A lithium battery production monitoring method and system based on foil ductility

Abstract

The application discloses a lithium battery production monitoring method and system based on foil ductility, and relates to the technical field of lithium battery production.The method comprises the following steps: acquiring images of a foil material roll before a rolling process, identifying the transverse size of the foil in the running direction on each of the images before the rolling process, and calculating the average transverse size; acquiring images of the foil material roll after the rolling process, identifying the transverse size of the foil in the running direction on each of the images after the rolling process in real time, and calculating the real-time transverse ductility in combination with the average transverse size; and if the real-time transverse ductility exceeds a ductility threshold range, triggering an abnormal alarm signal.The application solves the technical problems of the prior art, such as incomplete detection and long lag, in the detection of foil ductility through image visual detection and real-time calculation of the transverse ductility.

Description

Technical Field

[0001] This invention relates to the field of lithium battery production technology, and in particular to a lithium battery production monitoring method and system based on foil elongation. Background Technology

[0002] In the manufacturing process of lithium-ion battery electrodes, the coated foil needs to undergo a rolling process to compact the active material, thereby increasing the energy density of the battery. During the rolling process, the elongation of the foil is the main factor leading to foil breakage. Breakage reduces production efficiency, causes material waste, and thus affects capacity ramp-up, resulting in significant economic losses. Under the tension of the tension rollers and the pressure of the pressure rollers, the foil undergoes stretching in both the transverse and longitudinal directions. The transverse elongation is a parameter for evaluating the quality of the rolling process, electrode consistency, and the risk of foil breakage.

[0003] Currently, the main problems facing the testing methods for the transverse elongation of foil materials are as follows:

[0004] Firstly, the sampling inspection rate for incoming foil materials is limited, making it impossible to inspect all rolls. Lithium battery manufacturers use offline, sampling inspection methods for foil materials before production, leading to the risk of missed inspections. Furthermore, batch sampling inspection methods for foil materials cannot provide accurate results down to the roll level.

[0005] Secondly, the output of test results is delayed. Because offline elongation testing methods require a certain time period, they cannot immediately provide feedback on the elongation of the foil. When abnormal elongation occurs, a large batch of materials may already be defective, leading to material waste and increased production costs. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a lithium battery production monitoring method and system based on foil elongation, which solves the technical problems of insufficient detection and long lag in the detection of foil elongation by existing detection methods.

[0007] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0008] In a first aspect, the present invention provides a method for monitoring lithium battery production based on foil elongation, comprising:

[0009] Obtain images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension.

[0010] The image of the foil roll after the rolling process is obtained, the transverse dimension of the foil in the conveyor direction on each image after the rolling process is identified in real time, and the real-time transverse elongation is calculated by combining the average value of the transverse dimension.

[0011] If the real-time lateral stretching rate exceeds the stretching rate threshold range, an abnormal alarm signal will be triggered.

[0012] This invention achieves real-time online calculation of lateral elongation by using the average lateral dimension before the rolling process and the real-time lateral dimension after the rolling process. This calculation is highly efficient, overcoming the long lag problem of existing detection methods. Furthermore, both the lateral dimensions before and after the rolling process are detected using image vision, enabling rapid and comprehensive inspection of all rolls and overcoming the risk of missed detection in existing methods.

[0013] Optionally, the real-time lateral stretch rate for:

[0014]

[0015] In the formula, This represents the average transverse dimension before the rolling process. These represent the average lateral dimension and the real-time lateral elongation at the i-th moment after the rolling process, respectively.

[0016] This invention differs from the conventional method of directly calculating the lateral elongation rate by measuring the lateral dimensions before and after the rolling process. Instead, it uses the average lateral dimension before the rolling process and the real-time lateral dimension after the rolling process for calculation. The advantages of this method are twofold: firstly, it allows for direct calculation of the real-time lateral elongation rate; secondly, the conventional method requires aligning the lateral dimensions before and after the rolling process before calculating the lateral elongation rate of the corresponding area. However, in practice, alignment is difficult and complex. The calculation method of this invention avoids this problem and is simpler and more efficient.

[0017] Optionally, while triggering the abnormal alarm signal, optimization suggestions for the process parameters of the rolling process are provided based on the real-time lateral elongation rate.

[0018] This invention achieves proactive optimization and adjustment of the process parameters of the rolling process by linking the detection results with the process parameters of the rolling process in real time. Optimization suggestions are pushed to the system in real time via pop-up windows to guide parameter adjustments. After adjustment, the elongation rate is continuously monitored until it returns to the normal range, thus realizing closed-loop intelligent control of the production process.

[0019] Optionally, the optimization suggestions for the process parameters of the rolling process include:

[0020] If the real-time lateral extension rate If so, it is recommended to reduce the roller pressing speed or decrease the roller gap value;

[0021] If the real-time lateral extension rate If so, it is recommended to increase the tension of the foil roll or widen the roll gap;

[0022] in, These are the upper and lower limits of the elongation specification, respectively.

[0023] This invention provides optimization suggestions for excessive and insufficient elongation, namely, reducing tensile deformation when elongation is excessive and enhancing the material's elongation effect when elongation is insufficient. Through reasonable adjustments, the elongation parameter can be brought back to the normal range, avoiding strip breakage that leads to reduced production efficiency, material waste, and consequently, hinders capacity ramp-up and causes significant economic losses.

[0024] Optionally, it also includes an evaluation index for calculating production consistency in real time based on the real-time lateral stretching rate, used to assess the fluctuation of the lateral stretching rate.

[0025] This invention quantifies the uniformity of elongation and process stability by calculating evaluation indicators for production consistency.

[0026] Optionally, the evaluation metrics for production consistency include:

[0027] Obtain the current time series of real-time horizontal stretch rate and calculate the current average stretch rate. :

[0028]

[0029] In the formula, This represents the real-time lateral elongation at the i-th moment after the rolling process. This represents the current time series length.

[0030] Based on the current average elongation Calculate the standard deviation of the current elongation. Current elongation coefficient of variation Current process capability index :

[0031]

[0032]

[0033] In the formula, These are the upper and lower limits of the elongation specification, respectively.

[0034] In this invention, the evaluation metric for production consistency primarily focuses on the standard deviation of the current elongation rate. Current elongation coefficient of variation Current process capability index Three items, current stretch rate standard deviation It can reflect the extent of fluctuation in the lateral elongation rate; the current elongation rate variation coefficient. It can reflect whether the lateral extension rate is too large relative to the target, and the current process capability index. It can reflect whether the lateral elongation rate will frequently exceed the tolerance under the existing fluctuations. Through the three evaluation indicators, we can fully understand the stability of the lateral elongation rate and provide effective data support for lithium battery production monitoring.

[0035] Secondly, the present invention provides a lithium battery production monitoring system based on foil elongation, comprising:

[0036] The first data processing module is configured to acquire images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension.

[0037] The second data processing module is configured to acquire images of the foil roll after the rolling process, identify the lateral dimension of the foil in the belt-carrying direction in each image after the rolling process in real time, and calculate the real-time lateral elongation rate by combining the average value of the lateral dimension.

[0038] The anomaly detection alarm module is configured to trigger an anomaly alarm signal if the real-time lateral stretching rate exceeds the stretching rate threshold range.

[0039] Thirdly, the present invention provides an electronic device, including a processor and a storage medium;

[0040] The storage medium is used to store instructions;

[0041] The processor is configured to operate according to the instructions to perform the steps according to the method described above.

[0042] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0043] Fifthly, the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0044] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0045] This invention provides a lithium battery production monitoring method and system based on foil elongation. It achieves real-time online calculation of lateral elongation by using the average lateral dimension before and after the rolling process, resulting in extremely high calculation efficiency and overcoming the long lag problem of existing detection methods. Simultaneously, image-based visual inspection is used for both lateral dimensions before and after the rolling process, enabling rapid and comprehensive inspection of all rolls and overcoming the risk of missed detection in existing methods. Furthermore, by combining multiple evaluation indicators such as the standard deviation, coefficient of variation, and process capability index of the real-time lateral elongation, the uniformity and process stability of the elongation are quantitatively characterized, improving the dimensionality and accuracy of foil quality assessment. Real-time linkage between the detection results and the optimization of rolling process parameters enables proactive optimization and adjustment of these parameters, achieving closed-loop intelligent control of the production process. Attached Figure Description

[0046] Figure 1 This is a schematic flowchart of a lithium battery production monitoring method based on foil elongation provided by the present invention. Detailed Implementation

[0047] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0048] Example 1

[0049] like Figure 1 As shown, this embodiment of the invention provides a lithium battery production monitoring method based on foil elongation, including the following steps:

[0050] Step S1: Obtain images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension.

[0051] Step S2: Obtain images of the foil roll after the rolling process, identify the lateral dimensions of the foil in the belt conveyor direction in real time in each image after the rolling process, and calculate the real-time lateral elongation rate by combining the average lateral dimensions.

[0052] In actual production, the coating process precedes the rolling process. Images after the rolling process and before the rolling process can be directly obtained from the CCD cameras on the rolling and coating processes. A data sharing connection is built between the industrial control computer at the coating end and the industrial control computer at the rolling end based on the MES network, and the image data is stored in a shared folder for subsequent unified access.

[0053] When calling the data, attention should be paid to data association and validity verification. The foil material rolls of the coating process and the foil material rolls of the rolling process should be coded and matched to build a production data association ledger for coating-rolling, clarify the consistency of calculations, and avoid calculation errors.

[0054] Specifically, in this embodiment, the real-time lateral stretch rate for:

[0055]

[0056] In the formula, This represents the average transverse dimension before the rolling process. These represent the average lateral dimension and the real-time lateral elongation at the i-th moment after the rolling process, respectively.

[0057] This invention differs from the conventional method of directly calculating the lateral elongation rate by measuring the lateral dimensions before and after the rolling process. Instead, it uses the average lateral dimension before the rolling process and the real-time lateral dimension after the rolling process for calculation. The advantages of this method are twofold: firstly, it allows for direct calculation of the real-time lateral elongation rate; secondly, the conventional method requires aligning the lateral dimensions before and after the rolling process before calculating the lateral elongation rate of the corresponding area. However, in practice, alignment is difficult and complex. The calculation method of this invention avoids this problem and is simpler and more efficient.

[0058] Step S3: If the real-time horizontal stretching rate exceeds the stretching rate threshold range, an abnormal alarm signal is triggered.

[0059] Steps S1 to S3 of this invention achieve real-time online calculation of the lateral elongation rate by using the average lateral dimension before the rolling process and the real-time lateral dimension after the rolling process. This calculation is highly efficient and overcomes the technical problem of long lag in existing detection methods. Simultaneously, both the lateral dimensions before and after the rolling process are detected using image vision, enabling rapid and comprehensive inspection of all rolls and overcoming the risk of missed detection in existing methods.

[0060] As a refinement and supplement to the solution after triggering an abnormal alarm signal, this solution provides optimization suggestions for the rolling process parameters based on the real-time lateral elongation rate upon triggering the alarm signal. For example:

[0061] If the real-time lateral stretch rate If so, it is recommended to reduce the roller pressing speed or decrease the roller gap value;

[0062] If the real-time lateral stretch rate If so, it is recommended to increase the tension of the foil roll or widen the roll gap;

[0063] in, These are the upper and lower limits of the elongation specification, respectively.

[0064] This invention provides optimization suggestions for excessive and insufficient elongation, namely, reducing tensile deformation when elongation is excessive and enhancing material elongation when elongation is insufficient. Through reasonable adjustments, the elongation parameter can be brought back to the normal range, avoiding strip breakage that leads to reduced production efficiency, material waste, and consequently, hinders capacity ramp-up and causes significant economic losses. In other optional embodiments, operators can also set other suggestions as needed, which can be easily invoked when abnormal alarm signals are triggered.

[0065] This invention achieves proactive optimization and adjustment of the process parameters of the rolling process by linking the detection results with the process parameters of the rolling process in real time. Optimization suggestions are pushed to the system in real time via pop-up windows to guide parameter adjustments. After adjustment, the elongation rate is continuously monitored until it returns to the normal range, thus realizing closed-loop intelligent control of the production process.

[0066] As a refinement and supplement to the lateral elongation rate detection scheme, this invention also includes an evaluation index for real-time calculation of production consistency based on the real-time lateral elongation rate, used to assess the fluctuation of the lateral elongation rate. This invention quantitatively characterizes the uniformity of the elongation rate and process stability by calculating the evaluation index for production consistency.

[0067] Specifically, in this implementation method, the evaluation indicators for production consistency include:

[0068] Obtain the current time series of real-time horizontal stretch rate and calculate the current average stretch rate. :

[0069]

[0070] In the formula, This represents the real-time lateral elongation at the i-th moment after the rolling process. This represents the current time series length.

[0071] Based on the current average elongation Calculate the standard deviation of the current elongation. Current elongation coefficient of variation Current process capability index :

[0072]

[0073]

[0074] In the formula, These are the upper and lower limits of the elongation specification, respectively.

[0075] In this invention, the evaluation metric for production consistency primarily focuses on the standard deviation of the current elongation rate. Current elongation coefficient of variation Current process capability index Three items, current stretch rate standard deviation It can reflect the extent of fluctuation in the lateral elongation rate; the current elongation rate variation coefficient. It can reflect whether the lateral extension rate is too large relative to the target, and the current process capability index. It can reflect whether the lateral elongation rate will frequently exceed the tolerance under the existing fluctuations. The stability of the lateral elongation rate can be fully understood through three evaluation indicators. The evaluation indicators are stored in the MES database in a structured manner to provide effective data support for lithium battery production monitoring.

[0076] Example 2

[0077] This invention provides a lithium battery production monitoring system based on foil elongation, comprising:

[0078] The first data processing module is configured to acquire images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension.

[0079] The second data processing module is configured to acquire images of the foil roll after the rolling process, identify the lateral dimension of the foil in the belt-carrying direction in each image after the rolling process in real time, and calculate the real-time lateral elongation rate by combining the average lateral dimension.

[0080] The anomaly detection alarm module is configured to trigger an anomaly alarm signal if the real-time lateral stretching exceeds the stretching threshold range.

[0081] Example 3

[0082] Based on the lithium battery production monitoring method provided in Embodiment 1, this embodiment of the invention provides an electronic device, including a processor and a storage medium;

[0083] Storage media are used to store instructions;

[0084] The processor is used to perform operations according to instructions to execute the steps according to the method described above.

[0085] Example 4

[0086] Based on the lithium battery production monitoring method provided in Embodiment 1, this embodiment of the invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above method.

[0087] Example 5

[0088] Based on the lithium battery production monitoring method provided in Embodiment 1, this embodiment of the invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above method.

[0089] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for monitoring lithium battery production based on foil elongation, characterized in that, include: Obtain images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension. The image of the foil roll after the rolling process is obtained, the transverse dimension of the foil in the conveyor direction on each image after the rolling process is identified in real time, and the real-time transverse elongation is calculated by combining the average value of the transverse dimension. If the real-time lateral stretching rate exceeds the stretching rate threshold range, an abnormal alarm signal will be triggered.

2. The lithium battery production monitoring method based on foil elongation according to claim 1, characterized in that, The real-time lateral elongation for: ； In the formula, This represents the average transverse dimension before the rolling process. These represent the average lateral dimension and the real-time lateral elongation at the i-th moment after the rolling process, respectively.

3. The lithium battery production monitoring method based on foil elongation according to claim 1, characterized in that, Simultaneously with triggering the abnormal alarm signal, optimization suggestions for the process parameters of the rolling process are provided based on the real-time lateral elongation rate.

4. The lithium battery production monitoring method based on foil elongation according to claim 3, characterized in that, The proposed optimization suggestions for the process parameters of the rolling process include: If the real-time lateral extension rate If so, it is recommended to reduce the roller pressing speed or decrease the roller gap value; If the real-time lateral extension rate If so, it is recommended to increase the tension of the foil roll or widen the roll gap; in, These are the upper and lower limits of the elongation specification, respectively.

5. The lithium battery production monitoring method based on foil elongation according to claim 1, characterized in that, It also includes an evaluation index for calculating production consistency in real time based on the real-time lateral stretching rate, used to assess the fluctuation of the lateral stretching rate.

6. The lithium battery production monitoring method based on foil elongation according to claim 5, characterized in that, The evaluation indicators for production consistency include: Obtain the current time series of real-time horizontal stretch rate and calculate the current average stretch rate. : ； In the formula, This represents the real-time lateral elongation at the i-th moment after the rolling process. This represents the current time series length. Based on the current average elongation Calculate the standard deviation of the current elongation. Current elongation coefficient of variation Current process capability index : ； ； ； In the formula, These are the upper and lower limits of the elongation specification, respectively.

7. A lithium battery production monitoring system based on foil elongation, characterized in that, include: The first data processing module is configured to acquire images of the foil roll before the rolling process, identify the lateral dimension of the foil in the conveyor direction in each image before the rolling process, and calculate the average lateral dimension. The second data processing module is configured to acquire images of the foil roll after the rolling process, identify the lateral dimension of the foil in the belt-carrying direction in each image after the rolling process in real time, and calculate the real-time lateral elongation rate by combining the average value of the lateral dimension. The anomaly detection alarm module is configured to trigger an anomaly alarm signal if the real-time lateral stretching rate exceeds the stretching rate threshold range.

8. An electronic device, characterized in that, Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-6.

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