Comprehensive evaluation method and system based on battery disassembly production line, terminal and medium

Abstract

The present application is applicable to the technical field of data processing, and provides a comprehensive evaluation method and system based on a battery disassembly production line, a terminal, and a medium. The method comprises: first, on the basis of a preset camera, obtaining a plurality of pieces of image information to be evaluated that is corresponding to a specified quantity of disassembled battery pieces; then, on the basis of a contour extraction algorithm and the plurality of pieces of image information to be evaluated, accurately generating corrosion region information corresponding to each piece of image information to be evaluated; and finally, on the basis of the plurality of pieces of corrosion region information, effectively generating target disassembled battery piece information. In the present application, by automatically predicting the disassembled battery pieces having an adhesion condition, the disassembled battery pieces that need to be disassembled for the second time can be intelligently determined, which helps to reduce the disassembled battery pieces having an adhesion condition, improve the classification and recycling effects; also, the product defects of a hydrogen fuel cell can be determined and the design of the hydrogen fuel cell can be optimized.

Description

Battery disassembly production line-based comprehensive evaluation method, system, terminal and medium TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a battery disassembly production line-based comprehensive evaluation method, system, terminal and medium. BACKGROUND

[0002] In the disassembly and recycling process of hydrogen fuel cells, a battery disassembly production line is usually used to classify and recycle key components containing high-value materials in hydrogen fuel cells, such as current collectors, bipolar plates and membrane electrodes.

[0003] At present, the existing battery disassembly production line usually disassembles hydrogen fuel cells according to fixed procedures. However, for aged and scrapped hydrogen fuel cells, their bipolar plates may have corrosion phenomena. Corroded bipolar plates can cause component adhesion, such as adhesion between bipolar plates and membrane electrodes or adhesion between current collectors and bipolar plates. Moreover, the existing battery disassembly production line lacks real-time monitoring mechanisms and cannot effectively identify component adhesion, which is not conducive to improving classification and recycling effects and needs to be further improved. SUMMARY

[0004] Therefore, the present application provides a battery disassembly production line-based comprehensive evaluation method, system, terminal and medium to solve the problem of not being conducive to improving classification and recycling effects in the prior art.

[0005] In a first aspect, the present application provides a battery disassembly production line-based comprehensive evaluation method, which comprises:

[0006] Based on a preset camera, obtain specified number of battery disassembly pieces corresponding to to-be-evaluated image information, wherein the total number of battery disassembly pieces is at least 10;

[0007] Based on a preset contour extraction algorithm, generate corrosion area information corresponding to each to-be-evaluated image information according to a plurality of to-be-evaluated image information;

[0008] Generate target disassembly piece information according to a plurality of corrosion area information, wherein the target disassembly piece information is used to describe battery disassembly pieces that are predicted to have adhesion.

[0009] Compared with existing technologies, the beneficial effects are as follows: The comprehensive evaluation method based on a battery dismantling production line provided in this application allows the terminal device to first acquire image information corresponding to a specified number of battery dismantling pieces to be evaluated. Then, based on the contour extraction algorithm and multiple image information to be evaluated, corrosion area information corresponding to each image information to be evaluated is generated. Finally, based on the multiple corrosion area information, target dismantling piece information is effectively generated. This enables the prediction of battery dismantling pieces with adhesion through target dismantling piece information, marking the objects that need to be dismantled a second time for production personnel. This helps to reduce the number of battery dismantling pieces with adhesion in the dismantled parts, which is conducive to improving the classification and recycling effect and solves the current problem of not being able to improve the classification and recycling effect to a certain extent.

[0010] Secondly, embodiments of this application provide a comprehensive evaluation system based on a battery dismantling production line, the system comprising:

[0011] Image information acquisition module: used to acquire image information of a specified number of battery disassembly pieces based on a preset camera, wherein the total number of battery disassembly pieces is at least 10;

[0012] Corrosion region information generation module: used to generate corrosion region information corresponding to each of the multiple images to be evaluated based on a preset contour extraction algorithm;

[0013] Target disassembly piece information generation module: used to generate target disassembly piece information based on multiple corrosion area information, wherein the target disassembly piece information is used to describe the battery disassembly piece predicted to have adhesion.

[0014] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0016] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0018] Figure 1 is a flowchart illustrating a comprehensive evaluation method provided in an embodiment of this application;

[0019] Figure 2 is a flowchart illustrating step S200 in a comprehensive evaluation method provided in an embodiment of this application;

[0020] Figure 3 is a flowchart illustrating step S300 in a comprehensive evaluation method provided in an embodiment of this application;

[0021] Figure 4 is a flowchart illustrating the process after step S391 in the comprehensive evaluation method provided in an embodiment of this application;

[0022] Figure 5 is a flowchart illustrating the process after step S300 in the comprehensive evaluation method provided in an embodiment of this application;

[0023] Figure 6 is a block diagram of a comprehensive evaluation system provided in an embodiment of this application;

[0024] Figure 7 is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation

[0025] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0026] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0028] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0029] Please refer to Figure 1, which is a flowchart illustrating the comprehensive evaluation method based on a battery dismantling production line provided in this embodiment. In this embodiment, the execution subject of the comprehensive evaluation method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, mobile phones, tablets, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.

[0030] Please refer to Figure 1. The comprehensive evaluation method provided in this application embodiment includes, but is not limited to, the following steps:

[0031] The S100, based on a preset camera, acquires image information corresponding to a specified number of battery disassembly pieces to be evaluated.

[0032] Generally speaking, a camera can be pre-installed above the conveyor belt of the battery dismantling production line; the battery dismantling production line can dismantle aged and scrapped hydrogen fuel cells, and remove the current collector, bipolar plate and membrane electrode assembly from the hydrogen fuel cells and place them on the bearing surface of the conveyor belt.

[0033] Specifically, the terminal device can respond to the disassembly completion instruction of the battery disassembly production line, and acquire image information to be evaluated corresponding to a specified number of battery disassembly pieces based on a preset camera. The battery disassembly pieces are used to describe the disassembled bipolar plates; the image information to be evaluated is used to describe the images obtained by the camera when taking pictures of the bipolar plates; the total number of battery disassembly pieces is at least 10, and for example, the total number of battery disassembly pieces can be 10, 12 or 14.

[0034] It should be noted that identifying the bipolar plate among the transported objects on the conveyor belt bearing surface can be done using existing technologies, such as object recognition algorithms based on convolutional neural networks, so this will not be elaborated upon.

[0035] S200, based on a preset contour extraction algorithm, generates erosion region information corresponding to each image to be evaluated based on multiple images to be evaluated.

[0036] Specifically, the terminal device can perform contour extraction processing on each image information to be evaluated based on a preset contour extraction algorithm, and generate corrosion region information corresponding to each image information to be evaluated. The corrosion region information is used to describe the corrosion region corresponding to the battery disassembly piece in the image information to be evaluated.

[0037] In some possible implementations, in order to effectively determine the erosion region information corresponding to each image information to be evaluated, please refer to Figure 2. Step S200 includes, but is not limited to, the following steps:

[0038] S210, for each image information to be evaluated: perform grayscale processing on the image information to be evaluated to generate grayscale image information.

[0039] Specifically, the terminal device can perform this processing on each image information to be evaluated: perform grayscale processing on the image information to be evaluated to generate grayscale image information, wherein the grayscale image information is used to describe the image information to be evaluated after grayscale processing. The grayscale processing can use existing technologies, such as monochrome channel extraction method, averaging method or maximum value method, so it will not be elaborated.

[0040] S220, based on a preset contour extraction algorithm, performs contour extraction processing on grayscale image information to generate the contour information of the first candidate region.

[0041] Specifically, after the terminal device generates grayscale image information, the terminal device can perform contour extraction processing on the grayscale image information based on a preset contour extraction algorithm to generate the contour information of the first candidate region. The contour extraction algorithm can be a contour extraction algorithm based on the Scharr operator, a contour extraction algorithm based on the Prewitt operator, or a contour extraction algorithm based on the Laplacian operator. The contour information of the first candidate region is used to describe the contour lines in the grayscale image information.

[0042] S230, based on the contour information of the first candidate region, generate the first region information of the grayscale image information.

[0043] Specifically, after the terminal device generates the first candidate region contour information, the terminal device can generate the first region information of the grayscale image information based on the first candidate region contour information. The first region information is used to describe the region enclosed by the contour lines in the grayscale image information.

[0044] S240, Obtain the grayscale value information of each first region point corresponding to the first region point in the first region information.

[0045] Specifically, the terminal device can obtain the grayscale value information of the first region point corresponding to each first region point in the first region information, wherein the first region point is used to describe the pixel point in the first region information, and the grayscale value information of the first region point is used to describe the grayscale value of the first region point.

[0046] S250, based on the grayscale value information of multiple first region points, generate the first average grayscale value information of the first region information.

[0047] Specifically, the terminal device can determine the sum of grayscale values ​​of multiple first area points and the total number of grayscale values ​​of the first area points, and then determine the quotient obtained by dividing the sum by the total number as the first average grayscale value of the first area information, wherein the first average grayscale value is used to describe the average grayscale value of the first area information.

[0048] S260, compare the first average gray value information with the preset gray value threshold information.

[0049] Specifically, after the terminal device generates the first average grayscale value information, the terminal device can compare the first average grayscale value information with the preset grayscale value threshold information. The grayscale value threshold information can be customized in advance. For example, the grayscale value threshold information can be 8, 16 or 32.

[0050] S270, if the first average gray value information is less than the gray value threshold information, then the first region information is determined to be the corrosion region information.

[0051] Specifically, if the first average gray value information is less than the gray value threshold information, the terminal device can determine the first region information as the corrosion region information, thereby effectively determining the corrosion region information corresponding to each image information to be evaluated.

[0052] S300 generates target disassembly information based on information from multiple corrosion zones.

[0053] Specifically, the target dismantling piece information is used to describe battery dismantling pieces that are predicted to have adhesion issues. The terminal equipment can generate target dismantling piece information based on multiple corrosion area information, thereby predicting battery dismantling pieces with adhesion issues through the target dismantling piece information. This helps production personnel identify objects that need to be dismantled a second time, which helps reduce the number of battery dismantling pieces with adhesion issues among the dismantled parts and is conducive to improving the classification and recycling effect.

[0054] In some possible implementations, to improve the sorting and recycling effect, please refer to Figure 3. Step S300 includes, but is not limited to, the following steps:

[0055] S310, for each image information to be evaluated: generate faded gray value information by multiplying the first average gray value information corresponding to the eroded area information by the preset faded factor information.

[0056] Without loss of generality, the faded grayscale value information is used to describe the average grayscale value information after faded processing; the specific value of the faded factor information can be a preset custom value, or it can refer to the total number of battery disassembly pieces. For example, when the first average grayscale value information is 24 and the total number of battery disassembly pieces is 10, the faded grayscale value information can be 240.

[0057] Specifically, the terminal device can perform this processing on each image information to be evaluated: by dividing the first average gray value information corresponding to the corrosion area information by the quotient of the total number of battery disassembly pieces, a faded gray value information is generated, thereby realizing intelligent adjustment of the gray value of each image information to be evaluated, which facilitates the subsequent effective determination of the target area information.

[0058] S320, modify the first average grayscale value information to fade the grayscale value information.

[0059] Specifically, after the terminal device generates the faded grayscale value information, the terminal device can modify the first average grayscale value information to the faded grayscale value information.

[0060] S330, based on preset disassembly sequence information, fuses the image information to be evaluated corresponding to each battery disassembly piece to generate composite image information.

[0061] It should be noted that for multiple adjacent battery disassembly pieces that are stuck together, since the corrosion area information corresponding to each of these multiple battery disassembly pieces has a large overlap area, the overlap area of ​​the corrosion area information can help to identify the battery disassembly pieces that are stuck together.

[0062] Without loss of generality, composite image information is used to describe the fused multiple images to be evaluated; disassembly sequence information is used to describe the original sequence of each battery disassembly piece in the hydrogen fuel cell before disassembly. The disassembly sequence information can be derived from the order in which each battery disassembly piece is on the conveyor belt or the specific shooting time of the images to be evaluated.

[0063] For example, during the dismantling of aged and depleted hydrogen fuel cells on a battery dismantling production line, the production line can dismantle the hydrogen fuel cells in sequence from the top cover to the bottom cover. Each dismantled battery piece is placed on the carrier surface of a conveyor belt, and the terminal equipment can control a camera to take pictures of multiple battery pieces on the carrier surface of the conveyor belt in sequence. This allows the specific shooting time of the image information to be evaluated to be associated with the original sequence of each battery piece in the hydrogen fuel cell.

[0064] Specifically, after the terminal device modifies the first average grayscale value information, the terminal device performs fusion processing on the image information to be evaluated corresponding to each battery disassembly piece based on the preset disassembly sequence information, so that the corrosion area information corresponding to each image information to be evaluated can be mapped to the same dimension, effectively generating composite image information.

[0065] For example, regarding the first image information to be evaluated, the second image information to be evaluated, and the third image information to be evaluated, the object of the first image information to be evaluated is a first battery disassembled piece in a hydrogen fuel cell, the object of the second image information to be evaluated is a second battery disassembled piece in a hydrogen fuel cell, and the object of the third image information to be evaluated is a third battery disassembled piece in a hydrogen fuel cell; the first battery disassembled piece is in a higher order than the second battery disassembled piece in the disassembly sequence information, and the second battery disassembled piece is in a higher order than the third battery disassembled piece in the disassembly sequence information. Since the dimensions of the bipolar plates and membrane electrode assemblies in a hydrogen fuel cell are usually the same, the terminal device can first determine the common feature points among the first, second, and third battery disassembly pieces. For example, the lower left corner of the first, second, and third battery disassembly pieces can be determined as the common feature points. Then, the relative position of the corrosion area information in the first image information to be evaluated relative to the common feature points can be determined. Based on this relative position, the corrosion area information in the first image information to be evaluated can be mapped to the second image information to be evaluated. This mapping step is then repeated to map both the newly added corrosion area information and the original corrosion area information in the second image information to the third image information to be evaluated. Finally, the image information to be evaluated, which integrates the corrosion area information corresponding to multiple different images, is the composite image information, thereby achieving the fusion of valuable data from multiple image information to be evaluated.

[0066] In one possible implementation, the multiple image information to be evaluated that are fused can be all the image information to be evaluated.

[0067] S340, based on a contour extraction algorithm, performs contour extraction processing on composite image information to generate second region information.

[0068] Specifically, the terminal device can perform contour extraction processing on the composite image information based on the contour extraction algorithm to generate second region information. The specific process of generating the second region information can be referred to the relevant content in steps S220 and S230 above, so it will not be repeated here.

[0069] S350, obtain the grayscale value information of each second region point in the second region information.

[0070] Specifically, the terminal device can obtain the grayscale value information of the second region point corresponding to each second region point in the second region information, wherein the grayscale value information of the second region point is used to describe the grayscale value corresponding to the second region point.

[0071] S360 generates the second average gray value information of the second region information based on the gray value information of multiple second region points.

[0072] Specifically, the terminal device can generate a second average gray value of the second region information based on the gray value information of multiple second region points. The specific process of generating the second average gray value information can be referred to the relevant content in step S250 above, so it will not be repeated here.

[0073] S370, determine the second region information corresponding to the smallest second average gray value information as the target region information.

[0074] Specifically, after the terminal device generates the second average gray value information corresponding to all the second region information in the composite image information, the terminal device can determine the second region information corresponding to the smallest second average gray value information as the target region information. The target region information can represent the overlapping area between the corrosion region information corresponding to multiple adjacent battery disassembly pieces that are stuck together.

[0075] S380, determine the center point of the target area information as the target area point information.

[0076] Specifically, after the terminal device determines the target area information, it can determine the center point of the target area information based on the centroid method, the minimum covering circle method, or the rectangular boundary method, and determine the center point of the target area information as the target area point information, which is used to describe the center point of the target area information.

[0077] S390, based on the target area point information, retrieve the corrosion area information corresponding to each image information to be evaluated, and determine the target image information.

[0078] Specifically, after the terminal device determines the target area point information, it can retrieve the corrosion area information corresponding to each image information to be evaluated based on the target area point information, and determine at least one target image information. The target area point information is located in the central area of ​​the corrosion area information corresponding to the target image information. The central area is used to describe the circular area enclosed by the center point of the corrosion area information and a preset distance value as the radius. This distance value can be customized by the production personnel based on the specific size of the battery disassembly piece.

[0079] S391, determine that the battery disassembly piece corresponding to the target image information is the target disassembly piece information.

[0080] Specifically, after the terminal device determines the target image information, the terminal device can determine that the battery disassembly piece corresponding to the target image information is the target disassembly piece information.

[0081] In some possible implementations, to further facilitate the secondary disassembly of battery fragments that are stuck together, thereby improving the sorting and recycling effect, please refer to Figure 4. After step S391, the method also includes, but is not limited to, the following steps:

[0082] S392, determine whether there are multiple consecutive target disassembly pieces.

[0083] Specifically, after the terminal device identifies all the target disassembled pieces in the battery disassembled pieces, the terminal device can determine whether there are multiple consecutive target disassembled piece information. For example, the terminal device can determine whether there are five, seven, or nine consecutive target disassembled piece information.

[0084] S393, if there are multiple consecutive target disassembly pieces, then the target disassembly piece information in the middle of the sorting position is determined as the most probable adhered piece information.

[0085] Specifically, if there are multiple consecutive target disassembly pieces, the terminal device can determine the target disassembly piece information in the middle of the sorting position as the most probable sticky piece information. It should be noted that when it is determined whether there are an even number of consecutive target disassembly pieces, the terminal device can determine either of the two target disassembly pieces information in the middle of the sorting position as the most probable sticky piece information.

[0086] In some possible implementations, to further improve the sorting and recycling effect, please refer to Figure 5. After step S300, the method also includes, but is not limited to, the following steps:

[0087] S400 retrieves the battery model information corresponding to the battery disassembly chip.

[0088] Specifically, the terminal device can obtain the battery model information corresponding to the battery dismantling pieces. The battery model information is used to describe the model of the aged and decommissioned hydrogen fuel cell composed of the battery dismantling pieces.

[0089] S410 associates the location of the target disassembled piece information with the battery model information to generate data association information.

[0090] Specifically, the terminal device can associate the location of the target disassembled piece information with the battery model information to generate data association information. The data association information is used to describe the data associated with the location of the target disassembled piece information and the battery model information.

[0091] S420, uploads data association information to the preset manufacturing execution system.

[0092] Specifically, the terminal equipment can upload data association information to a preset manufacturing execution system, thereby facilitating the control of the battery disassembly production line to perform secondary disassembly of the target disassembled piece information, and to identify the product defects of this type of hydrogen fuel cell, which helps to optimize the design of this type of hydrogen fuel cell.

[0093] The implementation principle of the comprehensive evaluation method based on the battery dismantling production line in this application embodiment is as follows: The terminal equipment can first acquire image information of a specified number of battery dismantling pieces based on a preset camera. Then, based on a preset contour extraction algorithm and multiple image information to be evaluated, corrosion area information corresponding to each image information to be evaluated is generated. Finally, based on multiple corrosion area information, target dismantling piece information is effectively generated. Thus, the target dismantling piece information is used to predict battery dismantling pieces with adhesion, marking the objects that need to be dismantled again for production personnel. This helps to reduce the number of battery dismantling pieces with adhesion in the dismantled parts and is conducive to improving the classification and recycling effect.

[0094] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0095] Embodiments of this application also provide a comprehensive evaluation system based on a battery dismantling production line. For ease of explanation, only the parts relevant to this application are shown, as shown in Figure 6. The system 60 includes:

[0096] Image information acquisition module 61 to be evaluated: used to acquire image information to be evaluated corresponding to a specified number of battery disassembly pieces based on a preset camera, wherein the total number of battery disassembly pieces is at least 10;

[0097] Corrosion region information generation module 62: Based on a preset contour extraction algorithm, it generates corrosion region information corresponding to each image to be evaluated according to multiple image information to be evaluated.

[0098] Target disassembly piece information generation module 63: used to generate target disassembly piece information based on multiple corrosion area information, wherein the target disassembly piece information is used to describe battery disassembly pieces that are predicted to have adhesion.

[0099] Optionally, the corrosion area information generation module 62 mentioned above includes:

[0100] Grayscale image information generation submodule: used to perform grayscale processing on each image information to be evaluated, and generate grayscale image information;

[0101] The first candidate region contour information generation submodule is used to perform contour extraction processing on grayscale image information based on a preset contour extraction algorithm to generate the first candidate region contour information.

[0102] First region information generation submodule: used to generate first region information of grayscale image information based on the contour information of the first candidate region;

[0103] First Region Point Gray Value Information Acquisition Submodule: Used to acquire the gray value information of each first region point in the first region information;

[0104] First average gray value information generation submodule: used to generate first average gray value information of first region information based on gray value information of multiple first region points;

[0105] First average grayscale value information comparison submodule: used to compare the first average grayscale value information with the preset grayscale value threshold information;

[0106] Corrosion area information determination submodule: If the first average gray value information is less than the gray value threshold information, then the first area information is determined to be corrosion area information.

[0107] Optionally, the target disassembled piece information generation module 63 includes:

[0108] The faded grayscale value generation submodule is used to generate faded grayscale value information for each image information to be evaluated by multiplying the first average grayscale value information corresponding to the erosion area information by the preset faded factor information.

[0109] The submodule for modifying faded grayscale value information is used to modify the first average grayscale value information to faded grayscale value information;

[0110] Composite image information generation submodule: Based on the preset disassembly sequence information, it performs fusion processing on the image information to be evaluated corresponding to each battery disassembly piece to generate composite image information;

[0111] The second region information generation submodule is used to perform contour extraction processing on composite image information based on contour extraction algorithms to generate second region information.

[0112] The second region point grayscale value information acquisition submodule is used to acquire the grayscale value information of each second region point in the second region information.

[0113] Second average gray value information generation submodule: used to generate second average gray value information of second region information based on gray value information of multiple second region points;

[0114] Target area information determination submodule: used to determine the second area information corresponding to the smallest second average gray value as the target area information;

[0115] Center point determination submodule: used to determine the center point of the target area information as the target area point information;

[0116] The target image information determination submodule is used to retrieve the erosion area information corresponding to each image information to be evaluated based on the target area point information, and determine the target image information. The target area point information is located in the central area of ​​the erosion area information corresponding to the target image information. The central area is used to describe the circular area enclosed by the center point of the erosion area information as the center and a preset distance value as the radius.

[0117] Target Disassembly Piece Information Determination Submodule: Used to determine the battery disassembly piece corresponding to the target image information as the target disassembly piece information.

[0118] Optionally, the system 60 also includes:

[0119] Target fragment information determination module: used to determine whether there are multiple consecutive target fragment information;

[0120] Maximum probability adhered piece information determination module: If there are multiple consecutive target disassembled piece information, the target disassembled piece information in the middle of the sorting position is determined as the maximum probability adhered piece information.

[0121] Optionally, the system 60 also includes:

[0122] Battery model information acquisition module: used to acquire battery model information corresponding to the battery disassembly piece;

[0123] Data association information generation module: used to associate the location of the target disassembled piece information with the battery model information to generate data association information;

[0124] Data association information upload module: used to upload data association information to the preset manufacturing execution system.

[0125] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0126] This application also provides a terminal device, as shown in FIG7. The terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps in the above-described comprehensive evaluation method embodiment, such as steps S100 to S300 shown in FIG1; or, when the processor 71 executes the computer program 73, it implements the functions of each module in the above-described device, such as the functions of modules 61 to 63 shown in FIG6.

[0127] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The terminal device 70 includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that Figure 7 is merely an example of the terminal device 70 and does not constitute a limitation on the terminal device 70. It may include more or fewer components than shown in the figure, or combine certain components, or use different components. For example, the terminal device 70 may also include input / output devices, network access devices, buses, etc.

[0128] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0129] The memory 72 can be an internal storage unit of the terminal device 70, such as a hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.

[0130] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0131] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.

Claims

1. A comprehensive evaluation method based on a battery disassembly production line, characterized by, The method comprises: Based on the preset camera, the specified number of battery disassembly pieces corresponding to the to-be-evaluated image information is obtained, wherein the total number of the battery disassembly pieces is at least 10; Based on the preset contour extraction algorithm, the corrosion area information corresponding to each of the to-be-evaluated image information is generated according to the plurality of to-be-evaluated image information; According to a plurality of corrosion area information, the target disassembly piece information is generated, wherein the target disassembly piece information is used to describe the battery disassembly piece which is predicted to exist in the adhesion condition.

2. The method of claim 1, wherein, According to the plurality of to-be-evaluated image information, the corrosion area information corresponding to each of the to-be-evaluated image information is generated based on the preset contour extraction algorithm, comprising: For each of the to-be-evaluated image information: the to-be-evaluated image information is subjected to gray processing to generate gray image information; Based on the preset contour extraction algorithm, the contour extraction processing is performed on the gray image information to generate the first candidate region contour information; Based on the first candidate region contour information, the first region information of the gray image information is generated; The first region point gray value information corresponding to each first region point in the first region information is obtained; According to a plurality of the first region point gray value information, the first average gray value information of the first region information is generated; The first average gray value information is compared with the preset gray value threshold information; If the first average gray value information is less than the gray value threshold information, the first region information is determined as the corrosion area information.

3. The method of claim 2, wherein, According to a plurality of the corrosion area information, the target disassembly piece information is generated, comprising: For each of the to-be-evaluated image information: according to the product of the first average gray value information corresponding to the corrosion area information and the preset lightening multiple information, the lightening gray value information is generated; The first average gray value information is modified as the lightening gray value information; Based on the preset disassembly sequence information, the to-be-evaluated image information corresponding to each of the battery disassembly pieces is subjected to fusion processing to generate composite image information; Based on the contour extraction algorithm, the contour extraction processing is performed on the composite image information to generate the second region information; The second region point gray value information corresponding to each second region point in the second region information is obtained; According to a plurality of the second region point gray value information, the second average gray value information of the second region information is generated; The second region information corresponding to the smallest second average gray value information is determined as the target region information; The center point of the target region information is determined as the target region point information; Based on the target region point information, the corrosion area information corresponding to each of the to-be-evaluated image information is searched to determine the target image information, wherein the target region point information is located in the central region of the corrosion area information corresponding to the target image information, and the central region is used to describe the circular region with the center point of the corrosion area information as the center and the preset distance value as the radius; The battery disassembly piece corresponding to the target image information is determined as the target disassembly piece information.

4. The method of claim 3, wherein, After the target disassembled piece information is generated according to the plurality of corrosion area information, the method further comprises: determining whether there are a plurality of continuous target disassembled piece information; if there are a plurality of continuous target disassembled piece information, determining the target disassembled piece information in the middle of the sorting position as the maximum probability of sticking piece information.

5. The method of claim 1, wherein, After the target disassembled piece information is generated according to the plurality of corrosion area information, the method further comprises: obtaining the battery model information corresponding to the battery disassembled piece; associating the position of the target disassembled piece information with the battery model information to generate data association information; uploading the data association information to a preset manufacturing execution system.

6. A comprehensive evaluation system based on a battery disassembly production line, characterized by, The system comprises: a to-be-evaluated image information acquisition module configured to acquire to-be-evaluated image information corresponding to a specified number of battery disassembled pieces based on a preset camera, wherein the total number of the battery disassembled pieces is at least 10; a corrosion area information generation module configured to generate corrosion area information corresponding to each of the to-be-evaluated image information based on a preset contour extraction algorithm according to a plurality of the to-be-evaluated image information; a target disassembled piece information generation module configured to generate target disassembled piece information according to a plurality of the corrosion area information, wherein the target disassembled piece information is used to describe the battery disassembled pieces that are predicted to have sticking conditions.

7. The system of claim 6, wherein, The system further comprises: a battery model information acquisition module configured to obtain battery model information corresponding to the battery disassembled piece; a data association information generation module configured to associate the position of the target disassembled piece information with the battery model information to generate data association information; a data association information upload module configured to upload the data association information to a preset manufacturing execution system.

8. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the method of any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. The computer program is executed by the processor to realize the steps of the method of any one of claims 1 to 5.

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