Intelligent detection method and system for battery module assembly and medium

Abstract

The invention provides a battery module assembly intelligent detection method and system and a medium. The method comprises the following steps: preprocessing a shot image of a target battery module to obtain a processed image, carrying out feature extraction to obtain feature data of the processed image, further processing to obtain a module appearance evaluation index, carrying out appearance qualification judgment on the target battery module, and carrying out electrical performance detection test on the target battery module. Processing to obtain an electrical performance conformity index, performing connection reliability detection test on the target battery module, processing to obtain a connection reliability index, performing safety performance detection test on the target battery module, processing to obtain a safety index, and processing in combination with the electrical performance conformity index and the connection reliability index. And the battery module comprehensive evaluation index is obtained, and the assembly qualification of the target battery module is judged and corresponding processing is performed, so that the battery module assembly intelligent detection technology is realized.

Description

Technical Field

[0001] The present application relates to the technical field of battery module assembly, and in particular to a battery module assembly intelligent detection method, system and medium. Background Art

[0002] Battery module assembly involves key links such as precise assembly and electrical connection of multiple parts. During the battery module assembly process, the assembly accuracy, connection status, appearance integrity, etc. of multiple parts need to be strictly inspected to ensure the performance and reliability of the battery module. A single sensor detection method has limitations when detecting the assembly quality of battery modules. For example, it is difficult to accurately detect the electrical connection performance inside the battery by relying solely on machine vision, and it is impossible to fully evaluate the appearance assembly accuracy of parts using only electrical sensors. Traditional manual detection methods are inefficient, unstable in accuracy, and difficult to meet the needs of large-scale production. Therefore, a multi-sensor fusion detection method is needed to comprehensively and accurately detect the assembly quality of battery modules.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of the present application is to provide a method, system and medium for intelligent detection of battery module assembly, which can obtain a processed image by pre-processing the captured image of the target battery module, obtain feature data of the processed image by feature extraction, further process to obtain a module appearance evaluation index, and make an appearance qualification judgment on the target battery module, perform an electrical performance detection test on the target battery module to obtain an electrical performance compliance index, perform a connection reliability detection test on the target battery module to obtain a connection reliability index, perform a safety performance detection test on the target battery module to obtain a safety index, and process the electrical performance compliance index and the connection reliability index to obtain a comprehensive evaluation index of the battery module, judge the assembly qualification of the target battery module and perform corresponding processing, thereby realizing the technology of intelligent detection of battery module assembly.

[0005] The present application also provides a battery module assembly intelligent detection method, comprising the following steps: Acquire a captured image of a target battery module and perform preprocessing to obtain a processed image; Extracting features from the processed image to obtain processed image feature data, processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; If the appearance of the target battery module is qualified, an electrical performance test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance test result; Performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; Performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; The electrical performance compliance index, connection reliability index and safety index are processed to obtain a comprehensive evaluation index of the battery module, and the assembly conformity of the target battery module is judged and processed accordingly.

[0006] Optionally, in the battery module assembly intelligent detection method described in the present application, the acquiring of the captured image of the target battery module and performing preprocessing to obtain the processed image includes: Select an appropriate industrial camera based on the standard size and detection accuracy of the target battery module; Shooting the target battery module at multiple angles according to the adapted industrial camera to obtain a photographed image of the target battery module; Processing the captured image according to an image preprocessing method to obtain a processed image; The image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

[0007] Optionally, in the battery module assembly intelligent detection method described in the present application, the feature extraction of the processed image to obtain the processed image feature data is performed, and the processed image is combined with the standard image feature data to obtain the module appearance evaluation index, and the appearance qualification of the target battery module is determined, including: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

[0008] Optionally, in the battery module assembly intelligent detection method described in the present application, if the appearance of the target battery module is qualified, the target battery module is subjected to an electrical performance detection test, and the electrical performance test result is processed to obtain an electrical performance compliance index, including: If the appearance of the target battery module is qualified, performing an electrical performance test on the target battery module; The electrical performance detection test includes a voltage detection test, an internal resistance detection test and a capacity detection test; Extract the test result record data of the voltage detection test to obtain the total module voltage data, the maximum value data of the single cell voltage and the extreme value data of the single cell voltage; Extracting the test result record data of the internal resistance detection test to obtain module internal resistance data and module internal resistance growth rate data; Extracting the test result record data of the capacity detection test to obtain the actual capacity data of the module; The module total voltage data, the single cell voltage maximum value data, the single cell voltage extreme value data, the module internal resistance data and the module internal resistance growth rate data are processed in combination with the module actual capacity data to obtain an electrical performance compliance index.

[0009] Optionally, in the battery module assembly intelligent detection method described in the present application, performing a connection reliability detection test on the target battery module and processing the connection reliability detection result to obtain a connection reliability index include: Performing a connection reliability test on the target battery module, including a connection sheet tension test and a connection resistance test; Extracting data recorded according to the test result of the connecting piece tension detection test to obtain the connecting piece limit tension value data; Extracting the data recorded according to the test result of the connection resistance detection test to obtain the maximum value data of the connection point resistance; The connection reliability index is obtained by processing the data of the ultimate tensile force value of the connection piece and the data of the maximum value of the resistance of the connection point.

[0010] Optionally, in the battery module assembly intelligent detection method described in the present application, the processing is performed according to the electrical performance compliance index, the connection reliability index and the safety index to obtain a battery module comprehensive evaluation index, and the assembly qualification of the target battery module is judged and processed accordingly, including: Processing is performed according to the electrical performance compliance index, connection reliability index and safety index to obtain a comprehensive evaluation index of the battery module; Comparing the battery module comprehensive evaluation index with a preset battery module comprehensive evaluation threshold to obtain a threshold comparison result; Determining whether the assembly of the target battery module is qualified according to the threshold comparison result; If the threshold comparison result is greater than a preset threshold, the assembly of the target battery module is qualified; Otherwise, it will be judged as unqualified and handled accordingly.

[0011] In a second aspect, the present application provides a battery module assembly intelligent detection system, the system comprising: a memory and a processor, the memory comprising a program of a battery module assembly intelligent detection method, the program of the battery module assembly intelligent detection method being executed by the processor to implement the following steps: Acquire a captured image of a target battery module and perform preprocessing to obtain a processed image; Extracting features from the processed image to obtain processed image feature data, processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; If the appearance of the target battery module is qualified, an electrical performance test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance test result; Performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; Performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; The electrical performance compliance index, connection reliability index and safety index are processed to obtain a comprehensive evaluation index of the battery module, and the assembly conformity of the target battery module is judged and processed accordingly.

[0012] Optionally, in the battery module assembly intelligent detection system described in the present application, the step of acquiring a captured image of the target battery module and performing preprocessing to obtain a processed image includes: Select an appropriate industrial camera based on the standard size and detection accuracy of the target battery module; Shooting the target battery module at multiple angles according to the adapted industrial camera to obtain a photographed image of the target battery module; Processing the captured image according to an image preprocessing method to obtain a processed image; The image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

[0013] Optionally, in the battery module assembly intelligent detection system described in the present application, the feature extraction of the processed image to obtain the processed image feature data, and processing in combination with the standard image feature data to obtain the module appearance evaluation index, and performing the appearance qualification judgment of the target battery module, includes: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

[0014] In a third aspect, the present application also provides a computer-readable storage medium, in which a battery module assembly intelligent detection method program is stored. When the battery module assembly intelligent detection method program is executed by a processor, the steps of the battery module assembly intelligent detection method as described in any one of the above items are implemented.

[0015] As can be seen from the above, the battery module assembly intelligent detection method, system and medium disclosed in the present invention obtain a captured image of the target battery module, perform preprocessing to obtain a processed image, perform feature extraction on the processed image, obtain feature data of the processed image, and process it in combination with the standard image feature data to obtain a module appearance evaluation index, and make a judgment on the appearance conformity of the target battery module. If the appearance of the target battery module is qualified, an electrical performance detection test is performed on the target battery module, and the electrical performance compliance index is obtained according to the electrical performance detection result. A connection reliability detection test is performed on the target battery module, and the connection reliability index is obtained according to the connection reliability detection result. A safety performance detection test is performed on the target battery module, and the safety index is obtained according to the safety performance detection result. A comprehensive evaluation index of the battery module is obtained according to the electrical performance compliance index, the connection reliability index and the safety index. The assembly conformity of the target battery module is judged and processed accordingly, thereby realizing the technology of intelligent detection of battery module assembly.

[0016] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flow chart of a battery module assembly intelligent detection method provided in an embodiment of the present application; Figure 2 A flowchart of obtaining a processed image of a battery module assembly intelligent detection method provided in an embodiment of the present application; Figure 3 A flow chart of obtaining an electrical performance compliance index for a battery module assembly intelligent detection method provided in an embodiment of the present application; Figure 4 A flow chart for obtaining a connection reliability index for a battery module assembly intelligent detection method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0020] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0021] Please refer to Figure 1 , Figure 11 is a flow chart of a battery module assembly intelligent detection method in some embodiments of the present application. The battery module assembly intelligent detection method is used in terminal devices, such as computers, mobile phone terminals, etc. The battery module assembly intelligent detection method includes the following steps: S11, obtaining a captured image of a target battery module, and performing preprocessing to obtain a processed image; S12, extracting features from the processed image to obtain processed image feature data, and processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; S13, if the appearance of the target battery module is qualified, perform an electrical performance test on the target battery module, and obtain an electrical performance compliance index according to the electrical performance test result; S14, performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; S15, performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; S16, performing processing according to the electrical performance compliance index, connection reliability index and safety index to obtain a comprehensive evaluation index of the battery module, judging the assembly conformity of the target battery module and performing corresponding processing.

[0022] It should be noted that the assembly of battery modules involves key links such as the precise assembly and electrical connection of multiple parts. During the assembly of battery modules, the assembly accuracy, connection status, and appearance integrity of multiple parts need to be strictly inspected to ensure the performance and reliability of the battery module. A single sensor detection method has limitations in detecting the assembly quality of battery modules. For example, it is difficult to accurately detect the electrical connection performance inside the battery by relying solely on machine vision, and it is impossible to fully evaluate the appearance assembly accuracy of parts using only electrical sensors. Traditional manual detection methods are inefficient, unstable in accuracy, and difficult to meet the needs of large-scale production. Therefore, a multi-sensor fusion detection method is needed to comprehensively and accurately detect the assembly quality of battery modules. In this embodiment, firstly, a captured image of the target battery module is acquired, and a processed image is obtained by preprocessing. The feature extraction of the post-image is performed to obtain the feature data of the processed image, and the processed data is combined with the standard image feature data to obtain the module appearance evaluation index, and the appearance qualification of the target battery module is judged. If the appearance of the target battery module is qualified, the target battery module is tested for electrical performance, and the electrical performance compliance index is obtained according to the electrical performance test results. The target battery module is tested for connection reliability, and the connection reliability index is obtained according to the connection reliability test results. The target battery module is tested for safety performance, and the safety index is obtained according to the safety performance test results. The comprehensive evaluation index of the battery module is obtained according to the electrical performance compliance index, the connection reliability index and the safety index. The assembly qualification of the target battery module is judged and processed accordingly, thereby realizing the technology of intelligent detection of battery module assembly.

[0023] Please refer to Figure 2 , Figure 2 The flowchart of obtaining the processed image of the battery module assembly intelligent detection method in some embodiments of the present application. According to the embodiment of the present invention, the acquisition of the captured image of the target battery module and the preprocessing to obtain the processed image include: S21. Select an appropriate industrial camera according to the standard size and detection accuracy of the target battery module; S22, photographing the target battery module at multiple angles using the adapted industrial camera to obtain photographed images of the target battery module; S23, processing the captured image according to an image preprocessing method to obtain a processed image; S24, the image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

[0024] It should be noted that for the assembly inspection of battery modules, the first step is to conduct an appearance integrity inspection. During the image acquisition system construction stage, the resolution and frame rate of the selected industrial camera are determined based on the standard size and inspection accuracy of the battery module. In addition, cameras are installed on the top and sides of the battery module as needed to obtain images at different angles. For image preprocessing, common algorithms such as weighted averaging can be used for grayscale processing. When filtering and denoising, appropriate filtering parameters are selected according to the characteristics of the noise. Image enhancement operations can be adaptively adjusted according to the histogram distribution of the image.

[0025] According to an embodiment of the present invention, the step of extracting features from the processed image to obtain processed image feature data, processing the processed image feature data in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module includes: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

[0026] It should be noted that for the preprocessed image, feature data, grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data are further extracted, and the corresponding standard feature data are obtained and processed one by one to obtain grayscale difference, texture deviation, shape accuracy, color difference and spatial relationship deviation data. The above data are then processed to obtain the module appearance evaluation index, which is then compared with the preset module appearance evaluation threshold, and whether the appearance of the target battery module is qualified is judged according to the comparison result; The calculation formula of the module appearance evaluation index is: ; in, is the module appearance evaluation index, , , , , They are grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data. , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0027] Please refer to Figure 3 , Figure 3 The flowchart of obtaining the electrical performance compliance index of the battery module assembly intelligent detection method in some embodiments of the present application. According to the embodiment of the present invention, if the appearance of the target battery module is qualified, the target battery module is subjected to an electrical performance detection test, and the electrical performance compliance index is obtained according to the electrical performance detection result, including: S31, if the appearance of the target battery module is qualified, perform an electrical performance test on the target battery module; S32, the electrical performance detection test includes a voltage detection test, an internal resistance detection test and a capacity detection test; S33, extracting the test result record data of the voltage detection test to obtain the module total voltage data, the single cell voltage maximum value data and the single cell voltage extreme difference value data; S34, extracting the test result record data of the internal resistance detection test to obtain module internal resistance data and module internal resistance growth rate data; S35, extracting the test result record data of the capacity detection test to obtain the actual capacity data of the module; S36, processing the module total voltage data, the single cell voltage maximum value data, the single cell voltage extreme value data, the module internal resistance data and the module internal resistance growth rate data in combination with the module actual capacity data to obtain an electrical performance compliance index.

[0028] It should be noted that if the appearance of the battery module is unqualified, it needs to be processed accordingly. Only when the appearance of the battery module is qualified, the target battery module is subjected to electrical performance testing, including voltage testing, internal resistance testing and capacity testing. The data recorded according to the test results of the voltage detection test are extracted to obtain the total module voltage, the maximum value of the single cell voltage and the extreme value of the single cell voltage. The difference in the single cell voltage should be within a certain range. For example, for lithium-ion battery modules, the voltage difference of the single cell generally does not exceed 0.05V. The data recorded according to the test results of the internal resistance detection test are extracted to obtain the module internal resistance and the module internal resistance growth rate data. By analyzing the internal resistance data, the health of the battery module can be judged. The data recorded according to the test results of the capacity detection test are extracted to obtain the actual capacity data of the module, wherein the actual capacity can be calculated based on the actual discharge time and discharge current. Finally, the above data are processed to obtain the electrical performance compliance index. The calculation formula of the electrical performance compliance index is: ; in, is the electrical performance compliance index, , , They are the total voltage data of the module, the maximum value data of the single cell voltage, and the extreme difference value data of the single cell voltage. , They are module internal resistance data and module internal resistance growth rate data. The actual capacity data of the module. , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0029] Please refer to Figure 4 , Figure 4 The flowchart of obtaining the connection reliability index of the battery module assembly intelligent detection method in some embodiments of the present application. According to the embodiment of the present invention, the connection reliability detection test is performed on the target battery module, and the connection reliability index is obtained according to the connection reliability detection result, including: S41, performing a connection reliability test on the target battery module, including a connection sheet tension test and a connection resistance test; S42, extracting the test result record data of the connecting piece tension detection test to obtain the connecting piece limit tension value data; S43, extracting the test result record data of the connection resistance detection test to obtain the maximum value data of the connection point resistance; S44, processing is performed according to the data of the ultimate tensile force value of the connecting piece and the data of the maximum value of the resistance of the connecting point to obtain a connection reliability index.

[0030] It should be noted that in order to ensure the reliable connection of the battery module, it is necessary to perform connection reliability detection tests on it, including connection piece tension detection tests and connection resistance detection tests. On the one hand, a special tension test device is designed to perform tension tests on the connection pieces of the battery module, and the data is extracted according to the test results to obtain the connection piece limit tension value data. On the other hand, a microohmmeter or milliohmmeter is used to detect the resistance of the connection part of the battery module, and the data is extracted according to the test results to obtain the maximum value data of the connection point resistance, and then the connection piece limit tension value data and the connection point resistance maximum value data are processed to obtain the connection reliability index. The calculation formula of the connection reliability index is: ; in, is the connection reliability index, , They are the data of the ultimate tensile force of the connecting piece and the maximum value of the resistance of the connecting point. , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0031] According to an embodiment of the present invention, the electrical performance compliance index, the connection reliability index and the safety index are processed to obtain a comprehensive evaluation index of a battery module, and the assembly eligibility of the target battery module is judged and processed accordingly, including: Processing is performed according to the electrical performance compliance index, connection reliability index and safety index to obtain a comprehensive evaluation index of the battery module; Comparing the battery module comprehensive evaluation index with a preset battery module comprehensive evaluation threshold to obtain a threshold comparison result; Determining whether the assembly of the target battery module is qualified according to the threshold comparison result; If the threshold comparison result is greater than a preset threshold, the assembly of the target battery module is qualified; Otherwise, it will be judged as unqualified and handled accordingly.

[0032] It should be noted that the electrical performance compliance index, connection reliability index and safety index obtained through several detection processes are processed to obtain a comprehensive evaluation index of the battery module, which is then compared with a preset threshold value. The comparison result is used to determine whether the assembly of the target battery module is qualified. If the threshold comparison result is greater than the preset threshold value, the assembly of the target battery module is qualified. Otherwise, it is determined to be unqualified and corresponding processing is performed; The calculation formula of the comprehensive evaluation index of the battery module is: ; in, It is the comprehensive evaluation index of battery module. , , They are electrical performance compliance index, connection reliability index, and safety index. , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0033] According to an embodiment of the present invention, it also includes: The safety performance test of the target battery module is performed, and the safety index is obtained according to the safety performance test result, specifically including: Performing safety performance testing on the target battery module, including insulation performance testing and air tightness testing; Extract the test result record data of the insulation performance detection test to obtain insulation resistance value data and withstand voltage value data; Extracting the test result record data of the air tightness detection test to obtain pressure decay rate data; According to the insulation resistance value data and the withstand voltage value data, combined with the pressure decay rate data, a safety index is obtained; The calculation formula of the safety index is: ; in, is the safety index, , They are insulation resistance data and withstand voltage data. is the pressure decay rate data, , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0034] It should be noted that the target battery module is subjected to safety performance testing, including insulation performance testing and air tightness testing. The test result record data of the insulation performance testing is extracted to obtain insulation resistance value data and withstand voltage value data. The test result record data of the air tightness testing is extracted to obtain pressure decay rate data. The insulation resistance value data and withstand voltage value data are processed in combination with the pressure decay rate data to obtain a safety index.

[0035] In a second aspect, the present invention further discloses a battery module assembly intelligent detection system, comprising a memory and a processor, wherein the memory comprises a battery module assembly intelligent detection method program, and when the battery module assembly intelligent detection method program is executed by the processor, the following steps are implemented: Acquire a captured image of a target battery module and perform preprocessing to obtain a processed image; Extracting features from the processed image to obtain processed image feature data, processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; If the appearance of the target battery module is qualified, an electrical performance test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance test result; Performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; Performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; The electrical performance compliance index, connection reliability index and safety index are processed to obtain a comprehensive evaluation index of the battery module, and the assembly conformity of the target battery module is judged and processed accordingly.

[0036] It should be noted that the assembly of battery modules involves key links such as the precise assembly and electrical connection of multiple parts. During the assembly of battery modules, the assembly accuracy, connection status, and appearance integrity of multiple parts need to be strictly inspected to ensure the performance and reliability of the battery module. A single sensor detection method has limitations in detecting the assembly quality of battery modules. For example, it is difficult to accurately detect the electrical connection performance inside the battery by relying solely on machine vision, and it is impossible to fully evaluate the appearance assembly accuracy of parts using only electrical sensors. Traditional manual detection methods are inefficient, unstable in accuracy, and difficult to meet the needs of large-scale production. Therefore, a multi-sensor fusion detection method is needed to comprehensively and accurately detect the assembly quality of battery modules. In this embodiment, firstly, a captured image of the target battery module is acquired, and a processed image is obtained by preprocessing. The feature extraction of the post-image is performed to obtain the feature data of the processed image, and the processed data is combined with the standard image feature data to obtain the module appearance evaluation index, and the appearance qualification of the target battery module is judged. If the appearance of the target battery module is qualified, the target battery module is tested for electrical performance, and the electrical performance compliance index is obtained according to the electrical performance test results. The target battery module is tested for connection reliability, and the connection reliability index is obtained according to the connection reliability test results. The target battery module is tested for safety performance, and the safety index is obtained according to the safety performance test results. The comprehensive evaluation index of the battery module is obtained according to the electrical performance compliance index, the connection reliability index and the safety index. The assembly qualification of the target battery module is judged and processed accordingly, thereby realizing the technology of intelligent detection of battery module assembly.

[0037] According to an embodiment of the present invention, the step of acquiring a captured image of a target battery module and performing preprocessing to obtain a processed image includes: Select an appropriate industrial camera based on the standard size and detection accuracy of the target battery module; Shooting the target battery module at multiple angles according to the adapted industrial camera to obtain a photographed image of the target battery module; Processing the captured image according to an image preprocessing method to obtain a processed image; The image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

[0038] It should be noted that for the assembly inspection of battery modules, the first step is to conduct an appearance integrity inspection. During the image acquisition system construction stage, the resolution and frame rate of the selected industrial camera are determined based on the standard size and inspection accuracy of the battery module. In addition, cameras are installed on the top and sides of the battery module as needed to obtain images at different angles. For image preprocessing, common algorithms such as weighted averaging can be used for grayscale processing. When filtering and denoising, appropriate filtering parameters are selected according to the characteristics of the noise. Image enhancement operations can be adaptively adjusted according to the histogram distribution of the image.

[0039] According to an embodiment of the present invention, the step of extracting features from the processed image to obtain processed image feature data, processing the processed image feature data in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module includes: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

[0040] It should be noted that for the preprocessed image, feature data, grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data are further extracted, and the corresponding standard feature data are obtained and processed one by one to obtain grayscale difference, texture deviation, shape accuracy, color difference and spatial relationship deviation data. The above data are then processed to obtain the module appearance evaluation index, which is then compared with the preset module appearance evaluation threshold, and whether the appearance of the target battery module is qualified is judged according to the comparison result; The calculation formula of the module appearance evaluation index is: ; in, is the module appearance evaluation index, , , , , They are grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data. , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0041] According to an embodiment of the present invention, if the appearance of the target battery module is qualified, the target battery module is subjected to an electrical performance test, and an electrical performance compliance index is obtained according to the electrical performance test result, including: If the appearance of the target battery module is qualified, performing an electrical performance test on the target battery module; The electrical performance detection test includes a voltage detection test, an internal resistance detection test and a capacity detection test; Extract the test result record data of the voltage detection test to obtain the total module voltage data, the maximum value data of the single cell voltage and the extreme value data of the single cell voltage; Extracting the test result record data of the internal resistance detection test to obtain module internal resistance data and module internal resistance growth rate data; Extracting the test result record data of the capacity detection test to obtain the actual capacity data of the module; The module total voltage data, the single cell voltage maximum value data, the single cell voltage extreme value data, the module internal resistance data and the module internal resistance growth rate data are processed in combination with the module actual capacity data to obtain the electrical performance compliance index.

[0042] It should be noted that if the appearance of the battery module is unqualified, it needs to be processed accordingly. Only when the appearance of the battery module is qualified, the target battery module is subjected to electrical performance testing, including voltage testing, internal resistance testing and capacity testing. The data recorded according to the test results of the voltage detection test are extracted to obtain the total module voltage, the maximum value of the single cell voltage and the extreme value of the single cell voltage. The difference in the single cell voltage should be within a certain range. For example, for lithium-ion battery modules, the voltage difference of the single cell generally does not exceed 0.05V. The data recorded according to the test results of the internal resistance detection test are extracted to obtain the module internal resistance and the module internal resistance growth rate data. By analyzing the internal resistance data, the health of the battery module can be judged. The data recorded according to the test results of the capacity detection test are extracted to obtain the actual capacity data of the module, wherein the actual capacity can be calculated based on the actual discharge time and discharge current. Finally, the above data are processed to obtain the electrical performance compliance index. The calculation formula of the electrical performance compliance index is: ; in, is the electrical performance compliance index, , , They are the total voltage data of the module, the maximum value data of the single cell voltage, and the extreme difference value data of the single cell voltage. , They are module internal resistance data and module internal resistance growth rate data. The actual capacity data of the module. , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0043] According to an embodiment of the present invention, the step of performing a connection reliability detection test on the target battery module and obtaining a connection reliability index according to the connection reliability detection result includes: Performing a connection reliability test on the target battery module, including a connection sheet tension test and a connection resistance test; Extracting data recorded according to the test result of the connecting piece tension detection test to obtain the connecting piece limit tension value data; Extracting the data recorded according to the test result of the connection resistance detection test to obtain the maximum value data of the connection point resistance; The connection reliability index is obtained by processing the data of the ultimate tensile force value of the connection piece and the data of the maximum value of the resistance of the connection point.

[0044] It should be noted that in order to ensure the reliable connection of the battery module, it is necessary to perform connection reliability detection tests on it, including connection piece tension detection tests and connection resistance detection tests. On the one hand, a special tension test device is designed to perform tension tests on the connection pieces of the battery module, and the data is extracted according to the test results to obtain the connection piece limit tension value data. On the other hand, a microohmmeter or milliohmmeter is used to detect the resistance of the connection part of the battery module, and the data is extracted according to the test results to obtain the maximum value data of the connection point resistance, and then the connection piece limit tension value data and the connection point resistance maximum value data are processed to obtain the connection reliability index. The calculation formula of the connection reliability index is: ; in, is the connection reliability index, , They are the data of the ultimate tensile force of the connecting piece and the maximum value of the resistance of the connecting point. , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0045] According to an embodiment of the present invention, the electrical performance compliance index, the connection reliability index and the safety index are processed to obtain a comprehensive evaluation index of a battery module, and the assembly eligibility of the target battery module is judged and processed accordingly, including: Processing is performed according to the electrical performance compliance index, connection reliability index and safety index to obtain a comprehensive evaluation index of the battery module; Comparing the battery module comprehensive evaluation index with a preset battery module comprehensive evaluation threshold to obtain a threshold comparison result; Determining whether the assembly of the target battery module is qualified according to the threshold comparison result; If the threshold comparison result is greater than a preset threshold, the assembly of the target battery module is qualified; Otherwise, it will be judged as unqualified and handled accordingly.

[0046] It should be noted that the electrical performance compliance index, connection reliability index and safety index obtained through several detection processes are processed to obtain a comprehensive evaluation index of the battery module, which is then compared with a preset threshold value. The comparison result is used to determine whether the assembly of the target battery module is qualified. If the threshold comparison result is greater than the preset threshold value, the assembly of the target battery module is qualified. Otherwise, it is determined to be unqualified and corresponding processing is performed; The calculation formula of the comprehensive evaluation index of the battery module is: ; in, It is the comprehensive evaluation index of battery module. , , They are electrical performance compliance index, connection reliability index, and safety index. , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0047] According to an embodiment of the present invention, it also includes: The safety performance test of the target battery module is performed, and the safety index is obtained according to the safety performance test result, specifically including: Performing safety performance testing on the target battery module, including insulation performance testing and air tightness testing; Extract the test result record data of the insulation performance detection test to obtain insulation resistance value data and withstand voltage value data; Extracting the test result record data of the air tightness detection test to obtain pressure decay rate data; According to the insulation resistance value data and the withstand voltage value data, combined with the pressure decay rate data, a safety index is obtained; The calculation formula of the safety index is: ; in, is the safety index, , They are insulation resistance data and withstand voltage data. is the pressure decay rate data, , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset battery module assembly database).

[0048] It should be noted that the target battery module is subjected to safety performance testing, including insulation performance testing and air tightness testing. The test result record data of the insulation performance testing is extracted to obtain insulation resistance value data and withstand voltage value data. The test result record data of the air tightness testing is extracted to obtain pressure decay rate data. The insulation resistance value data and withstand voltage value data are processed in combination with the pressure decay rate data to obtain a safety index.

[0049] A third aspect of the present invention provides a readable storage medium, in which a battery module assembly intelligent detection method program is stored. When the battery module assembly intelligent detection method program is executed by a processor, the steps of the battery module assembly intelligent detection method as described in any one of the above items are implemented.

[0050] The battery module assembly intelligent detection method, system and medium disclosed in the present invention obtain a captured image of a target battery module, perform preprocessing to obtain a processed image, perform feature extraction on the processed image to obtain feature data of the processed image, and perform processing in combination with the feature data of a standard image to obtain a module appearance evaluation index, and perform appearance qualification judgment on the target battery module. If the appearance of the target battery module is qualified, an electrical performance detection test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance detection result. A connection reliability detection test is performed on the target battery module, and a connection reliability index is obtained according to the connection reliability detection result. A safety performance detection test is performed on the target battery module, and a safety index is obtained according to the safety performance detection result. The electrical performance compliance index, the connection reliability index and the safety index are processed to obtain a battery module comprehensive evaluation index, and the assembly qualification of the target battery module is judged and corresponding processing is performed, thereby realizing the technology of battery module assembly intelligent detection.

[0051] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0052] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0053] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0054] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0055] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A battery module assembly intelligent detection method, characterized in that: The following steps are involved: Acquire a captured image of a target battery module and perform preprocessing to obtain a processed image; Extracting features from the processed image to obtain processed image feature data, processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; If the appearance of the target battery module is qualified, an electrical performance test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance test result; Performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; Performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; The electrical performance compliance index, connection reliability index and safety index are processed to obtain a comprehensive evaluation index of the battery module, and the assembly conformity of the target battery module is judged and processed accordingly.

2. The battery module assembly intelligent detection method according to claim 1, characterized in that: The step of acquiring a captured image of the target battery module and performing preprocessing to obtain a processed image includes: Select an appropriate industrial camera based on the standard size and detection accuracy of the target battery module; Shooting the target battery module at multiple angles according to the adapted industrial camera to obtain a photographed image of the target battery module; Processing the captured image according to an image preprocessing method to obtain a processed image; The image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

3. The battery module assembly intelligent detection method according to claim 2, characterized in that: The feature extraction of the processed image to obtain feature data of the processed image is combined with the feature data of the standard image for processing to obtain a module appearance evaluation index, and the appearance qualification determination of the target battery module is performed, including: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

4. The battery module assembly intelligent detection method according to claim 3, characterized in that: If the appearance of the target battery module is qualified, the target battery module is subjected to an electrical performance test, and an electrical performance compliance index is obtained according to the electrical performance test result, including: If the appearance of the target battery module is qualified, performing an electrical performance test on the target battery module; The electrical performance detection test includes a voltage detection test, an internal resistance detection test and a capacity detection test; Extract the test result record data of the voltage detection test to obtain the total module voltage data, the maximum value data of the single cell voltage and the extreme value data of the single cell voltage; Extracting the test result record data of the internal resistance detection test to obtain module internal resistance data and module internal resistance growth rate data; Extracting the test result record data of the capacity detection test to obtain the actual capacity data of the module; The module total voltage data, the single cell voltage maximum value data, the single cell voltage extreme value data, the module internal resistance data and the module internal resistance growth rate data are processed in combination with the module actual capacity data to obtain the electrical performance compliance index.

5. The battery module assembly intelligent detection method according to claim 4, characterized in that: The performing a connection reliability test on the target battery module and obtaining a connection reliability index according to the connection reliability test result includes: Performing a connection reliability test on the target battery module, including a connection sheet tension test and a connection resistance test; Extracting data recorded according to the test result of the connecting piece tension detection test to obtain the connecting piece limit tension value data; Extracting the data recorded according to the test result of the connection resistance detection test to obtain the maximum value data of the connection point resistance; The connection reliability index is obtained by processing the data of the ultimate tensile force value of the connection piece and the data of the maximum value of the resistance of the connection point.

6. The battery module assembly intelligent detection method according to claim 5, characterized in that: The processing is performed according to the electrical performance compliance index, the connection reliability index and the safety index to obtain a comprehensive evaluation index of the battery module, and the assembly qualification of the target battery module is judged and processed accordingly, including: Processing is performed according to the electrical performance compliance index, connection reliability index and safety index to obtain a comprehensive evaluation index of the battery module; Comparing the battery module comprehensive evaluation index with a preset battery module comprehensive evaluation threshold to obtain a threshold comparison result; Determining whether the assembly of the target battery module is qualified according to the threshold comparison result; If the threshold comparison result is greater than a preset threshold, the assembly of the target battery module is qualified; Otherwise, it will be judged as unqualified and handled accordingly.

7. A battery module assembly intelligent detection system, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program of a battery module assembly intelligent detection method, and when the program of the battery module assembly intelligent detection method is executed by the processor, the following steps are implemented: Acquire a captured image of a target battery module and perform preprocessing to obtain a processed image; Extracting features from the processed image to obtain processed image feature data, processing the processed image in combination with the standard image feature data to obtain a module appearance evaluation index, and determining the appearance eligibility of the target battery module; If the appearance of the target battery module is qualified, an electrical performance test is performed on the target battery module, and an electrical performance compliance index is obtained according to the electrical performance test result; Performing a connection reliability test on the target battery module, and obtaining a connection reliability index according to the connection reliability test result; Performing a safety performance test on the target battery module, and obtaining a safety index according to the safety performance test result; The electrical performance compliance index, connection reliability index and safety index are processed to obtain a comprehensive evaluation index of the battery module, and the assembly conformity of the target battery module is judged and processed accordingly.

8. The battery module assembly intelligent detection system according to claim 7, characterized in that: The step of acquiring a captured image of the target battery module and performing preprocessing to obtain a processed image includes: Select an appropriate industrial camera based on the standard size and detection accuracy of the target battery module; Shooting the target battery module at multiple angles according to the adapted industrial camera to obtain a photographed image of the target battery module; Processing the captured image according to an image preprocessing method to obtain a processed image; The image preprocessing method includes grayscale processing, filtering and noise reduction processing, and image enhancement processing.

9. The battery module assembly intelligent detection system according to claim 8, characterized in that: The feature extraction of the processed image to obtain feature data of the processed image is combined with the feature data of the standard image for processing to obtain a module appearance evaluation index, and the appearance qualification determination of the target battery module is performed, including: Extracting features from the processed image to obtain feature data of the processed image; The processed image feature data includes grayscale feature data, texture feature data, shape feature data, color feature data and spatial relationship feature data; Comparing the processed image feature data with the standard image feature data, obtaining grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data; Processing the grayscale difference data, texture deviation data, shape accuracy data, color difference data, and spatial relationship deviation data to obtain a module appearance evaluation index; Comparing the module appearance evaluation index with a preset module appearance evaluation threshold to obtain a threshold comparison result; If the threshold comparison result is less than a preset threshold, the appearance of the target battery module is qualified, otherwise it is judged to be unqualified.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a battery module assembly intelligent detection method program, and when the battery module assembly intelligent detection method program is executed by a processor, the steps of the battery module assembly intelligent detection method as described in any one of claims 1 to 6 are implemented.

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