Method and system for detecting thickness distribution of oxide layer on battery surface

Abstract

The present invention provides a method and system for detecting the thickness distribution of an oxide layer on a battery surface, wherein the method comprises the following steps: obtaining RGB images of a battery to be detected and a comparison battery through a reflectivity detector; graying the two RGB images and their color scale images to obtain corresponding grayscale images; selecting a plurality of fixed points on the grayscale images of the color scale images of the two RGB images respectively, and obtaining reflectivity values ​​and grayscale values ​​of the plurality of fixed points; fitting the corresponding relationship between the reflectivity values ​​and grayscale values ​​of the plurality of fixed points; obtaining the grayscale value of each point of the two batteries according to the grayscale images of the two RGB images, and calculating the reflectivity value of each point of each battery according to the corresponding relationship between the reflectivity value and the grayscale value of each battery; calculating the reflectivity difference of the corresponding points of the two batteries according to the reflectivity value of each point of the two batteries; and obtaining the thickness distribution of the oxide layer on the surface of the battery to be detected according to the reflectivity difference of the corresponding points of the two batteries.

Description

Technical Field

[0001] The invention relates to the technical field of solar cell production and manufacturing, and in particular to a method for detecting the thickness distribution of an oxide layer on a cell surface and a system for detecting the thickness distribution of an oxide layer on a cell surface. Background Art

[0002] In recent years, solar cells have been widely used in production and life. Since the thickness of the battery oxide layer has a great influence on the battery performance, how to detect the distribution of the thickness of the battery surface oxide layer has become particularly important.

[0003] General production lines will use hydrophilic and hydrophobic methods to characterize whether the silicon wafer surface has an oxide layer. In the production process of solar cells, after wet etching of the silicon wafer, it is necessary to oxidize the surface of the silicon wafer to form a layer of oxide film silicon dioxide. The surface of silicon dioxide contains hydroxyl groups, which can briefly combine with water molecules. Therefore, the surface of the oxidized silicon wafer changes from hydrophobic to hydrophilic. The second method is to use an ellipsometer to test the thickness of the film layer at a single point. The difference between silicon and silicon oxide is used to convert circular polarized light into elliptically polarized light. The stacked film model is generally used, that is, the thickness of the oxide layer plus the periodic thickness, such as SiOx+SiyNx, but the thickness of a single layer of SiOx cannot be directly obtained. Therefore, no matter which method is used, it cannot fully and intuitively reflect the thickness of the oxide layer on the entire surface of the battery. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for detecting the thickness distribution of the oxide layer on the surface of a battery, which can conveniently and intuitively obtain the thickness distribution of the oxide layer on the surface of the battery.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for detecting the thickness distribution of an oxide layer on a battery surface, comprising the following steps: obtaining RGB images of a battery to be detected and a comparison battery respectively through a reflectivity detector, wherein the RGB image of the battery to be detected and the RGB image of the comparison battery respectively have corresponding color scale diagrams, the color scale diagrams are annotated with reflectivity values, and the difference between the battery to be detected and the comparison battery is that the surface of the battery to be detected has an oxide layer, and the surface of the comparison battery has no oxide layer; graying the RGB image of the battery to be detected and its color scale diagram, and the RGB image of the comparison battery and its color scale diagram respectively to obtain corresponding grayscale diagrams; selecting a plurality of first fixed points on the grayscale diagram of the color scale diagram of the RGB image of the battery to be detected, and obtaining the reflectivity values ​​and grayscale values ​​of the plurality of first fixed points, selecting a plurality of second fixed points on the grayscale diagram of the color scale diagram of the RGB image of the comparison battery, and obtaining the reflectivity values ​​and grayscale values ​​of the plurality of second fixed points; and calculating the grayscale values ​​of the plurality of first fixed points according to the plurality of first fixed points. The reflectivity value and grayscale value of the fixed point are fitted to the corresponding relationship between the reflectivity value and grayscale value of the battery to be detected, and the corresponding relationship between the reflectivity value and grayscale value of the comparison battery is fitted according to the reflectivity value and grayscale value of the multiple second fixed points; the grayscale value of each point of the battery to be detected is obtained according to the grayscale image of the RGB image of the battery to be detected, and the reflectivity value of each point of the battery to be detected is calculated according to the corresponding relationship between the reflectivity value and grayscale value of the battery to be detected, the grayscale value of each point of the comparison battery is obtained according to the grayscale image of the RGB image of the comparison battery, and the reflectivity value of each point of the comparison battery is calculated according to the corresponding relationship between the reflectivity value and grayscale value of the comparison battery; the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery is calculated according to the reflectivity value of each point of the battery to be detected and the reflectivity value of each point of the comparison battery; the oxide layer thickness distribution on the surface of the battery to be detected is obtained according to the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery.

[0007] The oxide layer is phosphosilicate glass or borosilicate glass.

[0008] The RGB image and the color scale diagram of the battery to be tested, and the RGB image and the color scale diagram of the comparison battery are grayed out by imageJ to obtain corresponding grayscale images, and the grayscale value of any point in any grayscale image is read by imageJ.

[0009] The corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested or the comparison battery is: R%=k*i+b, wherein R% represents the reflectivity value, i represents the grayscale value, k represents the slope, and b represents the intercept.

[0010] The thickness of the oxide layer at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point.

[0011] A detection system for the thickness distribution of an oxide layer on a battery surface, comprising: a reflectivity detector, the reflectivity detector is used to respectively obtain RGB images of a battery to be detected and a comparison battery, wherein the RGB image of the battery to be detected and the RGB image of the comparison battery respectively have corresponding color scale diagrams, the color scale diagrams are annotated with reflectivity values, and the difference between the battery to be detected and the comparison battery is that the surface of the battery to be detected has an oxide layer, and the surface of the comparison battery has no oxide layer; a processing device, the processing device is used to grayscale the RGB image of the battery to be detected and its color scale diagram to obtain a corresponding grayscale diagram, and grayscale the RGB image of the comparison battery and its color scale diagram to obtain a corresponding grayscale diagram; a first acquisition device, the first acquisition device is used to obtain the reflectivity value and grayscale value of a plurality of first fixed points selected on the grayscale diagram of the color scale diagram of the RGB image of the battery to be detected, and obtain the reflectivity value and grayscale value of a plurality of second fixed points selected on the grayscale diagram of the color scale diagram of the RGB image of the comparison battery; a fitting device, the fitting device is used to fit the plurality of first fixed points according to the plurality of first fixed points. The reflectivity value and grayscale value of the battery to be detected are matched to the corresponding relationship between the reflectivity value and grayscale value of the battery to be detected, and the reflectivity value and grayscale value of the comparison battery are matched according to the reflectivity value and grayscale value of the multiple second fixed points; a first calculation device, the first calculation device is used to obtain the grayscale value of each point of the battery to be detected according to the grayscale image of the RGB image of the battery to be detected, and calculate the reflectivity value of each point of the battery to be detected according to the corresponding relationship between the reflectivity value and grayscale value of the battery to be detected, obtain the grayscale value of each point of the comparison battery according to the grayscale image of the RGB image of the comparison battery, and calculate the reflectivity value of each point of the comparison battery according to the corresponding relationship between the reflectivity value and grayscale value of the comparison battery; a second calculation device, the second calculation device is used to calculate the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery according to the reflectivity value of each point of the battery to be detected and the reflectivity value of each point of the comparison battery; a second acquisition device, the acquisition device is used to acquire the oxide layer thickness distribution on the surface of the battery to be detected according to the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery.

[0012] The oxide layer is phosphosilicate glass or borosilicate glass.

[0013] The processing device grayscales the RGB image and the color scale map of the battery to be detected and the RGB image and the color scale map of the comparison battery through imageJ to obtain corresponding grayscale maps. The first acquisition device reads the grayscale values ​​of the multiple first fixed points and the grayscale values ​​of the multiple second fixed points through imageJ. The first calculation device reads the grayscale value of each point of the battery to be detected and the grayscale value of each point of the comparison battery through imageJ.

[0014] The corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested or the comparison battery is: R%=k*i+b, wherein R% represents the reflectivity value, i represents the grayscale value, k represents the slope, and b represents the intercept.

[0015] The thickness of the oxide layer at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point.

[0016] Beneficial effects of the present invention:

[0017] The present invention outputs the RGB image of the battery through a reflectivity detector, and adopts image processing and data fitting to characterize the oxide layer thickness as reflectivity, thereby obtaining the oxide layer thickness distribution on the battery surface. Therefore, the thickness distribution of the oxide layer on the battery surface can be conveniently and intuitively known. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a method for detecting the thickness distribution of an oxide layer on a battery surface according to an embodiment of the present invention;

[0019] Figure 2 A schematic diagram of a detection result interface of a reflectivity detector according to an embodiment of the present invention;

[0020] Figure 3 A schematic diagram of a grayscale image of an RGB image of a battery to be tested or a battery to be compared according to an embodiment of the present invention;

[0021] Figure 4 A schematic diagram of a grayscale image of a color scale image of a battery to be tested or a comparison battery according to an embodiment of the present invention;

[0022] Figure 5 A schematic diagram of an enlarged image of a grayscale image of a color scale image of a battery to be tested or a comparison battery according to an embodiment of the present invention;

[0023] Figure 6 A schematic diagram of an imageJ readout result interface according to an embodiment of the present invention;

[0024] Figure 7 Schematic diagram of a detection system for the thickness distribution of an oxide layer on a battery surface according to an embodiment of the present invention. DETAILED DESCRIPTION

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

[0026] like Figure 1 As shown, the method for detecting the thickness distribution of the oxide layer on the surface of a battery according to an embodiment of the present invention comprises the following steps:

[0027] S1, respectively obtaining RGB images of the battery to be tested and the battery to be compared by a reflectivity detector, wherein the RGB image of the battery to be tested and the RGB image of the battery to be compared have corresponding color scale diagrams, and the color scale diagrams are marked with reflectivity values. The difference between the battery to be tested and the battery to be compared is that the surface of the battery to be tested has an oxide layer, and the surface of the battery to be compared has no oxide layer.

[0028] In one embodiment of the present invention, the format of the RGB image acquired by the reflectivity detector may be a JMP format.

[0029] like Figure 2 As shown, in one embodiment of the present invention, the detection result interface of the reflectivity detector includes an RGB image and a color scale diagram of the battery, and the color scale diagram is divided into a color scale part and a scale part, wherein the scale part is marked with a reflectivity value.

[0030] In one embodiment of the present invention, the oxide layer can be phosphosilicate glass after diffusion of a P-type battery or borosilicate glass after diffusion of an N-type battery. In addition, in order to prevent other factors from interfering with the test results, the process of the battery to be tested and the comparison battery should be completely consistent except for the difference in the oxide layer, such as shape, material, etc. For example, the battery to be tested and the comparison battery can be batteries of the same model produced in the same batch.

[0031] S2, grayscale processing is performed on the RGB image and color scale map of the battery to be tested, and the RGB image and color scale map of the comparison battery, respectively, to obtain corresponding grayscale maps.

[0032] In one embodiment of the present invention, the RGB image of the battery to be tested and its color scale map, and the RGB image of the comparison battery and its color scale map can be grayed out by imageJ to obtain corresponding grayscale images. The specific operations are as follows: open the test result interface of the battery to be tested and the comparison battery respectively with imageJ, select the RGB image in the test result interface with the mouse box, press and hold the shortcut key "Ctrl+shift+X" to capture the RGB image part of the battery to be tested and the comparison battery respectively, and save the images for later use; open the test result interface of the battery to be tested and the comparison battery respectively with imageJ again, select the color scale map part of the RGB image with the mouse box, press and hold the shortcut key "Ctrl+shift+X" to obtain the color scale map of the battery to be tested and the comparison battery respectively, and save the images for later use; open the RGB image with imageJ, convert the color image into an 8-bit grayscale image, and the grayscale image of the converted RGB image is as shown in the figure. Figure 3Similarly, use imageJ to open the color scale map of the RGB image and convert the color image into an 8-bit grayscale image. The grayscale image of the converted color scale map is as follows: Figure 4 shown.

[0033] S3, select multiple first fixed points on the grayscale map of the color scale map of the RGB image of the battery to be tested, and obtain the reflectivity values ​​and grayscale values ​​of the multiple first fixed points, select multiple second fixed points on the grayscale map of the color scale map of the RGB image of the comparison battery, and obtain the reflectivity values ​​and grayscale values ​​of the multiple second fixed points.

[0034] In one embodiment of the present invention, multiple fixed points can be selected on a color scale diagram marked with reflectance values, and the reflectance values ​​and grayscale values ​​of the multiple fixed points can be obtained. The specific operation is as follows: Figure 5 As shown, if you want to select a point with a reflectance value of 8.6 on the color scale map, you can place the mouse at the 8.6 scale of the grayscale map of the color scale map of the RGB image, that is, the box position, and obtain the Y-axis coordinate of the point, and then move the mouse to the left to the circle position in the color scale part of the grayscale map of the color scale map of the RGB image, ensuring that the Y-axis coordinate of the color scale part where the mouse is located after the translation is consistent with the Y-axis coordinate of the scale part. At this time, imageJ outputs the grayscale value of the point according to the circle position of the color scale part where the mouse is located.

[0035] S4, fitting the correspondence between the reflectivity value and the grayscale value of the battery to be tested according to the reflectivity values ​​and the grayscale values ​​of the multiple first fixed points, and fitting the correspondence between the reflectivity value and the grayscale value of the comparison battery according to the reflectivity values ​​and the grayscale values ​​of the multiple second fixed points.

[0036] In one embodiment of the present invention, the specific operation of fitting the relationship between the reflectivity value and the grayscale value of the battery through the reflectivity value and the grayscale value of multiple fixed points is as follows: after outputting the reflectivity value and the grayscale value of multiple fixed points through imageJ, the reflectivity value and the corresponding grayscale value of the multiple fixed points can be fitted with origin to find the corresponding relationship between the reflectivity value and the grayscale value, and the relationship between the reflectivity value and the grayscale value can be expressed by a function expression. By fitting the reflectivity value and the grayscale value of multiple fixed points, the corresponding functional relationship between the reflectivity value and the grayscale value can be obtained, for example, it can be: R% = k*i+b, where R% represents the reflectivity value, i represents the grayscale value, k is the slope, and b is the intercept. The fitting process is the process of solving the k value and the b value.

[0037] S5, obtaining the grayscale value of each point of the battery to be detected according to the grayscale image of the RGB image of the battery to be detected, and calculating the reflectivity value of each point of the battery to be detected according to the correspondence between the reflectivity value and the grayscale value of the battery to be detected, obtaining the grayscale value of each point of the comparison battery according to the grayscale image of the RGB image of the comparison battery, and calculating the reflectivity value of each point of the comparison battery according to the correspondence between the reflectivity value and the grayscale value of the comparison battery.

[0038] In one embodiment of the present invention, when the mouse is placed on any point of the grayscale image of the RGB image, imageJ can automatically read the coordinates (x, y) of the point on the grayscale image of the RGB image and output the grayscale value of the point. The read result interface is as follows: Figure 6 As shown. Therefore, after knowing the relationship R% = k*i + b, the reflectivity value of the battery to be tested can be calculated by the gray value of any point. Similarly, by using imageJ to obtain the gray value of any point of the comparison battery, the reflectivity value of the comparison battery can be calculated.

[0039] S6, calculating the reflectivity difference between the corresponding points of the battery to be tested and the comparison battery according to the reflectivity value of each point of the battery to be tested and the reflectivity value of each point of the comparison battery.

[0040] S7, obtaining the oxide layer thickness distribution on the surface of the battery to be tested according to the reflectivity difference between the corresponding points of the battery to be tested and the comparison battery.

[0041] In one embodiment of the present invention, the oxide layer thickness at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point. That is, the greater the reflectivity difference, the thicker the oxide layer, and the distribution of the reflectivity difference can represent the distribution of the oxide layer thickness.

[0042] In summary, according to the method for detecting the thickness distribution of the oxide layer on the surface of a battery in an embodiment of the present invention, a reflectivity detector outputs an RGB image of the battery, and image processing and data fitting are used to characterize the oxide layer thickness as reflectivity, thereby obtaining the oxide layer thickness distribution on the surface of the battery. As a result, the thickness distribution of the oxide layer on the surface of the battery can be conveniently and intuitively known.

[0043] In order to implement the method for detecting the thickness distribution of the oxide layer on the surface of a battery in the above-mentioned embodiment, the present invention further proposes a system for detecting the thickness distribution of the oxide layer on the surface of a battery.

[0044] like Figure 7As shown, the detection system for the battery surface oxide layer thickness distribution of an embodiment of the present invention includes a reflectivity detector 10, a processing device 20, a first acquisition device 30, a fitting device 40, a first calculation device 50, a second calculation device 60 and a second acquisition device 70. The reflectivity detector 10 is used to obtain RGB images of the battery to be tested and the comparison battery respectively, wherein the RGB image of the battery to be tested and the RGB image of the comparison battery respectively have corresponding color scale diagrams, and the color scale diagrams are annotated with reflectivity values. The difference between the battery to be tested and the comparison battery is that the surface of the battery to be tested has an oxide layer, and the surface of the comparison battery has no oxide layer; the processing device 20 is used to grayscale the RGB image of the battery to be tested and its color scale diagram, and the RGB image of the comparison battery and its color scale diagram, respectively, to obtain corresponding grayscale diagrams; the first acquisition device 30 is used to obtain the reflectivity value and grayscale value of multiple first fixed points selected on the grayscale diagram of the color scale diagram of the RGB image of the battery to be tested, and the reflectivity value and grayscale value of multiple second fixed points selected on the grayscale diagram of the color scale diagram of the RGB image of the comparison battery; the fitting device 40 is used to fit the reflectivity value and grayscale value of the battery to be tested according to the reflectivity value and grayscale value of the multiple first fixed points The first calculating device 50 is used to obtain the grayscale value of each point of the battery to be detected according to the grayscale image of the RGB image of the battery to be detected, and calculate the reflectivity value of each point of the battery to be detected according to the corresponding relationship between the reflectivity value and the grayscale value of the battery to be detected, obtain the grayscale value of each point of the comparison battery according to the grayscale image of the RGB image of the comparison battery, and calculate the reflectivity value of each point of the comparison battery according to the corresponding relationship between the reflectivity value and the grayscale value of the comparison battery; the second calculating device 60 is used to calculate the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery according to the reflectivity value of each point of the battery to be detected and the reflectivity value of each point of the comparison battery; the second obtaining device 70 is used to obtain the oxide layer thickness distribution on the surface of the battery to be detected according to the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery.

[0045] In one embodiment of the present invention, the oxide layer may be phosphosilicate glass after diffusion of a P-type cell or borosilicate glass after diffusion of an N-type cell.

[0046] In one embodiment of the present invention, the processing device 20 grayscales the RGB image and the color scale map of the battery to be tested and the RGB image and the color scale map of the comparison battery through imageJ to obtain the corresponding grayscale map, the first acquisition device 30 reads the grayscale values ​​of multiple first fixed points and the grayscale values ​​of multiple second fixed points through imageJ, and the first calculation device 50 reads the grayscale value of each point of the battery to be tested and the grayscale value of each point of the comparison battery through imageJ, wherein the processing device 20 may include imageJ image processing software. Specifically, imageJ obtains the RGB image part and the color scale map of the battery to be tested and the comparison battery through the test result interface of the battery to be tested and the comparison battery, respectively, and converts the color image into an 8-bit grayscale image, thereby obtaining the grayscale map of the battery to be tested and the comparison battery. The first acquisition device 30 can read the grayscale values ​​of multiple fixed points selected on the color scale map of the RGB image through imageJ, and the first calculation device 50 can also read the grayscale value of any point on the RGB image through imageJ.

[0047] In one embodiment of the present invention, the first acquisition device 30 is used to obtain the reflectivity value and grayscale value of multiple fixed points of the battery to be tested and the comparison battery. Specifically, the mouse is placed on the scale part of the color scale diagram marked with the reflectivity value to obtain the reflectivity value of the fixed point, and then the mouse is translated to the left to the color scale part of the color scale diagram to obtain the grayscale of the fixed point. At this time, it should be ensured that the reflectivity value corresponding to the fixed point is consistent with the Y-axis coordinate of the fixed point. At the same time, imageJ outputs the grayscale value of the fixed point.

[0048] In one embodiment of the present invention, the fitting device 40 fits the reflectivity values ​​and grayscale values ​​of multiple fixed points output by imageJ, finds the corresponding relationship between the reflectivity values ​​and the grayscale values, and expresses the relationship between the reflectivity values ​​and the grayscale values ​​in the form of a function expression. By fitting the reflectivity values ​​and grayscale values ​​of multiple fixed points, the corresponding functional relationship between the reflectivity values ​​and the grayscale values ​​can be obtained as: R% = k*i+b, where R% represents the reflectivity value, i represents the grayscale value, k is the slope, b is the intercept, and the fitting process is the process of solving the k value and the b value. Among them, the fitting device 40 may include function drawing software such as origin.

[0049] In one embodiment of the present invention, the first calculation device 50 is used to calculate the reflectivity value of each point of the battery to be tested and the comparison battery. ImageJ reads the reflectivity value and grayscale value of multiple fixed points, and obtains the functional relationship between the reflectivity value and the grayscale value through the fitting device 40, thereby calculating the reflectivity value according to the grayscale value of any point of the battery to be tested or the comparison battery. For example, find any point on the grayscale map of the RGB image, imageJ reads the grayscale value of the point according to the coordinates of the point, and substitutes the grayscale value of the point into the corresponding relationship between the reflectivity value and the grayscale value to obtain the reflectivity value of the point.

[0050] In one embodiment of the present invention, the second calculation device 60 is used to calculate the difference in reflectivity values ​​of corresponding points of the battery to be tested and the comparison battery, and the thickness of the oxide layer at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point, wherein the larger the difference, the thicker the oxide layer thickness, and the distribution of the reflectivity difference can represent the distribution of the oxide layer thickness.

[0051] According to the method for detecting the thickness distribution of the oxide layer on the surface of a battery in an embodiment of the present invention, a reflectivity detector outputs an RGB image of the battery, and image processing and data fitting are used to characterize the oxide layer thickness as reflectivity, thereby obtaining the oxide layer thickness distribution on the surface of the battery. As a result, the thickness distribution of the oxide layer on the surface of the battery can be conveniently and intuitively known.

[0052] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0053] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0055] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0056] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0057] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0058] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0059] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0060] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0061] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for detecting the thickness distribution of the oxide layer on the surface of a battery, characterized in that: The following steps are involved: The RGB images of the battery to be tested and the comparison battery are respectively obtained by a reflectivity detector, wherein the RGB image of the battery to be tested and the RGB image of the comparison battery respectively have corresponding color scale diagrams, and the color scale diagrams are marked with reflectivity values. The difference between the battery to be tested and the comparison battery is that the surface of the battery to be tested has an oxide layer, and the surface of the comparison battery has no oxide layer; Respectively grayscale the RGB image and the color scale diagram of the battery to be tested, and the RGB image and the color scale diagram of the comparison battery to obtain corresponding grayscale diagrams; Selecting a plurality of first fixed points on the grayscale map of the color scale map of the RGB image of the battery to be tested, and obtaining reflectivity values ​​and grayscale values ​​of the plurality of first fixed points, selecting a plurality of second fixed points on the grayscale map of the color scale map of the RGB image of the comparison battery, and obtaining reflectivity values ​​and grayscale values ​​of the plurality of second fixed points; Fitting the corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested according to the reflectivity values ​​and the grayscale values ​​of the multiple first fixed points, and fitting the corresponding relationship between the reflectivity value and the grayscale value of the comparison battery according to the reflectivity values ​​and the grayscale values ​​of the multiple second fixed points; Obtaining the grayscale value of each point of the battery to be detected according to the grayscale image of the RGB image of the battery to be detected, and calculating the reflectivity value of each point of the battery to be detected according to the correspondence between the reflectivity value and the grayscale value of the battery to be detected, obtaining the grayscale value of each point of the comparison battery according to the grayscale image of the RGB image of the comparison battery, and calculating the reflectivity value of each point of the comparison battery according to the correspondence between the reflectivity value and the grayscale value of the comparison battery; Calculate the reflectivity difference between the corresponding points of the battery to be tested and the comparison battery according to the reflectivity value of each point of the battery to be tested and the reflectivity value of each point of the comparison battery; The oxide layer thickness distribution on the surface of the battery to be detected is obtained according to the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery.

2. The method for detecting the thickness distribution of the oxide layer on the surface of a battery according to claim 1, characterized in that: The oxide layer is phosphosilicate glass or borosilicate glass.

3. The method for detecting the thickness distribution of the oxide layer on the surface of a battery according to claim 1, characterized in that: The RGB image and the color scale diagram of the battery to be tested, and the RGB image and the color scale diagram of the comparison battery are grayed out by imageJ to obtain corresponding grayscale images, and the grayscale value of any point in any grayscale image is read by imageJ.

4. The method for detecting the thickness distribution of the oxide layer on the surface of a battery according to claim 1, characterized in that: The corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested or the comparison battery is: R%=k*i+b Wherein, R% represents the reflectance value, i represents the gray value, k represents the slope, and b represents the intercept.

5. The method for detecting the thickness distribution of the oxide layer on the surface of a battery according to any one of claims 1 to 4, characterized in that: The thickness of the oxide layer at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point.

6. A detection system for the thickness distribution of the oxide layer on the surface of a battery, characterized in that: include: A reflectivity detector, the reflectivity detector is used to obtain RGB images of the battery to be tested and the comparison battery, respectively, wherein the RGB image of the battery to be tested and the RGB image of the comparison battery respectively have corresponding color scale diagrams, the color scale diagrams are annotated with reflectivity values, and the difference between the battery to be tested and the comparison battery is that the surface of the battery to be tested has an oxide layer, and the surface of the comparison battery has no oxide layer; A processing device, the processing device is used to perform grayscale processing on the RGB image and the color scale map of the battery to be tested, and the RGB image and the color scale map of the comparison battery, respectively, to obtain corresponding grayscale maps; A first acquisition device, the first acquisition device is used to acquire the reflectivity value and grayscale value of a plurality of first fixed points selected on the grayscale image of the color scale image of the RGB image of the battery to be tested, and acquire the reflectivity value and grayscale value of a plurality of second fixed points selected on the grayscale image of the color scale image of the RGB image of the comparison battery; A fitting device, the fitting device is used to fit the corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested according to the reflectivity values ​​and the grayscale values ​​of the multiple first fixed points, and to fit the corresponding relationship between the reflectivity value and the grayscale value of the comparison battery according to the reflectivity values ​​and the grayscale values ​​of the multiple second fixed points; A first calculation device, the first calculation device is used to obtain the grayscale value of each point of the battery to be detected according to the grayscale image of the RGB image of the battery to be detected, and calculate the reflectivity value of each point of the battery to be detected according to the correspondence between the reflectivity value and the grayscale value of the battery to be detected, obtain the grayscale value of each point of the comparison battery according to the grayscale image of the RGB image of the comparison battery, and calculate the reflectivity value of each point of the comparison battery according to the correspondence between the reflectivity value and the grayscale value of the comparison battery; A second calculation device, the second calculation device is used to calculate the reflectivity difference between the corresponding points of the battery to be tested and the comparison battery according to the reflectivity value of each point of the battery to be tested and the reflectivity value of each point of the comparison battery; The second acquisition device is used to acquire the oxide layer thickness distribution on the surface of the battery to be detected according to the reflectivity difference between the corresponding points of the battery to be detected and the comparison battery.

7. The detection system for the thickness distribution of the battery surface oxide layer according to claim 6, characterized in that: The oxide layer is phosphosilicate glass or borosilicate glass.

8. The detection system for the thickness distribution of the battery surface oxide layer according to claim 6, characterized in that: The processing device grayscales the RGB image and the color scale map of the battery to be detected and the RGB image and the color scale map of the comparison battery through imageJ to obtain corresponding grayscale maps. The first acquisition device reads the grayscale values ​​of the multiple first fixed points and the grayscale values ​​of the multiple second fixed points through imageJ. The first calculation device reads the grayscale value of each point of the battery to be detected and the grayscale value of each point of the comparison battery through imageJ.

9. The detection system for the thickness distribution of the oxide layer on the surface of a battery according to claim 6, characterized in that: The corresponding relationship between the reflectivity value and the grayscale value of the battery to be tested or the comparison battery is: R%=k*i+b Wherein, R% represents the reflectance value, i represents the gray value, k represents the slope, and b represents the intercept.

10. The detection system for the thickness distribution of the oxide layer on the surface of a battery according to any one of claims 6 to 9, characterized in that: The thickness of the oxide layer at any point on the surface of the battery to be tested is positively correlated with the reflectivity difference at that point.

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