A method and system for quality detection and analysis of an ultra-thin aluminum foil for lithium batteries

Abstract

The application discloses a kind of quality detection analysis methods and systems of ultra-thin lithium battery aluminum foil, it is related to image processing technical field, including image shooting equipment according to image shooting parameter is to the aluminum foil of detection to image acquisition processing, obtains the aluminum foil image of analysis;Image analysis processing is carried out to the aluminum foil image of analysis, determines aluminum foil surface abnormal area.The application sets the aluminum foil of best performance test as control group, and the spectrum analysis is carried out to the aluminum foil image of analysis, determines whether the spectrum of the aluminum foil image of analysis exists abnormal, if the spectrum of the aluminum foil image of analysis exists abnormal, then it indicates that the aluminum foil surface of detection exists abnormal, finally, the abnormal area of the aluminum foil surface of detection is compared and judged, determines whether the quality of the aluminum foil of detection meets standard, the above-mentioned mode avoids that aluminum foil with abnormal surface is directly put into use, improves the quality of lithium ion battery, also, prolongs the service life of lithium ion battery.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, specifically to a method and system for quality inspection and analysis of aluminum foil for ultra-thin lithium batteries. Background Technology

[0002] Aluminum foil is a thin sheet material made by directly rolling metallic aluminum. Because its hot stamping effect is similar to that of pure silver foil, it is also known as "fake silver foil". Aluminum foil is mainly used in the packaging industry, electronics and electrical appliances, construction and automobiles.

[0003] Aluminum foil for ultra-thin lithium batteries is a core material for the positive electrode current collector of lithium-ion batteries.

[0004] Since aluminum foil is used as the positive electrode material for lithium-ion batteries, using aluminum foil with abnormalities on its surface as the positive electrode material for lithium-ion batteries will reduce the quality of the lithium-ion batteries and also reduce their lifespan. Summary of the Invention

[0005] To address the aforementioned technical problems, a quality inspection and analysis method and system for ultra-thin aluminum foil used in lithium batteries is provided. This technical solution solves the problem mentioned in the background art that if aluminum foil with abnormal surface is used as the positive electrode material of a lithium-ion battery, the quality of the lithium-ion battery will be reduced, and at the same time, the service life of the lithium-ion battery will also be reduced.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries includes: The image acquisition device acquires and processes images of the aluminum foil to be inspected based on the image acquisition parameters, thereby obtaining an image of the aluminum foil to be analyzed. Image analysis processing is performed on the aluminum foil image to be analyzed to determine the area of ​​abnormality on the aluminum foil surface; Comparative analysis of abnormal areas on the surface of aluminum foil is performed to determine the quality of the aluminum foil. The image analysis processing of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: Based on the Fast Fourier Transform algorithm, frequency domain transformation processing is performed on the aluminum foil image with the best performance and the aluminum foil image to be analyzed to obtain the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed. Data analysis and processing are performed on the factory parameters of the image capturing equipment to determine the type of noise that will be generated in the captured images; The noise types generated by the captured images are analyzed to determine the noise frequency range, and a bandpass filter is set according to the noise frequency range. Based on a bandpass filter, noise reduction processing is performed on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, respectively. The spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed are calculated and processed to determine the abnormal area on the aluminum foil surface.

[0007] Preferably, the image capturing device performs image acquisition and processing on the aluminum foil to be detected according to the image capturing parameters to obtain the image of the aluminum foil to be analyzed, specifically including the following steps: Obtain data for all aluminum foils that have completed performance testing; All aluminum foil data that have completed performance testing are filtered to determine the aluminum foil data with the best performance. Data is read and processed from the aluminum foil with the best performance in the test to determine the aluminum foil number with the best performance. The database system is used to read and process data based on the aluminum foil number that performed best in the performance test, in order to obtain relevant data on the aluminum foil that performed best in the performance test. Data related to the aluminum foil with the best performance test is read and processed to determine the image shooting parameters and image shooting equipment; The parameters of the image capturing device are adjusted according to the image capturing parameters, and the image of the aluminum foil to be detected is captured and processed to obtain the image of the aluminum foil to be analyzed.

[0008] Preferably, the process of reading and processing the data related to the aluminum foil with the best performance in the test to determine the image capturing parameters and the image capturing device specifically includes the following steps: Data reading and processing were performed on the aluminum foil with the best performance in the test, and images of the aluminum foil with the best performance and the image capturing equipment were obtained. Data reading and processing are performed on the aluminum foil image with the best performance to obtain image shooting parameters; wherein the image shooting parameters include focal length data, field of view data, and image shooting background.

[0009] Preferably, the step of calculating and analyzing the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: Data reading and processing were performed on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, respectively, to obtain the amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed; The amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed are subtracted to determine whether there is an abnormal spectrum in the aluminum foil image to be analyzed; wherein, the subtraction calculation is performed on the amplitude values ​​of the same phase of the reference aluminum foil image and the aluminum foil image to be analyzed. If there are no abnormal spectra in the aluminum foil image to be analyzed, then the quality of the aluminum foil to be tested meets the standard; If there are abnormal spectra in the aluminum foil image to be analyzed, perform function calculations on the abnormal spectra to determine the abnormal area on the aluminum foil surface.

[0010] Preferably, the step of performing function calculations on the abnormal spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: The abnormal spectrum of the aluminum foil image to be analyzed is subjected to function matching processing to determine the frequency domain function corresponding to the abnormal spectrum; Based on the inverse Fourier transform algorithm, the frequency domain function corresponding to the abnormal spectrum is transformed into the time domain to determine the time domain function corresponding to the abnormal spectrum. The time-domain function corresponding to the abnormal spectrum is calculated to determine the abnormal area on the aluminum foil surface.

[0011] Preferably, the step of calculating the time-domain function corresponding to the abnormal spectrum to determine the abnormal area on the aluminum foil surface specifically includes the following steps: Based on the time-domain function corresponding to the abnormal spectrum, image plotting is performed in a rectangular coordinate system to obtain the image of the time-domain function corresponding to the abnormal spectrum; Shape and range analysis are performed on the time-domain function image corresponding to the abnormal spectrum to determine the shape of the time-domain function image and the range of the time-domain function. The abnormal area on the aluminum foil surface is obtained by performing integral calculation on the time-domain function image corresponding to the abnormal spectrum based on the shape of the time-domain function image and the range of the time-domain function.

[0012] Preferably, the step of comparing and analyzing the abnormal areas on the aluminum foil surface to determine the quality of the aluminum foil specifically includes the following steps: Judgment and processing of abnormal area on aluminum foil surface and set abnormal area threshold; If the abnormal area on the surface of the aluminum foil is greater than or equal to the set abnormal area threshold, the quality of the aluminum foil to be tested does not meet the standard. If the abnormal area on the aluminum foil surface is less than the set abnormal area threshold, the quality of the aluminum foil to be tested meets the standard.

[0013] Furthermore, a quality inspection and analysis system for ultra-thin aluminum foil used in lithium batteries is proposed to implement the quality inspection and analysis method for ultra-thin aluminum foil used in lithium batteries as described above, including: The intelligent analysis terminal controls various modules to perform image acquisition and processing, image spectrum analysis, function matching processing, and function calculation analysis on the aluminum foil to be inspected, in order to determine whether the quality of the aluminum foil to be inspected meets the standards; the intelligent analysis terminal also controls data transmission and information interaction between the various modules. A database system for storing all aluminum foil data that has completed performance testing and related data on the aluminum foil with the best performance. The data reading module and the data analysis module are used to perform data analysis and processing on all aluminum foil data that have completed performance testing and the relevant data of the aluminum foil with the best performance testing, and to determine the image capturing parameters. An image capturing device, wherein the image capturing device is used to acquire and process images of the aluminum foil to be inspected; The image analysis module is used to perform frequency domain analysis on the aluminum foil image to be analyzed, and to determine the frequency domain function corresponding to the abnormal spectrum; An area calculation module is used to perform time-domain transformation and integral calculation on the frequency domain function corresponding to the abnormal spectrum to determine the abnormal area of ​​the aluminum foil surface. The comparison and judgment module is used to judge the abnormal area on the surface of the aluminum foil and the set abnormal area threshold to determine whether the quality of the aluminum foil to be tested meets the standard.

[0014] Compared with the prior art, the present invention provides a quality inspection and analysis method and system for ultra-thin aluminum foil for lithium batteries, which has the following beneficial effects: This invention sets the aluminum foil with the best performance in the test as a control group and performs spectral analysis on the image of the aluminum foil to be analyzed to determine whether there are any abnormalities in the spectrum of the image. If there are abnormalities in the spectrum of the image, it indicates that there are abnormalities on the surface of the aluminum foil to be tested. Finally, the abnormal area on the surface of the aluminum foil to be tested is compared and judged to determine whether the quality of the aluminum foil to be tested meets the standard. The above method avoids the direct use of aluminum foil with abnormal surfaces, improves the quality of lithium-ion batteries, and also extends the service life of lithium-ion batteries. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating steps S100-S300 in a quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries proposed in this invention. Figure 2 This is a structural block diagram of a quality inspection and analysis system for ultra-thin aluminum foil used in lithium batteries proposed in this invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, a quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries includes: S100: The image capturing device performs image acquisition and processing on the aluminum foil to be detected according to the image capturing parameters, and obtains the image of the aluminum foil to be analyzed. S200. Perform image analysis processing on the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface; S300. Compare and analyze the abnormal areas on the surface of the aluminum foil to determine the quality of the aluminum foil. Those skilled in the art will understand that the positive electrode of a lithium-ion battery is extremely thin, and electrons must flow through it. Therefore, if there is an abnormality in the positive electrode, the electron flow rate will be reduced. When there are too many electrons, they will accumulate at the positive electrode, indirectly increasing the temperature of the positive electrode. When the temperature of the positive electrode is too high, it will damage the positive electrode, rendering the lithium-ion battery unusable. Therefore, in order to extend the service life of lithium-ion batteries, image processing is used to analyze the surface of aluminum foil to determine whether there are any abnormalities. The abnormalities are then assessed to determine whether aluminum foil with surface abnormalities can be used, thereby indirectly improving the quality of the produced lithium-ion batteries. Specifically, S200, image analysis processing of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface, includes the following steps: S201. Based on the Fast Fourier Transform algorithm, frequency domain transformation processing is performed on the aluminum foil image with the best performance test and the aluminum foil image to be analyzed to obtain the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed. It is understandable that visually inspecting the surface of aluminum foil to determine whether there are any abnormalities could increase the false positive rate for a period of time. This is because the attention span of inspectors decreases over long periods of work, which in turn increases the error rate during that time. However, by acquiring images of the aluminum foil to be inspected and then performing frequency domain analysis to compare and analyze the image spectra, the difference between the spectrum of the inspected group and the control group can be determined. This difference in spectrum indicates that there are abnormalities on the surface of the aluminum foil to be inspected, thus improving the accuracy of aluminum foil anomaly detection. S202. Perform data analysis and processing on the factory parameters of the image capturing device to determine the type of noise that will be generated in the captured image; S203. Perform type analysis on the noise types generated by the captured images, determine the noise frequency range, and set a bandpass filter according to the noise frequency range. S204. Based on the bandpass filter, the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed are denoised respectively. It is understandable that bandpass filters can remove noise at different frequencies. By simply designing the internal frequency parameters of the bandpass filter, different types of noise can be removed. Therefore, instead of designing just one bandpass filter, multiple bandpass filters are designed, each with different internal parameters, to remove different types of noise. This achieves comprehensive denoising of the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, reducing the impact of noise on subsequent analysis and indirectly improving the accuracy of subsequent analysis. S205. Perform calculation and analysis on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface; It is understandable that when different imaging devices are used to photograph the same object, the types of noise in the resulting images may differ. Different noise types require different bandpass filters, which may lead to differences in the spectrum between the image of the aluminum foil to be analyzed and the control group image. If the surface of the aluminum foil to be tested is not abnormal, but the amplitude values ​​of certain phases of the image of the aluminum foil to be analyzed differ from those of the control group due to the use of different bandpass filters, it will be misjudged as having an abnormality on the surface of the aluminum foil, indirectly increasing the scrap rate and production costs. Therefore, when using the same imaging device to photograph different objects, even if the objects have some differences, the types of noise in the captured images are the same, so denoising them with the same bandpass filter will not produce any differences.

[0018] Example 1 S100. The image acquisition device performs image acquisition and processing on the aluminum foil to be detected according to the image acquisition parameters to obtain the image of the aluminum foil to be analyzed. The specific steps include the following: S101. Obtain data for all aluminum foils that have completed performance tests; It is understandable that the aluminum foil for which performance testing has been completed is different from the aluminum foil to be tested; S102. Screen all aluminum foil data that have completed performance testing to determine the aluminum foil data with the best performance. Understandably, the aluminum foil with the best performance test data among all the aluminum foils that have completed performance tests represents the aluminum foil with the best quality, and the positive electrode of the lithium battery produced using the aluminum foil is also of the best quality. Therefore, in order to improve the quality of the positive electrode produced for lithium-ion batteries, the aluminum foil to be tested is screened by using the aluminum foil with the best performance test data. S103. Read and process the data of the aluminum foil with the best performance test, and determine the aluminum foil number with the best performance test. S104. Based on the aluminum foil number with the best performance in the performance test, perform data reading and processing on the database system to obtain relevant data of the aluminum foil with the best performance in the performance test; S105. Read and process the relevant data of the aluminum foil with the best performance test to determine the image shooting parameters and image shooting equipment; It is understandable that when determining the quality of aluminum foil to be inspected through image processing, a control group needs to be set up. This is because without a control group, it is impossible to determine whether there are any abnormalities on the surface of the aluminum foil to be inspected. The control group should also be image data. Therefore, the parameters of the acquired images of the aluminum foil to be inspected should be consistent with those of the control group images. Otherwise, it will be impossible to determine whether there are any abnormalities on the surface of the aluminum foil to be inspected by performing quality analysis on the acquired images. Therefore, it is necessary to analyze the images of the control group to determine the imaging equipment, the shooting background, and the shooting parameters used when taking the images of the control group. S105. Adjust the parameters of the image capturing device according to the image capturing parameters, and perform image capturing and processing on the aluminum foil to be detected to obtain the image of the aluminum foil to be analyzed.

[0019] Specifically, S105 involves reading and processing the data related to the aluminum foil with the best performance in the test to determine the image capturing parameters and the image capturing equipment, including the following steps: S1051. Read and process the relevant data of the aluminum foil with the best performance test, and obtain the image of the aluminum foil with the best performance test and the image capturing device. S1052. Perform data reading and processing on the aluminum foil image with the best performance test to obtain image shooting parameters; wherein the image shooting parameters include focal length data, field of view data, and image shooting background. It is understandable that if the image capture parameters of the aluminum foil to be detected are inconsistent with the capture background and the parameters of the aluminum foil image with the best performance test, it is impossible to determine the abnormality of the aluminum foil surface to be detected. This is because if the capture background and image capture parameters of the two images are inconsistent, the amplitude values ​​at the same phase may be different if the aluminum foil to be detected is normal. Therefore, in order to ensure the normal analysis of subsequent anomalies, it is necessary to set the same image capture parameters and image capture background.

[0020] Example 2 S205. Calculate and analyze the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface. This specifically includes the following steps: S2051. Perform data reading and processing on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, respectively, to obtain the amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed. S2052. Perform a difference calculation on the amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed to determine whether there is an abnormal spectrum in the aluminum foil image to be analyzed; wherein, the difference calculation is performed on the amplitude values ​​of the same phase of the reference aluminum foil image and the aluminum foil image to be analyzed. S2053. If there is no abnormal spectrum in the aluminum foil image to be analyzed, then the quality of the aluminum foil to be tested meets the standard. S2054. If there is an abnormal spectrum in the aluminum foil image to be analyzed, perform function calculation on the abnormal spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface. It is understandable that when there are abnormalities on the surface of the aluminum foil to be tested, the images of the aluminum foil to be analyzed will differ from those of the control group. This is because the production process of aluminum foil is the same. If no abnormalities occur during the production process, the produced aluminum foil should be identical, and the images captured will also be identical, resulting in identical image spectra. Therefore, the presence of abnormalities in the image of the aluminum foil to be analyzed can be determined by calculating the image spectrum. It is worth noting that the amplitude values ​​of the same phase are calculated during the spectrum calculation. That is, the phase of the aluminum foil image to be analyzed is the same as the phase of the reference aluminum foil image. Then, the difference between the amplitude values ​​of the same phase is calculated. If the difference is zero, it means that there are no abnormalities on the surface of the aluminum foil to be tested. If the difference is not zero, it means that there are abnormalities on the surface of the aluminum foil to be tested. However, during the aluminum foil production process, it is impossible to guarantee that every aluminum foil surface will be free of abnormalities. Aluminum foil with a small area of ​​abnormality on the surface can still be used normally. Therefore, it is necessary to judge the area of ​​abnormality on the aluminum foil surface to determine whether the aluminum foil to be tested meets the standard. Specifically, S2054, performing function calculations on the abnormal spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface, includes the following steps: S20541. Perform function matching processing on the abnormal spectrum of the aluminum foil image to be analyzed to determine the frequency domain function corresponding to the abnormal spectrum; S20542. Based on the inverse Fourier transform algorithm, the frequency domain function corresponding to the abnormal spectrum is transformed into the time domain to determine the time domain function corresponding to the abnormal spectrum. S20543. Calculate and process the time-domain function corresponding to the abnormal spectrum to determine the abnormal area on the aluminum foil surface; It is understandable that when there is an anomaly on the surface of the aluminum foil to be detected, the spectrum of its image will differ from that of the reference aluminum foil image. When this difference is calculated, the difference between the aluminum foil to be detected and the reference aluminum foil can be obtained. This difference is reflected in the frequency domain through the spectral difference. After determining the spectral difference, a type analysis is performed to determine the corresponding spectral function. Finally, the spectral function is converted into the corresponding time domain function through the inverse Fourier transform algorithm. Calculating the time domain function will yield the corresponding area of ​​the aluminum foil surface anomaly. Specifically, S20543, calculating and processing the time-domain function corresponding to the abnormal spectrum to determine the abnormal area on the aluminum foil surface includes the following steps: S205431. Based on the time-domain function corresponding to the abnormal spectrum, perform image plotting in a rectangular coordinate system to obtain the image of the time-domain function corresponding to the abnormal spectrum; S205432. Perform shape analysis and range analysis on the time-domain function image corresponding to the abnormal spectrum to determine the shape of the time-domain function image and the range of the time-domain function. S205433. Based on the shape of the time-domain function image and the range of the time-domain function, perform integral calculation on the time-domain function image corresponding to the abnormal spectrum to obtain the abnormal area on the aluminum foil surface. It is understandable that abnormal shapes can be described by functions, and the area of ​​abnormal shapes can also be determined by calculating the function. Therefore, by plotting the time-domain function image corresponding to the abnormal spectrum and performing integration, the area enclosed by the function can be determined. This area is the abnormal area of ​​the aluminum foil surface. Not all aluminum foils with surface abnormalities are unusable. In most scientific fields, an error range is set, and product data within this error range is usable. Therefore, by comparing and judging the abnormal area of ​​the aluminum foil surface, it can be determined whether the quality of the aluminum foil to be tested meets the standard.

[0021] Example 3 S300. Comparative analysis of abnormal areas on the aluminum foil surface is performed to determine the quality of the aluminum foil. Specific steps include the following: S301. Judge and process the abnormal area of ​​the aluminum foil surface and the set abnormal area threshold. S302. If the abnormal area on the surface of the aluminum foil is greater than or equal to the set abnormal area threshold, the quality of the aluminum foil to be tested does not meet the standard. S303. If the abnormal area on the surface of the aluminum foil is less than the set abnormal area threshold, the quality of the aluminum foil to be tested meets the standard. Understandably, not all aluminum foil with abnormalities is unusable. During the experimental design process, an error parameter is set for the aluminum foil. If the abnormal area is within this parameter range, the foil can be used normally. If the abnormal area is outside this range, the foil is unusable. Even if used, its lifespan or the speed of electron movement is slower than normal foil. This leads to a slower discharge rate in lithium-ion batteries and may even cause overheating of the positive electrode. A large accumulation of electrons in one location raises the temperature at that point, shortening the battery's lifespan. Therefore, aluminum foil with abnormal areas that do not meet the standards needs to be discarded, ensuring that all materials used in the positive electrode of lithium-ion batteries meet the standards, thus indirectly improving the quality of lithium-ion batteries.

[0022] Reference Figure 2 As shown, a quality inspection and analysis system for ultra-thin aluminum foil for lithium batteries is used to implement the quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries as described above, including: The intelligent analysis terminal controls various modules to perform image acquisition and processing, image spectrum analysis, function matching processing, and function calculation analysis on the aluminum foil to be inspected, in order to determine whether the quality of the aluminum foil to be inspected meets the standards; the intelligent analysis terminal also controls data transmission and information interaction between the various modules. A database system for storing all aluminum foil data that has completed performance testing and related data on the aluminum foil with the best performance. The data reading module and the data analysis module are used to perform data analysis and processing on all aluminum foil data that have completed performance testing and the relevant data of the aluminum foil with the best performance testing, and to determine the image capturing parameters. An image capturing device, wherein the image capturing device is used to acquire and process images of the aluminum foil to be inspected; The image analysis module is used to perform frequency domain analysis on the aluminum foil image to be analyzed, and to determine the frequency domain function corresponding to the abnormal spectrum; An area calculation module is used to perform time-domain transformation and integral calculation on the frequency domain function corresponding to the abnormal spectrum to determine the abnormal area of ​​the aluminum foil surface. The comparison and judgment module is used to judge the abnormal area on the surface of the aluminum foil and the set abnormal area threshold to determine whether the quality of the aluminum foil to be tested meets the standard.

[0023] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for quality inspection and analysis of aluminum foil for ultra-thin lithium batteries, characterized in that, include: The image acquisition device acquires and processes images of the aluminum foil to be inspected based on the image acquisition parameters, thereby obtaining an image of the aluminum foil to be analyzed. Image analysis processing is performed on the aluminum foil image to be analyzed to determine the area of ​​abnormality on the aluminum foil surface; Comparative analysis of abnormal areas on the surface of aluminum foil is performed to determine the quality of the aluminum foil. The image analysis and processing of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: Based on the Fast Fourier Transform algorithm, frequency domain transformation processing is performed on the aluminum foil image with the best performance and the aluminum foil image to be analyzed to obtain the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed. Data analysis and processing are performed on the factory parameters of the image capturing equipment to determine the type of noise that will be generated in the captured images; The noise types generated by the captured images are analyzed to determine the noise frequency range, and a bandpass filter is set according to the noise frequency range. Based on a bandpass filter, noise reduction processing is performed on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, respectively. The spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed are calculated and processed to determine the abnormal area on the aluminum foil surface; The process of calculating and analyzing the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: Data reading and processing were performed on the spectrum of the reference aluminum foil image and the spectrum of the aluminum foil image to be analyzed, respectively, to obtain the amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed; The amplitude values ​​of different phases of the reference aluminum foil image and the amplitude values ​​of different phases of the aluminum foil image to be analyzed are subtracted to determine whether there is an abnormal spectrum in the aluminum foil image to be analyzed; wherein, the subtraction calculation is performed on the amplitude values ​​of the same phase of the reference aluminum foil image and the aluminum foil image to be analyzed. If there are no abnormal spectra in the aluminum foil image to be analyzed, then the quality of the aluminum foil to be tested meets the standard; If there are abnormal spectra in the aluminum foil image to be analyzed, perform function calculations on the abnormal spectra of the aluminum foil image to determine the abnormal area on the aluminum foil surface. The process of performing function calculations on the abnormal spectrum of the aluminum foil image to be analyzed to determine the abnormal area on the aluminum foil surface specifically includes the following steps: The abnormal spectrum of the aluminum foil image to be analyzed is subjected to function matching processing to determine the frequency domain function corresponding to the abnormal spectrum; Based on the inverse Fourier transform algorithm, the frequency domain function corresponding to the abnormal spectrum is transformed into the time domain to determine the time domain function corresponding to the abnormal spectrum. The time-domain function corresponding to the abnormal spectrum is calculated to determine the abnormal area on the aluminum foil surface; The process of calculating the time-domain function corresponding to the abnormal spectrum to determine the abnormal area on the aluminum foil surface includes the following steps: Based on the time-domain function corresponding to the abnormal spectrum, image plotting is performed in a rectangular coordinate system to obtain the image of the time-domain function corresponding to the abnormal spectrum; Shape and range analysis are performed on the time-domain function image corresponding to the abnormal spectrum to determine the shape of the time-domain function image and the range of the time-domain function. The abnormal area on the aluminum foil surface is obtained by performing integral calculation on the time-domain function image corresponding to the abnormal spectrum based on the shape of the time-domain function image and the range of the time-domain function.

2. The quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries according to claim 1, characterized in that, The image capturing device acquires and processes images of the aluminum foil to be detected according to image capturing parameters, and the specific steps for obtaining the image of the aluminum foil to be analyzed include the following: Obtain data for all aluminum foils that have completed performance testing; All aluminum foil data that have completed performance testing are filtered to determine the aluminum foil data with the best performance. Data is read and processed from the aluminum foil with the best performance in the test to determine the aluminum foil number with the best performance. The database system is used to read and process data based on the aluminum foil number that performed best in the performance test, in order to obtain relevant data on the aluminum foil that performed best in the performance test. Data related to the aluminum foil with the best performance test is read and processed to determine the image shooting parameters and image shooting equipment; The parameters of the image capturing device are adjusted according to the image capturing parameters, and the image of the aluminum foil to be detected is captured and processed to obtain the image of the aluminum foil to be analyzed.

3. The quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries according to claim 2, characterized in that, The process of reading and processing the data related to the aluminum foil with the best performance test to determine the image capturing parameters and the image capturing device includes the following steps: Data reading and processing were performed on the aluminum foil with the best performance in the test, and images of the aluminum foil with the best performance and the image capturing equipment were obtained. Data reading and processing are performed on the aluminum foil image with the best performance to obtain image shooting parameters; wherein the image shooting parameters include focal length data, field of view data, and image shooting background.

4. The quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries according to claim 1, characterized in that, The process of comparing and analyzing abnormal areas on the aluminum foil surface to determine the quality of the aluminum foil includes the following steps: Judgment and processing of abnormal area on aluminum foil surface and set abnormal area threshold; If the abnormal area on the surface of the aluminum foil is greater than or equal to the set abnormal area threshold, the quality of the aluminum foil to be tested does not meet the standard. If the abnormal area on the aluminum foil surface is less than the set abnormal area threshold, the quality of the aluminum foil to be tested meets the standard.

5. A quality inspection and analysis system for ultra-thin aluminum foil for lithium batteries, used to implement the quality inspection and analysis method for ultra-thin aluminum foil for lithium batteries as described in any one of claims 1-4, characterized in that, include: The intelligent analysis terminal controls various modules to perform image acquisition and processing, image spectrum analysis, function matching processing, and function calculation analysis on the aluminum foil to be inspected, in order to determine whether the quality of the aluminum foil to be inspected meets the standards; the intelligent analysis terminal also controls data transmission and information interaction between the various modules. A database system for storing all aluminum foil data that has completed performance testing and related data on the aluminum foil with the best performance. The data reading module is used to perform data analysis and processing on all aluminum foil data that have completed performance testing and the relevant data of the aluminum foil with the best performance test, and to determine the image shooting parameters. An image capturing device, wherein the image capturing device is used to acquire and process images of the aluminum foil to be inspected; The image analysis module is used to perform frequency domain analysis on the aluminum foil image to be analyzed, and to determine the frequency domain function corresponding to the abnormal spectrum; An area calculation module is used to perform time-domain transformation and integral calculation on the frequency domain function corresponding to the abnormal spectrum to determine the abnormal area of ​​the aluminum foil surface. The comparison and judgment module is used to judge the abnormal area on the surface of the aluminum foil and the set abnormal area threshold to determine whether the quality of the aluminum foil to be tested meets the standard.

Images