A quality detection method and system for laminated soft-pack lithium battery

Abstract

The present invention discloses a laminated soft-pack lithium battery quality detection method and system, which relates to the field of laminated soft-pack battery detection. First, the production raw materials such as diaphragms, positive plates and negative plates are segmented and associated to form raw material segment groups; then, the raw material segment groups are defect-detected using visual analysis technology, and different defect levels are defined; then, the laminated soft-pack lithium batteries corresponding to the raw material segment groups are performance-tested, and the performance indicators are associated with the historical defect level groups to obtain quality detection reference data; finally, the production line is inspected in real time. If the real-time defect level group is consistent with the historical defect level group, corrections are made and accumulated and summed. If the total defect level reaches a preset value, an unqualified alarm is issued. Through the above technical solution, the present invention realizes timely quality warnings in the production stage, reduces production costs and improves the yield rate.

Description

Technical Field

[0001] The present invention relates to the field of laminated soft-pack battery detection, and in particular to a laminated soft-pack lithium battery quality detection method and system. Background Art

[0002] In the field of lithium battery manufacturing, laminated soft-pack lithium batteries have gradually become the mainstream products in the market due to their high energy density, good safety performance and flexible design characteristics. However, the production process of laminated soft-pack lithium batteries is complicated, involving multiple production links and multiple raw materials, which places extremely high demands on quality control.

[0003] Existing laminated soft-pack lithium battery inspection methods mainly rely on manual sampling and simple automated inspection equipment. These methods have the following shortcomings: First, they cannot comprehensively and accurately identify defects in raw materials, such as wrinkles, scratches, dirt and holes, resulting in some defective products flowing into subsequent production links; second, they cannot effectively associate raw material defects with battery performance, making it impossible to make timely adjustments and optimizations during the production process; third, there is a lack of real-time quality control and unqualified early warning mechanisms, making it difficult to discover and deal with potential quality problems in the first place. Summary of the invention

[0004] The purpose of the present invention is to provide a laminated soft-pack lithium battery quality detection method and system that can perform real-time detection on the production of laminated soft-pack lithium batteries and issue timely alarms.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for detecting quality of laminated soft-pack lithium batteries, comprising:

[0007] The production materials of the separator, the positive electrode sheet and the negative electrode sheet are segmented respectively to form a number of separator segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and the separator segments, positive electrode sheet segments and negative electrode sheet segments are associated based on the equivalent assembly sequence to which they belong, and recorded as a raw material segment group;

[0008] Using visual analysis technology, the separator segment, the positive electrode sheet segment and the negative electrode sheet segment in each raw material segment group are analyzed, and based on the analysis results, a first defect degree is defined for the separator segment, a second defect degree is defined for the positive electrode sheet, and a third defect degree is defined for the negative electrode sheet, and a combination of the first defect degree, the second defect degree and the third defect degree is identified as a historical defect degree group, and the historical defect degree group is associated with the raw material segment group;

[0009] Perform performance tests on the laminated soft-pack lithium batteries corresponding to the raw material segmentation groups, define performance indicators based on the test results, and associate the performance indicators with the historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results;

[0010] The diaphragms, positive electrodes and negative electrodes of the production line are inspected in real time, and the degree of defects is defined in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degree in the real-time defect degree group is corrected and accumulated and summed. Otherwise, the defect degree in the real-time defect degree group is directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, the corresponding diaphragm, positive electrode and negative electrode will be alarmed as unqualified.

[0011] In some embodiments disclosed in the present invention, the method of analyzing the separator segment, the positive electrode segment and the negative electrode segment in each raw material segment group by using visual analysis technology includes:

[0012] Collecting the separator segmentation image, the positive electrode sheet segmentation image and the negative electrode sheet segmentation image corresponding to each raw material segmentation group to obtain a raw material segmentation image group;

[0013] Preprocessing each image in the raw segmented image group, and extracting features from the preprocessed image, wherein the extracted features include color, texture and shape;

[0014] The extracted image features are compared with the preset defect templates to identify the defects in each image and mark the defects in the image.

[0015] In some embodiments disclosed herein, defects in the image include wrinkles, scratches, dirt, and holes.

[0016] In some embodiments disclosed in the present invention, based on the analysis results, the method of defining the degree of defects for the separator segment, the positive electrode segment and the negative electrode segment respectively includes:

[0017] Several defect types are set for defects, and a length comparison array [a1, a2, ..., an] and an area comparison array [s1, s2, ..., sn] are set for each defect type;

[0018] Determine the defect type of the defect, and call the corresponding length comparison array and area comparison array based on the defect type to obtain the longest distance A0 between the defect edges and the area S0 of the defect mapping, and compare the longest length A0 with the area comparison array [a1, a2, ..., an]:

[0019] If a1≤A0<a2, the defect degree of the defect is defined as A1;

[0020] If a2≤A0<a3, the defect degree of the defect is defined as A2; ...;

[0022] If an-1≤A0<an, the defect degree of the defect is defined as An-1;

[0023] The area S0 of the defect mapping is analyzed. If it is greater than or equal to the preset value, the area S0 is compared with the area comparison array [s1, s2, ..., sn], and the defect degree is corrected based on the comparison result.

[0024] In some embodiments disclosed in the present invention, the method for correcting the degree of defect includes:

[0025] Compare the area S0 with the area comparison array [s1,s2,...,sn]:

[0026] If s1≤S0<s2, the correction coefficient for the defect degree is determined to be K1, and the corrected defect degree is [A1 orA2 or...or An-1]*K1;

[0027] If s2≤S0<s3, the correction coefficient for the defect degree is determined to be K2, and the corrected defect degree is [A1 orA2 or...or An-1]*K2; ...;

[0029] If sn-1≤S0<sn, the correction coefficient for the defect degree is determined to be Kn, and the corrected defect degree is [A1or A2 or...or An-1]*Kn.

[0030] In some embodiments disclosed in the present invention, a method for performing performance testing on a laminated soft-pack lithium battery includes:

[0031] Test the charge and discharge current of laminated soft-pack lithium batteries, and collect the abnormal difference current value G0 of charge and discharge when the charge and discharge current exceeds or falls below the charge and discharge standard range;

[0032] Test the charge and discharge voltage of laminated soft-pack lithium batteries, and collect the abnormal charge and discharge difference voltage value V0 when the charge and discharge voltage exceeds or is lower than the charge and discharge standard range;

[0033] The integral value of the abnormal charge and discharge difference current value G0 over the test time is calculated and recorded as the current negative performance index. The integral value of the abnormal charge and discharge difference voltage value V0 over the test time is calculated and recorded as the voltage negative performance index.

[0034] In some embodiments disclosed in the present invention, a method for correcting the defect level in a real-time defect level group includes:

[0035] If the current negative performance index or the voltage negative performance index is greater than or equal to a preset value, each defect level in the real-time defect level group is amplified so that the accumulated value of the amplified defect levels is greater than or equal to the preset value.

[0036] In some embodiments disclosed in the present invention, a method for determining whether a historical defect level group and a real-time defect level group in a quality inspection reference are consistent includes:

[0037] Compare each defect degree in the historical defect degree group and the real-time defect degree group, and calculate the defect degree difference to obtain a first defect degree difference, a second defect degree difference, and a third defect degree difference;

[0038] Based on the degree of influence of the defects of the preset diaphragm, the positive electrode sheet and the negative electrode sheet on the quality of the laminated soft-pack lithium battery, a first influence degree weight is configured for the first defect degree difference, and the first corresponding negative impact parameter is obtained by product, a second influence degree weight is configured for the second defect degree difference, and the second corresponding negative impact parameter is obtained by product, a third influence degree weight is configured for the third defect degree difference, and the third corresponding negative impact parameter is obtained by product, and the sum of the first corresponding negative impact parameter, the second corresponding negative impact parameter and the third corresponding negative impact parameter is calculated to obtain a comprehensive corresponding negative impact parameter;

[0039] Calculate the difference between the preset standard compliance parameter and the comprehensive compliance negative impact parameter to obtain the compliance parameter. If the compliance parameter is greater than or equal to the preset value, it is determined that the historical defect degree group and the real-time defect degree group in the quality inspection reference are consistent.

[0040] In some embodiments disclosed in the present invention, there is also disclosed a laminated soft-pack lithium battery quality detection system, comprising:

[0041] The first module is used to segment the raw materials for the production of the diaphragm, the positive electrode sheet and the negative electrode sheet respectively, to form a number of diaphragm segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and to associate the diaphragm segments, positive electrode sheet segments and negative electrode sheet segments based on their equivalent assembly sequences, and record them as raw material segment groups;

[0042] The second module is used to analyze the diaphragm segment, the positive electrode segment and the negative electrode segment in each raw material segment group by using visual analysis technology, and based on the analysis results, define a first defect degree for the diaphragm segment, a second defect degree for the positive electrode sheet, and a third defect degree for the negative electrode sheet, identify the combination of the first defect degree, the second defect degree and the third defect degree as a historical defect degree group, and associate the historical defect degree group with the raw material segment group;

[0043] The third module is used to perform performance testing on the laminated soft-pack lithium battery corresponding to the raw material segmentation group, define performance indicators based on the test results, and associate the performance indicators with the historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results;

[0044] The fourth module is used to perform real-time detection of the diaphragms, positive electrodes and negative electrodes of the production line, and to define the degree of defects in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degree in the real-time defect degree group is corrected and accumulated and summed. Otherwise, the defect degree in the real-time defect degree group is directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, an unqualified alarm is issued for the corresponding diaphragm, positive electrode and negative electrode.

[0045] The present invention discloses a laminated soft-pack lithium battery quality detection method and system, which relates to the field of laminated soft-pack battery detection. First, the production raw materials such as diaphragms, positive plates and negative plates are segmented and associated to form raw material segment groups; then, the raw material segment groups are defect-detected using visual analysis technology, and different defect levels are defined; then, the laminated soft-pack lithium batteries corresponding to the raw material segment groups are performance-tested, and the performance indicators are associated with the historical defect level groups to obtain quality detection reference data; finally, the production line is inspected in real time. If the real-time defect level group is consistent with the historical defect level group, corrections are made and accumulated and summed. If the total defect level reaches a preset value, an unqualified alarm is issued. Through the above technical solution, the present invention realizes timely quality warnings in the production stage, reduces production costs and improves the yield rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A method step diagram of a laminated soft-pack lithium battery quality detection method disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0048] The purpose of the present invention is to provide a laminated soft-pack lithium battery quality detection method and system that can perform real-time detection on the production of laminated soft-pack lithium batteries and issue timely alarms.

[0049] In order to achieve the above object, the present invention adopts the following technical solutions:

[0050] See also Figure 1 , a laminated soft-pack lithium battery quality detection method, comprising:

[0051] Step S100, the production raw materials of the diaphragm, the positive electrode sheet and the negative electrode sheet are segmented respectively to form a number of diaphragm segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and based on the equivalent assembly sequence they belong to, the diaphragm segments, positive electrode sheet segments and negative electrode sheet segments are associated and recorded as raw material segment groups.

[0052] Step S200, using visual analysis technology, analyze the diaphragm segment, positive electrode sheet segment and negative electrode sheet segment in each raw material segment group, and based on the analysis results, define a first defect degree for the diaphragm segment, a second defect degree for the positive electrode sheet, and a third defect degree for the negative electrode sheet, and identify the combination of the first defect degree, the second defect degree and the third defect degree as a historical defect degree group, and associate the historical defect degree group with the raw material segment group.

[0053] This step uses visual analysis technology to analyze the separator segments, positive electrode segments, and negative electrode segments in each raw material segment group. The principle is that visual analysis technology can identify defects in raw materials with high accuracy, such as wrinkles, scratches, dirt, and holes. By defining the first, second, and third defect levels, these defects can be quantified to provide data support for subsequent quality control and decision-making. This defect detection method based on visual analysis technology is the key to achieving accurate quality control.

[0054] In some embodiments disclosed in the present invention, the method of analyzing the separator segment, the positive electrode segment and the negative electrode segment in each raw material segment group by using visual analysis technology includes:

[0055] Step S201 , collecting the separator segmentation image, the positive electrode sheet segmentation image and the negative electrode sheet segmentation image corresponding to each raw material segmentation group, to obtain a raw material segmentation image group.

[0056] Step S202, preprocessing each image in the raw segmented image group, and extracting features from the preprocessed image, wherein the extracted features include color, texture and shape.

[0057] This step preprocesses each image in the raw material segmentation image group and performs feature extraction. Preprocessing may include denoising, contrast enhancement, grayscale and other operations to improve image quality and improve the accuracy of defect detection. Feature extraction focuses on extracting meaningful features from the image, such as color, texture and shape. These features are the key basis for identifying defects and are crucial for subsequent defect comparison and identification.

[0058] Step S203 , comparing the extracted image features with a preset defect template, identifying defects in each image, and marking the defects in the image.

[0059] This step compares the extracted image features with the preset defect templates to identify and mark the defects in each image. The principle is that by pre-defining the feature templates of various defects, a defect library can be established. After the features are extracted from the raw material segmented image, they can be compared with the templates in the defect library to identify whether there are defects. This comparison method is based on pattern recognition and machine learning technology, which can achieve efficient and accurate defect detection. By marking defects, an intuitive and visual basis can be provided for subsequent quality control and decision-making.

[0060] In some embodiments disclosed herein, defects in the image include wrinkles, scratches, dirt, and holes.

[0061] In some embodiments disclosed in the present invention, based on the analysis results, the method of defining the degree of defects for the separator segment, the positive electrode segment and the negative electrode segment respectively includes:

[0062] In step S204 , a number of defect types are set for defects, and a length comparison array [a1, a2, ..., an] and an area comparison array [s1, s2, ..., sn] are set for each defect type.

[0063] Step S205, determine the defect type of the defect, and call the corresponding length comparison array and area comparison array based on the defect type, obtain the longest distance A0 between the defect edges and the area S0 of the defect mapping, and compare the longest length A0 and the area comparison array [a1, a2, ..., an].

[0064] If a1≤A0<a2, the defect degree of the defect is defined as A1.

[0065] If a2≤A0<a3, the defect degree of the defect is defined as A2.

[0066] If an-1≤A0<an, the defect degree of the defect is defined as An-1.

[0067] Step 206 , analyzing the area S0 of the defect mapping, if it is greater than or equal to a preset value, comparing the area S0 with the area comparison array [s1, s2, ..., sn], and correcting the defect degree based on the comparison result.

[0068] In some embodiments disclosed in the present invention, the method for correcting the degree of defect includes:

[0069] Step S207, comparing the area S0 with the area comparison array [s1, s2, ..., sn].

[0070] If s1≤S0<s2, the correction coefficient for the defect degree is determined to be K1, and the corrected defect degree is [A1 orA2 or...or An-1]*K1.

[0071] If s2≤S0<s3, the correction coefficient for the defect degree is determined to be K2, and the corrected defect degree is [A1 orA2 or...or An-1]*K2.

[0072] If sn-1≤S0<sn, the correction coefficient for the defect degree is determined to be Kn, and the corrected defect degree is [A1or A2 or...or An-1]*Kn.

[0073] Step S300, perform performance testing on the laminated soft-pack lithium batteries corresponding to the raw material segmentation group, define performance indicators based on the test results, and associate the performance indicators with the historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results.

[0074] This step performs performance testing on the laminated soft-pack lithium batteries corresponding to the raw material segmentation group, and associates the performance indicators with the historical defect degree group. The principle is that the performance indicators of lithium batteries (such as voltage and current) are often affected by raw material defects. By associating the performance indicators with the historical defect degree group, quality inspection reference data can be obtained to understand how raw material defects affect battery performance. This association method provides a basis for timely adjustment and optimization in the production process.

[0075] In some embodiments disclosed in the present invention, a method for performing performance testing on a laminated soft-pack lithium battery includes:

[0076] Step S301, testing the charge and discharge current of the laminated soft-pack lithium battery, and collecting the charge and discharge abnormal difference current value G0 when the charge and discharge current exceeds or is lower than the charge and discharge standard range.

[0077] Step S302, testing the charge and discharge voltage of the laminated soft-pack lithium battery, and collecting the charge and discharge abnormal difference voltage value V0 when the charge and discharge voltage exceeds or is lower than the charge and discharge standard range.

[0078] Step S303, calculating the integral value of the abnormal charge and discharge difference current value G0 over the test time, which is recorded as the current negative performance index, and calculating the integral value of the abnormal charge and discharge difference voltage value V0 over the test time, which is recorded as the voltage negative performance index.

[0079] Step S400, real-time detection is performed on the diaphragms, positive electrodes and negative electrodes of the production line, and the degree of defects is defined in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degrees in the real-time defect degree group are corrected and accumulated and summed. Otherwise, the defect degrees in the real-time defect degree group are directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, an unqualified alarm is issued for the corresponding diaphragm, positive electrode and negative electrode.

[0080] This step performs real-time inspection of the diaphragms, positive plates, and negative plates of the production line, and defines the degree of defects in real time. The principle is that real-time quality control is the key to ensuring product quality. Through real-time inspection and correction of defect levels, potential quality problems can be discovered and dealt with in a timely manner to avoid the production of unqualified products. When the real-time cumulative defect level reaches or exceeds the preset value, the system will issue an unqualified alarm, which helps production personnel take timely measures to make adjustments to ensure the stable operation of the production line and the consistency of product quality.

[0081] In some embodiments disclosed in the present invention, a method for correcting the defect level in a real-time defect level group includes:

[0082] Step S401 : if the current negative performance index or the voltage negative performance index is greater than or equal to a preset value, each defect level in the real-time defect level group is amplified so that the accumulated value of the defect levels after amplification is greater than or equal to a preset value.

[0083] In some embodiments disclosed in the present invention, a method for determining whether a historical defect level group and a real-time defect level group in a quality inspection reference are consistent includes:

[0084] Step S402 , compare each defect level in the historical defect level group and the real-time defect level group, and calculate the defect level difference to obtain a first defect level difference, a second defect level difference, and a third defect level difference.

[0085] Step S403, based on the degree of influence of the preset defects of the diaphragm, the positive electrode sheet and the negative electrode sheet on the quality of the laminated soft-pack lithium battery, a first influence degree weight is configured for the first defect degree difference, and the first corresponding negative impact parameter is obtained by product, a second influence degree weight is configured for the second defect degree difference, and the second corresponding negative impact parameter is obtained by product, a third influence degree weight is configured for the third defect degree difference, and the third corresponding negative impact parameter is obtained by product, and the sum of the first corresponding negative impact parameter, the second corresponding negative impact parameter and the third corresponding negative impact parameter is calculated to obtain a comprehensive corresponding negative impact parameter.

[0086] Step S404, calculate the difference between the preset standard conforming parameter and the comprehensive conforming negative impact parameter to obtain the conforming parameter. If the conforming parameter is greater than or equal to the preset value, it is determined that the historical defect degree group and the real-time defect degree group in the quality inspection reference are consistent.

[0087] In some embodiments disclosed in the present invention, there is also disclosed a laminated soft-pack lithium battery quality detection system, comprising:

[0088] The first module is used to segment the raw materials for the production of diaphragms, positive electrode sheets and negative electrode sheets respectively, forming a number of diaphragm segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and based on the equivalent assembly sequence they belong to, the diaphragm segments, positive electrode sheet segments and negative electrode sheet segments are associated and recorded as raw material segment groups.

[0089] The second module is used to use visual analysis technology to analyze the diaphragm segment, positive electrode sheet segment and negative electrode sheet segment in each raw material segment group, and based on the analysis results, define a first defect degree for the diaphragm segment, a second defect degree for the positive electrode sheet, and a third defect degree for the negative electrode sheet, identify the combination of the first defect degree, the second defect degree and the third defect degree as a historical defect degree group, and associate the historical defect degree group with the raw material segment group.

[0090] The third module is used to perform performance testing on the laminated soft-pack lithium batteries corresponding to the raw material segmentation group, define performance indicators based on the test results, and associate the performance indicators with historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results.

[0091] The fourth module is used to perform real-time detection of the diaphragms, positive electrodes and negative electrodes of the production line, and to define the degree of defects in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degree in the real-time defect degree group is corrected and accumulated and summed. Otherwise, the defect degree in the real-time defect degree group is directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, an unqualified alarm is issued for the corresponding diaphragm, positive electrode and negative electrode.

[0092] The present invention discloses a laminated soft-pack lithium battery quality detection method and system, which relates to the field of laminated soft-pack battery detection. First, the production raw materials such as diaphragms, positive plates and negative plates are segmented and associated to form raw material segment groups; then, the raw material segment groups are defect-detected using visual analysis technology, and different defect levels are defined; then, the laminated soft-pack lithium batteries corresponding to the raw material segment groups are performance-tested, and the performance indicators are associated with the historical defect level groups to obtain quality detection reference data; finally, the production line is inspected in real time. If the real-time defect level group is consistent with the historical defect level group, corrections are made and accumulated and summed. If the total defect level reaches a preset value, an unqualified alarm is issued. Through the above technical solution, the present invention realizes timely quality warnings in the production stage, reduces production costs and improves the yield rate.

[0093] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for quality inspection of laminated soft-pack lithium batteries, characterized in that: include: The production materials of the separator, the positive electrode sheet and the negative electrode sheet are segmented respectively to form a number of separator segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and the separator segments, positive electrode sheet segments and negative electrode sheet segments are associated based on the equivalent assembly sequence to which they belong, and recorded as a raw material segment group; Using visual analysis technology, the separator segment, the positive electrode sheet segment and the negative electrode sheet segment in each raw material segment group are analyzed, and based on the analysis results, a first defect degree is defined for the separator segment, a second defect degree is defined for the positive electrode sheet, and a third defect degree is defined for the negative electrode sheet, and a combination of the first defect degree, the second defect degree and the third defect degree is identified as a historical defect degree group, and the historical defect degree group is associated with the raw material segment group; Perform performance tests on the laminated soft-pack lithium batteries corresponding to the raw material segmentation groups, define performance indicators based on the test results, and associate the performance indicators with the historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results; The diaphragms, positive electrodes and negative electrodes of the production line are inspected in real time, and the degree of defects is defined in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degree in the real-time defect degree group is corrected and accumulated and summed. Otherwise, the defect degree in the real-time defect degree group is directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, the corresponding diaphragm, positive electrode and negative electrode will be alarmed as unqualified.

2. A laminated soft-pack lithium battery quality detection method according to claim 1, characterized in that: The method for analyzing the separator segment, the positive electrode segment and the negative electrode segment in each raw material segment group by using visual analysis technology includes: Collecting the separator segmentation image, the positive electrode sheet segmentation image and the negative electrode sheet segmentation image corresponding to each raw material segmentation group to obtain a raw material segmentation image group; Preprocessing each image in the raw segmented image group, and extracting features from the preprocessed image, wherein the extracted features include color, texture and shape; The extracted image features are compared with the preset defect templates to identify the defects in each image and mark the defects in the image.

3. A laminated soft-pack lithium battery quality detection method according to claim 2, characterized in that: Defects in the image include wrinkles, scratches, dirt, and holes.

4. A laminated soft-pack lithium battery quality detection method according to claim 2, characterized in that: Based on the analysis results, the methods for defining the degree of defects for the separator segment, the positive electrode segment and the negative electrode segment include: Several defect types are set for defects, and a length comparison array [a1, a2, ..., an] and an area comparison array [s1, s2, ..., sn] are set for each defect type; Determine the defect type of the defect, and call the corresponding length comparison array and area comparison array based on the defect type to obtain the longest distance A0 between the defect edges and the area S0 of the defect mapping, and compare the longest length A0 with the area comparison array [a1, a2, ..., an]: If a1≤A0<a2, the defect degree of the defect is defined as A1; If a2≤A0<a3, the defect degree of the defect is defined as A2; ...； If an-1≤A0<an, the defect degree of the defect is defined as An-1; The area S0 of the defect mapping is analyzed. If it is greater than or equal to the preset value, the area S0 is compared with the area comparison array [s1, s2, ..., sn], and the defect degree is corrected based on the comparison result.

5. A laminated soft-pack lithium battery quality detection method according to claim 4, characterized in that: Methods for correcting the degree of defects include: Compare the area S0 with the area comparison array [s1,s2,...,sn]: If s1≤S0<s2, the correction coefficient for the defect degree is determined to be K1, and the corrected defect degree is [A1 or A2or...or An-1]*K1; If s2≤S0<s3, the correction coefficient for the defect degree is determined to be K2, and the corrected defect degree is [A1 or A2or...or An-1]*K2; ...； If sn-1≤S0<sn, the correction coefficient for the defect degree is determined to be Kn, and the corrected defect degree is [A1 or A2or...or An-1]*Kn.

6. A laminated soft-pack lithium battery quality detection method according to claim 1, characterized in that: The method for testing the performance of laminated soft-pack lithium batteries includes: Test the charge and discharge current of laminated soft-pack lithium batteries, and collect the abnormal difference current value G0 of charge and discharge when the charge and discharge current exceeds or falls below the charge and discharge standard range; Test the charge and discharge voltage of laminated soft-pack lithium batteries, and collect the abnormal charge and discharge difference voltage value V0 when the charge and discharge voltage exceeds or is lower than the charge and discharge standard range; The integral value of the abnormal charge and discharge difference current value G0 over the test time is calculated and recorded as the current negative performance index. The integral value of the abnormal charge and discharge difference voltage value V0 over the test time is calculated and recorded as the voltage negative performance index.

7. A laminated soft-pack lithium battery quality detection method according to claim 6, characterized in that: The method for correcting the defect level in the real-time defect level group includes: If the current negative performance index or the voltage negative performance index is greater than or equal to a preset value, each defect level in the real-time defect level group is amplified so that the accumulated value of the amplified defect levels is greater than or equal to the preset value.

8. A laminated soft-pack lithium battery quality detection method according to claim 1, characterized in that: Methods for determining whether the historical defect level group in the quality inspection reference and the real-time defect level group are consistent include: Compare each defect degree in the historical defect degree group and the real-time defect degree group, and calculate the defect degree difference to obtain a first defect degree difference, a second defect degree difference, and a third defect degree difference; Based on the degree of influence of the defects of the preset diaphragm, the positive electrode sheet and the negative electrode sheet on the quality of the laminated soft-pack lithium battery, a first influence degree weight is configured for the first defect degree difference, and the first corresponding negative impact parameter is obtained by product, a second influence degree weight is configured for the second defect degree difference, and the second corresponding negative impact parameter is obtained by product, a third influence degree weight is configured for the third defect degree difference, and the third corresponding negative impact parameter is obtained by product, and the sum of the first corresponding negative impact parameter, the second corresponding negative impact parameter and the third corresponding negative impact parameter is calculated to obtain a comprehensive corresponding negative impact parameter; Calculate the difference between the preset standard compliance parameter and the comprehensive compliance negative impact parameter to obtain the compliance parameter. If the compliance parameter is greater than or equal to the preset value, it is determined that the historical defect degree group and the real-time defect degree group in the quality inspection reference are consistent.

9. A laminated soft-pack lithium battery quality inspection system, characterized in that: include: The first module is used to segment the raw materials for the production of the diaphragm, the positive electrode sheet and the negative electrode sheet respectively, to form a number of diaphragm segments, positive electrode sheet segments and negative electrode sheet segments corresponding to the production process of the production line, and to associate the diaphragm segments, positive electrode sheet segments and negative electrode sheet segments based on their equivalent assembly sequences, and record them as raw material segment groups; The second module is used to analyze the diaphragm segment, the positive electrode segment and the negative electrode segment in each raw material segment group by using visual analysis technology, and based on the analysis results, define a first defect degree for the diaphragm segment, a second defect degree for the positive electrode sheet, and a third defect degree for the negative electrode sheet, identify the combination of the first defect degree, the second defect degree and the third defect degree as a historical defect degree group, and associate the historical defect degree group with the raw material segment group; The third module is used to perform performance testing on the laminated soft-pack lithium battery corresponding to the raw material segmentation group, define performance indicators based on the test results, and associate the performance indicators with the historical defect degree groups to obtain quality inspection reference data, analyze several performance indicators, and mark the historical defect degree groups based on the analysis results; The fourth module is used to perform real-time detection of the diaphragms, positive electrodes and negative electrodes of the production line, and to define the degree of defects in real time to form a real-time defect degree group. If there is a historical defect degree group in the quality inspection reference data that matches the real-time defect degree group, the defect degree in the real-time defect degree group is corrected and accumulated and summed. Otherwise, the defect degree in the real-time defect degree group is directly accumulated and summed. The result of the accumulation and summation is the total defect degree. If the total defect degree is greater than or equal to the preset value, an unqualified alarm is issued for the corresponding diaphragm, positive electrode and negative electrode.

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