Slurry bubble testing method and device, storage medium and electronic equipment

Abstract

The invention discloses a slurry bubble testing method and device, a storage medium and electronic equipment. The method comprises the steps that image collection is conducted on a target PE plate, an initial image is obtained, the target PE plate is a PE plate soaked into slurry to be detected in advance, and bubbles are distributed on the surface of the target PE plate; determining the bubble density on the target PE plate based on the initial image; according to the bubble density, the bubble state test result of the to-be-tested slurry is determined, the bubble state test result is used for indicating the potential defect risk of the to-be-tested slurry in the coating process, and the coating process is the process of uniformly coating the to-be-tested slurry to the battery metal foil. The technical problem that the potential defect risk in the slurry coating process is difficult to identify effectively is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery, in particular to a slurry bubble testing method and device, a storage medium and an electronic device. BACKGROUND

[0002] In the field of new energy vehicles, especially in the manufacturing process of lithium ion batteries, slurry coating is a crucial link, which directly affects the performance and safety of the battery cell. Silicon-carbon negative electrode material, as one of the preferred materials for the next generation of high energy density batteries, has a complex processing technology and is sensitive to temperature, which is prone to produce bubbles. The existence of bubbles will lead to foil leakage and other defects in the coating process, which seriously reduces the electrical performance and service life of the battery. However, the slurry quality control method in the related art mainly relies on manual visual inspection or experience judgment, and lacks accurate quantitative analysis of the bubble distribution state in the slurry, making it difficult to accurately assess the impact of bubbles on the subsequent coating process. In addition, since the generation of bubbles is related to many factors such as the composition of the slurry, the processing conditions and the storage time, the evaluation method in the related art cannot monitor the changes in the state of the slurry in real time, and it is difficult to discover and solve the problem of bubble residual abnormalities in a timely manner during the production process. Therefore, the related art has great limitations in identifying potential defect risks in the slurry coating process, especially in the double-screw slurry production of high-silicon negative electrode materials, the generation and impact of bubbles are particularly significant, and the potential defect risks in the slurry coating process are difficult to effectively identify.

[0003] At present, there is no effective solution to the above problems. SUMMARY

[0004] The embodiments of the present application provide a slurry bubble testing method, device, storage medium and electronic device to at least solve the technical problem that potential defect risks in the slurry coating process are difficult to effectively identify.

[0005] According to an aspect of the embodiments of the present application, a slurry bubble testing method is provided, comprising: image acquisition on a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate pre-immersed in a to-be-tested slurry, and the target PE plate surface is distributed with bubbles; determining the bubble density on the target PE plate based on the initial image; and determining a bubble state test result of the to-be-tested slurry according to the bubble density, wherein the bubble state test result is used to indicate the potential defect risk of the to-be-tested slurry in the coating process, and the coating process is the process of uniformly coating the to-be-tested slurry to the battery metal foil.

[0006] Optionally, the bubble density on the target PE plate is determined based on the initial image, comprising: performing binaryzation processing on the initial image to obtain a binaryzation image; identifying the total number of bubbles on the target PE plate based on the binaryzation image; and determining the bubble density based on the total number of bubbles and the size information of the target PE plate.

[0007] By the above method, the total number and density of the bubbles are accurately calculated by using image binarization processing and counting algorithm combined with the size information of the PE plate, which can significantly improve the accuracy and reliability of bubble detection.

[0008] Optionally, according to the bubble density, the bubble state test result of the to-be-tested slurry is determined, including: determining a bubble distribution score according to the bubble density; in a case where the bubble distribution score is greater than a preset score threshold, determining that the bubble state test result is that the to-be-tested slurry has a potential defect risk in the coating process; or in a case where the bubble distribution score is less than or equal to the preset score threshold, determining that the bubble state test result is that the to-be-tested slurry does not have a potential defect risk in the coating process.

[0009] By the above method, a threshold is set according to the bubble density to provide a method for quantitatively evaluating the bubble state of the slurry, the potential defect risk of the slurry in the coating process is judged through the scoring system, which provides a scientific basis for dynamic monitoring and real-time adjustment of the slurry formula, makes the slurry quality control more scientific and accurate, helps to improve the yield and consistency of battery manufacturing, reduces production cost, and strengthens the safety and reliability of the battery.

[0010] Optionally, the bubble distribution score is determined according to the bubble density, including: determining the bubble size distribution, the bubble aggregation degree, and the bubble distribution uniformity on the target PE plate based on the initial image; and determining the bubble distribution score based on the bubble density, the bubble size distribution, the bubble aggregation degree, and the bubble distribution uniformity.

[0011] By the above method, the size distribution, aggregation degree, and distribution uniformity of the bubbles are comprehensively considered together with the bubble density to calculate the bubble distribution score, which can realize comprehensive evaluation of the bubble characteristics and enhance the objectivity and accuracy of the evaluation result.

[0012] Optionally, the bubble distribution score of the target PE plate is determined based on the bubble density, the bubble size distribution, the bubble aggregation degree, and the bubble distribution uniformity, including: determining a first weight corresponding to the bubble density, a second weight corresponding to the bubble size distribution, a third weight corresponding to the bubble aggregation degree, and a fourth weight corresponding to the bubble distribution uniformity; and determining the bubble distribution score based on the bubble density, the bubble size distribution, the bubble aggregation degree, the bubble distribution uniformity, the first weight, the second weight, the third weight, and the fourth weight.

[0013] By the above method, the relative importance of the bubble density, size distribution, aggregation degree, and distribution uniformity in the scoring is established, and the bubble distribution score determined by weighting can more comprehensively evaluate the stability and risk of the slurry in the coating process, so that the evaluation standard is more in line with the actual production demand.

[0014] Optionally, in a case that the initial image includes multiple, the corresponding bubble density is multiple, and the multiple initial images correspond to the multiple sampling time points one by one, the bubble distribution score is determined according to the bubble density, including: determining a weight value corresponding to each of the multiple bubble densities, wherein the weight value is inversely proportional to the sampling time point of the initial image corresponding to the bubble density; and obtaining the bubble distribution score based on the multiple bubble densities and the weight values corresponding to the multiple bubble densities.

[0015] In the above manner, the time dimension is introduced to determine the bubble distribution score, which can realize dynamic monitoring and scoring of the bubble state of the slurry, can reveal the law of bubble evolution over time, and can evaluate the stability and potential defect risk of the slurry in the coating process. Especially in the scenario that the bubble of the slurry may change after being placed for a period of time, it can provide strong data support for real-time adjustment of the production process and long-term control of the slurry quality, thereby improving the coating effect and product quality.

[0016] According to another aspect of the embodiments of the present application, a slurry bubble testing device is also provided, including: an image acquisition module configured to acquire an image of a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate pre-immersed in a to-be-tested slurry, and the target PE plate has bubbles distributed on the surface thereof; a bubble density determination module configured to determine a bubble density on the target PE plate based on the initial image; and a bubble state testing module configured to determine a bubble state testing result of the to-be-tested slurry according to the bubble density, wherein the bubble state testing result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry on a battery metal foil.

[0017] According to another aspect of the embodiments of the present application, a non-volatile storage medium is also provided, which stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement any one of the slurry bubble testing methods.

[0018] According to another aspect of the embodiments of the present application, an electronic device is also provided, which includes one or more processors and a memory, and the memory is configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement any one of the slurry bubble testing methods.

[0019] According to another aspect of the embodiments of the present application, a computer program product is also provided, which includes a computer program, and the computer program is executed by a processor to implement the steps of any one of the slurry bubble testing methods.

[0020] In the embodiment of the present application, the initial image is obtained by image acquisition of the target polyethylene (PE) plate, wherein the target PE plate is a PE plate immersed in the to-be-tested slurry in advance, and the target PE plate surface is distributed with bubbles; the bubble density on the target PE plate is determined based on the initial image; and the bubble state test result of the to-be-tested slurry is determined according to the bubble density, wherein the bubble state test result is used to indicate the potential defect risk of the to-be-tested slurry in the coating process, and the coating process is a process of uniformly coating the to-be-tested slurry to the battery metal foil. The purpose of accurately evaluating the bubble state of the slurry is achieved by collecting the image of the surface bubbles of the PE plate immersed in the slurry in advance and analyzing the bubble density, so as to realize the accurate evaluation of the bubble state of the slurry, effectively predict and reduce the defects (such as missing foil) in the coating process of the battery metal foil, optimize the slurry quality and coating process, and improve the overall performance and production yield of the battery, thereby solving the technical problem that the potential defect risk in the slurry coating process is difficult to be effectively identified. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings, which are included to provide a further understanding of the present application and constitute a part of this application, illustrate certain illustrative embodiments of the present application and show the features of the present application, and do not limit the present application. In the drawings:

[0022] Figure 1 is a flowchart of a slurry bubble test method according to an embodiment of the present application;

[0023] Figure 2 is a flowchart of an optional slurry bubble test method according to an embodiment of the present application;

[0024] Figure 3 is a schematic diagram of a slurry bubble test device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0027] According to an embodiment of the present application, a method embodiment of slurry bubble testing is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0028] Figure 1 is a flowchart of a slurry bubble testing method according to an embodiment of the present application, as Figure 1 shown, the method comprises the following steps:

[0029] Step S102, image acquisition is performed on the target PE plate to obtain an initial image, wherein the target PE plate is a PE plate pre-immersed in the slurry to be tested, and the target PE plate has bubbles distributed on its surface;

[0030] Optionally, the PE plate pre-immersed in the slurry to be tested is used as the test object, and a camera or a mobile phone or other image acquisition device is used to take pictures of the surface of the PE plate according to specific shooting parameters (such as focal length, shutter speed, ISO sensitivity, etc.), thereby obtaining an original image (initial image) containing bubble distribution information. The purpose of image acquisition is to capture the accurate morphology and distribution of bubbles after the slurry contacts the PE plate, and to provide intuitive data sources for subsequent analysis.

[0031] Optionally, before step S102 is performed, the slurry to be tested is taken, a PE sheet of a specific size is completely immersed in the slurry to be tested and then taken out, there will be bubble distribution on the PE plate (i.e. the target PE plate) immersed by the slurry to be tested, and image acquisition is performed on the PE plate to obtain an initial image. The target PE plate can be imaged at different sampling times to obtain a plurality of initial images for subsequent slurry bubble detection. A beaker or other three-dimensional container can be used as a sampling container for sampling the slurry to be tested and immersing the PE plate; the PE plate can be 6 6 (cm), 10 10 (cm), 15 15 (cm), etc. The PE plate thickness can be 0.5 mm, 1 mm, etc. and can be set according to the specific scene requirements.

[0032] In step S104, the bubble density on the target PE plate is determined based on the initial image.

[0033] Optionally, after obtaining the initial image, the image is processed using image processing software (such as ImageJ) to obtain the bubble density on the target PE plate, which reflects the density of the bubble distribution on the target PE plate.

[0034] In an optional embodiment, based on the initial image, the bubble density on the target PE plate is determined, including: performing binaryzation processing on the initial image to obtain a binaryzation image; identifying the total number of bubbles on the target PE plate based on the binaryzation image; and determining the bubble density based on the total number of bubbles and the size information of the target PE plate.

[0035] Optionally, first, based on the obtained initial image, binaryzation processing is performed using image processing software (such as ImageJ). Binaryzation is an image processing technique that converts a grayscale image into an image with only two colors (such as black and white) to clearly distinguish bubbles (as foreground) and normal parts of the PE plate (as background). By adjusting the contrast and brightness of the image, the difference between the bubbles and the background can be maximized, making it easy for the software to automatically identify the bubble area. For example, after binaryzation processing, the bubbles are presented as white or black spots, while the other parts of the PE plate form a single-color background. Based on the binaryzation image, the bubble area is automatically identified or identified through a set algorithm to count all bubble particles in the image. The bubble boundary can be identified by setting a threshold, thereby accurately calculating the total number of bubbles, effectively excluding background noise, focusing only on bubbles, and ensuring the accuracy of the count. Finally, the total number of identified bubbles is combined with the actual size (length and width) of the target PE plate to calculate the bubble density. Bubble density refers to the number of bubbles per unit area, which can be expressed as the number of bubbles per square centimeter (pcs / cm²) or the number of bubbles per square meter (pcs / m²). By dividing the total number of bubbles by the area of the target PE plate, the important parameter of bubble density can be obtained, which can directly reflect the distribution density of bubbles on the surface of the PE plate. Bubble density information plays a key role in evaluating the quality of the slurry and predicting the risk of defects such as foil leakage during coating, because the higher the density, the greater the likelihood of defects during coating.

[0036] Through the above method, by using image binaryzation processing and counting algorithm, combined with the size information of the PE plate, the total number and density of bubbles are accurately calculated, which can significantly improve the accuracy and reliability of bubble detection.

[0037] In step S106, a bubble state test result of the to-be-tested slurry is determined according to the bubble density, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, which is a process of uniformly coating the to-be-tested slurry on a battery metal foil.

[0038] Optionally, the bubble state test result determined according to the bubble density can be used to indicate a potential defect risk of the slurry in a subsequent coating process, to evaluate whether the slurry is suitable for coating, and to predict possible defects or missing foil defects on the battery metal foil after coating. The test result can guide the adjustment of the slurry formula and process parameters to reduce coating abnormalities caused by bubbles and ensure quality control in the battery manufacturing process.

[0039] In an optional embodiment, determining the bubble state test result of the to-be-tested slurry according to the bubble density comprises: determining a bubble distribution score according to the bubble density; in a case where the bubble distribution score is greater than a preset score threshold, determining that the bubble state test result is that the to-be-tested slurry has a potential defect risk in the coating process; or in a case where the bubble distribution score is less than or equal to the preset score threshold, determining that the bubble state test result is that the to-be-tested slurry has no potential defect risk in the coating process.

[0040] Optionally, after determining the bubble density on the target PE plate, a bubble distribution score is further calculated based on this density data. The bubble distribution score is a measure of the distribution of bubbles on the surface of the PE plate. The scoring standard can be preset, and according to different application requirements and slurry characteristics, a high bubble density can correspond to a low score, a low bubble density can correspond to a high score, or different score intervals can be set according to the distribution range of the bubble density. When the bubble distribution score exceeds the preset score threshold, it means that the distribution of bubbles on the target PE plate is likely to be more, and there is a greater potential defect risk. The preset score threshold can be determined based on a large amount of experimental data and coating effect feedback, and is used to reflect the problems that may be encountered in the coating process caused by bubbles, such as missing foil, local resistance increase, and electrochemical performance decline. The score result exceeding this threshold indicates that the to-be-tested slurry may be difficult to form a uniform coating film during coating, thereby affecting the performance and safety of the battery. On the contrary, if the bubble distribution score is less than or equal to the preset score threshold, it means that the distribution density of the bubbles is moderate, and the to-be-tested slurry has a lower potential defect risk in the coating process. In this case, the slurry can be considered to be within a better quality control range and is suitable for subsequent coating operations, thereby ensuring that the coating layer on the battery metal foil is uniform and has no obvious defects, which is conducive to improving the overall performance and productivity of the battery.

[0041] By the above method, a quantitative evaluation method of the bubble state of the slurry is provided according to the bubble density threshold, the potential defect risk of the slurry in the coating process is judged through the scoring system, a scientific basis is provided for dynamic monitoring and real-time adjustment of the slurry formula, the slurry quality control is more scientific and accurate, which helps to improve the yield and consistency of battery manufacturing, reduce production cost, and strengthen the safety and reliability of the battery.

[0042] In an optional embodiment, according to the bubble density, the bubble distribution score is determined, including: based on the initial image, determining the bubble size distribution, bubble aggregation degree, and bubble distribution uniformity on the target PE plate; based on the bubble density, bubble size distribution, bubble aggregation degree, and bubble distribution uniformity, determining the bubble distribution score.

[0043] Optionally, the bubble characteristics in the initial image can be set, which is not limited to the consideration of bubble density, but also can evaluate the state of the bubble from multiple angles, including bubble density, bubble size distribution, bubble aggregation degree, and bubble distribution uniformity. Among them, the bubble size distribution is used to describe the size and distribution of the bubble, which can reflect the diversity of the bubble size in the slurry, and can be described by histogram or statistical analysis. Large size bubbles have a greater impact on the coating process, so the bubble size distribution is also an important consideration factor. The bubble aggregation degree is used to describe whether the bubbles appear in groups, and the size and shape of the bubble group (whether the bubbles on the PE plate surface tend to gather together or are more dispersed). High aggregation degree may indicate that there is a local instability or poor mixing problem in the slurry, which will also challenge the coating uniformity. The bubble distribution uniformity is used to describe the uniformity of the bubble distribution on the entire PE plate surface, which can be used to investigate the consistency of the bubble distribution on the entire PE plate surface, whether there is a concentration phenomenon in some areas. Uneven distribution may cause inconsistent performance of the battery foil after coating, affecting the overall quality of the battery. The uniformity of the distribution can be evaluated by calculating the local variation or standard deviation of the bubble density. By comprehensively calculating the bubble density, bubble size distribution, bubble aggregation degree, and bubble distribution uniformity, a comprehensive bubble distribution score is obtained. This score can more accurately reflect the comprehensive performance of the slurry in the coating process, including the potential impact of bubbles on coating uniformity, battery foil quality, and production yield.

[0044] By the above method, the size distribution, aggregation degree, and distribution uniformity of the bubble are comprehensively considered together with the bubble density to calculate the bubble distribution score, which can realize comprehensive evaluation of the bubble characteristics and enhance the objectivity and accuracy of the evaluation results.

[0045] In an optional embodiment, the bubble distribution score of the target PE plate is determined based on the bubble density, the bubble size distribution, the bubble aggregation degree, and the bubble distribution uniformity, including: determining a first weight corresponding to the bubble density, a second weight corresponding to the bubble size distribution, a third weight corresponding to the bubble aggregation degree, and a fourth weight corresponding to the bubble distribution uniformity; and determining the bubble distribution score based on the bubble density, the bubble size distribution, the bubble aggregation degree, the bubble distribution uniformity, the first weight, the second weight, the third weight, and the fourth weight.

[0046] Optionally, when evaluating the impact of bubbles on the slurry coating process, different bubble attributes (such as density, size distribution, aggregation degree, and distribution uniformity) can have different importance. Therefore, when determining the bubble distribution score, a weight can be assigned to each bubble attribute to reflect the relative size of its potential impact on the coating effect. The determination of the weight can be pre-set as needed, for example, the weight can be set based on experimental data, process experience, and production targets. For example, if it is found that the bubble size has the most significant impact on the uniformity of coating, then the bubble size distribution (second weight) can be given a higher value; otherwise, the weight is reduced. After determining the weight of each bubble attribute, the next step is to calculate the bubble distribution score. The quantitative values of bubble density, bubble size distribution, bubble aggregation degree, and bubble distribution uniformity can be combined into a comprehensive score (i.e., the bubble distribution score) by weighted average operation (such as multiplication, exponential operation, etc.) according to their respective weights. The purpose of this is to highlight the bubble attributes that have the greatest impact on the coating effect while considering all relevant factors, so that the score can better reflect the true state of the slurry and the coating risk.

[0047] Optionally, to avoid the influence of dimensional differences on the calculation of the bubble distribution score, the bubble density, the bubble size distribution, the bubble aggregation degree, and the bubble distribution uniformity can be normalized first, and then the normalized bubble density, the normalized bubble size distribution, the normalized bubble aggregation degree, and the normalized bubble distribution uniformity can be weighted calculated based on the corresponding weight values to obtain the bubble distribution score.

[0048] In this way, the relative importance of bubble density, size distribution, aggregation degree, and distribution uniformity in the score is established, and the bubble distribution score determined by weighting can more comprehensively evaluate the stability and risk of the slurry in the coating process, making the evaluation standard more in line with actual production needs.

[0049] In an optional embodiment, in the case that the initial images include multiple, the corresponding bubble densities are multiple, and the multiple initial images correspond to the multiple sampling time points one by one, the bubble distribution score is determined according to the bubble densities, including: determining a weight value corresponding to each of the multiple bubble densities, wherein the weight value is inversely proportional to the sampling time point of the initial image corresponding to the bubble density; and obtaining the bubble distribution score based on the multiple bubble densities and the weight values corresponding to the multiple bubble densities.

[0050] Optionally, a plurality of initial images can be collected for the target PE plate, each image corresponding to a different time point (i.e., sampling time) at which the slurry is placed, and each time point has a corresponding bubble density. This means that the test method can track the trend of bubbles in the slurry over time, evaluate the stability of the slurry and the speed of bubble generation or disappearance. In the multi-time point analysis, the setting of the weight value takes into account the relationship between the bubble density and the sampling time. The weight value is inversely proportional to the sampling time, which means that the closer to the current or pre-coating sampling time, the greater the influence of the bubble density on the final bubble distribution score. This is because the state of the slurry just before coating best represents the bubble condition in the actual coating process, while the early bubble density may not fully reflect the true situation under the final coating conditions due to the physical and chemical changes of the slurry. Through this weight distribution, the scoring system can pay more attention to the data when the slurry is about to be used, thereby providing a more realistic evaluation result. Multiply the bubble density at each time point by its weight value, then combine these weighted values to get the final bubble distribution score. This score integrates information on the bubble state at different times, taking into account both the immediate effect of the bubbles and the impact of long-term trends on the coating process.

[0051] By the above method, introducing the time dimension to determine the bubble distribution score can achieve dynamic monitoring and scoring of the bubble state of the slurry, reveal the law of bubble evolution over time, and evaluate the stability of the slurry in the coating process and the potential defect risk. Especially in the scenario where the slurry may change after being placed for a period of time, it can provide strong data support for real-time adjustment of production processes and long-term control of slurry quality, thereby improving coating effect and product quality.

[0052] Through the above steps S102 to S106, the purpose of accurately evaluating the bubble state of the slurry can be achieved by collecting images of bubbles on the surface of the PE plate pre-soaked with the slurry and analyzing the bubble density, thereby achieving accurate evaluation of the bubble state of the slurry, effectively predicting and reducing defects (such as foil leakage, etc.) in the battery metal foil coating process, optimizing slurry quality and coating process, and improving the overall performance and production yield of the battery, thereby solving the technical problem that the potential defect risk in the slurry coating process is difficult to effectively identify.

[0053] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation of a slurry bubble test method, Figure 2 is a flow chart of an optional slurry bubble test method according to an embodiment of the present application, as shown in the figure, the method comprises: Figure 2

[0054] S1, sampling, collecting bubbles, wherein the sampling container can be a beaker or other three-dimensional container; the PE plate can be any size such as 6 6 (cm), 10 10 (cm), 15 15 (cm) and the like, and the thickness of the PE plate can be 0.5 mm, 1 mm or the like, which can be set according to specific application requirements.

[0055] S2, taking a picture to obtain an initial image, recording bubble distribution to complete sample collection of the tested sample. After obtaining the initial image, the image can be filtered and cleaned without reflection points. When collecting the image, the specific parameters can be set as follows: the focal length is set to 50 mm, the shutter speed is ≥ 1 / 50 s, and the sensitivity ISO is ≤ 200.

[0056] S3, using ImageJ image processing software to process the picture. The picture can be processed using ImageJ image processing software, and the picture can be further processed to obtain a more obvious contrast between the defect bubbles and the normal film area by using certain parameters (such as adjusting the contrast and saturation).

[0057] S4, calculating the number of bubbles, which can be calculated by using the counting function of ImageJ software.

[0058] S5, normalization processing, obtaining bubble distribution level, and objectively evaluating the slurry state. The data calculated by ImageJ can be used to calculate the bubble spatial density distribution according to the specific area of the PE sheet taken, to guide and evaluate the slurry state and improvement effect.

[0059] In an optional embodiment, silicon-carbon material is used as one of the negative electrode coating main materials, wherein the design value of the discharge solid content is 46%, and the flow design value is 80% of the full production, i.e. 1600 kg / h. After discharging, a cup is taken and placed for 0 hours, 6 hours, 12 hours and 24 hours, respectively, and the bubble number is evaluated by using the above embodiment method; the bubble density obtained by testing is 0.00 pcs / cm²; 0.027 pcs / cm²; 0.083 pcs / cm²; 0.55 pcs / cm²; the average foil leakage defect rate of the pole piece in the corresponding time period is 0.00 pcs / m; 0.00 pcs / m; 0.017 pcs / m; 0.225 pcs / m; showing a strong positive correlation, which proves the effectiveness of the embodiment method. ​

[0060] A slurry bubble testing apparatus is also provided in the embodiments, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" "apparatus" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementation of hardware, or a combination of software and hardware, is also possible and contemplated.

[0061] According to the embodiments of the present application, a device embodiment for implementing the above-mentioned slurry bubble testing method is also provided, Figure 3 is a structural schematic diagram of a slurry bubble testing apparatus according to the embodiments of the present application, as Figure 3 shown, the above-mentioned slurry bubble testing apparatus comprises an image acquisition module 300, a bubble density determination module 302, and a bubble state testing module 304, wherein:

[0062] The image acquisition module 300 is configured to acquire an image of a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate pre-immersed in a to-be-tested slurry, and the target PE plate has bubbles distributed on the surface thereof.

[0063] The bubble density determination module 302 is connected to the image acquisition module 300 and is configured to determine a bubble density on the target PE plate based on the initial image.

[0064] The bubble state testing module 304 is connected to the bubble density determination module 302 and is configured to determine a bubble state testing result of the to-be-tested slurry according to the bubble density, wherein the bubble state testing result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry on a battery metal foil.

[0065] In the embodiment of the present application, the image acquisition module 300 is arranged to acquire an image of the target polyethylene (PE) plate, and an initial image is obtained, wherein the target PE plate is a PE plate immersed in the to-be-tested slurry in advance, and the target PE plate has bubbles distributed on the surface; the bubble density determination module 302 is connected to the image acquisition module 300, and is configured to determine the bubble density on the target PE plate based on the initial image; and the bubble state test module 304 is connected to the bubble density determination module 302, and is configured to determine a bubble state test result of the to-be-tested slurry according to the bubble density, wherein the bubble state test result is used to indicate the potential defect risk of the to-be-tested slurry in the coating process, and the coating process is a process of uniformly coating the to-be-tested slurry on the battery metal foil. The purpose of accurately evaluating the bubble state of the slurry is achieved by acquiring the image of the bubbles on the surface of the PE plate immersed in the slurry in advance and analyzing the bubble density, so as to accurately evaluate the bubble state of the slurry, effectively predict and reduce defects (such as missing foil) in the coating process of the battery metal foil, optimize the quality of the slurry and the coating process, and improve the overall performance and production yield of the battery, thereby solving the technical problem that the potential defect risk in the coating process of the slurry is difficult to be effectively identified.

[0066] It should be noted that each of the above modules can be implemented by software or hardware. For example, for the latter, each of the above modules can be located in the same processor, or each of the above modules can be located in different processors in any combination.

[0067] It should be noted that the image acquisition module 300, the bubble density determination module 302, and the bubble state test module 304 correspond to steps S102 to S106 in the embodiment, and the above modules have the same instances and application scenarios as the corresponding steps, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules can run in a computer terminal as part of the device.

[0068] It should be noted that the optional or preferred embodiments of the present embodiment can refer to the related description in the embodiment, which will not be repeated here.

[0069] The above slurry bubble test device can further include a processor and a memory, and the image acquisition module 300, the bubble density determination module 302, the bubble state test module 304, and the like are stored in the memory as program modules, and the processor executes the above program modules stored in the memory to realize the corresponding functions.

[0070] The processor comprises a core, and the core is used to call corresponding program modules in the memory. The core can be one or more. The memory can comprise a non-permanent memory in a computer readable medium, a random access memory (RAM) and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory comprises at least one memory chip.

[0071] According to the embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in the embodiment, the non-volatile storage medium comprises a stored program, and when the program runs, the non-volatile storage medium controls a device where the non-volatile storage medium is located to perform any of the pulp bubble test methods.

[0072] Optionally, in the embodiment, the non-volatile storage medium can be located in any of computer terminals in a computer terminal group in a computer network, or in any of mobile terminals in a mobile terminal group, and the non-volatile storage medium comprises a stored program.

[0073] Optionally, when the program runs, the non-volatile storage medium controls a device where the non-volatile storage medium is located to perform the following functions: image acquisition on a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate pre-immersed in a to-be-tested pulp, and the target PE plate has bubbles distributed on the surface; determining a bubble density on the target PE plate based on the initial image; and determining a bubble state test result of the to-be-tested pulp according to the bubble density, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested pulp in a coating process, and the coating process is a process of uniformly coating the to-be-tested pulp on a battery metal foil.

[0074] According to the embodiment of the present application, an embodiment of a processor is also provided. Optionally, in the embodiment, the processor is used to run a program, and when the program runs, the processor performs any of the pulp bubble test methods.

[0075] According to the embodiment of the present application, an embodiment of a computer program product is also provided, which is adapted to execute a program initialized with steps of any of the pulp bubble test methods when executed on a data processing device.

[0076] Optionally, the computer program product described above, when executed on the data processing device, is adapted to execute the program steps of: image acquisition is performed on a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate that is immersed in advance into a to-be-tested slurry, and the target PE plate is distributed with bubbles on the surface; based on the initial image, a bubble density on the target PE plate is determined; and based on the bubble density, a bubble state test result of the to-be-tested slurry is determined, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry to a battery metal foil.

[0077] The electronic device provided by the embodiment of the present application comprises a processor, a memory and a program stored on the memory and executable on the processor, and the processor implements the following steps when executing the program: image acquisition is performed on a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate that is immersed in advance into a to-be-tested slurry, and the target PE plate is distributed with bubbles on the surface; based on the initial image, a bubble density on the target PE plate is determined; and based on the bubble density, a bubble state test result of the to-be-tested slurry is determined, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry to a battery metal foil.

[0078] The sequence of the above-mentioned embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments.

[0079] In the above-mentioned embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0080] In the several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. Of course, the device embodiment described above is only illustrative, and for example, the division of the above-mentioned modules can be a logical function division, and actual implementation can have another division manner, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed can be through some interfaces, indirect coupling or communication connection between modules or modules, which can be electrical or other forms.

[0081] The modules described above as separate components can or can not be physically separate, and the components shown as modules can or can not be physical modules, i.e. they can be located in one place or distributed to multiple modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0082] In addition, each function module in each embodiment of the present application can be integrated in one processing module, or each module can exist physically independently, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module.

[0083] When the integrated module is realized in the form of a software function module and sold or used as an independent product, the module can be stored in a computer readable nonvolatile storage medium. Based on this understanding, the technical solutions of the present application or the part of the prior art that contributes essentially or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a nonvolatile storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The foregoing nonvolatile storage medium includes a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk and various media that can store program codes.

[0084] The above is only the preferred embodiment of the present application. It should be noted that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A slurry bubble test method characterized by, The method comprises the following steps: image acquisition is performed on a target polyethylene (PE) plate to obtain an initial image, wherein the target PE plate is a PE plate immersed in a to-be-tested slurry in advance, and the target PE plate is distributed with bubbles on the surface; a bubble density on the target PE plate is determined based on the initial image; a bubble state test result of the to-be-tested slurry is determined according to the bubble density, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry on a battery metal foil.

2. The method of claim 1, wherein, The method further comprises the following steps: a binaryzation process is performed on the initial image to obtain a binaryzation image; a total number of bubbles on the target PE plate is identified based on the binaryzation image; the bubble density is determined based on the total number of bubbles and size information of the target PE plate.

3. The method of claim 1, wherein, The method further comprises the following steps: a bubble distribution score is determined according to the bubble density; in a case where the bubble distribution score is greater than a preset score threshold, it is determined that the bubble state test result is that the to-be-tested slurry has a potential defect risk in the coating process; or in a case where the bubble distribution score is less than or equal to the preset score threshold, it is determined that the bubble state test result is that the to-be-tested slurry does not have a potential defect risk in the coating process.

4. The method of claim 3, wherein, The method further comprises the following steps: a bubble size distribution, a bubble aggregation degree and a bubble distribution uniformity on the target PE plate are determined based on the initial image; the bubble distribution score is determined based on the bubble density, the bubble size distribution, the bubble aggregation degree and the bubble distribution uniformity.

5. The method of claim 4, wherein, The method further comprises the following steps: a first weight corresponding to the bubble density, a second weight corresponding to the bubble size distribution, a third weight corresponding to the bubble aggregation degree and a fourth weight corresponding to the bubble distribution uniformity are determined; the bubble distribution score is determined based on the bubble density, the bubble size distribution, the bubble aggregation degree, the bubble distribution uniformity, the first weight, the second weight, the third weight and the fourth weight.

6. The method of claim 3, wherein, In a case where the initial image comprises a plurality of initial images, the corresponding bubble densities are a plurality of bubble densities, and the plurality of initial images correspond to a plurality of sampling time points one by one, the method further comprises the following steps: a weight value corresponding to each of the plurality of bubble densities is determined, wherein the weight value is inversely proportional to a sampling time point of an initial image corresponding to the bubble density; the bubble distribution score is obtained based on the plurality of bubble densities and the weight value corresponding to each of the plurality of bubble densities.

7. A slurry bubble test device characterized by, The method comprises the following steps: An image acquisition module is configured to acquire an initial image of a target polyethylene (PE) plate, wherein the target PE plate is a PE plate immersed in a to-be-tested slurry, and the target PE plate has bubbles distributed on a surface thereof; A bubble density determination module is configured to determine a bubble density on the target PE plate based on the initial image; A bubble state test module is configured to determine a bubble state test result of the to-be-tested slurry according to the bubble density, wherein the bubble state test result is used to indicate a potential defect risk of the to-be-tested slurry in a coating process, and the coating process is a process of uniformly coating the to-be-tested slurry on a metal foil of a battery.

8. A non-volatile storage medium, characterized by The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement the slurry bubble test method in any one of claims 1 to 6.

9. An electronic device, comprising: The computer program is executed by a processor to implement the steps of the slurry bubble test method in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the slurry bubble test method in any one of claims 1 to 6.

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