A solar cell defect detection method and system based on image recognition

Abstract

The present invention discloses a solar cell defect detection method and system based on image recognition, belonging to the field of image recognition. The present invention collects image data of a solar cell to be detected, and collects equipment operation data of the solar cell at the same time, obtains the image data of the solar cell and imports it into an image processing model to analyze abnormal image defects of the solar cell, imports the collected equipment operation data of the solar cell into an abnormal operation defect analysis model to analyze abnormal operation defects of the solar cell, performs operation analysis of the solar cell according to the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell, repairs defect points according to the operation analysis results of the solar cell, quickly analyzes abnormal solar failures, and greatly improves the quality and efficiency of the solar cell.

Description

Technical Field

[0001] The present invention belongs to the technical field of image recognition, and in particular to a method and system for detecting defects in solar cells based on image recognition. Background Art

[0002] Solar cell defect detection based on image recognition uses computer vision technology to perform image analysis and defect detection on solar cell modules to achieve automatic, efficient and accurate detection of defects on the surface of solar cell modules, thereby improving production efficiency and quality. Solar cell defect detection technology based on image recognition can greatly improve detection efficiency and accuracy, reduce labor costs and time, and ensure product quality and safety.

[0003] For example, a Chinese patent with the authorization announcement number CN116485785B discloses a method for detecting surface defects of solar cells, including: collecting the surface image of the solar cell, obtaining the maximum width of the main grid line, establishing a window according to the maximum width, obtaining the grayscale fluctuation degree of each window, and then obtaining multiple areas, obtaining the reference degree of each area according to the mixed Gaussian model of each area, obtaining the reference area and the area to be enhanced, obtaining the illumination influence factor of each area to be enhanced, and then obtaining the first illumination area and the second illumination area, obtaining the updated grayscale histogram of each second illumination area according to the significance of the first pixel point in the second illumination area, obtaining the enhanced image according to the grayscale histogram of the reference area, the first illumination area and the updated grayscale histogram of the second illumination area, and identifying the surface defects of the solar cell according to the enhanced image. This technical solution eliminates the influence of illumination, has a better enhancement effect, and more accurately identifies defects.

[0004] The above patents have the problems raised by this background technology: the prior art is unable to perform solar cell operation analysis through image abnormal defect analysis results and solar cell operation abnormal defect analysis results, and thus is unable to perform operation analysis of solar cells, and is unable to quickly analyze abnormal solar energy failures, greatly reducing the quality and efficiency of solar cells. The above problems exist in the prior art. In order to solve these problems, the present application designs a solar cell defect detection method and system based on image recognition. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention proposes a method and system for detecting solar cell defects based on image recognition.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for detecting defects in solar cells based on image recognition comprises the following specific steps:

[0008] S1, collecting image data of the solar cell to be inspected, and collecting equipment operation data of the solar cell;

[0009] S2, acquiring image data of the solar cell and importing it into an image processing model to analyze abnormal defects of the solar cell image;

[0010] S3, importing the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell;

[0011] S4, performing solar cell operation analysis based on the obtained image abnormality defect analysis results of the solar cell and the operation abnormality defect analysis results of the solar cell;

[0012] S5. Repair defective points according to the analysis results of the solar cell operation.

[0013] A further improvement of the present invention is that S1 comprises the following specific steps:

[0014] S11, using an image acquisition terminal to acquire surface image data of a solar cell to be inspected, importing the surface image data of the solar cell into an image processing software to obtain a pixel value of each pixel point of the solar cell image, and storing the pixel value in a first storage component;

[0015] S12, collecting the operating data of the solar cell during the detection phase, wherein the operating data of the solar cell includes a temperature change curve, a light intensity change curve and a power generation data change curve, and storing the data in a second storage component;

[0016] It should be noted that the surface image data here is the surface image data of the solar cell after cleaning;

[0017] A further improvement of the present invention is that the specific content of the image processing model in S2 is as follows:

[0018] S21, obtaining the pixel value of each pixel point of the collected solar cell image to be detected, and obtaining the pixel value of each corresponding pixel point of the finished solar cell image;

[0019] S22, obtaining the coordinates of the pixel points whose absolute value of the pixel value difference between the solar cell to be inspected and the corresponding pixel points of the finished solar cell image is greater than or equal to the pixel difference threshold, setting them as abnormal pixel points, and displaying the abnormal pixel points at the corresponding positions of the surface image of the solar cell to be inspected;

[0020] S23, obtaining the corresponding position of the abnormal pixel point, obtaining the contour of the image formed by the abnormal pixel points, setting the contour of the image formed by the abnormal pixel points as the abnormal contour, and obtaining the pixel value of the abnormal pixel point, and obtaining the absolute value of the height of the abnormal pixel point relative to the plane of the solar cell, setting it as the absolute height, taking the abnormal pixel point with the largest absolute height as the center point, and obtaining the distances of other abnormal pixel points from the center point;

[0021] S24, importing the obtained distances of other abnormal pixel points from the center point, the absolute heights of the abnormal pixel points, and the pixel values ​​of the abnormal pixel points into the image abnormality feature value calculation formula to calculate the image abnormality feature value, wherein the image abnormality feature value calculation formula is: Among them, ktx is the abnormal feature value of the image, n is the number of abnormal pixels, H i is the height of the i-th abnormal pixel, x i is the pixel value of the i-th abnormal pixel, x i1 is the pixel value of the pixel of the solar cell image product corresponding to the i-th abnormal pixel, β i is the distance between the ith pixel and the center point, is the length of the solar cell, is the average thickness of the solar cell.

[0022] In this way, abnormal analysis of solar cell surface images is performed to improve the evaluation effect of solar cell quality;

[0023] A further improvement of the present invention is that the specific content of the abnormal defect analysis model in S3 is:

[0024] S31, obtaining the temperature change curve, light intensity change curve and power generation data change curve of the solar cell in the detection phase, and obtaining the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity, wherein the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity at time c is: Where P is the rated power under the reference environment, P c is the real-time power generation at time c, λ1 is the influence of temperature on power generation, λ2 is the influence of light intensity on power generation, exp() is the power of e, T c is the temperature at time c, T k is the temperature of the reference environment, S c is the light intensity at time c, S k is the light intensity under the reference environment; the influence of temperature on power generation and the influence of light intensity on power generation are provided by the supplier;

[0025] S32, obtaining the real-time temperature change curve, light intensity change curve and power generation data change curve of the solar cell during the detection phase, calculating the change curve of the standard power generation under the action of the temperature change curve and the light intensity change curve, substituting the real-time power generation data change curve and the standard power generation change curve into the operation abnormality defect analysis value calculation formula to calculate the operation abnormality defect analysis value, wherein the operation abnormality defect analysis value calculation formula is: Among them, M is the abnormal operation defect analysis value, T is the detection phase duration, dt is the time integral, P t is the real-time power generation at time t, is the standard power generation at time t;

[0026] It should be noted here that the abnormal power generation process is comprehensively analyzed in this way to quickly analyze the abnormality of the solar cell;

[0027] A further improvement of the present invention is that the solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell includes the following specific contents:

[0028] S41, obtaining the calculated image abnormality feature value and operation abnormality defect analysis value;

[0029] S42. Substitute the acquired image abnormality feature value and operation abnormality defect analysis value into the solar cell operation analysis value calculation formula to calculate the solar cell operation analysis value, wherein the solar cell operation analysis value calculation formula is: Y=γktx+(1-γ)M, wherein Y is the solar cell operation analysis value, and γ is the image abnormality feature ratio.

[0030] A further improvement of the present invention is that S5 includes the following specific contents:

[0031] The calculated solar cell operation analysis value is compared with the set solar cell operation analysis threshold. If the obtained solar cell operation analysis value is greater than or equal to the set solar cell operation analysis threshold, a maintenance warning of the abnormal pixel point is issued; if the obtained solar cell operation analysis value is less than the set solar cell operation analysis threshold, no maintenance warning of the abnormal pixel point is issued.

[0032] It should be noted that the proportion of abnormal image features and the solar cell operation analysis threshold are determined in the following manner: image data of several groups of solar cells and equipment operation data of solar cells are obtained, and experts are hired to determine whether the solar cells need maintenance. The obtained image data of the solar cells and the equipment operation data of the solar cells are correspondingly substituted into the solar cell operation analysis value calculation formula to calculate the solar cell operation analysis value, and the calculated solar cell operation analysis value and the result of the judgment on whether maintenance is needed are imported into the fitting software to output the proportion of abnormal image features and the value of the solar cell operation analysis threshold that meet the highest judgment accuracy.

[0033] A solar cell defect detection system based on image recognition is implemented based on the above-mentioned solar cell defect detection method based on image recognition, and specifically includes:

[0034] A data acquisition module is used to acquire image data of the solar cell to be inspected and to acquire equipment operation data of the solar cell;

[0035] An image abnormality defect analysis module is used to obtain image data of solar cells and import it into an image processing model to analyze image abnormality defects of solar cells;

[0036] An operation abnormality defect analysis module is used to import the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell;

[0037] A solar cell operation analysis module, used for performing solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell;

[0038] Maintenance warning module, used to repair defective points according to the operation analysis results of solar cells;

[0039] The control module is used to control the operation of the data acquisition module, the image abnormality defect analysis module, the operation abnormality defect analysis module, the solar cell operation analysis module and the maintenance early warning module.

[0040] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0041] The processor executes the above-mentioned solar cell defect detection method based on image recognition by calling the computer program stored in the memory.

[0042] A computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer is enabled to execute the above-mentioned solar cell defect detection method based on image recognition.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention collects image data of a solar cell that needs to be inspected, and collects equipment operation data of the solar cell at the same time, obtains the image data of the solar cell and imports it into an image processing model to analyze abnormal image defects of the solar cell, imports the collected equipment operation data of the solar cell into an abnormal operation defect analysis model to analyze abnormal operation defects of the solar cell, performs operation analysis of the solar cell based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell, repairs defective points based on the solar cell operation analysis results, quickly analyzes abnormal solar failures, and greatly improves the quality and efficiency of the solar cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a process flow of a solar cell defect detection method based on image recognition according to the present invention;

[0046] Figure 2 This is a schematic diagram of a specific process of step S2 of a solar cell defect detection method based on image recognition according to the present invention;

[0047] Figure 3 A schematic diagram of a solar cell defect detection system framework based on image recognition according to the present invention;

[0048] Figure 4 The figure is a schematic diagram of an electronic device according to the present invention. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0050] Example 1

[0051] like Figure 1-Figure 2 As shown, an embodiment of the present invention provides: a method for detecting solar cell defects based on image recognition, which includes the following specific steps:

[0052] S1, collecting image data of the solar cell to be inspected, and collecting equipment operation data of the solar cell;

[0053] This step is further described here. S1 includes the following specific steps:

[0054] S11, using an image acquisition terminal to acquire surface image data of a solar cell to be inspected, importing the surface image data of the solar cell into an image processing software to obtain a pixel value of each pixel point of the solar cell image, and storing the pixel value in a first storage component;

[0055] S12, collecting the operating data of the solar cell during the detection phase, wherein the operating data of the solar cell includes a temperature change curve, a light intensity change curve and a power generation data change curve, and storing the data in a second storage component;

[0056] It should be noted that the surface image data here is the surface image data of the solar cell after cleaning;

[0057] S2, acquiring image data of the solar cell and importing it into an image processing model to analyze abnormal defects of the solar cell image;

[0058] This step is further described here. The specific content of the image processing model in S2 is as follows:

[0059] S21, obtaining the pixel value of each pixel point of the collected solar cell image to be detected, and obtaining the pixel value of each corresponding pixel point of the finished solar cell image;

[0060] S22, obtaining the coordinates of the pixel points whose absolute value of the pixel value difference between the solar cell to be inspected and the corresponding pixel points of the finished solar cell image is greater than or equal to the pixel difference threshold, setting them as abnormal pixel points, and displaying the abnormal pixel points at the corresponding positions of the surface image of the solar cell to be inspected;

[0061] S23, obtaining the corresponding position of the abnormal pixel point, obtaining the contour of the image formed by the abnormal pixel points, setting the contour of the image formed by the abnormal pixel points as the abnormal contour, and obtaining the pixel value of the abnormal pixel point, and obtaining the absolute value of the height of the abnormal pixel point relative to the plane of the solar cell, setting it as the absolute height, taking the abnormal pixel point with the largest absolute height as the center point, and obtaining the distances of other abnormal pixel points from the center point;

[0062] The following C language code implements this step:

[0063]

[0064]

[0065]

[0066] S24, importing the obtained distances of other abnormal pixel points from the center point, the absolute heights of the abnormal pixel points, and the pixel values ​​of the abnormal pixel points into the image abnormality feature value calculation formula to calculate the image abnormality feature value, wherein the image abnormality feature value calculation formula is: Among them, ktx is the abnormal feature value of the image, n is the number of abnormal pixels, H i is the height of the i-th abnormal pixel, x i is the pixel value of the i-th abnormal pixel, x i1 is the pixel value of the pixel of the solar cell image product corresponding to the i-th abnormal pixel, β i is the distance between the ith pixel and the center point, is the length of the solar cell, is the average thickness of the solar cell.

[0067] In this way, abnormal analysis of solar cell surface images is performed to improve the evaluation effect of solar cell quality;

[0068] S3, importing the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell;

[0069] Here, this step is further described. The specific content of running the abnormal defect analysis model in S3 is:

[0070] S31, obtaining the temperature change curve, light intensity change curve and power generation data change curve of the solar cell in the detection phase, and obtaining the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity, wherein the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity at time c is: Where P is the rated power under the reference environment, P c is the real-time power generation at time c, λ1 is the influence of temperature on power generation, λ2 is the influence of light intensity on power generation, exp() is the power of e, T c is the temperature at time c, T k is the temperature of the reference environment, S c is the light intensity at time c, S k is the light intensity under the reference environment; the influence of temperature on power generation and the influence of light intensity on power generation are provided by the supplier;

[0071] S32, obtaining the real-time temperature change curve, light intensity change curve and power generation data change curve of the solar cell during the detection phase, calculating the change curve of the standard power generation under the action of the temperature change curve and the light intensity change curve, substituting the real-time power generation data change curve and the standard power generation change curve into the operation abnormality defect analysis value calculation formula to calculate the operation abnormality defect analysis value, wherein the operation abnormality defect analysis value calculation formula is: Among them, M is the abnormal operation defect analysis value, T is the detection phase duration, dt is the time integral, P t is the real-time power generation at time t, is the standard power generation at time t;

[0072] It should be noted here that the abnormal power generation process is comprehensively analyzed in this way to quickly analyze the abnormality of the solar cell;

[0073] S4, performing solar cell operation analysis based on the obtained image abnormality defect analysis results of the solar cell and the operation abnormality defect analysis results of the solar cell;

[0074] It should be noted that the operation analysis of the solar cell based on the obtained image abnormality defect analysis results of the solar cell and the operation abnormality defect analysis results of the solar cell includes the following specific contents:

[0075] S41, obtaining the calculated image abnormality feature value and operation abnormality defect analysis value;

[0076] S42, substituting the acquired image abnormality feature value and operation abnormality defect analysis value into the solar cell operation analysis value calculation formula to calculate the solar cell operation analysis value, wherein the solar cell operation analysis value calculation formula is: Y=γktx+(1-γ)M, wherein Y is the solar cell operation analysis value, and γ is the image abnormality feature ratio;

[0077] S5. Repair defective points according to the operation analysis results of the solar cell;

[0078] It should be noted that S5 includes the following specific contents:

[0079] The calculated solar cell operation analysis value is compared with the set solar cell operation analysis threshold. If the obtained solar cell operation analysis value is greater than or equal to the set solar cell operation analysis threshold, a maintenance warning of the abnormal pixel point is issued; if the obtained solar cell operation analysis value is less than the set solar cell operation analysis threshold, no maintenance warning of the abnormal pixel point is issued.

[0080] It should be noted that the proportion of abnormal image features and the solar cell operation analysis threshold are determined in the following manner: image data of several groups of solar cells and equipment operation data of solar cells are obtained, and experts are hired to determine whether the solar cells need maintenance. The obtained image data of the solar cells and the equipment operation data of the solar cells are correspondingly substituted into the solar cell operation analysis value calculation formula to calculate the solar cell operation analysis value, and the calculated solar cell operation analysis value and the result of the judgment on whether maintenance is needed are imported into the fitting software to output the proportion of abnormal image features and the value of the solar cell operation analysis threshold that meet the highest judgment accuracy.

[0081] A solar cell defect detection system based on image recognition is implemented based on the above-mentioned solar cell defect detection method based on image recognition, and specifically includes:

[0082] A data acquisition module is used to acquire image data of the solar cell to be inspected and to acquire equipment operation data of the solar cell;

[0083] An image abnormality defect analysis module is used to obtain image data of solar cells and import it into an image processing model to analyze image abnormality defects of solar cells;

[0084] An operation abnormality defect analysis module is used to import the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell;

[0085] A solar cell operation analysis module, used for performing solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell;

[0086] Maintenance warning module, used to repair defective points according to the operation analysis results of solar cells;

[0087] A control module, used to control the operation of the data acquisition module, the image abnormality defect analysis module, the operation abnormality defect analysis module, the solar cell operation analysis module and the maintenance early warning module;

[0088] Through this embodiment, it is possible to achieve the following: collecting image data of solar cells that need to be inspected, and collecting equipment operation data of solar cells at the same time, obtaining the image data of solar cells and importing them into an image processing model to perform image abnormality defect analysis on solar cells, importing the collected equipment operation data of solar cells into an operation abnormality defect analysis model to perform operation abnormality defect analysis on solar cells, performing operation analysis on solar cells based on the obtained image abnormality defect analysis results and operation abnormality defect analysis results of solar cells, repairing defective points based on the operation analysis results of solar cells, and quickly analyzing abnormal solar failures, thereby greatly improving the quality and efficiency of solar cells.

[0089] Example 2

[0090] like Figure 3 As shown, a solar cell defect detection system based on image recognition is implemented based on the above-mentioned solar cell defect detection method based on image recognition, and a data acquisition module is used to collect image data of the solar cell to be detected and collect equipment operation data of the solar cell at the same time;

[0091] An image abnormality defect analysis module is used to obtain image data of solar cells and import it into an image processing model to analyze image abnormality defects of solar cells;

[0092] An operation abnormality defect analysis module is used to import the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell;

[0093] A solar cell operation analysis module, used for performing solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell;

[0094] Maintenance warning module, used to repair defective points according to the operation analysis results of solar cells;

[0095] The control module is used to control the operation of the data acquisition module, the image abnormality defect analysis module, the operation abnormality defect analysis module, the solar cell operation analysis module and the maintenance early warning module.

[0096] Example 3

[0097] This embodiment provides an electronic device, such as Figure 4 As shown, it includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0098] The processor executes the above-mentioned solar cell defect detection method based on image recognition by calling the computer program stored in the memory.

[0099] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement a solar cell defect detection method based on image recognition provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0100] Example 4

[0101] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0102] When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned solar cell defect detection method based on image recognition.

[0103] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0104] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

Claims

1. A solar cell defect detection method based on image recognition, characterized in that: It includes the following specific steps: S1, collecting image data of the solar cell to be inspected, and collecting equipment operation data of the solar cell; S2, acquiring image data of the solar cell and importing it into an image processing model to analyze abnormal defects of the solar cell image; The specific contents of the image processing model in S2 are as follows: S21, obtaining the pixel value of each pixel point of the collected solar cell image to be detected, and obtaining the pixel value of each corresponding pixel point of the finished solar cell image; S22, obtaining the coordinates of the pixel points whose absolute value of the pixel value difference between the solar cell to be inspected and the corresponding pixel points of the finished solar cell image is greater than or equal to the pixel difference threshold, setting them as abnormal pixel points, and displaying the abnormal pixel points at the corresponding positions of the surface image of the solar cell to be inspected; S23, obtaining the corresponding position of the abnormal pixel point, obtaining the contour of the image formed by the abnormal pixel points, setting the contour of the image formed by the abnormal pixel points as the abnormal contour, and obtaining the pixel value of the abnormal pixel point, and obtaining the absolute value of the height of the abnormal pixel point relative to the plane of the solar cell, setting it as the absolute height, taking the abnormal pixel point with the largest absolute height as the center point, and obtaining the distances of other abnormal pixel points from the center point; S24, importing the obtained distances of other abnormal pixel points from the center point, the absolute heights of the abnormal pixel points, and the pixel values ​​of the abnormal pixel points into the image abnormality feature value calculation formula to calculate the image abnormality feature value, wherein the image abnormality feature value calculation formula is: Among them, ktx is the abnormal feature value of the image, n is the number of abnormal pixels, H i is the height of the i-th abnormal pixel, x i is the pixel value of the i-th abnormal pixel, x i1 is the pixel value of the pixel of the solar cell image product corresponding to the i-th abnormal pixel, β i is the distance between the ith pixel and the center point, is the length of the solar cell, is the average thickness of the solar cell; S3, importing the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell; The specific content of the abnormal defect analysis model in S3 is: S31, obtaining the temperature change curve, light intensity change curve and power generation data change curve of the solar cell in the detection phase, and obtaining the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity, wherein the calculation formula of the standard power generation of the solar cell as a function of temperature and light intensity at time c is: Where P is the rated power under the reference environment, P c is the real-time power generation at time c, λ1 is the influence of temperature on power generation, λ2 is the influence of light intensity on power generation, exp() is the power of e, T c is the temperature at time c, T k is the temperature of the reference environment, S c is the light intensity at time c, S k is the light intensity under the reference environment; the influence of temperature on power generation and the influence of light intensity on power generation are provided by the supplier; S32, obtaining the real-time temperature change curve, light intensity change curve and power generation data change curve of the solar cell during the detection phase, calculating the change curve of the standard power generation under the action of the temperature change curve and the light intensity change curve, substituting the real-time power generation data change curve and the standard power generation change curve into the operation abnormality defect analysis value calculation formula to calculate the operation abnormality defect analysis value, wherein the operation abnormality defect analysis value calculation formula is: Among them, M is the abnormal operation defect analysis value, T is the detection phase duration, dt is the time integral, P t is the real-time power generation at time t, is the standard power generation at time t; S4, performing solar cell operation analysis based on the obtained image abnormality defect analysis results of the solar cell and the operation abnormality defect analysis results of the solar cell; S5. Repair defective points according to the analysis results of the solar cell operation.

2. A solar cell defect detection method based on image recognition as claimed in claim 1, characterized in that: The S1 comprises the following specific steps: S11, using an image acquisition terminal to acquire surface image data of a solar cell to be inspected, importing the surface image data of the solar cell into an image processing software to obtain a pixel value of each pixel point of the solar cell image, and storing the pixel value in a first storage component; S12, collecting the operating data of the solar cell during the detection phase, wherein the operating data of the solar cell includes a temperature change curve, a light intensity change curve and a power generation data change curve, and storing the data in a second storage component.

3. The method for detecting solar cell defects based on image recognition according to claim 2, characterized in that: The solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell includes the following specific contents: S41, obtaining the calculated image abnormality feature value and operation abnormality defect analysis value; S42. Substitute the acquired image abnormality feature value and operation abnormality defect analysis value into the solar cell operation analysis value calculation formula to calculate the solar cell operation analysis value, wherein the solar cell operation analysis value calculation formula is: Y=γktx+(1-γ)M, wherein Y is the solar cell operation analysis value, and γ is the image abnormality feature ratio.

4. A solar cell defect detection method based on image recognition as claimed in claim 3, characterized in that: The S5 includes the following specific contents: The calculated solar cell operation analysis value is compared with the set solar cell operation analysis threshold value. If the obtained solar cell operation analysis value is greater than or equal to the set solar cell operation analysis threshold value, a maintenance warning of the abnormal pixel point is issued; If the obtained solar cell operation analysis value is less than the set solar cell operation analysis threshold, no maintenance warning of the abnormal pixel point is performed.

5. A solar cell defect detection system based on image recognition, which is implemented based on a solar cell defect detection method based on image recognition as claimed in any one of claims 1 to 4, characterized in that: Specifically include: A data acquisition module is used to acquire image data of the solar cell to be inspected and to acquire equipment operation data of the solar cell; An image abnormality defect analysis module is used to obtain image data of solar cells and import it into an image processing model to analyze image abnormality defects of solar cells; An operation abnormality defect analysis module is used to import the collected equipment operation data of the solar cell into the operation abnormality defect analysis model to perform operation abnormality defect analysis on the solar cell; A solar cell operation analysis module, used for performing solar cell operation analysis based on the obtained abnormal image defect analysis results of the solar cell and the abnormal operation defect analysis results of the solar cell; Maintenance warning module, used to repair defective points according to the operation analysis results of solar cells; The control module is used to control the operation of the data acquisition module, the image abnormality defect analysis module, the operation abnormality defect analysis module, the solar cell operation analysis module and the maintenance early warning module.

6. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the solar cell defect detection method based on image recognition as described in any one of claims 1 to 4 by calling the computer program stored in the memory.

7. A computer-readable storage medium storing instructions, which, when executed on a computer, enables the computer to execute the solar cell defect detection method based on image recognition according to any one of claims 1 to 4.

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