A high-efficiency disassembling system and process for waste lead-acid storage batteries

Abstract

The application relates to the technical field of battery disassembly, in particular to a high-efficiency disassembly system and process for waste lead-acid storage batteries. The system comprises a data acquisition module, a data analysis module and a cutting control module. The data acquisition module acquires X-ray three-dimensional scanning data and battery design parameters of the waste lead-acid storage battery. The data analysis module analyzes the gray scale distribution of the X-ray three-dimensional scanning data, determines the bus bar-grid plate transition point and the grid plate root position, dynamically calculates the Z-direction height of the cutting path according to the connecting line equation of the bus bar-grid plate transition point and the grid plate root position and in combination with the battery design parameters, and the cutting control module performs a separation operation along the sealing seam based on the Z-direction height, and simultaneously implements thermal deformation compensation and vibration suppression. The problems of preset path failure caused by thermal deformation are solved, the cutting precision is maintained, and the shell rupture or material mixing caused by path deviation is avoided; the problems of cutting precision and imaging clarity affected by mechanical vibration are solved, and the operation stability and cutting quality are improved.

Description

Technical Field

[0001] This application relates to the field of battery dismantling technology, and in particular to a high-efficiency dismantling system and process for waste lead-acid batteries. Background Technology

[0002] Because waste lead-acid batteries contain high concentrations of lead, sulfuric acid, and other heavy metals, their recycling and processing technology has evolved from simple crushing to multi-stage sorting in order to address the serious pollution risks to water bodies and soil from waste acid and lead heavy metals.

[0003] However, during the dismantling process, the recycling process of waste lead-acid batteries generally adopts a multi-stage crushing combined with wet sorting method. Its core is "destruction before separation". The stirring and water flow impact during the crushing and sorting process can easily cause splashing, dripping or discharge of lead-acid liquid with wastewater. Even with collection tanks and pressure filtration steps, it is difficult to achieve complete sealing and zero leakage, which poses a risk of polluting the working environment and surrounding water and soil. Summary of the Invention

[0004] This application provides a high-efficiency dismantling system and process for waste lead-acid batteries to solve the above-mentioned problems.

[0005] In a first aspect, this application provides a high-efficiency dismantling system for waste lead-acid batteries, the system comprising a data acquisition module, a data analysis module, and a cutting control module:

[0006] The data acquisition module, the data analysis module, and the cutting control module are connected in sequence;

[0007] The data acquisition module is used to acquire X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries;

[0008] The data analysis module is used to analyze the grayscale distribution of the X-ray three-dimensional scan data and determine the transition point between the busbar and the grid plate and the root position of the grid plate.

[0009] Based on the equation connecting the busbar-grid transition point and the root position of the grid, and combined with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated.

[0010] The cutting control module is used to perform a separation operation along the sealing seam based on the Z-axis height, and simultaneously implement thermal deformation compensation and vibration suppression.

[0011] This solution utilizes a data acquisition module to obtain X-ray 3D scan data and battery design parameters from waste lead-acid batteries. This visualizes the key internal structures of the batteries, preventing physical damage and mitigating potential acid leakage or lead dust diffusion during initial disassembly. Simultaneously, it ensures the reliability of the cutting path calculation, reduces positioning errors caused by battery model differences, optimizes cutting parameters, and improves overall disassembly efficiency. The data analysis module analyzes the grayscale distribution of the X-ray 3D scan data to determine the busbar-grid transition point and the grid root position, solving the problem of non-destructive high-precision positioning and ensuring the accuracy of key point coordinates, avoiding damage to internal materials caused by blind cutting. Based on the equation connecting the busbar-grid transition point and the grid root position, combined with battery design parameters, the Z-axis height of the cutting path is dynamically calculated, enabling real-time adjustment of the cutting path to adapt to individual battery differences. This ensures the path is always precisely aligned with the sealing seam, preventing damage to lead paste or lead grids during cutting. Furthermore, it optimizes calculations using battery design parameters, improving efficiency and reducing trial and error. The cutting control module is used to perform separation operations along the sealing seam based on the Z-axis height, and simultaneously implement thermal deformation compensation and vibration suppression to solve the problem of preset path failure caused by thermal deformation, maintain cutting accuracy, and avoid shell breakage or material mixing caused by path deviation; it also solves the problem of mechanical vibration affecting cutting accuracy and imaging clarity, and improves operational stability and cutting quality.

[0012] Optionally, when the data analysis module analyzes the grayscale distribution of the X-ray three-dimensional scan data to determine the busbar-grid transition point and the root position of the grid, it is used for:

[0013] Analyze the grayscale distribution of the X-ray three-dimensional scan data to identify the grayscale value jump intervals;

[0014] Within the aforementioned transition range, the busbar-grid transition point is determined by the extreme points of the second derivative;

[0015] Based on the coordinates of the busbar-grid transition point, determine the extension trajectory between the grid edge line and the bottom of the battery;

[0016] The root position of the grid plate is determined based on the extended trajectory.

[0017] This solution analyzes the grayscale distribution of X-ray 3D scanning data, identifies abrupt grayscale value changes, and locates areas with significant grayscale gradient variations in the X-ray scanning data, avoiding the waste of resources in global scanning. Within these abrupt changes, the transition point between the busbar and grid is determined using the extreme points of the second derivative, solving the challenge of locating this transition point and providing a high-precision starting point for the cutting path. Based on the coordinates of the busbar-grid transition point, the extended trajectory between the grid edge line and the bottom of the battery is determined, expanding the discrete transition point into a continuous path, providing directional guidance for root location, and ensuring that the trajectory covers the complete spatial orientation of the grid. Based on the extended trajectory, the root position of the grid is determined, avoiding cutting damage to the internal lead grid or lead paste.

[0018] Optionally, when the data analysis module dynamically calculates the Z-axis height of the cutting path based on the equation of the line connecting the busbar-grid transition point and the grid root position, combined with the battery design parameters, it is used for:

[0019] Establish the equation for the line connecting the transition point of the busbar-grid plate and the root position of the grid plate;

[0020] Analyze the battery design parameters to determine the sealing width of the battery top cover sealing seam and the preset offset of the seam centerline from the shell surface;

[0021] Based on the connection equation and the preset offset, a set of cutting path points is generated by mapping.

[0022] Extract the Z-axis coordinate components of the cutting path point set;

[0023] Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path.

[0024] This solution establishes a line equation connecting the busbar-grid transition point to the grid root position, ensuring that the start and end points of the cutting path are strictly aligned with the critical boundaries of the battery's internal structure. This prevents the cutting tool from accidentally cutting internal lead paste or lead grid components and supports dynamic calculation of the cutting trajectory along the sealing seam. Battery design parameters are analyzed to determine the sealing seam width and the preset offset from the seam centerline to the casing surface, ensuring that the cutting path point set is accurately mapped to the sealing seam centerline position. This avoids path deviations due to differences in battery models and provides an input benchmark for generating the cutting point set. Based on the line equation and preset offset, the cutting path point set is generated, ensuring that the cutting path accurately corresponds to the geometric center of the battery cover sealing seam in three-dimensional space. This provides spatial point data for height calculation and supports dynamic path generation. The Z-axis coordinate component of the cutting path point set is extracted to ensure more efficient adjustment of the cutting tool's movement along the Z-axis. Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path. This ensures that the Z-axis height of the cutting path adapts to the actual shape of the sealing joint, making the cutting tool move smoothly and reducing the risk of path deviation during the cutting process.

[0025] Optionally, when the data analysis module establishes the equation connecting the busbar-grid transition point and the root position of the grid plate, it is used for:

[0026] Analyze the X-ray three-dimensional scan data to determine the battery height orientation;

[0027] A coordinate system is established with the root position of the grid plate as the origin O and the height direction of the battery as the Z-axis;

[0028] Analyze the spatial vector between the busbar-grid transition point and the origin O to generate the connection equation.

[0029] This solution analyzes X-ray 3D scan data to determine the battery height direction, eliminating directional deviations caused by battery tilting or deformation. A coordinate system is established with the root of the grid plate as the origin O and the battery height direction as the Z-axis. This eliminates the influence of overall battery positional offset, ensuring that the calculated Z-axis height of the cutting path matches the actual physical direction of the battery and reducing vector computation complexity. The spatial vector between the busbar-grid transition point and the origin O is analyzed to generate a connection equation, ensuring the cutting tool moves strictly along the lead grid boundary and avoids cutting into the lead paste area.

[0030] Optionally, before the cutting control module performs the separation operation along the sealing seam based on the Z-axis height, the data analysis module is further configured to: obtain the battery casing identification code; query the historical cutting parameter database according to the identification code; and when a matching record exists, load the optimal cutting speed and pressure value of the corresponding matching record.

[0031] This solution obtains the battery casing identification code, addressing the need to reduce trial and error and skipping the stage of blindly exploring parameters for new battery models. It queries the historical cutting parameter database based on the identification code, avoiding fluctuations in cutting quality caused by differences in battery models. When a matching record exists, it loads the optimal cutting speed and pressure values ​​for that record, reducing trial and error during the cutting process and increasing the first-time success rate.

[0032] Optionally, the data analysis module includes a speed setting unit, used for:

[0033] The X-ray three-dimensional scan data was analyzed to determine the battery casing thickness and battery material.

[0034] Determine the coefficient of thermal expansion of the battery material based on the battery material.

[0035] The melting point temperature of the battery casing is determined based on the thickness of the battery casing and the battery material.

[0036] The heat generated per unit time is calculated based on the thickness of the battery casing and the coefficient of thermal expansion of the material; the upper limit of the cutting speed is dynamically set based on the difference between the heat generated per unit time and the melting point temperature of the casing to obtain the optimal cutting speed.

[0037] This solution analyzes X-ray 3D scan data to determine the battery casing thickness and material, ensuring that the speed setting unit can be customized for the physical characteristics of different batteries. This avoids the risk of thermal deformation during cutting due to unknown casing thickness or material. Based on the battery material, the thermal expansion coefficient is determined, ensuring that heat generation calculations and speed adjustments are based on data, preventing deviations from the preset cutting path due to inaccurate expansion coefficients. Based on the battery casing thickness and material, the casing melting point temperature is determined to prevent melting or excessive softening of the casing due to cutting heat, ensuring that the cutting tool will not damage the casing structure due to excessive temperature, thus maintaining the stability and sealing of the cutting path. Based on the battery casing thickness and material thermal expansion coefficient, the heat generation per unit time is calculated, ensuring real-time assessment of heat accumulation risk and preventing localized thermal expansion and path deviation caused by excessive heat generation. Based on the difference between the heat generation per unit time and the casing melting point temperature, the upper limit of the cutting speed is dynamically set to obtain the optimal cutting speed, ensuring that the cutting process is carried out within a safe temperature range, effectively suppressing thermal deformation and maintaining cutting accuracy.

[0038] Optionally, the cutting control module includes an acceleration sensor connected to the data acquisition module;

[0039] While the cutting control module performs the separation operation along the sealing seam, the data acquisition module simultaneously acquires the vibration spectrum and sends it to the data analysis module;

[0040] The data analysis module is used to analyze the vibration spectrum, determine the reverse damping force, and send it to the acceleration sensor.

[0041] The accelerometer is used to adjust the acceleration to generate the reverse damping force to counteract mechanical vibration.

[0042] This solution enables the data acquisition module to simultaneously acquire the vibration spectrum and send it to the data analysis module while the cutting control module performs the separation operation along the sealing seam. This provides precise characterization of the vibration state, offering real-time and complete input data to the analysis module, avoiding signal delay or distortion, and ensuring strict synchronization between vibration monitoring and the cutting action. The data analysis module analyzes the vibration spectrum, determines the reverse damping force, and sends it to the accelerometer to enable rapid transmission of compensation commands. This ensures that the analysis results are directly applied to the execution end, forming a closed-loop link from analysis to execution. The accelerometer adjusts the acceleration to generate a reverse damping force to counteract mechanical vibration, thereby reducing or eliminating the amplitude of mechanical vibration during the cutting process, stabilizing the cutting path, preventing vibration interference, and ensuring smooth separation operations.

[0043] Optionally, the system further includes a sealed negative pressure adsorption device connected to the data acquisition module;

[0044] When the cutting control module performs a separation operation along the sealing seam, the data acquisition module is used to acquire separation operation data;

[0045] The data analysis module is used to analyze the separation operation data and determine the cutting slit opening rate.

[0046] The real-time negative pressure adsorption intensity is determined based on the cutting slit opening rate;

[0047] The sealed negative pressure adsorption device is used to adjust the adsorption parameters in real time according to the real-time negative pressure adsorption intensity.

[0048] This solution employs a data acquisition module to obtain separation operation data while the cutting control module performs separation operations along the sealed seam. This ensures that the contamination control process is synchronized with the cutting operation, preventing control lag due to data loss. The data analysis module analyzes the separation operation data to determine the cutting seam opening rate, quantify the dynamic changes of the cutting seam, and identify the potential risk level of contaminant escape. Based on the cutting seam opening rate, the real-time negative pressure adsorption intensity is determined, enabling precise response in contamination control and reducing the risk of acid splashing and lead dust diffusion. The sealed negative pressure adsorption device adjusts adsorption parameters in real-time based on the real-time negative pressure adsorption intensity, effectively preventing contaminants from escaping into the environment. This ensures that the cutting process meets the emphasized clean dismantling requirements, reducing environmental pollution and occupational exposure risks.

[0049] Secondly, this application provides a high-efficiency dismantling process for waste lead-acid batteries, the process comprising:

[0050] Obtain X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries;

[0051] Analyze the grayscale distribution of the X-ray three-dimensional scan data to determine the transition point between the busbar and the grid plate, as well as the location of the grid plate root.

[0052] Based on the equation connecting the busbar-grid transition point and the root position of the grid, and combined with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated.

[0053] Based on the Z-axis height, the cutting tool is controlled to perform a separation operation along the sealing seam, while thermal deformation compensation and vibration suppression are implemented simultaneously.

[0054] Optionally, analyzing the grayscale distribution of the X-ray three-dimensional scan data to determine the busbar-grid transition point and the grid root position includes:

[0055] Analyze the grayscale distribution of the X-ray three-dimensional scan data to identify the grayscale value jump intervals;

[0056] Within the aforementioned transition range, the busbar-grid transition point is determined by the extreme points of the second derivative;

[0057] Based on the coordinates of the busbar-grid transition point, determine the extension trajectory between the grid edge line and the bottom of the battery;

[0058] The root position of the grid plate is determined based on the extended trajectory.

[0059] Optionally, the step of dynamically calculating the Z-axis height of the cutting path based on the equation of the line connecting the busbar-grid transition point and the grid root position, combined with the battery design parameters, includes:

[0060] Establish the equation for the line connecting the transition point of the busbar-grid plate and the root position of the grid plate;

[0061] Analyze the battery design parameters to determine the sealing width of the battery top cover sealing seam and the preset offset of the seam centerline from the shell surface;

[0062] Based on the connection equation and the preset offset, a set of cutting path points is generated by mapping.

[0063] Extract the Z-axis coordinate components of the cutting path point set;

[0064] Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path.

[0065] Optionally, establishing the equation for the line connecting the busbar-grid transition point and the root position of the grid plate includes:

[0066] Analyze the X-ray three-dimensional scan data to determine the battery height orientation;

[0067] A coordinate system is established with the root position of the grid plate as the origin O and the height direction of the battery as the Z-axis;

[0068] Analyze the spatial vector between the busbar-grid transition point and the origin O to generate the connection equation.

[0069] Optionally, before performing the separation operation along the sealing seam based on the Z-axis height, the method further includes: obtaining the battery casing identification code; querying the historical cutting parameter database according to the identification code; and when a matching record exists, loading the optimal cutting speed and pressure value of the corresponding matching record.

[0070] Optionally, the method further includes:

[0071] The X-ray three-dimensional scan data was analyzed to determine the battery casing thickness and battery material.

[0072] Determine the coefficient of thermal expansion of the battery material based on the battery material.

[0073] The melting point temperature of the battery casing is determined based on the thickness of the battery casing and the battery material.

[0074] The heat generated per unit time is calculated based on the thickness of the battery casing and the coefficient of thermal expansion of the material; the upper limit of the cutting speed is dynamically set based on the difference between the heat generated per unit time and the melting point temperature of the casing to obtain the optimal cutting speed.

[0075] Optionally, the method further includes:

[0076] During the separation operation along the sealing seam, the vibration spectrum is acquired synchronously.

[0077] The vibration spectrum is analyzed to determine the reverse damping force, which is then sent to the acceleration sensor.

[0078] The accelerometer is used to adjust the acceleration to generate the reverse damping force to counteract mechanical vibration.

[0079] Optionally, the method further includes:

[0080] During the separation operation performed along the sealing seam, the separation operation data is acquired;

[0081] The separation operation data is analyzed to determine the cutting kerf opening rate.

[0082] The real-time negative pressure adsorption intensity is determined based on the cutting slit opening rate;

[0083] The sealed negative pressure adsorption device is used to adjust the adsorption parameters in real time according to the real-time negative pressure adsorption intensity. Attached Figure Description

[0084] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0085] Figure 1 This application provides a schematic diagram of a high-efficiency dismantling system for waste lead-acid batteries, as an embodiment of the present application.

[0086] Figure 2 This is a schematic diagram of the structure of a high-efficiency dismantling system for waste lead-acid batteries provided in an embodiment of this application, in a specific implementation.

[0087] Figure 3 This is a flowchart of an efficient dismantling process for waste lead-acid batteries provided in an embodiment of this application. Detailed Implementation

[0088] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0089] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0090] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0091] During the dismantling process, the recycling process of waste lead-acid batteries generally adopts a multi-stage crushing combined with wet sorting method. Its core is "destruction before separation". The stirring and water flow impact during the crushing and sorting process can easily cause lead-acid liquid to splash, drip or be discharged with wastewater. Even with collection tanks and pressure filtration steps, it is difficult to achieve complete sealing and zero leakage, which poses a risk of polluting the working environment and surrounding water and soil.

[0092] Based on this, this application provides a high-efficiency dismantling system and process for waste lead-acid batteries. It acquires X-ray three-dimensional scanning data and battery design parameters of the waste lead-acid batteries, enabling visualization of key internal structures, avoiding physical damage to the batteries, and preventing acid leakage or lead dust diffusion that may occur during the initial dismantling process. Simultaneously, it ensures the reliability of the cutting path calculation, reduces positioning errors caused by differences in battery models, and optimizes cutting parameters to improve overall dismantling efficiency. Analyzing the grayscale distribution of the X-ray three-dimensional scanning data determines the busbar-grid transition point and the grid root position, solving the problem of non-destructive high-precision positioning, ensuring the accuracy of key point coordinates, and avoiding damage to internal materials caused by blind cutting. Based on the line equation connecting the busbar-grid transition point and the grid root position, combined with battery design parameters, the Z-axis height of the cutting path is dynamically calculated, enabling real-time adjustment of the cutting path to adapt to individual battery differences, ensuring the path is always precisely aligned with the sealing seam, and preventing damage to lead paste or lead grids during cutting. Furthermore, the calculation is optimized using battery design parameters, improving efficiency and reducing trial and error. Based on the Z-axis height, the separation operation is performed along the sealing seam, simultaneously implementing thermal deformation compensation and vibration suppression. This solves the problem of preset path failure caused by thermal deformation, maintains cutting accuracy, and avoids shell breakage or material mixing caused by path deviation. It also solves the problem of mechanical vibration affecting cutting accuracy and imaging clarity, improving operational stability and cutting quality. Specific implementation methods can be found in the following embodiments.

[0093] Figure 1 This is a schematic diagram of the structure of a high-efficiency dismantling system for waste lead-acid batteries provided in an embodiment of this application, as shown below. Figure 1 As shown, the high-efficiency dismantling system 100 for waste lead-acid batteries in this embodiment includes: a data acquisition module 101, a data analysis module 102, and a cutting control module 103.

[0094] The data acquisition module 101, the data analysis module 102, and the cutting control module 103 are connected in sequence.

[0095] The data acquisition module 101 is used to acquire X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries;

[0096] Data analysis module 102 is used to analyze the grayscale distribution of X-ray three-dimensional scanning data to determine the transition point between the busbar and the grid and the root position of the grid.

[0097] Based on the equation connecting the busbar-grid transition point and the grid root position, and combined with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated.

[0098] The cutting control module 103 is used to perform separation operations along the sealing seam based on the Z-axis height, and simultaneously implement thermal deformation compensation and vibration suppression.

[0099] Waste lead-acid batteries can be lead-acid batteries that have already been scrapped.

[0100] X-ray 3D scan data can be the three-dimensional density distribution data inside a battery generated by X-ray computed tomography.

[0101] Battery design parameters can be standardized attribute data preset by the battery manufacturer, including battery model, seal width, standard dimensions, and reference positions of internal components.

[0102] Grayscale distribution can be the distribution pattern of brightness values ​​of each pixel in X-ray 3D scan data.

[0103] The busbar-grid transition point can be the physical connection point between the busbar and the grid inside the battery.

[0104] The base of the grid plate can be the anchor point for fixing the grid plate to the bottom of the battery casing.

[0105] The equation of the connection can be a mathematical parametric equation of a straight line connecting the transition point of the busbar-grid plate to the root position of the grid plate.

[0106] The Z-axis height can be the precise position value of the cutting path in the vertical direction.

[0107] A sealing seam can be a physical gap at the junction of the battery cover and the casing.

[0108] Thermal deformation compensation can correct the offset of the shell expansion caused by heat generation in real time during the cutting process.

[0109] Vibration suppression can reduce the interference of mechanical vibration of cutting tools on stability.

[0110] Specifically, the data acquisition module 101 fixes the waste lead-acid battery to be dismantled onto the scanning platform of the X-ray computed tomography (CT) equipment; starts the scanning equipment to perform a three-dimensional scan of the waste lead-acid battery; during the scanning process, X-rays penetrate the battery, and X-ray three-dimensional scan data is generated based on the density differences of different materials inside (such as lead and plastic) (differences in the absorption rate of X-rays by different materials (lead and plastic) inside the waste lead-acid battery). Among them, high-density materials such as lead absorb more X-rays and appear as high grayscale values ​​(pixel values ​​of high-density materials) in the scan data; low-density materials such as plastic absorb less X-rays and appear as low grayscale values ​​(pixel values ​​of low-density materials). The data acquisition module 101 reads the identification code (such as QR code or barcode) on the casing of the waste lead-acid battery and retrieves the corresponding battery design parameters (battery model, sealing gap width (physical gap between the battery cover and the casing), standard dimensions (such as length, width, and height) and internal component reference positions (the theoretical three-dimensional coordinates of the internal components (busbars, grids) of different battery models) from the preset battery model database (which stores different battery design parameters) established based on the design drawings and specifications of different models of waste lead-acid batteries.

[0111] Receives X-ray three-dimensional scan data and battery design parameters transmitted by data acquisition module 101.

[0112] Image analysis software (used to calculate grayscale value distribution to generate a grayscale histogram) is used to calculate the grayscale value distribution (statistical frequency characteristics of grayscale values) of each voxel (three-dimensional pixel) in the X-ray three-dimensional scan data acquired by the data acquisition module 101, generating a grayscale histogram (a two-dimensional chart, where the horizontal axis represents grayscale value and the vertical axis represents the number of voxels (frequency) corresponding to the grayscale value); then, the data is segmented according to the grayscale threshold set by the battery design parameters (used to segment the X-ray three-dimensional scan data into high grayscale regions and low grayscale regions) (e.g., high grayscale regions correspond to lead components, low grayscale regions...). The system generates high-grayscale and low-grayscale regions (corresponding to plastic). Based on these regions, it identifies the contours of the busbars (lead strips connecting battery electrodes) and the lead grids (mesh structures supporting lead paste). Then, it uses edge detection algorithms (such as the Canny algorithm, used to locate the busbar-grid transition point and the root position of the grid) to locate the busbar-grid transition point (the connection point between the busbar and the lead grid) and the root position of the grid (the anchor point where the lead grid is fixed to the bottom of the battery, and the distance between the extended trajectory and the inner wall of the battery casing is less than 0.5 mm).

[0113] A virtual straight line or curve, i.e., a connection equation, is generated by geometric calculations (such as the least squares method) connecting the transition point of the busbar-grid to the root position of the grid. Then, combined with battery design parameters (such as the width of the sealing seam and the reference position of internal components), the connection equation is dynamically adjusted to calculate the Z-axis height (vertical height value) of the cutting path.

[0114] Receive the Z-axis height of the cutting path transmitted by the data analysis module 102.

[0115] The cutting tool (such as a laser or mechanical saw) is controlled to cut along the sealing seam path with the Z-axis height as a reference (e.g., moving the cutting head along the seam trajectory while maintaining a constant Z-axis height). During the cutting process, the temperature change of the housing is monitored by a temperature sensor fixed to the working end sidewall of the cutting tool (laser head / mechanical saw) (the amount of rise or fall of the battery housing surface temperature relative to the initial state (before cutting) during the cutting process). When local thermal deformation is detected (the change in physical shape of different small areas (not the whole) of the battery housing during cutting (e.g., expansion or contraction)), thermal deformation compensation is implemented (e.g., dynamically fine-tuning the Z-axis height of the cutting path). Vibration suppression is implemented synchronously while the cutting tool is running, for example, by activating a damping device (e.g., a hydraulic damper) or adjusting the cutting speed / pressure (the rate at which the cutting tool moves along the sealing seam path / the force applied by the cutting tool to the housing surface) to reduce mechanical vibration and ensure that vibration does not affect the stability of the X-ray scan data of the data acquisition module.

[0116] This solution utilizes a data acquisition module to obtain X-ray 3D scan data and battery design parameters from waste lead-acid batteries. This visualizes the key internal structures of the batteries, preventing physical damage and mitigating potential acid leakage or lead dust diffusion during initial disassembly. Simultaneously, it ensures the reliability of the cutting path calculation, reduces positioning errors caused by battery model differences, optimizes cutting parameters, and improves overall disassembly efficiency. The data analysis module analyzes the grayscale distribution of the X-ray 3D scan data to determine the busbar-grid transition point and the grid root position, solving the problem of non-destructive high-precision positioning and ensuring the accuracy of key point coordinates, avoiding damage to internal materials caused by blind cutting. Based on the equation connecting the busbar-grid transition point and the grid root position, combined with battery design parameters, the Z-axis height of the cutting path is dynamically calculated, enabling real-time adjustment of the cutting path to adapt to individual battery differences. This ensures the path is always precisely aligned with the sealing seam, preventing damage to lead paste or lead grids during cutting. Furthermore, it optimizes calculations using battery design parameters, improving efficiency and reducing trial and error. The cutting control module is used to perform separation operations along the sealing seam based on the Z-axis height, and simultaneously implement thermal deformation compensation and vibration suppression to solve the problem of preset path failure caused by thermal deformation, maintain cutting accuracy, and avoid shell breakage or material mixing caused by path deviation; it also solves the problem of mechanical vibration affecting cutting accuracy and imaging clarity, and improves operational stability and cutting quality.

[0117] Figure 2 This is a schematic diagram of the structure of a high-efficiency dismantling system for waste lead-acid batteries provided in an embodiment of this application, as shown below. Figure 2 Shown:

[0118] In some embodiments, the grayscale distribution of X-ray three-dimensional scanning data is analyzed to identify grayscale value jump intervals; within the jump interval, the busbar-grid transition point is determined by the second derivative extreme point; based on the coordinates of the busbar-grid transition point, the extension trajectory between the grid edge line and the bottom of the battery is determined; based on the extension trajectory, the root position of the grid is determined.

[0119] A grayscale value jump range can be a continuous region in X-ray 3D scan data where the grayscale value changes drastically.

[0120] The extreme points of the second derivative can be local maximum or minimum points identified by calculating the second derivative of the gray value sequence within the gray value jump range.

[0121] The coordinates of the busbar-grid transition point can be the three-dimensional spatial coordinates of the connection between the busbar and the grid.

[0122] The edge line of the grid plate can be the boundary contour line of the grid plate assembly in three-dimensional space.

[0123] The bottom of the battery can serve as a reference point for the bottom of a waste lead-acid battery.

[0124] The extended trajectory can be a sequence of three-dimensional coordinate points generated by linearly extrapolating from the busbar-grid transition point coordinates along the grid edge towards the bottom of the battery.

[0125] Specifically, the grayscale distribution of the X-ray 3D scan data is traversed to extract the grayscale value sequence (an ordered set of grayscale values); based on the grayscale value sequence, the gradient (first derivative) of the grayscale values ​​is calculated, and the grayscale change rate (representing how fast the grayscale value changes with position) is analyzed along the X, Y, and Z directions; when the grayscale change rate exceeds a preset threshold set based on expert experience (used to mark the grayscale value jump interval), it is marked as a grayscale value jump interval, where the grayscale value transitions sharply from low to high or from high to low (such as the boundary area between lead components and plastic components).

[0126] Within the grayscale value transition range, the second derivative is calculated along the grayscale value sequence. When the second derivative reaches a local maximum or minimum value (the highest point (local maximum) or lowest point (local minimum) reached in different local neighborhoods in the second derivative), it is marked as an extreme point of the second derivative. The extreme points of the second derivative are mapped back to three-dimensional spatial coordinates as candidate positions for the busbar-grid transition point. Then, based on the candidate positions, the most significant extreme points are selected by clustering algorithm and determined as the busbar-grid transition point.

[0127] Starting from the coordinates of the busbar-grid transition point, extend linearly along the grid edge direction (the extension direction of the grid assembly boundary profile); in three-dimensional space, fit a straight line from the busbar-grid transition point to the bottom of the battery (representing the theoretical direction of the grid edge line); along the fitted straight line, push outward from the busbar-grid transition point towards the bottom of the battery to generate the extension trajectory between the grid edge line and the bottom of the battery.

[0128] Scan along the extended trajectory and detect the intersection of the trajectory with the reference plane at the bottom of the battery (representing the bottom position of the waste lead-acid battery). If the distance between the extended trajectory and the inner wall of the battery casing is less than 0.5mm, it is the root position of the grid plate.

[0129] This solution analyzes the grayscale distribution of X-ray 3D scanning data, identifies abrupt grayscale value changes, and locates areas with significant grayscale gradient variations in the X-ray scanning data, avoiding the waste of resources in global scanning. Within these abrupt changes, the transition point between the busbar and grid is determined using the extreme points of the second derivative, solving the challenge of locating this transition point and providing a high-precision starting point for the cutting path. Based on the coordinates of the busbar-grid transition point, the extended trajectory between the grid edge line and the bottom of the battery is determined, expanding the discrete transition point into a continuous path, providing directional guidance for root location, and ensuring that the trajectory covers the complete spatial orientation of the grid. Based on the extended trajectory, the root position of the grid is determined, avoiding cutting damage to the internal lead grid or lead paste.

[0130] In some embodiments, a line equation is established connecting the transition point of the busbar-grid plate and the root position of the grid plate; the battery design parameters are analyzed to determine the sealing width of the battery cover sealing seam and the preset offset from the center line of the seam to the surface of the casing; based on the line equation and the preset offset, a cutting path point set is generated; the Z-axis coordinate component of the cutting path point set is extracted; based on the sealing seam width, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path.

[0131] The sealing seam of the battery cover can be the physical connection gap between the cover and the casing of a waste lead-acid battery.

[0132] The width of the sealing seam can be the lateral dimension of the sealing seam on the battery cover.

[0133] The center line of the seam can be the geometric center line in the width direction of the sealing seam.

[0134] The casing surface can be the outer surface of the battery casing.

[0135] The preset offset can be the vertical distance from the center line of the seal to the surface of the battery casing, which is pre-stored in the server and called when needed.

[0136] The cutting path point set can be a three-dimensional coordinate sequence used to define the cutting trajectory.

[0137] The Z-axis coordinate component can be the Z-axis coordinate value of each point in the cutting path point set.

[0138] The final cutting height curve can be a continuous curve representing the height change of the cutting path in the Z-axis direction, generated after Gaussian filtering and smoothing the Z-axis coordinate components.

[0139] The cutting path can be the trajectory that the cutting tool needs to dynamically execute.

[0140] Specifically, based on the transition point between the busbar and the grid plate and the position of the grid plate root, a linear fitting method is used to generate the connection equation. Battery design parameters are analyzed, and the physical width representing the battery cover seal seam is retrieved and extracted from a battery design parameter database (which stores data on seal seam width and preset offset) built based on the battery manufacturer's design drawings. This width is used as the seal seam width. Simultaneously, the vertical distance from the seal seam centerline to the battery casing surface is retrieved and extracted as the preset offset.

[0141] Multiple points are sampled at equal intervals along the connecting line equation, and the number of sampling points is set. The coordinates of each point are calculated. Then, the coordinates of each point are offset by a preset offset along the normal direction of the shell surface (the direction vector perpendicular to the surface tangent plane at any point on the battery shell surface) (ensuring that the point set is accurately located on the center line of the sealing seam), and the cutting path point set is generated. For each point in the traversed cutting path point set, the Z-axis coordinate component is separated and extracted.

[0142] Based on the width of the sealing joint, set the parameters of the Gaussian filter (the filter control variable is set according to the width of the sealing joint); use the Gaussian kernel function to perform convolution operation on the Z-axis coordinate components to smooth the Z-axis values, reduce local fluctuations, and generate a smoothed Z-sequence (an ordered sequence of Z-axis coordinate components); then convert the smoothed Z-sequence into the final cutting height curve; and finally output the final cutting height curve directly as the Z-axis height of the cutting path.

[0143] This solution establishes a line equation connecting the busbar-grid transition point to the grid root position, ensuring that the start and end points of the cutting path are strictly aligned with the critical boundaries of the battery's internal structure. This prevents the cutting tool from accidentally cutting internal lead paste or lead grid components and supports dynamic calculation of the cutting trajectory along the sealing seam. Battery design parameters are analyzed to determine the sealing seam width and the preset offset from the seam centerline to the casing surface, ensuring that the cutting path point set is accurately mapped to the sealing seam centerline position. This avoids path deviations due to differences in battery models and provides an input benchmark for generating the cutting point set. Based on the line equation and preset offset, the cutting path point set is generated, ensuring that the cutting path accurately corresponds to the geometric center of the battery cover sealing seam in three-dimensional space. This provides spatial point data for height calculation and supports dynamic path generation. The Z-axis coordinate component of the cutting path point set is extracted to ensure more efficient adjustment of the cutting tool's movement along the Z-axis. Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path. This ensures that the Z-axis height of the cutting path adapts to the actual shape of the sealing joint, making the cutting tool move smoothly and reducing the risk of path deviation during the cutting process.

[0144] In some embodiments, X-ray three-dimensional scanning data is analyzed to determine the battery height direction; a coordinate system is established with the root position of the grid plate as the origin O and the battery height direction as the Z-axis; the spatial vector between the busbar-grid plate transition point and the origin O is analyzed to generate the connection equation.

[0145] The height direction of the battery can be the physical vertical direction from bottom to top of the waste lead-acid battery.

[0146] The origin O can be the zero point of the coordinate system.

[0147] The coordinate system can be a three-dimensional rectangular coordinate system constructed with the origin O as the zero point and the battery height direction as the positive Z-axis.

[0148] A spatial vector can be a directed line segment pointing from the origin O to the transition point of the busbar-grid.

[0149] Specifically, the geometric features (such as shape, size, and spatial arrangement) of the X-ray three-dimensional scan data are analyzed to identify the overall external contour of the battery (the physical boundary of the battery casing) and the distribution trend of internal components (including casing, top cover, lead paste, lead grid, etc.); based on the distribution trend, the vertical direction of the battery, i.e. the height direction of the battery, is determined.

[0150] Set the three-dimensional coordinates of the base of the grid as the origin O of the coordinate system (i.e., coordinate point (0,0,0)); then define the height direction of the battery as the Z-axis (pointing towards the top of the battery), and establish the coordinate system based on the origin O.

[0151] Based on the coordinate system, calculate the spatial vector of the busbar-grid transition point relative to the origin O; with the origin O as the starting point and the busbar-grid transition point as the ending point, define a straight path using the spatial vector and generate the connection equation.

[0152] This solution analyzes X-ray 3D scan data to determine the battery height direction, eliminating directional deviations caused by battery tilting or deformation. A coordinate system is established with the root of the grid plate as the origin O and the battery height direction as the Z-axis. This eliminates the influence of overall battery positional offset, ensuring that the calculated Z-axis height of the cutting path matches the actual physical direction of the battery and reducing vector computation complexity. The spatial vector between the busbar-grid transition point and the origin O is analyzed to generate a connection equation, ensuring the cutting tool moves strictly along the lead grid boundary and avoids cutting into the lead paste area.

[0153] In some embodiments, the battery casing identification code is obtained; the historical cutting parameter database is queried based on the identification code; when a matching record exists, the optimal cutting speed and pressure value of the corresponding matching record are loaded.

[0154] The battery casing identification code can be a unique code printed or affixed to the surface of a waste lead-acid battery casing.

[0155] The historical cutting parameter library can be a structured database that stores historical cutting operation parameter records corresponding to different identifier codes.

[0156] The matching record can be a data entry in the historical cutting parameter library that is completely consistent with the current battery casing identification code.

[0157] The optimal cutting speed can be the tool movement rate for separating the top cover of the battery with the identification code, as stored in the matching record.

[0158] The pressure value can be the pressure applied by the tool used to perform the cover separation operation on the identified battery, which is stored in the matching record.

[0159] Specifically, the identification code printed or attached to the surface of the waste lead-acid battery casing is directly read using scanning equipment (such as an optical barcode scanner or RFID reader). If the identification code is in image form, the string is extracted using OCR (Optical Character Recognition); if it is an RFID tag (a radio frequency identification electronic tag attached to the surface of the waste lead-acid battery casing), the electronic code is read directly.

[0160] Using the identification code as the query keyword, the system searches the historical cutting parameter database (which stores historical cutting operation parameter records corresponding to different identification codes) in the historical successful operation data (a collection of operation records of different models / batch batteries performing the complete dismantling process) of the waste lead-acid battery dismantling process. If a completely identical identification code is found, it is determined that a matching record exists; otherwise, it is determined that no matching record exists.

[0161] When a matching record exists, the optimal cutting speed and pressure value of the corresponding matching record are directly extracted.

[0162] This solution obtains the battery casing identification code, addressing the need to reduce trial and error and skipping the stage of blindly exploring parameters for new battery models. It queries the historical cutting parameter database based on the identification code, avoiding fluctuations in cutting quality caused by differences in battery models. When a matching record exists, it loads the optimal cutting speed and pressure values ​​for that record, reducing trial and error during the cutting process and increasing the first-time success rate.

[0163] In some embodiments, the data analysis module includes a speed setting unit 1021, used for: parsing X-ray three-dimensional scanning data to determine the battery casing thickness and battery material; determining the coefficient of thermal expansion of the material based on the battery material; determining the casing melting point temperature based on the battery casing thickness and battery material; calculating the heat generated per unit time based on the battery casing thickness and the coefficient of thermal expansion of the material; and dynamically setting the upper limit of the cutting speed based on the difference between the heat generated per unit time and the casing melting point temperature to obtain the optimal cutting speed.

[0164] The thickness of the battery casing can be the physical thickness of the battery's plastic outer shell.

[0165] The battery material can be the same as the battery casing material.

[0166] The coefficient of thermal expansion of a material can be defined as the relative rate of change of the material's length per unit temperature change.

[0167] The melting point temperature of the battery casing can be the critical temperature at which the battery casing material melts.

[0168] Heat generated per unit time can be the amount of heat generated per second during the cutting process.

[0169] The upper limit of the cutting speed can be the maximum allowable moving speed of the cutting tool, which is dynamically set to prevent the shell from overheating and failing.

[0170] Specifically, the X-ray 3D scan data is analyzed, and multiple measurement points are selected along the surface of the battery casing. The Euclidean distance from the outer surface of the casing to the inner surface (the surface in contact with the lead paste) is measured, and the average value of all measurement points is taken to obtain the battery casing thickness. Simultaneously, based on the density distribution characteristics in the X-ray 3D scan data (battery casings of different materials (such as polypropylene and ABS plastic) exhibit different grayscale value distributions in the scan; high-density areas such as lead paste appear bright white, while low-density areas such as plastic casings appear grayish-black), the battery material is identified by matching it against a predefined material database (storing common battery materials).

[0171] Based on the battery material, the system queries a material property database (which stores material types and their corresponding coefficients of thermal expansion) established according to industry standards to obtain the corresponding coefficient of thermal expansion. Based on the battery casing thickness, the system queries a pre-set material property database (which stores the melting point temperature of materials) using the battery material as the keyword to obtain the corresponding casing melting point temperature.

[0172] Based on the battery casing thickness and the thermal expansion coefficient of the material, a heat generation rate lookup table (which stores the mapping relationship between battery casing thickness and material thermal expansion coefficient and heat generation per unit time) is established based on experimental data (simulating cutting heat generation experiments under different combinations of thickness and thermal expansion coefficient). The heat generation per unit time is determined, where the heat generation per unit time is directly proportional to the material thermal expansion coefficient (the higher the material thermal expansion coefficient, the greater the thermal deformation and the higher the heat generation), and inversely proportional to the battery casing thickness (the greater the battery casing thickness, the slower the heat conduction and the higher the accumulated heat generation).

[0173] The difference between the heat generated per unit time and the shell's melting point temperature is calculated through thermodynamic equivalent conversion. Then, based on historical experimental data (critical conditions under which the shell did not melt or deform during numerous cutting tests), a safety threshold (a critical warning value for the difference between the heat generated per unit time and the shell's melting point temperature, used to compare the difference) is calibrated. If the difference is greater than the safety threshold, the upper limit of the cutting speed is reduced; if the difference is less than the safety threshold, the upper limit of the cutting speed is increased. The adjustment range (reduction or increase) is determined through a speed-difference mapping table (pre-stored speed adjustment values ​​corresponding to the difference range). Finally, the adjusted upper limit of the cutting speed is directly output as the optimal cutting speed.

[0174] This solution analyzes X-ray 3D scan data to determine the battery casing thickness and material, ensuring that the speed setting unit can be customized for the physical characteristics of different batteries. This avoids the risk of thermal deformation during cutting due to unknown casing thickness or material. Based on the battery material, the thermal expansion coefficient is determined, ensuring that heat generation calculations and speed adjustments are based on data, preventing deviations from the preset cutting path due to inaccurate expansion coefficients. Based on the battery casing thickness and material, the casing melting point temperature is determined to prevent melting or excessive softening of the casing due to cutting heat, ensuring that the cutting tool will not damage the casing structure due to excessive temperature, thus maintaining the stability and sealing of the cutting path. Based on the battery casing thickness and material thermal expansion coefficient, the heat generation per unit time is calculated, ensuring real-time assessment of heat accumulation risk and preventing localized thermal expansion and path deviation caused by excessive heat generation. Based on the difference between the heat generation per unit time and the casing melting point temperature, the upper limit of the cutting speed is dynamically set to obtain the optimal cutting speed, ensuring that the cutting process is carried out within a safe temperature range, effectively suppressing thermal deformation and maintaining cutting accuracy.

[0175] In some embodiments, the cutting control module 103 includes an acceleration sensor 1031 connected to the data acquisition module 101. When the cutting control module 103 performs a separation operation along the sealing seam, the data acquisition module 101 synchronously acquires the vibration spectrum and sends it to the data analysis module 102. The data analysis module 102 is used to analyze the vibration spectrum, determine the reverse damping force, and send it to the acceleration sensor. The acceleration sensor is used to adjust the acceleration to generate a reverse damping force to counteract the mechanical vibration.

[0176] Vibration spectrum can be frequency domain data that characterizes the distribution of mechanical vibration energy at different frequencies.

[0177] The reverse damping force can be a vector force value used to counteract vibration energy.

[0178] Acceleration can be a physical quantity that characterizes the rate of change of the motion state of a cutting tool.

[0179] Mechanical vibration can be mechanical fluctuations caused by cutting tools.

[0180] Specifically, the cutting control module 103 is activated, driving the cutting tool to move along the sealing seam path. During the movement, the tool head contacts the housing surface and performs a cutting action (such as sawing or laser ablation) to separate the top cover. While the cutting control module 103 is performing the separation operation, the data acquisition module 101 synchronously receives the raw vibration signal from the accelerometer (a component of the cutting control module 103) via a wired or wireless connection. Then, the data acquisition module 101 converts the raw vibration signal into a vibration spectrum and transmits it to the data analysis module 102 in real time.

[0181] The data analysis module 102 analyzes the vibration spectrum and identifies the main vibration frequency components (frequency components with significantly higher amplitude (i.e., stronger energy) in the vibration spectrum). Then, based on the frequency-force mapping table established by expert experience (which stores the correspondence between the main vibration frequency components and the reverse damping force, and is used to map the main vibration frequency components to the corresponding reverse damping force), the main vibration frequency components are mapped to the reverse damping force (e.g., high-frequency vibration corresponds to a larger reverse damping force), and the data is sent back to the acceleration sensor in real time.

[0182] After receiving the reverse damping force, the accelerometer generates a reverse mechanical force (such as applying a thrust opposite to the direction of vibration). This force acts directly on the cutting tool head, causing the mechanical vibration to be partially or completely canceled out, thereby ensuring the stability of the cutting process.

[0183] This solution enables the data acquisition module to simultaneously acquire the vibration spectrum and send it to the data analysis module while the cutting control module performs the separation operation along the sealing seam. This provides precise characterization of the vibration state, offering real-time and complete input data to the analysis module, avoiding signal delay or distortion, and ensuring strict synchronization between vibration monitoring and the cutting action. The data analysis module analyzes the vibration spectrum, determines the reverse damping force, and sends it to the accelerometer to enable rapid transmission of compensation commands. This ensures that the analysis results are directly applied to the execution end, forming a closed-loop link from analysis to execution. The accelerometer adjusts the acceleration to generate a reverse damping force to counteract mechanical vibration, thereby reducing or eliminating the amplitude of mechanical vibration during the cutting process, stabilizing the cutting path, preventing vibration interference, and ensuring smooth separation operations.

[0184] In some embodiments, the system further includes a sealed negative pressure adsorption device 104 connected to the data acquisition module 101; when the cutting control module 103 performs a separation operation along the sealing seam, the data acquisition module 101 is used to acquire separation operation data; the data analysis module 102 is used to analyze the separation operation data and determine the cutting seam opening rate; based on the cutting seam opening rate, the real-time negative pressure adsorption intensity is determined; and the sealed negative pressure adsorption device 104 is used to adjust the adsorption parameters in real time based on the real-time negative pressure adsorption intensity.

[0185] Separation operation data can be operation-related data that reflects the actual state of the cutting process.

[0186] The kerf opening rate can be the rate at which the width of the kerf changes.

[0187] Real-time negative pressure adsorption intensity can be defined as the magnitude of the adsorption force that a sealed negative pressure adsorption device should apply during the cutting process.

[0188] The adsorption parameters can be adjusted in real time based on the real-time negative pressure adsorption intensity.

[0189] Specifically, the cutting control module 103 drives a cutting tool (such as a saw blade or laser head) to move along the sealing seam. The cutting tool head contacts the surface of the battery casing and performs a cutting action (such as sawing or laser ablation) to separate the top cover. While the cutting control module 103 is performing the separation operation, the data acquisition module 101 monitors the cutting process in real time via a wired or wireless connection, acquires separation operation data (including the real-time width of the cutting seam, position coordinates, and timestamp), and transmits it to the data analysis module 102 in real time.

[0190] The data analysis module 102 analyzes the separation operation data, calculates the rate of change of the cutting slit opening size over time, and determines the cutting slit opening rate. For example, when the cutting slit opening rate is high, the risk of pollutants such as acid or lead dust escaping increases; when the cutting slit opening rate is low, the risk is relatively reduced.

[0191] Based on the slit opening rate, the system queries a pre-defined mapping relationship (which stores the mapping relationship between the slit opening rate and the real-time negative pressure adsorption intensity, used to quickly convert the slit opening rate into the real-time negative pressure adsorption intensity) to determine the real-time negative pressure adsorption intensity. For example, when the slit opening rate is high, a higher real-time negative pressure adsorption intensity is assigned to enhance the adsorption capacity for rapidly dissipating pollutants; when the slit opening rate is low, a lower real-time negative pressure adsorption intensity is assigned to optimize energy consumption and avoid over-adsorption.

[0192] After receiving the real-time negative pressure adsorption intensity sent by the data analysis module 102, the sealed negative pressure adsorption device 104 dynamically adjusts the adsorption parameters (vacuum degree / flow rate). For example, when the cutting slit opening rate is high, the adsorption intensity increases and the adsorption parameters rise, thereby enhancing the capture force of splashed acid / lead dust. When the cutting slit opening rate decreases, the adsorption intensity weakens and the adsorption parameters decrease, thereby reducing energy consumption and avoiding over-adsorption. When leakage or lead dust exceeds the standard, the adsorption intensity level is forcibly increased and the adsorption parameters increase sharply, thereby urgently strengthening pollution control of acid splash and lead dust diffusion.

[0193] This solution employs a data acquisition module to obtain separation operation data while the cutting control module performs separation operations along the sealed seam. This ensures that the contamination control process is synchronized with the cutting operation, preventing control lag due to data loss. The data analysis module analyzes the separation operation data to determine the cutting seam opening rate, quantify the dynamic changes of the cutting seam, and identify the potential risk level of contaminant escape. Based on the cutting seam opening rate, the real-time negative pressure adsorption intensity is determined, enabling precise response in contamination control and reducing the risk of acid splashing and lead dust diffusion. The sealed negative pressure adsorption device adjusts adsorption parameters in real-time based on the real-time negative pressure adsorption intensity, effectively preventing contaminants from escaping into the environment. This ensures that the cutting process meets the emphasized clean dismantling requirements, reducing environmental pollution and occupational exposure risks.

[0194] Figure 3 This document provides a flowchart of an efficient dismantling process for waste lead-acid batteries, as illustrated in one embodiment of this application. The method described in this embodiment can be applied to servers in the aforementioned scenarios. Figure 3 As shown, the method includes:

[0195] S201. Obtain X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries;

[0196] S202. Analyze the grayscale distribution of X-ray three-dimensional scanning data to determine the transition point between the busbar and the grid plate and the location of the grid plate root.

[0197] S203. Based on the equation of the line connecting the busbar-grid transition point and the root position of the grid, and combined with the battery design parameters, dynamically calculate the Z-axis height of the cutting path;

[0198] S204. Based on the Z-axis height, control the cutting tool to perform separation operation along the sealing seam, and simultaneously implement thermal deformation compensation and vibration suppression.

[0199] Optionally, analyze the grayscale distribution of the X-ray three-dimensional scan data to determine the busbar-grid transition point and the root position of the grid, including:

[0200] Analyze the grayscale distribution of X-ray three-dimensional scan data to identify grayscale value jump intervals;

[0201] Within the abrupt transition range, the busbar-grid transition point is determined by the extreme points of the second derivative;

[0202] Based on the coordinates of the transition point between the busbar and the grid, determine the extension trajectory between the grid edge line and the bottom of the battery;

[0203] The location of the root of the grid plate is determined based on the extended trajectory.

[0204] Optionally, based on the equation of the line connecting the busbar-grid transition point and the root position of the grid, and in conjunction with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated, including:

[0205] Establish the equation for the line connecting the busbar-grid transition point and the root position of the grid;

[0206] Analyze the battery design parameters to determine the sealing width of the battery top cover sealing seam and the preset offset of the seam centerline from the shell surface;

[0207] Based on the connection equation and the preset offset, a set of cutting path points is generated by mapping.

[0208] Extract the Z-axis coordinate components of the cutting path point set;

[0209] Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path.

[0210] Optionally, establish the equation for the line connecting the busbar-grid transition point and the root position of the grid, including:

[0211] Analyze X-ray 3D scan data to determine the battery height orientation;

[0212] Establish a coordinate system with the root of the grid plate as the origin O and the height direction of the battery as the Z-axis;

[0213] Analyze the spatial vectors between the busbar-grid transition point and the origin O to generate the connection equation.

[0214] Optionally, before performing the separation operation along the sealing seam based on the Z-axis height, the method further includes: obtaining the battery casing identification code; querying the historical cutting parameter library based on the identification code; and loading the optimal cutting speed and pressure value of the corresponding matching record when a matching record exists.

[0215] Optionally, the method also includes:

[0216] Analyze X-ray 3D scan data to determine the battery casing thickness and battery material;

[0217] Determine the coefficient of thermal expansion of the battery material;

[0218] Determine the melting point temperature of the battery casing based on its thickness and material.

[0219] The heat generated per unit time is calculated based on the thickness of the battery casing and the coefficient of thermal expansion of the material; the upper limit of the cutting speed is dynamically set based on the difference between the heat generated per unit time and the melting point temperature of the casing, so as to obtain the optimal cutting speed.

[0220] Optionally, the method also includes:

[0221] Vibration spectrum is acquired simultaneously during the separation operation along the sealing seam;

[0222] Analyze the vibration spectrum to determine the reverse damping force and send it to the accelerometer;

[0223] Accelerometers are used to adjust acceleration and generate a counter-damping force to counteract mechanical vibrations.

[0224] Optionally, the method also includes:

[0225] Separation operation data is acquired during the separation operation along the sealing seam;

[0226] Analyze the separation operation data to determine the cutting kerf opening rate;

[0227] The real-time negative pressure adsorption intensity is determined based on the cutting slit opening rate;

[0228] The sealed negative pressure adsorption device is used to adjust the adsorption parameters in real time based on the real-time negative pressure adsorption intensity.

[0229] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A high-efficiency dismantling system for waste lead-acid batteries, characterized in that, It includes a data acquisition module, a data analysis module, and a cutting control module; The data acquisition module, the data analysis module, and the cutting control module are connected in sequence; The data acquisition module is used to acquire X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries; The data analysis module is used to analyze the grayscale distribution of the X-ray three-dimensional scan data and determine the transition point between the busbar and the grid plate and the root position of the grid plate. Based on the equation connecting the busbar-grid transition point and the root position of the grid, and combined with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated. The cutting control module is used to perform a separation operation along the sealing seam based on the Z-axis height, and simultaneously implement thermal deformation compensation and vibration suppression.

2. The system according to claim 1, characterized in that, When the data analysis module analyzes the grayscale distribution of the X-ray three-dimensional scan data to determine the busbar-grid transition point and the root position of the grid, it is used for: Analyze the grayscale distribution of the X-ray three-dimensional scan data to identify the grayscale value jump intervals; Within the aforementioned transition range, the busbar-grid transition point is determined by the extreme points of the second derivative; Based on the coordinates of the busbar-grid transition point, determine the extension trajectory between the grid edge line and the bottom of the battery; The root position of the grid plate is determined based on the extended trajectory.

3. The system according to claim 1, characterized in that, The data analysis module, based on the equation connecting the busbar-grid transition point and the grid root position, and in conjunction with the battery design parameters, dynamically calculates the Z-axis height of the cutting path, and is used for: Establish the equation for the line connecting the transition point of the busbar-grid plate and the root position of the grid plate; Analyze the battery design parameters to determine the sealing width of the battery top cover sealing seam and the preset offset of the seam centerline from the shell surface; Based on the connection equation and the preset offset, a set of cutting path points is generated by mapping. Extract the Z-axis coordinate components of the cutting path point set; Based on the width of the sealing joint, the Z-axis coordinate component is smoothed by Gaussian filtering to generate the final cutting height curve, thus obtaining the Z-axis height of the cutting path.

4. The system according to claim 3, characterized in that, When the data analysis module establishes the equation connecting the busbar-grid transition point and the root position of the grid plate, it is used for: Analyze the X-ray three-dimensional scan data to determine the battery height orientation; A coordinate system is established with the root position of the grid plate as the origin O and the height direction of the battery as the Z-axis; Analyze the spatial vector between the busbar-grid transition point and the origin O to generate the connection equation.

5. The system according to claim 1, characterized in that, Before the cutting control module performs the separation operation along the sealing seam based on the Z-axis height, the data analysis module is also used to: obtain the battery casing identification code; query the historical cutting parameter library according to the identification code; and when a matching record exists, load the optimal cutting speed and pressure value of the corresponding matching record.

6. The system according to claim 5, characterized in that, The data analysis module includes a speed setting unit, used for: The X-ray three-dimensional scan data was analyzed to determine the battery casing thickness and battery material. Determine the coefficient of thermal expansion of the battery material based on the battery material. The melting point temperature of the battery casing is determined based on the thickness of the battery casing and the battery material. The heat generated per unit time is calculated based on the thickness of the battery casing and the coefficient of thermal expansion of the material. Based on the difference between the heat generated per unit time and the melting point temperature of the shell, the upper limit of the cutting speed is dynamically set to obtain the optimal cutting speed.

7. The system according to claim 5, characterized in that, The cutting control module includes an acceleration sensor, which is connected to the data acquisition module; While the cutting control module performs the separation operation along the sealing seam, the data acquisition module simultaneously acquires the vibration spectrum and sends it to the data analysis module; The data analysis module is used to analyze the vibration spectrum, determine the reverse damping force, and send it to the acceleration sensor. The accelerometer is used to adjust the acceleration to generate the reverse damping force to counteract mechanical vibration.

8. The system according to claim 5, characterized in that, The system also includes a sealed negative pressure adsorption device, which is connected to the data acquisition module; When the cutting control module performs a separation operation along the sealing seam, the data acquisition module is used to acquire separation operation data; The data analysis module is used to analyze the separation operation data and determine the cutting slit opening rate. The real-time negative pressure adsorption intensity is determined based on the cutting slit opening rate; The sealed negative pressure adsorption device is used to adjust the adsorption parameters in real time according to the real-time negative pressure adsorption intensity.

9. A high-efficiency dismantling process for waste lead-acid batteries, characterized in that, include: Obtain X-ray three-dimensional scanning data and battery design parameters of waste lead-acid batteries; Analyze the grayscale distribution of the X-ray three-dimensional scan data to determine the transition point between the busbar and the grid plate, as well as the location of the grid plate root. Based on the equation connecting the busbar-grid transition point and the root position of the grid, and combined with the battery design parameters, the Z-axis height of the cutting path is dynamically calculated. Based on the Z-axis height, the cutting tool is controlled to perform a separation operation along the sealing seam, while thermal deformation compensation and vibration suppression are implemented simultaneously.

10. The process according to claim 9, characterized in that, The analysis of the grayscale distribution of the X-ray three-dimensional scan data to determine the busbar-grid transition point and the root position of the grid includes: Analyze the grayscale distribution of the X-ray three-dimensional scan data to identify the grayscale value jump intervals; Within the aforementioned transition range, the busbar-grid transition point is determined by the extreme points of the second derivative; Based on the coordinates of the busbar-grid transition point, determine the extension trajectory between the grid edge line and the bottom of the battery; The root position of the grid plate is determined based on the extended trajectory.

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