Disclosure of Invention
The invention provides a method and a system for detecting the thickness distribution of an oxide layer on the surface of a battery, which can conveniently and intuitively know the thickness distribution condition of the oxide layer on the surface of the battery.
The technical scheme adopted by the invention is as follows:
The method for detecting the thickness distribution of the oxide layer on the surface of the battery comprises the following steps of respectively obtaining RGB images of the battery to be detected and the battery to be compared through a reflectivity detector, wherein the RGB images of the battery to be detected and the battery to be compared respectively have corresponding tone scale diagrams, the tone scale diagrams are marked with reflectivity values, and the battery to be detected is different from the battery to be compared in that the surface of the battery to be detected is provided with an oxide layer and the surface of the battery to be compared is not provided with the oxide layer; the RGB image of the battery to be detected and the tone scale image thereof, the RGB image of the battery to be compared and the tone scale image thereof are respectively subjected to graying processing to obtain corresponding gray scale images, a plurality of first fixed points are selected on the gray scale image of the tone scale image of the RGB image of the battery to be detected, the reflectivity value and the gray scale value of the first fixed points are obtained, a plurality of second fixed points are selected on the gray scale image of the tone scale image of the RGB image of the battery to be detected, the reflectivity value and the gray scale value of the second fixed points are obtained, the corresponding relation between the reflectivity value and the gray scale value of the battery to be detected is fitted according to the reflectivity value and the gray scale value of the first fixed points, the corresponding relation between the reflectivity value and the gray scale value of the battery to be detected is fitted according to the reflectivity value and the gray scale value of the RGB image of the battery to be detected, the reflectivity value of each point of the battery to be detected is calculated according to the corresponding relation between the reflectivity value of the battery to be detected and the gray scale value of the battery to be detected, the method comprises the steps of comparing a reflectance value of a battery to be detected with a gray value of the battery to be detected, calculating the reflectance value of each point of the battery to be detected according to the corresponding relation between the reflectance value of the battery to be detected and the gray value, calculating the reflectance difference value of the battery to be detected and the corresponding point of the battery to be detected according to the reflectance value of each point of the battery to be detected and the reflectance value of each point of the battery to be detected, and obtaining the oxide layer thickness distribution of the surface of the battery to be detected according to the reflectance difference value of the battery to be detected and the corresponding point of the battery to be detected.
The oxide layer is phosphosilicate glass or borosilicate glass.
And carrying out graying treatment on the RGB image of the battery to be detected, the tone scale image of the battery to be detected, the RGB image of the comparison battery and the tone scale image of the comparison battery through imageJ to obtain corresponding gray scale images, and reading the gray scale value of any point in any gray scale image through imageJ.
The corresponding relation between the reflectivity value and the gray value of the battery to be detected or the comparison battery is that R% = k is i+b, wherein R% represents the reflectivity value, i represents the gray value, k is the slope, and b is the intercept.
And the thickness of the oxide layer at any point on the surface of the battery to be detected and the reflectivity difference value at the point are in positive correlation.
A detection system for thickness distribution of an oxide layer on a battery surface comprises a reflectivity detector, a processing device, a first acquisition device, a second acquisition device, a first fitting device and a second fitting device, wherein the reflectivity detector is used for respectively acquiring RGB images of the battery to be detected and the comparison battery, the RGB images of the battery to be detected and the comparison battery are respectively provided with corresponding tone maps, the tone maps are filled with reflectivity values, the difference between the battery to be detected and the comparison battery is that the surface of the battery to be detected is provided with the oxide layer, the surface of the comparison battery is not provided with the oxide layer, the processing device is used for carrying out graying processing on the RGB images of the battery to be detected and the tone maps thereof to obtain corresponding tone maps, the first acquisition device is used for acquiring a plurality of reflectivity values and tone values selected on the tone maps of the RGB images of the battery to be detected, the first acquisition device is used for acquiring a plurality of reflectivity values and tone maps selected on the tone maps of the RGB images of the battery to be detected, the first acquisition device is used for acquiring the first fixed point-to-fit the reflectance values and the tone maps of the battery to be detected, the first acquisition device is used for calculating the first fixed point-to-fit the first fixed point-to the reflectance values and the first fitting device to the first fixed point-to the reflectance values and the first fixed point-to the battery to be fitted according to the reflectivity values and the first fixed point-to the reflectance values and the first fixed point-to be fitted to the first fixed point-to the reflectance values, the device comprises a first calculating device, a second calculating device and a second obtaining device, wherein the first calculating device is used for calculating the reflectivity difference value between the battery to be detected and the corresponding point of the battery to be detected according to the reflectivity value of the battery to be detected and the reflectivity value of the corresponding point of the battery to be detected, the gray value of each point of the battery to be detected is obtained according to the gray level map of the RGB image of the battery to be detected, the reflectivity value of each point of the battery to be detected is calculated according to the reflectivity value of the corresponding point of the battery to be detected and the corresponding point of the battery to be detected, and the second calculating device is used for obtaining the oxide layer thickness distribution of the surface of the battery to be detected according to the reflectivity difference value between the battery to be detected and the corresponding point of the battery to be detected.
The oxide layer is phosphosilicate glass or borosilicate glass.
The processing device performs graying processing on the RGB image of the battery to be detected and the tone scale image thereof and the RGB image of the comparison battery and the tone scale image thereof through the imageJ to obtain corresponding gray scale images, the first obtaining device reads gray scale values of the first fixed points and gray scale values of the second fixed points through the imageJ, and the first calculating device reads the gray scale values of each point of the battery to be detected and the gray scale values of each point of the comparison battery through the imageJ.
The corresponding relation between the reflectivity value and the gray value of the battery to be detected or the comparison battery is that R% = k is i+b, wherein R% represents the reflectivity value, i represents the gray value, k is the slope, and b is the intercept.
And the thickness of the oxide layer at any point on the surface of the battery to be detected and the reflectivity difference value at the point are in positive correlation.
The invention has the beneficial effects that:
According to the invention, the RGB image of the battery is output through the reflectivity detector, and the thickness of the oxide layer is represented into the reflectivity by adopting the image processing and data fitting modes, so that the thickness distribution of the oxide layer on the surface of the battery is obtained, and the thickness distribution condition of the oxide layer on the surface of the battery can be conveniently and intuitively known.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the method for detecting the thickness distribution of the oxide layer on the surface of the battery according to the embodiment of the invention comprises the following steps:
s1, respectively acquiring RGB images of a battery to be detected and a battery to be compared through a reflectivity detector, wherein the RGB images of the battery to be detected and the battery to be compared respectively have corresponding tone scale images, the tone scale images are provided with reflectivity values, and the battery to be detected is different from the battery to be compared in that the surface of the battery to be detected is provided with an oxide layer and the surface of the battery to be compared is not provided with the oxide layer.
In one embodiment of the present invention, the format of the RGB image acquired by the reflectance detector may be JMP format.
As shown in fig. 2, in one embodiment of the present invention, the detection result interface of the reflectivity detector includes an RGB image of the battery and a tone scale map, which is further divided into a tone scale portion and a scale portion, wherein the scale portion is labeled as a reflectivity value.
In one embodiment of the invention, the oxide layer may be a P-cell diffused phosphosilicate glass or an N-cell diffused borosilicate glass. In addition, in order to prevent interference of other factors to the detection result, other process steps of the battery to be detected and the comparison battery except for the difference of the oxide layers should be completely consistent, such as shape, material, etc., for example, the battery to be detected and the comparison battery may be the same type of battery produced in the same batch.
S2, respectively carrying out gray scale treatment on the RGB image of the battery to be detected and the tone scale diagram thereof, and comparing the RGB image of the battery and the tone scale diagram thereof to obtain a corresponding gray scale diagram.
In one embodiment of the present invention, the image j may be used to perform grayscale processing on the RGB image of the battery to be detected and the tone map thereof, and compare the RGB image of the battery with the tone map thereof, so as to obtain a corresponding grayscale map. The method comprises the steps of opening detection result interfaces of a battery to be detected and a battery to be compared by using an imageJ, selecting RGB images in the detection result interfaces by using a mouse frame, pressing a shortcut key 'ctrl+shift+X', intercepting RGB image parts of the battery to be detected and the battery to be compared, saving the images for standby, opening the detection result interfaces of the battery to be detected and the battery to be compared by using the imageJ again, selecting a tone map part of the RGB images by using the mouse frame, pressing the shortcut key 'ctrl+shift+X', acquiring tone maps of the battery to be detected and the battery to be compared, saving the images for standby, opening the RGB images by using the imageJ, converting the color images into 8-bit gray images, and enabling the gray maps of the converted RGB images to be shown in figure 3. Similarly, the image J is used to open the tone map of the RGB image, convert the color image into an 8bit gray scale image, and the gray scale map of the converted tone map is shown in FIG. 4.
S3, selecting a plurality of first fixed points on the gray level diagram of the RGB image of the battery to be detected, acquiring the reflectivity values and the gray level values of the first fixed points, selecting a plurality of second fixed points on the gray level diagram of the RGB image of the battery to be detected, and acquiring the reflectivity values and the gray level values of the second fixed points.
In one embodiment of the invention, a plurality of fixed points can be selected on the tone scale map marked with the reflectivity value, and the reflectivity value and the gray scale value of the plurality of fixed points are obtained, and the specific operation is as follows, if the point with the reflectivity value of 8.6 on the tone scale map is to be selected, as shown in fig. 5, a mouse can be placed at the 8.6 scale of the gray scale map of the tone scale map of the RGB image, namely a box position, the Y-axis coordinate of the point is obtained, then the mouse is translated leftwards to the circle position in the tone scale part of the tone scale map of the RGB image, the Y-axis coordinate of the tone scale part where the mouse is located after the translation is ensured to be consistent with the Y-axis coordinate of the scale part, and at this time, the imageJ outputs the gray scale value of the point according to the circle position of the tone scale part where the mouse is located.
And S4, fitting the corresponding relation between the reflectivity value and the gray value of the battery to be detected according to the reflectivity values and the gray values of the first fixed points, and fitting and comparing the corresponding relation between the reflectivity value and the gray value of the battery according to the reflectivity values and the gray values of the second fixed points.
In one embodiment of the invention, the specific operation of fitting the relationship between the reflectivity value and the gray value of the battery through the reflectivity values and the gray values of the plurality of fixed points is as follows, namely after the reflectivity values and the gray values of the plurality of fixed points are output through the imageJ, the reflectivity values and the corresponding gray values of the plurality of fixed points can be fitted through the origin, the corresponding relationship between the reflectivity values and the gray values is found, and the relationship between the reflectivity values and the gray values is represented in a function expression mode. By fitting the reflectance values and the gray values of the fixed points, a corresponding functional relationship between the reflectance values and the gray values may be obtained, for example, R% = k×i+b, where R% represents the reflectance value, i represents the gray value, k is the slope, and b is the intercept. The fitting process is a process of solving the k value and the b value.
S5, acquiring the gray value of each point of the battery to be detected according to the gray image of the RGB image of the battery to be detected, calculating the reflectivity value of each point of the battery to be detected according to the reflectivity value and gray value corresponding relation of the battery to be detected, acquiring the gray value of each point of the battery to be compared according to the gray image of the RGB image of the battery to be compared, and calculating the reflectivity value of each point of the battery to be compared according to the reflectivity value and gray value corresponding relation of the battery to be compared.
In one embodiment of the present invention, when a mouse is placed at any point of the gray scale image of the RGB image, the imageJ can automatically read the coordinates (x, y) of the point on the gray scale image of the RGB image and output the gray scale value of the point, and the interface of the read results is shown in fig. 6. Therefore, after knowing the relationship of R% = k×i+b, the reflectance value of the battery to be detected can be calculated by the gray value of any point. Similarly, the reflectance value of the comparison cell can be calculated by obtaining the gray value of any point of the comparison cell using imageJ.
And S6, calculating the difference value of the reflectivity of 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.
S7, obtaining the thickness distribution of the oxide layer on the surface of the battery to be detected according to the difference value of the reflectivity of the corresponding points of the battery to be detected and the comparison battery.
In one embodiment of the invention, the thickness of the oxide layer at any point on the surface of the cell to be detected is in positive correlation with the difference in reflectivity at that point. That is, the larger the reflectance difference, the thicker the oxide layer, and the distribution of the reflectance difference can be expressed as the distribution of the oxide layer thickness.
In summary, according to the method for detecting the thickness distribution of the oxide layer on the surface of the battery, the reflectance detector outputs the RGB image of the battery, and the oxide layer thickness is represented to be the reflectance by adopting the image processing and data fitting modes, so that the thickness distribution of the oxide layer on the surface of the battery is obtained, and therefore, the thickness distribution condition of the oxide layer on the surface of the battery can be conveniently and intuitively known.
In order to realize the method for detecting the thickness distribution of the oxide layer on the surface of the battery in the embodiment, the invention also provides a system for detecting the thickness distribution of the oxide layer on the surface of the battery.
As shown in fig. 7, the detection system for the thickness distribution of the oxide layer on the surface of the battery according to the 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 configured to obtain RGB images of a battery to be detected and an RGB image of a battery to be compared, where the RGB images of the battery to be detected and the RGB images of the battery to be compared have corresponding tone scale patterns, the tone scale patterns are annotated with reflectivity values, and the battery to be detected is different from the battery to be compared in that an oxide layer is present on the surface of the battery to be detected and no oxide layer is present on the surface of the battery to be compared; the processing device 20 is used for respectively carrying out graying processing on the RGB image of the battery to be detected and the tone chart thereof and the RGB image of the comparison battery and the tone chart thereof to obtain corresponding tone charts, the first obtaining device 30 is used for obtaining the reflectivity value and the tone chart of a plurality of first fixed points selected on the tone chart of the RGB image of the battery to be detected and the reflectivity value and the tone chart of a plurality of second fixed points selected on the tone chart of the comparison battery, the fitting device 40 is used for fitting the reflectivity value and the tone chart of the battery to be detected according to the reflectivity value and the tone chart of the plurality of first fixed points and fitting the reflectivity value and the tone chart of the comparison battery according to the reflectivity value and the tone chart of the plurality of second fixed points, the first calculating device 50 is used for obtaining the tone chart of each point of the battery to be detected according to the tone chart 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 reflectivity value and the tone chart of the comparison battery to be detected, and calculates the reflectivity value of each point of the comparison battery according to the reflectivity value and gray value corresponding relation of the comparison battery, the second calculating device 60 is used for calculating the reflectivity difference value between the battery to be detected and the corresponding point of 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, and the second obtaining device 70 is used for obtaining the oxide layer thickness distribution of the surface of the battery to be detected according to the reflectivity difference value between the battery to be detected and the corresponding point of the comparison battery.
In one embodiment of the invention, the oxide layer may be a P-cell diffused phosphosilicate glass or an N-cell diffused borosilicate glass.
In one embodiment of the present invention, the processing device 20 performs graying processing on the RGB image of the battery to be detected and the tone scale map thereof and the RGB image of the comparison battery and the tone scale map thereof through the imageJ to obtain corresponding gray scale maps, the first obtaining device 30 reads gray scale values of a plurality of first fixed points and gray scale values of a plurality of second fixed points through the imageJ, and the first calculating device 50 reads gray scale values of each point of the battery to be detected and the gray scale values of each point of the comparison battery through the imageJ, where the processing device 20 may include imageJ image processing software. Specifically, the imageJ obtains RGB image portions and tone maps of the battery to be detected and the battery to be compared through detection result interfaces of the battery to be detected and the battery to be compared, and converts the color images into 8-bit gray scale images, so that gray scale maps of the battery to be detected and the battery to be compared are obtained. The first obtaining device 30 may read the gray values of a plurality of fixed points selected on the tone map of the RGB image through imageJ, and the first calculating device 50 may also read the gray values of any point on the RGB image through imageJ.
In one embodiment of the invention, the first acquisition means 30 are used to acquire reflectance values and gray values of a plurality of fixed points of the battery to be detected and of the comparison battery. Specifically, a mouse is placed on a scale part of a tone scale map marked with a reflectivity value to obtain the reflectivity value of the fixed point, then the mouse is translated leftwards to the tone scale part of the tone scale map to obtain the gray scale of the fixed point, at the moment, the reflectivity value corresponding to the fixed point is ensured to be consistent with the Y-axis coordinate where the fixed point is located, and meanwhile, imageJ outputs the gray scale value of the fixed point.
In one embodiment of the present invention, the fitting device 40 fits the reflectance values and the gray values of the plurality of fixed points output by the imageJ, finds out the correspondence between the reflectance values and the gray values, and expresses the relationship between the reflectance values and the gray values by means of a functional expression. By fitting the reflectivity values and the gray values of the fixed points, a corresponding functional relationship between the reflectivity values and the gray values can be obtained, wherein R% = k×i+b, wherein R% represents the reflectivity value, i represents the gray 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. Wherein the fitting means 40 may comprise a function mapping software such as an origin.
In one embodiment of the invention, the first computing device 50 is used to calculate reflectance values for each point of the cell to be tested and the comparison cell. imageJ reads the reflectance values and gray values of a plurality of fixed points, and obtains the function relationship between the reflectance values and gray values through the fitting device 40, so that the reflectance values can be calculated according to the gray values of any point of the battery to be detected or the comparison battery. For example, a point is arbitrarily found on the gray scale of the RGB image, the imageJ reads the gray scale value of the point according to the coordinates of the point, and substitutes the gray scale value of the point into the correspondence between the reflectance value and the gray scale value to obtain the reflectance value of the point.
In one embodiment of the present invention, the second calculating device 60 is configured to calculate a difference between the reflectivity values of the corresponding points of the battery to be detected and the comparison battery, and the thickness of the oxide layer at any point on the surface of the battery to be detected and the reflectivity difference at that point are in positive correlation, where a larger difference indicates a thicker oxide layer thickness, and the distribution of the reflectivity difference can be represented as the distribution of the oxide layer thickness.
According to the method for detecting the thickness distribution of the oxide layer on the surface of the battery, disclosed by the embodiment of the invention, the RGB image of the battery is output through the reflectivity detector, and the oxide layer thickness is represented into the reflectivity in an image processing and data fitting mode, so that the thickness distribution of the oxide layer on the surface of the battery is obtained, and the thickness distribution condition of the oxide layer on the surface of the battery can be conveniently and intuitively known.
In the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The meaning of "a plurality of" is two or more, unless specifically defined otherwise.
In the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally formed, mechanically connected, electrically connected, directly connected, indirectly connected via an intervening medium, or in communication between two elements or in an interaction relationship between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
In the present invention, unless expressly stated or limited otherwise, a first feature "up" or "down" a second feature may be the first and second features in direct contact, or the first and second features in indirect contact via an intervening medium. Moreover, a first feature being "above," "over" and "on" a second feature may be a first feature being directly above or obliquely above the second feature, or simply indicating that the first feature is level higher than the second feature. The first feature being "under", "below" and "beneath" the second feature may be the first feature being directly under or obliquely below the second feature, or simply indicating that the first feature is less level than the second feature.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily for the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include an electrical connection (an electronic device) having one or more wires, a portable computer diskette (a magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of techniques known in the art, discrete logic circuits with logic gates for implementing logic functions on data signals, application specific integrated circuits with appropriate combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.