizing the results calculated according to the above-mentioned shadow rate formula, and the component coverage rate of the optical collection image can be obtained by summarizing the results calculated according to the above-mentioned coverage rate calculation formula, and then the occlusion rate of the photovoltaic component can be obtained based on the shadow rate of the optical collection image and the component coverage rate of the optical collection image.

[0043] In order to obtain more accurate results, the shadow area of ​​the optical collection image can be determined according to the shadow rate, and the component coverage area of ​​the optical collection image can be determined according to the component coverage rate. Then, the shading rate of the photovoltaic module can be obtained according to the shadow area of ​​the optical collection image and the component coverage area.

[0044] The photovoltaic component occlusion identification method provided in the embodiment of the present application obtains an optical acquisition image of the photovoltaic component, performs channel separation on the optical acquisition image, obtains a blue channel image and a green channel image after the channel separation, determines the shadow rate and component coverage rate of the optical acquisition image according to the blue channel image and the green channel image, and determines the occlusion rate of the photovoltaic component according to the shadow rate and the component coverage rate. This can realize automatic identification and calculation of the occlusion rate of the photovoltaic component, thereby improving the efficiency of identifying the occlusion rate of the photovoltaic component, and can also improve the accuracy of identifying the occlusion rate of the photovoltaic component.

[0045] In an optional embodiment, if Figure 2 As shown, step S106 may further include steps S200 to S204: Step S200: determining the shadow area of ​​the optically collected image according to the shadow ratio.

[0046] Specifically, the optically collected image may be binarized according to the shadow rate to construct a mask, and then the shadow area of ​​the optically collected image may be determined according to the constructed mask.

[0047] In an optional embodiment, if Figure 3 As shown, step S200 may further include steps S300 to S304: Step S300 , binarizing each pixel in the optically collected image according to the shadow rate to obtain a first binarization result of the optically collected image.

[0048] Step S302: Generate a first mask image according to the first binarization result.

[0049] Step S304: Apply the first mask image to the optically collected image to determine the shadow area of ​​the optically collected image.

[0050] Specifically, a first threshold value (such as 0.1) can be configured for the shadow rate. When the shadow rate of the current pixel is greater than the first threshold value, the binarization result of the current pixel is 1; when the shadow rate of the current pixel is less than or equal to the first threshold value, the binarization result of the current pixel is 0. After binarizing each pixel in the optically collected image, the first binarization result of the optically collected image can be obtained. Then, a mask image is constructed according to the binarization result of the optically collected image to obtain a first mask image; the first mask image is then applied to the optically collected image (i.e., the original image), and the shadow part of the optically collected image can be obtained according to the result of the application. The area of ​​the shadow part is calculated to determine the shadow area of ​​the optically collected image.

[0051] Please refer to Figure 4 and Figure 5 ,in Figure 4 is the optical acquisition image of the photovoltaic module (i.e. the original image), Figure 5 is the binary shadow rate image, such as Figure 5 As shown, the white part in the figure is the shaded part.

[0052] In practical applications, the optically collected image can be directly binarized according to the shadow rate, and the shadow area of ​​the optically collected image can be directly determined based on the binarization result without constructing a mask; however, by constructing a mask, morphological operations (such as dilation, erosion, etc.) can be performed on the mask to obtain a smoother and more connected shadow area; when the position of the photovoltaic module in the optically collected image is known, the shadow area can also be restricted to the area where the photovoltaic module is located through the mask, thereby improving the recognition accuracy.

[0053] In this optional embodiment, each pixel in the optical collection image is binarized according to the shadow rate to obtain a first binarization result of the optical collection image, a first mask image is generated according to the first binarization result, and the first mask image is applied to the optical collection image to determine the shadow area of ​​the optical collection image. The shadow area of ​​the optical collection image can be determined by constructing a mask, thereby effectively improving the convenience and accuracy of identifying the shadow rate of photovoltaic components in the optical collection image.

[0054] Step S202: determining the component coverage area of ​​the optically collected image according to the component coverage rate.

[0055] Specifically, the optically collected image may be binarized according to the component coverage ratio to construct a mask, and then the component coverage area of ​​the optically collected image may be determined according to the constructed mask.

[0056] In an optional embodiment, if Figure 6 As shown, step S202 may further include steps S400 to S404: Step S400 , binarizing each pixel in the optically collected image according to the component coverage rate to obtain a second binarization result of the optically collected image.

[0057] Step S402: Generate a second mask image according to the second binarization result.

[0058] Step S404: applying the second mask image to the optically collected image to determine the component coverage area of ​​the optically collected image.

[0059] Specifically, a second threshold (such as 0.028) can be configured for the component coverage. When the component coverage of the current pixel is greater than the second threshold, the binarization result of the current pixel is 1; when the component coverage of the current pixel is less than or equal to the second threshold, the binarization result of the current pixel is 0. After binarizing each pixel in the optical acquisition image, the second binarization result of the optical acquisition image can be obtained. Then, a mask image is constructed according to the binarization result of the optical acquisition image to obtain a second mask image; the second mask image is then applied to the optical acquisition image, and the component coverage part of the optical acquisition image can be obtained according to the result of the application. The area of ​​the component coverage part is calculated to determine the component coverage area of ​​the optical acquisition image.

[0060] Please refer to Figure 7 , which is the component coverage image after the photovoltaic component is binarized, as shown in the figure, the white part in the figure is the component coverage part.

[0061] In practical applications, the optically acquired image can be directly binarized according to the component coverage rate, and the component coverage area of ​​the optically acquired image can be directly determined based on the binarization result without constructing a mask; however, by constructing a mask, morphological operations (such as dilation, erosion, etc.) can be performed on the mask to obtain a smoother and more connected component coverage area.

[0062] In this optional embodiment, each pixel in the optical collection image is binarized according to the component coverage rate to obtain a second binarization result of the optical collection image, a second mask image is generated according to the second binarization result, and the second mask image is applied to the optical collection image to determine the component coverage area of ​​the optical collection image. The component coverage area of ​​the optical collection image can be determined by constructing a mask, thereby effectively improving the convenience and accuracy of identifying the coverage rate of photovoltaic components in the optical collection image.

[0063] Step S204, determining the shading rate of the photovoltaic module according to the shadow area and the module coverage area.

[0064] Specifically, the shading rate of the photovoltaic module can be obtained by dividing the shadow area of ​​the optical collection image by the module coverage area, that is, the shading rate of the photovoltaic module=the shadow area of ​​the optical collection image / the module coverage area of ​​the optical collection image.

[0065] Please refer to Figure 8 , which is a flow chart of a photovoltaic module shading identification method, as shown in the figure, which can generally include the following processes: 1. UAV inspection collects optical images of photovoltaic modules; 2. Separate the red, blue and green channels of the optically collected image; 3. Calculate the shadow rate based on the blue channel image and the green channel image obtained by channel separation, construct a mask based on the shadow rate, and obtain a shadow binary image; at the same time, calculate the component coverage rate based on the blue channel image and the green channel image, construct a mask based on the component coverage rate, and obtain a component binary image; 4. Solve the shadow area and component coverage area in the binary image; 5. Solve the shadow component ratio to obtain the shading rate of the PV module.

[0066] In this optional embodiment, the shadow area of ​​the optically collected image is determined according to the shadow rate, the component coverage area of ​​the optically collected image is determined according to the component coverage rate, and the occlusion rate of the photovoltaic component is determined according to the shadow area and the component coverage area. The occlusion rate of the photovoltaic component can be determined by separately determining the shadow area and the component coverage area, thereby improving the calculation accuracy of the occlusion rate of the photovoltaic component.

[0067] In an optional embodiment, in step S104, the shadow rate and component coverage rate of the optically collected image are determined according to the blue channel image and the green channel image, such as Fig. 9 As shown, it may further include steps S500-S502: Step S500 , performing median filtering processing on the blue channel image and the green channel image respectively to obtain a processed blue channel image and a processed green channel image.

[0068] Step S502 : determining the shadow rate and component coverage rate of the optically collected image according to the processed blue channel image and the processed green channel image.

[0069] Among them, median filtering is a nonlinear filtering technology, which is mainly used to eliminate noise in images. It achieves denoising effect by comparing each pixel value in the image with the pixel values ​​of its surrounding neighborhood and replacing the original pixel value with the median value of the pixel values ​​in the neighborhood.

[0070] In practical applications, the optically collected image can also be processed by median filtering, and then the channel separation can be performed on the optically collected image after the median filtering. However, since the noise characteristics of different color channels may be different, it will be better to first perform channel separation on the optically collected image and then perform median filtering on the channel image after the channel separation, so as to better retain the detail information of each channel.

[0071] In this optional embodiment, by performing median filtering on the blue channel image and the green channel image respectively to obtain a processed blue channel image and a processed green channel image, and determining the shadow rate and component coverage rate of the optically collected image based on the processed blue channel image and the processed green channel image, the noise of the channel image can be effectively removed and the accuracy of the calculation results can be improved.

[0072] Fig.10 The block diagram of the photovoltaic module shading identification device 600 provided in the embodiment of the present application is schematically shown. The device 600 can be divided into one or more program modules, one or more program modules are stored in a storage medium, and are executed by one or more processors to complete the embodiment of the present application. The program module referred to in the embodiment of the present application refers to a series of computer program instruction segments that can complete specific functions. The following description will specifically introduce the functions of each program module in this embodiment. Fig.10 As shown, the apparatus 600 may include an acquisition module 610, a separation module 620, a first determination module 630 and a second determination module 640, wherein: An acquisition module 610 is used to acquire an optical acquisition image of a photovoltaic module; A separation module 620 is used to perform channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation; A first determination module 630 is used to determine the shadow rate and component coverage rate of the optical acquisition image according to the blue channel image and the green channel image; The second determination module 640 is used to determine the shielding rate of the photovoltaic component according to the shadow rate and the component coverage rate.

[0073] In an optional embodiment, the first determining module 630 is further configured to: The shadow rate of each pixel in the optical acquisition image is determined by using a shadow rate calculation formula according to the blue channel image and the green channel image. The shadow rate calculation formula is:

[0074] Among them, the shadow ratio is the shadow ratio, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the shadow ratio is currently calculated.

[0075] In an optional embodiment, the first determining module 630 is further configured to: The component coverage of each pixel in the optical acquisition image is determined by using a coverage calculation formula according to the blue channel image and the green channel image. The coverage calculation formula is:

[0076] Among them, the module ratio is the component coverage, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the coverage is currently calculated.

[0077] In an optional embodiment, the second determining module 640 is further configured to: Determining a shadow area of ​​the optically collected image according to the shadow ratio; Determining a component coverage area of ​​the optically collected image according to the component coverage rate; The shielding rate of the photovoltaic component is determined according to the shadow area and the component coverage area.

[0078] In an optional embodiment, the second determining module 640 is further configured to: Binarizing each pixel in the optically collected image according to the shadow rate to obtain a first binarization result of the optically collected image; generating a first mask image according to the first binarization result; The first mask image is applied to the optically collected image to determine a shadow area of ​​the optically collected image.

[0079] In an optional embodiment, the second determining module 640 is further configured to: Binarizing each pixel in the optically collected image according to the component coverage to obtain a second binarization result of the optically collected image; generating a second mask image according to the second binarization result; The second mask image is applied to the optically collected image to determine a component coverage area of ​​the optically collected image.

[0080] In an optional embodiment, the first determining module 630 is further configured to: Performing median filtering on the blue channel image and the green channel image respectively to obtain a processed blue channel image and a processed green channel image; A shadow rate and a component coverage rate of the optically collected image are determined according to the processed blue channel image and the processed green channel image.

[0081] Fig.11 The hardware architecture diagram of the computer device 10000 suitable for implementing the photovoltaic module shading identification method provided in the embodiment of the present application is schematically shown. In some embodiments, the computer device 10000 can be a terminal device such as a smart phone, a wearable device, a tablet computer, a personal computer, a vehicle terminal, a game console, a virtual device, a workbench, a digital assistant, a set-top box, a robot, etc. In other embodiments, the computer device 10000 can be a rack server, a blade server, a tower server or a cabinet server (including an independent server, or a server cluster composed of multiple servers), etc. Fig.11 As shown, the computer device 10000 includes but is not limited to: a memory 10010, a processor 10020, and a network interface 10030 that can communicate with each other through a system bus. Among them: The memory 10010 includes at least one type of computer-readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 10010 can be an internal storage module of the computer device 10000, such as a hard disk or memory of the computer device 10000. In other embodiments, the memory 10010 can also be an external storage device of the computer device 10000, such as a plug-in hard disk equipped on the computer device 10000, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 10010 can also include both the internal storage module of the computer device 10000 and its external storage device. In this embodiment, the memory 10010 is generally used to store the operating system and various application software installed in the computer device 10000, such as the program code of the photovoltaic module shading identification method, etc. In addition, the memory 10010 can also be used to temporarily store various data that have been output or will be output.

[0082] In some embodiments, the processor 10020 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other chips. The processor 10020 is generally used to control the overall operation of the computer device 10000, such as performing control and processing related to data interaction or communication with the computer device 10000. In this embodiment, the processor 10020 is used to run the program code stored in the memory 10010 or process data.

[0083] The network interface 10030 may include a wireless network interface or a wired network interface, and the network interface 10030 is generally used to establish a communication link between the computer device 10000 and other computer devices. For example, the network interface 10030 is used to connect the computer device 10000 to an external terminal through a network, and to establish a data transmission channel and a communication link between the computer device 10000 and the external terminal. The network may be a wireless or wired network such as an intranet, the Internet, the Global System of Mobile communication (GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Bluetooth, Wi-Fi, etc.

[0084] It should be pointed out that Fig.11 Only a computer device having components 10010 - 10030 is shown, but it should be understood that implementation of all of the components shown is not a requirement, and more or fewer components may alternatively be implemented.

[0085] In this embodiment, the photovoltaic component shading identification method stored in the memory 10010 can also be divided into one or more program modules and executed by one or more processors (such as processor 10020) to complete the embodiment of the present application.

[0086] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the photovoltaic component shading identification method in the embodiment are implemented.

[0087] In this embodiment, the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the computer-readable storage medium may be an internal storage unit of a computer device, such as a hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium may also be an external storage device of a computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device. Of course, the computer-readable storage medium may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the computer-readable storage medium is generally used to store an operating system and various application software installed on the computer device, such as the program code of the photovoltaic module shading identification method in the embodiment. In addition, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are to be output.

[0088] An embodiment of the present application also provides a computer program product, including a computer program, which implements the method in the above embodiment when executed by a processor.

[0089] Obviously, those skilled in the art should understand that the modules or steps of the above-mentioned embodiments of the present application can be implemented by general-purpose computer devices, they can be concentrated on a single computer device, or distributed on a network composed of multiple computer devices, optionally, they can be implemented by executable program codes of computer devices, so that they can be stored in a storage device and executed by the computer device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0090] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] It should also be noted that the above are only preferred embodiments of the present application, and the patent protection scope of the present application is not limited thereto. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A photovoltaic module shading identification method, characterized in that: include: Acquire optical acquisition images of photovoltaic modules; Performing channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation; determining a shadow rate and a component coverage rate of the optically collected image according to the blue channel image and the green channel image; The shielding rate of the photovoltaic component is determined according to the shadow rate and the component coverage rate.

2. The method according to claim 1, characterized in that The determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image comprises: The shadow rate of each pixel in the optical acquisition image is determined by using a shadow rate calculation formula according to the blue channel image and the green channel image. The shadow rate calculation formula is: Among them, the shadow ratio is the shadow ratio, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the shadow ratio is currently calculated.

3. The method according to claim 1, characterized in that The determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image comprises: The component coverage of each pixel in the optical acquisition image is determined by using a coverage calculation formula according to the blue channel image and the green channel image. The coverage calculation formula is: Among them, the module ratio is the component coverage, b is the pixel value of the current pixel in the blue channel image, g is the pixel value of the current pixel in the green channel image, and the current pixel is the pixel for which the coverage is currently calculated.

4. The method according to claim 1, characterized in that: The determining the shielding rate of the photovoltaic assembly according to the shadow rate and the assembly coverage rate includes: Determining a shadow area of ​​the optically collected image according to the shadow ratio; Determining a component coverage area of ​​the optically collected image according to the component coverage rate; The shielding rate of the photovoltaic component is determined according to the shadow area and the component coverage area.

5. The method according to claim 4, characterized in that The determining the shadow area of ​​the optically collected image according to the shadow rate comprises: Binarizing each pixel in the optically collected image according to the shadow rate to obtain a first binarization result of the optically collected image; generating a first mask image according to the first binarization result; The first mask image is applied to the optically collected image to determine a shadow area of ​​the optically collected image.

6. The method according to claim 4, characterized in that The determining the component coverage area of ​​the optically collected image according to the component coverage rate comprises: Binarizing each pixel in the optically collected image according to the component coverage rate to obtain a second binarization result of the optically collected image; generating a second mask image according to the second binarization result; The second mask image is applied to the optically collected image to determine a component coverage area of ​​the optically collected image.

7. The method according to any one of claims 1 to 6, characterized in that: The determining the shadow rate and component coverage rate of the optically collected image according to the blue channel image and the green channel image comprises: Performing median filtering on the blue channel image and the green channel image respectively to obtain a processed blue channel image and a processed green channel image; A shadow rate and a component coverage rate of the optically collected image are determined according to the processed blue channel image and the processed green channel image.

8. A photovoltaic module shading identification device, characterized in that: include: An acquisition module, used for acquiring an optical acquisition image of a photovoltaic module; A separation module, used to perform channel separation on the optically collected image to obtain a blue channel image and a green channel image after channel separation; A first determination module, configured to determine a shadow rate and a component coverage rate of the optically collected image according to the blue channel image and the green channel image; The second determination module is used to determine the shielding rate of the photovoltaic component according to the shadow rate and the component coverage rate.

9. A computer device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein: The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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