A material roughening treatment method and device, electronic equipment and readable storage medium

Abstract

This application discloses a material texturing method, apparatus, electronic device, and readable storage medium, relating to the field of material processing technology. The method includes acquiring geometric parameter information of the material to be processed, and a first visual recognition result of visually recognizing the material; generating laser processing trajectory information by combining the geometric parameter information of the material and the first visual recognition result; acquiring a second visual recognition result of visually recognizing the material while it is fixed on an adsorption platform; adjusting the laser processing trajectory information based on the second visual recognition result; and performing laser texturing on the material based on the adjusted laser processing trajectory information. This application improves the efficiency of material electrode connection processing and achieves high-strength connection of material electrodes.

Description

Technical Field

[0001] This application relates to the field of material processing technology, and in particular to a material texturing method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] The tab-plate composite connection is an important part of the 3C battery manufacturing process. The tab-plate composite connection process is usually carried out by hot pressing with conductive adhesive. In order to improve conductivity and connection strength, the surface of the tab needs to be pretreated. The quality of the surface roughening of the tab will have a significant impact on the battery's internal resistance, capacity and connection strength.

[0003] In related technologies, electrode pretreatment often employs ultrasonic high-frequency vibration welding, a method known for its good stability and high reliability. However, due to limitations in the processing principle, the production process requires cleaning and grooving on both sides of the electrode, increasing process complexity, reducing the electrode coating area, and hindering the improvement of battery capacity. Summary of the Invention

[0004] The purpose of this application is to at least solve one of the technical problems existing in the prior art, and to provide a material texturing process method, apparatus, electronic device and readable storage medium, which aims to improve the efficiency of material electrode connection processing and achieve high-strength connection of material electrodes.

[0005] In a first aspect, embodiments of this application provide a material texturing treatment method, including:

[0006] Obtain the geometric parameter information of the material to be processed, and the first visual recognition result of visual recognition of the material to be processed;

[0007] By combining the geometric parameter information of the material to be processed and the first visual recognition result, laser processing trajectory information is generated;

[0008] A second visual recognition result is obtained when the material to be processed is fixed on the adsorption platform. The laser processing trajectory information is adjusted according to the second visual recognition result. The material to be processed is then subjected to laser texturing treatment according to the adjusted laser processing trajectory information.

[0009] According to the technical solution of the embodiments of this application, at least the following beneficial effects are achieved: laser texturing is performed on the material using laser technology. For example, through non-contact processing by the action of a high-energy laser beam, regular pits and crater-like protrusions can be formed on the surface of the tab to achieve texturing of the tab. This eliminates the need to clean and groove both sides of the electrode, reducing the complexity of the tab-electrode composite connection process and thus improving the efficiency of the tab-electrode connection process. Furthermore, by combining the geometric parameter information of the tab to be processed and the laser processing trajectory generated by the first visual recognition result, the accuracy and reliability of the laser processing trajectory can be enhanced, thereby achieving and strengthening the high-strength connection of the tab and the electrode.

[0010] According to some embodiments of this application, the step of generating laser processing trajectory information by combining the geometric parameter information of the material to be processed and the first visual recognition result includes:

[0011] By combining the geometric parameter information of the material to be processed and the first visual recognition result, an initial laser processing trajectory is generated;

[0012] A correction template is generated based on the geometric parameters of the material to be processed. The initial laser processing trajectory is then corrected using the correction template to obtain the laser processing trajectory information.

[0013] According to some embodiments of this application, the step of generating laser processing trajectory information by combining the geometric parameter information of the material to be processed and the first visual recognition result includes:

[0014] Based on the geometric parameters of the material to be processed, laser processing dot matrix information is generated;

[0015] Based on the first visual recognition result, the laser processing points in the laser processing dot matrix information are adaptively processed to obtain laser processing trajectory information; the adaptive processing includes filtering, adjusting and sorting the laser processing points.

[0016] According to some embodiments of this application, it also includes:

[0017] Based on the first visual recognition result, set the laser texturing processing operating parameters.

[0018] According to some embodiments of this application, obtaining a second visual recognition result of visually recognizing the material to be treated when it is fixed on the adsorption platform includes:

[0019] A second visual recognition result is obtained when the material to be treated is fixed on the adsorption platform and the negative pressure value of the adsorption platform meets the negative pressure threshold.

[0020] According to some embodiments of this application, the second visual recognition result includes the recognition result of identifying and locating a preset area of ​​the material;

[0021] The step of adjusting the laser processing trajectory information based on the second visual recognition result includes:

[0022] Based on the second visual recognition result, the preset area positioning coordinates are obtained, and the laser processing trajectory information is adjusted according to the preset area positioning coordinates.

[0023] According to some embodiments of this application, it also includes:

[0024] Visual recognition is performed on the materials that have undergone laser texturing to obtain third-vision recognition results;

[0025] Based on the third visual recognition result, laser processing feedback information is obtained.

[0026] Secondly, embodiments of this application provide an operation control device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the material texturing process method described in the first aspect.

[0027] Thirdly, embodiments of this application provide an electronic device including the operation control device described in the second aspect above.

[0028] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the material texturing process method as described in the first aspect above.

[0029] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0030] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0031] The present application will be further described below with reference to the accompanying drawings and embodiments;

[0032] Figure 1 This is a flowchart of a material texturing method provided in one embodiment of this application;

[0033] Figure 2This is a flowchart of a material texturing method provided in another embodiment of this application;

[0034] Figure 3 This is a flowchart of a material texturing method provided in another embodiment of this application;

[0035] Figure 4 This is a flowchart of a material texturing method provided in another embodiment of this application;

[0036] Figure 5 This is a flowchart of a material texturing method provided in another embodiment of this application;

[0037] Figure 6 This is a flowchart of a material texturing method provided in another embodiment of this application;

[0038] Figure 7 This is a flowchart of a material texturing method provided in another embodiment of this application;

[0039] Figure 8 This is a schematic diagram of an operation control device for performing a material texturing process according to an embodiment of this application. Detailed Implementation

[0040] This section will describe in detail the specific embodiments of this application. Preferred embodiments of this application are shown in the accompanying drawings. The purpose of the drawings is to supplement the textual description with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of this application, but they should not be construed as limiting the scope of protection of this application.

[0041] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0042] In the description of this application, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0043] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0044] The various embodiments of the material texturing method of this application will be further described below with reference to the accompanying drawings.

[0045] like Figure 1 As shown, Figure 1 This is a flowchart of a material texturing process provided in one embodiment of this application. The material texturing process may include, but is not limited to, steps S110, S120 and S130.

[0046] Step S110: Obtain the geometric parameter information of the material to be processed, and the first visual recognition result of visual recognition of the material to be processed;

[0047] Step S120: Combine the geometric parameter information of the material to be processed with the first visual recognition result to generate laser processing trajectory information;

[0048] Step S130: Obtain the second visual recognition result of the material to be processed when it is fixed on the adsorption platform, adjust the laser processing trajectory information according to the second visual recognition result, and perform laser texturing treatment on the material to be processed according to the adjusted laser processing trajectory information.

[0049] As is understandable, laser texturing pretreatment is a non-contact processing method based on the action of high-energy laser beams. It utilizes high-energy-density laser pulses to precisely and locally treat the material surface, forming specific microstructures through photothermal conversion. When the high-energy laser beam is focused on the material surface, the light pulse energy is rapidly absorbed and converted into heat energy, causing the local area to reach vaporization temperature in a very short time. This results in a selective material evaporation effect, forming regularly distributed micron-sized pits on the material surface. Simultaneously, volcano-like protrusions form at the edges of the pits due to the rapid condensation of molten material. This unique surface morphology significantly increases the effective specific surface area of ​​the material, improves surface wettability, and enhances interfacial mechanical bonding. Compared to traditional machining methods, laser texturing offers advantages such as a small heat-affected zone, strong morphological controllability, high processing precision, and no tool wear. Furthermore, the geometric characteristics of the surface microstructure can be precisely controlled by adjusting laser parameters, providing an ideal surface pretreatment state for subsequent processes.

[0050] It is understood that the material texturing method provided in this application embodiment can be applied to a laser marking system. The laser marking system may include a high-frequency modulated pulsed laser, a galvanometer, a field lens, a chiller, etc. The laser, as the core component, emits a high-energy-density laser beam, and the galvanometer system achieves high-speed, precise two-dimensional deflection. The field lens is used to focus the laser beam to a tiny spot, ensuring processing accuracy. In laser texturing processes, the laser marking system is mainly used to create specific microstructures on the surface of materials.

[0051] Laser marking systems can be applied to laser texturing processes. These systems typically include a laser marking system, an adsorption platform, and a vision positioning system. The adsorption platform is used to fix the material to be processed or other workpieces, ensuring stability during laser processing and preventing a decrease in processing accuracy due to vibration or displacement. The adsorption platform can use vacuum adsorption or electrostatic adsorption to firmly adhere the material to the processing table, preventing displacement under laser impact or thermal effects. The vision positioning system is used for automatic identification, positioning, and alignment of the material to be processed, ensuring high accuracy in laser processing. This system includes an industrial camera, optical lens, image processing software, and motion control unit, capable of capturing the position and contour information of the material in real time.

[0052] For example, in a laser texturing process system, a laser marking system, an adsorption platform, and a vision positioning system work together to achieve a high-precision and high-efficiency processing flow. The adsorption platform stably fixes the material to be processed, preventing displacement during processing. Subsequently, the vision positioning system scans the surface of the material to be processed, identifies its precise position and orientation, and feeds the data back to the laser control system to correct the laser processing path. Finally, the laser marking system performs high-precision texturing on the workpiece surface according to the adjusted coordinate parameters to form the required microstructure.

[0053] For example, the material to be processed can be a tab or foil to be processed, or other materials that require texturing.

[0054] For example, the geometric parameter information of the material to be processed includes basic data on the physical dimensions and spatial position of the material obtained before laser texturing. For instance, the geometric parameter information of the material to be processed includes the overall external dimensions of the material, including the three basic dimensions of length, width, and thickness; the edge feature parameters of the material, including edge straightness, corner radius, and cut angle; the flatness parameters of the material, including overall flatness and local warping; the reference marking information of the material surface, including the position coordinates of positioning holes, centerline markings, and the precise position of feature points such as QR codes; if the material has special structural features, such as bosses, grooves, or reinforcing ribs, the size and position information of these structures are also included; and the assembly position parameters of the material, including its positioning deviation and rotation angle on the processing platform, etc., which are used to match the design coordinate system with the actual processing coordinate system.

[0055] For example, the first visual recognition result of visually recognizing the material to be processed may include information obtained through a visual positioning system for preliminary positioning and assessment of the material's state. The visual positioning system can first identify the overall contour information of the material, including the coordinate set of the boundary points and the maximum outer envelope size, to determine the basic range of the processing area; secondly, it can identify the surface features of the material, including the location and size of defects such as obvious scratches, dents, and oxide spots, for subsequent adjustment of processing parameters; it can identify reference marks on the material, including features such as stamped positioning holes, engraved QR codes or barcodes, and edge notches, for use as reference points for coordinate system transformation; it can identify the actual position parameters of the material on the processing platform, including the offset in the X / Y direction, rotation angle, and other pose data, for compensating for mechanical positioning errors; and it can identify the material appearance characteristics of the material, including reflective properties and color distribution, for assisting in determining the material type and surface state.

[0056] In one embodiment, the first visual recognition result refers to the recognition result of visual recognition performed on the material to be processed to generate a laser processing trajectory.

[0057] For example, by combining the geometric parameters of the material to be processed with the results of the first visual recognition, laser processing trajectory information can be generated. This can be achieved through a coordinate transformation-based reference matching method. The actual pose data of the material obtained through visual recognition (including offset and rotation angle) is transformed with preset geometric parameters. An affine transformation matrix is ​​established to align the design coordinate system with the actual coordinate system. Then, based on the processing area size and reference mark position in the geometric parameters, a laser scanning path that perfectly matches the actual position of the material is generated. This method can be used when the incoming position of the material is not fixed but the shape of the material is standard. Alternatively, adaptive contour tracking technology can be used. High-precision point cloud data of the material edge is obtained through visual recognition. Combined with the width of the roughened area specified in the geometric parameters, an equidistant offset algorithm is used to generate a processing trajectory line parallel to the actual edge, either inwards or outwards. Simultaneously, the trajectory is dynamically adjusted based on the surface flatness data detected by vision. Laser focal length means that this method can automatically adapt to changes in the shape and position of materials, making it suitable for processing irregularly shaped materials. Alternatively, a feature-based intelligent path planning method can be used. This method first divides the material surface into different processing priority areas based on the functional area divisions in the geometric parameters and the actual feature positions identified visually. Then, a region filling algorithm (Z-shaped scanning, spiral scanning, etc.) is used to generate the optimal processing path for each area. At the same time, the path density is automatically adjusted or defect areas are skipped based on the visually detected surface defect positions. This method can be used when a balance between quality and efficiency is required. Another method is machine learning-assisted trajectory optimization. This method trains a neural network model using historical processing data, inputs the current geometric parameters and visual recognition results into the model, and directly outputs optimized processing trajectory parameters. This method can automatically learn the mapping relationship between different material characteristics and the optimal processing path.

[0058] Understandably, before laser pretreatment, the material can be cut. After cutting, the material is then adsorbed and fixed by the adsorption platform of the laser texturing process system for subsequent laser treatment. In other words, in the processing flow of the laser texturing process system, the uncutable material to be processed can be transferred to the laser texturing process system through an automated production line or automated robotic arm. Then, the material to be processed is visually identified by a vision positioning system, and then cut. After cutting, the material is adsorbed and fixed by the adsorption platform of the laser texturing process system.

[0059] Understandably, although the first visual recognition has acquired the basic geometric parameters and initial position information of the material, during the actual adsorption and fixation process, the material may undergo slight deformation or displacement due to factors such as vacuum adsorption force, mechanical clamping, or material stress release. This deformation, often at the micrometer level, is difficult to detect with the naked eye but significantly impacts high-precision laser texturing. Specifically, firstly, the adsorption process may cause slight warping in localized areas of the material, altering its original flatness. Without adjusting the laser focal length, this can lead to insufficient energy density or overheating in some areas. Secondly, the material may undergo slight translation or rotation during fixation, causing a deviation between the actual and theoretical positions, directly affecting the positional accuracy of the processed pattern. Furthermore, the surface state of the fixed material may differ from the initial detection, such as the appearance of new wrinkles or stress concentration areas, requiring corresponding adjustments to the processing parameters. Therefore, the second visual recognition is used for final calibration under these high-precision requirements, ensuring that the laser processing trajectory perfectly matches the actual state of the fixed material, greatly reducing any errors introduced by the fixation process and guaranteeing the uniformity and consistency of the texturing effect.

[0060] For example, adjusting the laser processing trajectory information based on the second visual recognition results can begin with position compensation adjustment. This involves comparing the actual coordinates obtained from the second visual recognition with the reference coordinates from the first visual recognition to calculate the translation and rotation angle of the material in the X / Y directions, and then performing corresponding coordinate transformations on the original processing trajectory. This adjustment is typically achieved using an affine transformation algorithm. Next, dynamic focal length adjustment is performed. Based on the three-dimensional surface topography data obtained from the second visual recognition, a height distribution map is established to provide the laser processing system with real-time Z-axis focal position compensation values, ensuring optimal focusing in different areas. For detected local deformation areas, the processing path can be automatically segmented, and a denser scanning interval or laser power can be used in the deformation area to ensure that the texturing effect in that area is consistent with other areas. Simultaneously, for newly discovered surface defects after fixing, the processing path can be replanned to automatically avoid these defective areas or mark them as areas for subsequent manual processing. During the adjustment process, optimization of processing efficiency can also be considered. Depending on the actual state of the material after fixing, the original continuous scanning path may be adjusted to a segmented processing strategy, or the scanning speed may be optimized while ensuring quality.

[0061] Understandably, the results of second-vision recognition and first-vision recognition can differ in their detection objectives, accuracy requirements, and content focus. First-vision recognition is a preliminary inspection performed when the material is not fixed, aiming to obtain basic geometric parameters and initial position. Second-vision recognition, on the other hand, is a final inspection performed after precise positioning and fixing, focusing on confirming the actual position and shape in the fixed state. Furthermore, in terms of detection accuracy, second-vision recognition can employ higher-resolution imaging systems and more stringent lighting conditions because it needs to capture micron-level deformations and displacements, while first-vision recognition has relatively lower accuracy requirements. Regarding the content being detected, first-vision recognition primarily focuses on overall dimensions, contours, and obvious features; second-vision recognition focuses more on microscopic deformations, local flatness changes, and precise positioning deviations. Moreover, first-vision recognition results are mainly used to establish a processing reference coordinate system, while second-vision recognition results are directly used for real-time trajectory correction and compensation. Additionally, second-vision recognition can employ multispectral or 3D imaging technology to acquire richer surface information, while first-vision recognition can use 2D visual inspection.

[0062] For example, the laser in the laser marking system can be a high-frequency modulated pulsed laser, and the high-frequency modulated pulsed laser can be a 500W power MOPA nanosecond laser. The laser beam can be transmitted through a 5m optical fiber, the pulse width can be adjusted from 10 to 500ns, the maximum single-point energy is 1.8mJ, and the output frequency can reach 3500KHz.

[0063] For example, the galvanometer and marking control system of the laser marking system can be controlled by the 20-bit SL2-100 protocol or the 16-bit XY2-100 enhanced protocol. Thanks to the digital PWM output stage, power consumption and heat are greatly reduced, and the fast dynamic response promotes production efficiency. Corresponding adjustment methods, lens materials and coatings are provided for different applications.

[0064] The parameters of the galvanometer and marking control system of the laser marking system can include

[0065] Typical deflection angle: ±0.393 rad;

[0066] Resolution: SL2-100 20-bit 12-bit;

[0067] Repeatability accuracy: <2urad;

[0068] Processing speed: 45-50 urad / s;

[0069] Page speed = F - Thata lens focal length * positioning speed.

[0070] In one embodiment, when the material to be processed is an electrode tab, in the processing flow of the laser texturing process system, the uncutable electrode tab to be processed can be transferred to the laser texturing process system through an automated production line or automated robotic arm. Then, the electrode tab to be processed is visually identified by a vision positioning system, and then cut. After cutting, the electrode tab to be processed is adsorbed and fixed by the adsorption platform of the laser texturing process system. Then, a second visual identification is performed by the vision positioning system. After obtaining the second visual identification result, the laser processing trajectory information is adjusted according to the second visual identification result. The electrode tab to be processed is laser texturized according to the adjusted laser processing trajectory information. Then, the electrode tab that has been laser texturized is dispensed. Then, the electrode sheet is transferred to the laser texturing process system through an automated production line or automated robotic arm, and then the electrode sheet and the electrode tab that has been dispensed are hot-pressed together to complete the composite connection process of the electrode tab and electrode sheet.

[0071] like Figure 2 As shown, Figure 2 This is a flowchart of a material texturing method provided in another embodiment of this application; the above step S120 may include, but is not limited to, steps S220 and S320.

[0072] Step S220: Combine the geometric parameter information of the material to be processed with the first visual recognition result to generate an initial laser processing trajectory;

[0073] Step S320: Generate a correction template based on the geometric parameter information of the material to be processed, and correct the initial laser processing trajectory using the correction template to obtain the laser processing trajectory information.

[0074] It is understandable that, in the process of generating laser processing trajectory information by combining the geometric parameter information of the material to be processed and the first visual recognition result, certain modifications and corrections can be made to improve the accuracy of the laser processing trajectory information, thereby ensuring the precision of subsequent laser texturing processing of the material to be processed.

[0075] For example, when initially combining the geometric parameters of the material to be processed with the first visual recognition result, various dynamic changes that may occur during the subsequent fixation and processing may not have been considered. Therefore, an initial laser processing trajectory is generated. The initial trajectory can be considered a theoretically ideal processing scheme, a reference path generated based on the nominal dimensions of the material and preliminary positioning information. However, variables in the actual processing environment dictate that the initial trajectory needs further adjustment. For instance, the material may undergo microscopic deformation during adsorption and fixation. Although the first visual recognition has acquired the free-state geometric features of the material, the vacuum adsorption force often causes unpredictable micro-warping or stretching of extremely thin materials. These deformations directly affect the accurate positioning of the laser focus. In addition, the accumulation of mechanical errors, including the positioning deviation of the galvanometer system, the optical distortion of the field lens, and the repeatability of the motion platform, all need to be compensated for before actual processing.

[0076] For example, a correction template is generated based on the geometric parameters of the material to be processed. Here, the correction template can be a spatial compensation model that transforms the geometric feature parameters of the material into quantifiable calculations. The correction template can be viewed as a set of algorithms containing data such as position offset, deformation compensation coefficient, and focal length adjustment parameters, used to establish a precise mapping relationship between the initial processing trajectory and the actual material state. In one embodiment, the correction template can establish a specific compensation strategy for the special properties of the material (anisotropy, thermal deformation characteristics, etc.). For example, for materials of different materials, the correction template may contain different thermal impact compensation coefficients.

[0077] For example, generating a correction template based on the geometric parameters of the material to be processed can be achieved using parametric modeling. This involves extracting the material's dimensional parameters to establish a parametric three-dimensional compensation model, which automatically calculates the expected deformation in different regions and generates corresponding positional compensation data. Alternatively, machine learning prediction can be employed. This involves training a deep learning model using historical processing data. After inputting the current material's geometric parameters, the model predicts potential processing deviation patterns and outputs a set of corresponding compensation parameters. Finite element simulation can be used. This involves performing virtual clamping simulations based on the material's geometric parameters and material properties to predict the stress distribution and deformation that may occur after adsorption and fixation, thereby generating a preventative compensation template. Feature weight allocation can be used. Different geometric features of the material are graded according to importance, generating differentiated compensation strategies for regions with different weights. A dynamic reference mesh method can be used. This involves establishing an adaptive mesh based on the material's key dimensions, with each mesh node assigned a specific compensation coefficient according to its local geometric features. Furthermore, these methods can be used individually or in combination. For instance, a basic template can be generated first through parametric modeling, and then optimized and adjusted using machine learning algorithms to ultimately form a high-precision correction template.

[0078] For example, to correct the initial laser processing trajectory using a calibration template and obtain the laser processing trajectory information, a coordinate system transformation is first required. This involves aligning the design coordinate system of the initial trajectory with the actual coordinate system of the calibration template through matrix operations. Then, based on the regional importance distribution in the calibration template, the path nodes of the initial trajectory are adaptively densified or simplified. The density of processing points is increased in critical areas, while the number of nodes is appropriately reduced in secondary areas. Next, the material thickness distribution data in the calibration template can be converted into adjustment curves for laser power and focal length, achieving precise energy control in different regions. For detected special deformation areas, local path replanning can be used, employing special paths such as circular or spiral scanning to replace the original straight-line scanning, thus eliminating processing non-uniformity caused by deformation. Furthermore, a real-time feedback mechanism can be introduced during the calibration process. By comparing the calibrated simulated processing effect with the expected target, the calibration parameters are automatically iteratively optimized.

[0079] For example, the initial laser processing trajectory can be an executable processing drawing file in the form of a dot array. The initial laser processing trajectory can be corrected by using a correction template. First, the dot array file can be centered back to the origin. Then, an elliptical positioning template can be drawn, centered in the X direction, and the upper edge of the template can be aligned with the upper edge of the dot array file in the Y direction. Points above the upper edge of the template can be deleted. Then, the laser red light outline can be compared with the material to see if they match. Based on the comparison results, the initial laser processing trajectory can be corrected to obtain the laser processing trajectory information.

[0080] like Figure 3 As shown, Figure 3 This is a flowchart of a material texturing method provided in another embodiment of this application; regarding the above step S120, it may include, but is not limited to, steps S420 and S520.

[0081] Step S420: Generate laser processing dot matrix information based on the geometric parameter information of the material to be processed;

[0082] Step S520: Based on the first visual recognition result, adaptive processing is performed on the laser processing points in the laser processing dot matrix information to obtain laser processing trajectory information; the adaptive processing includes filtering, adjusting and sorting the laser processing points.

[0083] For example, laser processing lattice information transforms abstract processing requirements into microscopic action points that can be directly executed by the laser control system. This lattice information includes three-dimensional coordinates with spatiotemporal relationships and laser parameters. Each data point not only contains X / Y / Z spatial position information but may also include process parameters such as laser power, pulse width, and frequency required at that location. Thus, a complete spatial energy interaction model is established using this lattice information. By precisely controlling the action position, intensity, and duration of each laser pulse, a suitable microscopic morphology structure can be constructed on the material surface. Furthermore, the lattice information needs to consider the balance between conductivity and weldability, i.e., an array of pits with a specific density distribution, where the diameter, depth, and edge morphology of each pit are precisely controlled by the corresponding lattice parameters.

[0084] For example, a laser processing dot matrix is ​​generated based on the geometric parameters of the material to be processed. The optimal laser point spacing can be calculated based on parameters such as the material's thickness and material composition. The two-dimensional processing surface is divided into a regular grid array. A surface height distribution function is constructed using geometric parameters such as the material's curvature and flatness. A Z-axis coordinate is assigned to each grid point to form a preliminary three-dimensional dot matrix framework. Subsequently, the laser power and pulse width of each point are adjusted according to local thickness changes. Low energy is used in thin areas to prevent breakdown, while high energy is used in thick areas to ensure penetration. For special geometric features of the material, such as chamfered edges and stamped protrusions, the dot matrix generation algorithm can be automatically switched, and a radial distribution or adaptive encryption strategy can be adopted to ensure the processing quality of special areas.

[0085] For example, a laser processing dot matrix can be generated based on the geometric parameters of the material to be processed. A reference dot matrix can be generated based on the basic geometric parameters of the material. The reference dot matrix will reserve multiple adjustable dimensions, including dot density, energy gradient, scanning order, etc., so that the laser processing points in the laser processing dot matrix information can be adaptively processed in the future. Alternatively, the laser processing points can be dynamically adjusted by monitoring the processing status data fed back by the system in real time. For example, when abnormal reflectivity of the material in a certain area is detected, the energy parameters of the dot matrix in that area are automatically increased; when excessive heat accumulation is found, the scanning order of the dot matrix is ​​adjusted to disperse the heat effect.

[0086] For example, adaptive processing is performed on the laser processing points in the laser processing dot matrix information. The adaptive processing includes filtering, adjusting, and sorting the laser processing points. The filtering process can identify the effective processing area on the material surface. By comparing the material contour obtained by visual recognition with the theoretical design boundary, redundant processing points that exceed the boundary are automatically filtered out. At the same time, for the detected surface defect areas, a no-go zone mask can be established to remove processing points located in these areas, so as to avoid wasting laser energy or causing poor processing results at defective locations. For functional areas on the material, the filtering algorithm can also selectively retain or remove specific types of processing points according to the regional attributes marked by visual recognition, so as to ensure that each functional area receives the most suitable processing.

[0087] The adjustment process can be based on the actual thickness distribution of the material measured by visual recognition. The laser power and focal length of each processing point are adjusted in a gradient. The energy density is reduced in thin areas to prevent breakdown, and the energy is increased in thick areas to ensure effective depth of action. For local deformation areas found by visual recognition, the spatial coordinates of the processing point are recalculated. The positional deviation caused by deformation is compensated by three-dimensional coordinate transformation. At the same time, the laser incident angle is adjusted according to the surface tilt angle to ensure vertical processing effect.

[0088] The sorting process can use thermal management optimization algorithms to rearrange the processing sequence, disperse high heat-affected areas to avoid excessive local temperature rise, and take into account the structural strength distribution of the material, processing from high-strength areas to fragile areas to reduce processing stress concentration; for the texture direction characteristics of the material, the scanning path direction can be optimized to match the anisotropy of the material, thereby improving the processing surface quality.

[0089] For example, a dot matrix image can be generated based on the material edge contour points in the geometric parameter information of the material to be processed. At the same time, different materials can be identified based on color difference, thereby determining whether to use a sequential or intermittent dot matrix arrangement, thus realizing the adaptive function of image size and processing trajectory.

[0090] like Figure 4 As shown, Figure 4 This is a flowchart of a material texturing process provided in another embodiment of this application; the above material texturing process may also include, but is not limited to, step S140.

[0091] Step S140: Based on the first visual recognition result, set the laser texturing processing operation parameters.

[0092] For example, the laser texturing operation parameters that need to be set may include energy parameters, time parameters, motion parameters, and environmental control parameters. Among them, energy parameters include laser power that affects the depth and diameter of the texturing pits, pulse energy that controls the amount of energy released by each laser pulse, and pulse width parameters that affect the size of the heat-affected zone. Narrow pulse widths can achieve a cold processing effect, while wide pulse widths enhance the melting effect. Time parameters may include pulse repetition frequency that affects processing efficiency, and duty cycle parameters that control the interval period of laser operation. Motion parameters may include scanning speed that, together with the pulse frequency, determines the dot spacing, and focus position and focus offset. Environmental control parameters may include auxiliary gas pressure and flow rate for controlling the degree of oxidation and removing slag, and processing platform temperature maintenance parameters.

[0093] For example, laser texturing parameters can be set based on the first visual recognition result. This can be achieved by establishing a thickness-power matching model, which converts the thickness distribution data obtained from visual measurements into a power gradient curve. Thin areas use exponentially decaying power to prevent breakdown, while thick areas use linearly increasing power to ensure penetration depth. For different material regions identified, a preset material parameter database is called to automatically match the optimal pulse width and wavelength parameters. For copper, a short pulse width and high frequency are used to avoid excessive heat conduction, while for aluminum, the pulse width is appropriately increased to enhance energy coupling. The compensation coefficient of the reference power can also be dynamically adjusted based on surface reflectivity measurement data. Power redundancy is increased for high-reflectivity surfaces and correspondingly reduced for low-reflectivity surfaces. Furthermore, the surface normal angle of each region can be calculated using a three-dimensional reconstruction algorithm based on the identified material deformation characteristics, and the laser incident angle compensation parameters can be adjusted accordingly to ensure vertical processing effect.

[0094] For example, a visual positioning system can identify different materials based on color differences, thereby triggering the laser marking system to call the corresponding laser texturing processing parameters, making the parameters adaptive to the material. In one embodiment, the laser texturing processing parameters corresponding to a certain material may include a power of 92%, a frequency of 1000KHz, and a pulse width of 30ns, and may be adjusted according to the product's crater height and hole depth specifications.

[0095] like Figure 5 As shown, Figure 5 This is a flowchart of a material texturing method provided in another embodiment of this application; regarding the above step S130, it may include, but is not limited to, step S230.

[0096] Step S230: Obtain the second visual recognition result of visual recognition of the material to be treated when the material to be treated is fixed on the adsorption platform and the negative pressure value of the adsorption platform meets the negative pressure threshold.

[0097] For example, the adsorption platform uses vacuum adsorption. The condition that the negative pressure value of the adsorption platform meets the negative pressure threshold means that the vacuum adsorption system has reached and maintained a preset stable negative pressure range. This condition can include two key indicators: first, the absolute value of the negative pressure must reach the minimum working pressure requirement to ensure sufficient adsorption force to overcome the rigidity of the material itself and possible deformation stress; second, pressure fluctuations must be controlled within the allowable range to ensure the stability of the adsorption state. This threshold may not be a fixed value, but rather a parameter that is dynamically adjusted according to the material's material, thickness, and size specifications.

[0098] For example, the negative pressure monitoring system collects data in real time through a high-precision pressure sensor with a sampling frequency of 100Hz or higher to ensure that instantaneous pressure fluctuations can be captured. Furthermore, the system will only trigger a condition-based judgment when the negative pressure value is detected to remain stable within a set threshold range for a predetermined time.

[0099] For example, after the adsorption platform starts vacuuming and the negative pressure value meets the negative pressure threshold, the visual positioning system is triggered to perform visual recognition on the material to be processed, and a second visual recognition result is obtained. The negative pressure value meeting the negative pressure threshold is used to determine whether a vacuum leak has occurred.

[0100] In another embodiment of the material texturing method provided in this application, the second visual recognition result includes the recognition result of identifying and locating a preset area of ​​the material; such as Figure 6 As shown, Figure 6 This is a flowchart of a material texturing method provided in another embodiment of this application; the above step S130 may include, but is not limited to, step S330.

[0101] Step S330: Based on the second visual recognition result, obtain the preset area positioning coordinates, and adjust the laser processing trajectory information according to the preset area positioning coordinates.

[0102] For example, a preset region can refer to a specific surface area with a clearly defined process function and special requirements for processing accuracy. This preset region may possess special electrochemical properties or mechanical connection functions. For instance, the preset region could be an electrical contact functional area of ​​the material, which needs to form a uniform roughened structure to ensure low-resistance contact with the current collector, and has strictly defined geometric boundaries and specific surface morphology requirements; it could be a welding pre-reserved area, which, although not requiring direct roughening, serves as a reference surface for subsequent welding processes, and its positional accuracy directly affects welding quality, thus requiring it as a reference for coordinate adjustment; or it could be a stress buffer transition area of ​​the material, located between the functional area and the edge, requiring special gradient roughening parameters to alleviate mechanical stress concentration.

[0103] For example, the preset area can be an area with clear geometric markings, such as positioning recesses formed by stamping, baselines etched by laser, or texture features of the material itself. These markings have high contrast and stable geometric features in visual recognition, and can provide sub-pixel-level positioning accuracy.

[0104] For example, the laser processing trajectory information can be adjusted according to the positioning coordinates of the preset area. By comparing the actual coordinates of the preset area with the theoretical coordinates, spatial transformation parameters including translation offset, rotation angle and scaling factor can be calculated. These parameters are used to form an affine transformation matrix. Then, the entire laser processing trajectory is transformed from the design coordinate system to the actual material coordinate system. For materials with local deformation, the deformation gradient is calculated for different preset areas to establish a non-uniform coordinate transformation model and achieve trajectory adaptation adjustment.

[0105] like Figure 7 As shown, Figure 7 This is a flowchart of a material texturing process provided in another embodiment of this application; the above material texturing process may also include, but is not limited to, steps S150 and S160.

[0106] Step S150: Perform visual recognition on the material that has undergone laser texturing to obtain the third visual recognition result;

[0107] Step S160: Obtain laser processing feedback information based on the third visual recognition result.

[0108] For example, third-vision recognition can differ from first-vision and second-vision recognition. For instance, third-vision recognition uses hyperspectral imaging to analyze reflectance characteristics at different wavelengths, which can not only detect surface morphology but also identify material phase transitions. When an abnormal peak is found in the reflectance spectrum of a specific area, it automatically determines that the area is overburned and provides feedback suggesting that the laser power be reduced and the auxiliary gas flow rate be increased. At the same time, it marks the area as needing to be re-inspected in subsequent processes. Alternatively, it can use three-dimensional morphology scanning to measure the depth distribution data of the roughening pits. By comparing the data with historical high-quality samples through a machine learning model, it can find that the roughness at the bottom of the pit being processed is too high and provide feedback indicating that the pulse width needs to be shortened and the focusing lens position adjusted.

[0109] For example, visual recognition is performed on the material that has undergone laser texturing to obtain a third visual recognition result. The third visual recognition result includes the edge of the processing area. By calculating whether the distance between the processing area and the edge of the material meets the specifications, laser processing feedback information is obtained. If it exceeds the specifications, an NG can be reported for manual investigation of the cause.

[0110] Based on the material texturing methods described in the above embodiments, the following presents various embodiments of the operation control device, electronic device, computer-readable storage medium, and computer program product of this application.

[0111] like Figure 8 As shown, Figure 8 This is a schematic diagram of an operation control device for performing a material texturing process according to an embodiment of this application. The operation control device 800 implemented in this application includes: a processor 820, a memory 810, and a computer program stored in the memory 810 and executable on the processor 820, wherein... Figure 8 The example uses a processor 820 and a memory 810.

[0112] The processor 820 and memory 810 can be connected via a bus or other means. Figure 8 Taking the example of a connection between China and Israel via a bus.

[0113] Memory 810, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 810 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 810 may optionally include remotely located memories 810 relative to processor 820, which can be connected to the operation control device 800 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0114] Those skilled in the art will understand that Figure 8 The device structure shown does not constitute a limitation on the operation control device 800, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0115] exist Figure 8 In the operation control device 800 shown, the processor 820 can be used to call the control program stored in the memory 810, thereby implementing the material texturing method described above. Specifically, the non-transitory software program and instructions required to implement the material texturing method of the above embodiment are stored in the memory 810, and when executed by the processor 820, the material texturing method of the above embodiment is executed.

[0116] It is worth noting that, since the operation control device 800 of this application embodiment can execute the material texturing process method of any of the above embodiments, the specific implementation method and technical effect of the operation control device 800 of this application embodiment can refer to the specific implementation method and technical effect of the material texturing process method of any of the above embodiments.

[0117] Furthermore, one embodiment of this application also provides an electronic device that includes the operation control device described in the above embodiment.

[0118] It is worth noting that, since the electronic device of this application embodiment includes the operation control device of the above embodiment, and the operation control device of the above embodiment can execute the material texturing process method of any of the above embodiments, the specific implementation method and technical effect of the electronic device of this application embodiment can refer to the specific implementation method and technical effect of the material texturing process method of any of the above embodiments.

[0119] Furthermore, one embodiment of this application provides a computer-readable storage medium storing computer-executable instructions for performing the material texturing method described above. Exemplarily, the above-described method is executed... Figures 1 to 7 The methods and steps in the text.

[0120] It is worth noting that, since the computer-readable storage medium of this application embodiment can perform the material texturing process method of any of the above embodiments, the specific implementation method and technical effect of the computer-readable storage medium of this application embodiment can be referred to the specific implementation method and technical effect of the material texturing process method of any of the above embodiments.

[0121] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which may include computer storage media or non-transitory media and communication media or transient media. As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc DVD or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed systems, instruments, and methods can be implemented in other ways. For example, the instrument embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between instruments or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0123] It should also be understood that the various implementation methods provided in this application can be combined arbitrarily to achieve different technical effects.

[0124] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A method for texturing materials, characterized in that, include: Obtain the geometric parameter information of the material to be processed, and the first visual recognition result of visual recognition of the material to be processed; By combining the geometric parameter information of the material to be processed and the first visual recognition result, laser processing trajectory information is generated; A second visual recognition result is obtained when the material to be processed is fixed on the adsorption platform. The laser processing trajectory information is adjusted according to the second visual recognition result. The material to be processed is then subjected to laser texturing treatment according to the adjusted laser processing trajectory information. The step of generating laser processing trajectory information by combining the geometric parameter information of the material to be processed and the first visual recognition result includes: generating an initial laser processing trajectory by combining the geometric parameter information of the material to be processed and the first visual recognition result; generating a correction template based on the geometric parameter information of the material to be processed; and correcting the initial laser processing trajectory using the correction template to obtain the laser processing trajectory information. In addition, the step of generating laser processing trajectory information by combining the geometric parameter information of the material to be processed and the first visual recognition result includes: generating laser processing dot matrix information based on the geometric parameter information of the material to be processed; and performing adaptive processing on the laser processing points in the laser processing dot matrix information based on the first visual recognition result to obtain laser processing trajectory information; the adaptive processing includes filtering, adjusting, and sorting the laser processing points. In addition, the second visual recognition result includes the recognition result of identifying and locating a preset area of ​​the material to be processed; the step of adjusting the laser processing trajectory information according to the second visual recognition result includes: obtaining the preset area positioning coordinates according to the second visual recognition result, and adjusting the laser processing trajectory information according to the preset area positioning coordinates.

2. The material texturing treatment method according to claim 1, characterized in that, Also includes: Based on the first visual recognition result, set the laser texturing processing operating parameters.

3. The material texturing method according to claim 1, characterized in that, The second visual recognition result of visually recognizing the material to be treated when it is fixed on the adsorption platform includes: A second visual recognition result is obtained when the material to be treated is fixed on the adsorption platform and the negative pressure value of the adsorption platform meets the negative pressure threshold.

4. The material texturing method according to claim 1, characterized in that, Also includes: Visual recognition is performed on the materials that have undergone laser texturing to obtain third-vision recognition results; Based on the third visual recognition result, laser processing feedback information is obtained.

5. An operation control device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the material texturing method as described in any one of claims 1 to 4.

6. An electronic device, characterized in that, Includes the operation control device as described in claim 5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the material texturing process as described in any one of claims 1 to 4.

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