A high-speed wire welding point pretreatment method and system based on laser cleaning

Abstract

The application relates to the field of intelligent manufacturing equipment, and relates to a high-speed wire welding point pretreatment method and system based on laser cleaning, which comprises the following steps: acquiring dynamic sensing data of a to-be-welded point and generating a dynamic compensation planning scheme, calculating a target cleaning parameter set according to the dynamic sensing data, obtaining a cleaned welding point based on the dynamic compensation planning scheme and the target cleaning parameter set, detecting the surface state of the cleaned welding point, obtaining an adjusted welding power through a pre-constructed cleaning-welding mapping model and performing welding, and obtaining a target welding point. The application can realize accurate laser cleaning of the to-be-welded point on the high-speed moving wire through dynamic sensing and space-time synchronous compensation, and can self-adaptively adjust the cleaning parameter according to the surface state after cleaning, so that the reliability of the cleaning effect is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing equipment, and in particular to a method and system for pre-treatment of high-speed line welding points based on laser cleaning. Background Technology

[0002] With the rapid development of high-end equipment manufacturing, high-speed wire is increasingly widely used in fields such as new energy vehicle motors and micro coaxial cables. Before welding, the insulating layer, oxide film, and other coverings adhering to the surface of high-speed wire must be thoroughly removed; otherwise, the welding strength and connection reliability will be directly affected. Therefore, pre-welding treatment of high-speed wire welding points has become a key process to ensure the welding quality of high-speed wire.

[0003] Currently, the pre-treatment of welding joints on high-speed lines typically involves removing surface coverings through chemical pickling or mechanical grinding, or by using laser thermal action to peel off the surface coverings.

[0004] However, existing laser cleaning technologies are mainly designed for cleaning large, stationary workpieces, relying on the premise that the workpiece is stationary. Laser cleaning solutions for stationary workpieces cannot address the cleaning needs of weld points on wire surfaces during high-speed, continuous motion. Therefore, this invention proposes a high-speed wire weld point pretreatment method based on laser cleaning to overcome the aforementioned shortcomings of existing technologies. Summary of the Invention

[0005] This invention provides a high-speed wire welding point pretreatment method based on laser cleaning. Its main purpose is to achieve precise laser cleaning of the welding points on high-speed moving wires through dynamic sensing and spatiotemporal synchronous compensation, and to ensure the reliability of the cleaning effect by adaptively adjusting the cleaning parameters based on the surface state after cleaning.

[0006] To achieve the above objectives, the present invention provides a high-speed wire bonding joint pretreatment method based on laser cleaning, comprising: The system receives a preprocessing start command and determines the high-speed line to be processed and the preprocessing execution system based on the preprocessing start command. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. Using a sensing module, n points to be soldered are identified from the high-speed line to be processed. For each of the n points to be soldered, the following operation is performed: Acquire dynamic sensing data of the point to be welded, perform spatiotemporal synchronous compensation processing on the laser cleaning module based on the dynamic sensing data, and generate a dynamic compensation planning scheme. The process parameters of the laser cleaning module are calculated based on the dynamic sensing data to obtain the target cleaning parameter set; Based on the dynamic compensation planning scheme and the target cleaning parameter set, the welding point to be welded is subjected to fixed-point laser cleaning to obtain the cleaned welding point. The surface condition detection module is used to detect the surface condition of the weld points after cleaning to obtain surface condition data. The surface condition data is then input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. The adjusted welding power is sent to the downstream welding equipment through the control module, and welding is performed on the cleaned welding points to obtain the target welding points. The target welding points are summarized to obtain n target welding points, thus completing the high-speed line welding point preprocessing based on laser cleaning.

[0007] Optionally, acquiring the dynamic sensing data of the point to be welded includes: Determine the center point of the light outlet of the laser cleaning module, and construct a three-dimensional rectangular coordinate system with the center point of the light outlet as the origin; Doppler velocity detection and coaxial vision imaging were performed on the high-speed line to be processed to obtain the initial motion velocity and the image of the line surface, respectively. Subpixel-level corner detection is performed on the wire surface image to determine the coordinates of the point to be welded in the three-dimensional Cartesian coordinate system; The image of the area to be welded is extracted from the wire surface image based on the coordinates of the point to be welded. The structured light velocity value is calculated based on the image of the area to be welded, and the initial motion velocity and the structured light velocity value are cross-validated to obtain the real-time motion velocity. Based on the coordinates of the point to be welded, the surface covering material of the point to be welded is collected. Spectral analysis and spectral thickness measurement of the surface covering material are performed to obtain the insulation layer type and insulation layer thickness. The insulation layer type and insulation layer thickness are summarized to obtain the surface covering material information. By summarizing real-time motion speed, coordinates of the welding point, and surface covering information, dynamic sensing data is obtained.

[0008] Optionally, the step of performing spatiotemporal synchronization compensation processing on the laser cleaning module based on dynamic sensing data to generate a dynamic compensation planning scheme includes: Based on the real-time motion speed and the coordinates of the point to be welded, the time required for the point to be welded to reach the center point of the light outlet is calculated, and the synchronization delay of the weld point is obtained. The triggering time and scanning frequency of the laser cleaning module are calculated based on the micro-area range of the solder joint, the preset spot diameter, and the synchronous delay of the solder joint. By combining the trigger time and the scanning frequency, the galvanometer timing parameter set is obtained; The range of the micro-area of ​​the solder joint is determined based on the coordinates of the solder joint to be welded. The scanning path of the laser cleaning module is planned within the range of the micro-area of ​​the solder joint to obtain the solder joint scanning path. Collect the surface height of the high-speed line to be processed at the coordinates of the welding point, and calculate the defocus compensation amount based on the surface height and the preset focal length; By summarizing the galvanometer timing parameter set, solder joint scanning path, and defocus compensation amount, a dynamic compensation planning scheme is obtained.

[0009] Optionally, the step of calculating the process parameters of the laser cleaning module based on dynamic sensing data to obtain the target cleaning parameter set includes: The base laser power and base scanning speed are determined based on the type and thickness of the insulating layer. Calculate the ratio of the insulation layer thickness to the preset reference thickness to obtain the thickness normalization coefficient; Multiply the thickness normalization coefficient by the preset overlap rate benchmark value to obtain the basic spot overlap rate; The target cleaning parameter set is obtained by summarizing the basic laser power, basic scanning speed, and basic spot overlap rate.

[0010] Optionally, the step of performing targeted laser cleaning on the welding point according to the dynamic compensation planning scheme and the target cleaning parameter set to obtain the cleaned welding point includes: The laser cleaning module is controlled to output laser pulses based on the trigger time and the basic laser power to obtain a laser pulse signal; Determine m scan points from the solder joint scan path, and perform the following operation on each of the m scan points: The laser cleaning module is controlled to deflect the galvanometer based on the scanning point and scanning frequency, thereby obtaining the galvanometer deflection control value. The laser cleaning module is adjusted according to the defocus compensation amount to obtain the focus position; By associating the galvanometer deflection control value with the focus position, the scanning node is obtained; Summarize the scanning nodes to obtain m scanning nodes. Calculate the movement rate of m-1 light spots based on the m scanning nodes, the basic scanning speed, and the basic spot overlap rate. Based on the laser pulse signal, m scanning nodes, and m-1 spot movement rates, a fixed-point laser cleaning is performed on the welding point to be welded, resulting in a cleaned welding point.

[0011] Optionally, the step of controlling the laser cleaning module to deflect the galvanometer based on the scanning point and scanning frequency to obtain the galvanometer deflection control amount includes: Obtain the galvanometer axis spacing and calibration working distance of the laser cleaning module; Determine the X-axis and Y-axis components of the scanning point in a three-dimensional rectangular coordinate system; The X-axis deflection angle and Y-axis deflection angle are calculated based on the galvanometer axis spacing, calibration working distance, X-axis component, and Y-axis component, using the following formulas:

[0012] in, This indicates the X-axis deflection angle. This represents the X-axis component. This indicates the calibrated working distance. This indicates the Y-axis deflection angle. This represents the Y-axis component. Indicates the galvanometer axis spacing. Represents the arctangent function. Represents the cosine function; The laser cleaning module is controlled to deflect the galvanometer based on the scanning frequency, X-axis deflection angle, and Y-axis deflection angle, thereby obtaining the galvanometer deflection control value.

[0013] Optionally, the surface condition detection module is used to detect the surface condition of the weld joints after cleaning to obtain surface condition data, including: Coaxial visual imaging was performed on the weld points after cleaning to obtain an image of the cleaned surface. Gray-scale features were extracted from the cleaned surface image to obtain surface gray-scale distribution data; Surface roughness is calculated based on surface grayscale distribution data; LIBS spectral analysis was performed on the cleaned weld joints to obtain the characteristic spectral lines of oxygen. The residual oxygen content was calculated based on the characteristic spectral lines of oxygen. By summarizing the surface roughness and residual oxygen content, surface condition data are obtained.

[0014] Optionally, the step of performing LIBS spectral analysis on the cleaned weld joints to obtain the characteristic spectral lines of oxygen includes: The surface condition detection module excites the weld points after cleaning to generate plasma plumes. Collect raw spectral data of plasma plume; The characteristic wavelengths of oxygen are identified from the raw spectral data, and the intensity of the oxygen spectral lines is determined based on these characteristic wavelengths. The characteristic spectral lines of oxygen are constructed based on the characteristic wavelength and intensity of oxygen spectral lines.

[0015] Optionally, the step of inputting surface state data into a pre-constructed cleaning-welding mapping model and obtaining the adjusted welding power based on the cleaning-welding mapping model includes: Set acceptable thresholds for surface roughness and oxygen content; The basic welding power, roughness correction factor, and oxygen content correction factor are obtained from the cleaning-welding mapping model. If the surface roughness is not greater than the acceptable roughness threshold and the residual oxygen content is not greater than the acceptable oxygen content threshold, the adjusted welding power is calculated based on the basic welding power, surface roughness, roughness correction coefficient, oxygen content correction coefficient, and the pre-constructed welding parameter correction formula. The welding parameter correction formula is as follows:

[0016] in, This indicates the adjusted welding power. This indicates the basic welding power. This represents the roughness correction coefficient. This indicates the surface roughness. This represents the oxygen content correction factor. This indicates the content of residual oxygen.

[0017] To achieve the above objectives, the present invention also provides a high-speed line welding joint pretreatment system based on laser cleaning, comprising: The instruction receiving and system determination module is used to receive a preprocessing start instruction and determine the high-speed line to be processed and the preprocessing execution system based on the preprocessing start instruction. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. The dynamic perception and planning generation module is used to determine n welding points from the high-speed line to be processed using the sensing module. For each of the n welding points, the following operations are performed: acquire the dynamic perception data of the welding point, perform spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic perception data, and generate a dynamic compensation planning scheme. The parameter calculation and cleaning execution module is used to calculate the process parameters of the laser cleaning module based on dynamic sensing data, obtain the target cleaning parameter set, and perform fixed-point laser cleaning on the welding point to be welded according to the dynamic compensation planning scheme and the target cleaning parameter set, so as to obtain the welded point after cleaning. The quality inspection and welding execution module is used to detect the surface condition of the weld points after cleaning using the surface condition detection module, obtain surface condition data, input the surface condition data into a pre-built cleaning-welding mapping model, obtain the adjusted welding power according to the cleaning-welding mapping model, and send the adjusted welding power to the downstream welding equipment through the control module to perform welding on the cleaned weld points, obtain the target weld points, summarize the target weld points, obtain n target weld points, and complete the high-speed line welding point preprocessing based on laser cleaning.

[0018] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; The processor executes the instructions stored in the memory to implement the laser cleaning-based high-speed wire bonding joint pretreatment method described above.

[0019] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned laser-cleaning-based high-speed wire bonding joint preprocessing method.

[0020] To address the problems described in the background section, this invention first receives a preprocessing start command. Based on this command, it determines the high-speed wire to be processed and the preprocessing execution system. The preprocessing execution system includes a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. This invention considers the characteristics of high-speed wires moving continuously on the production line and the discrete distribution of welding points. Through a modular system architecture, it achieves precise processing of each welding point on the high-speed wire, avoiding damage to non-welding areas and resource waste caused by the overall processing of the wire in traditional solutions.Then, this invention uses a sensing module to determine n welding points from the high-speed wire to be processed. For each of the n welding points, the following operations are performed: acquiring dynamic sensing data of the welding point, performing spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic sensing data, and generating a dynamic compensation planning scheme. It is evident that this invention considers the real-time changes in the spatial position of the welding points during the movement of the high-speed wire, and the problem that traditional static cleaning schemes cannot lock onto the moving target. Therefore, by collecting real-time motion speed and welding point coordinates and performing spatiotemporal synchronization compensation, a dynamic compensation planning scheme is generated, including welding point synchronization delay, galvanometer timing parameter set, and defocus compensation amount. This enables the laser cleaning module to accurately track the welding points moving at high speed. Secondly... This invention calculates the process parameters of the laser cleaning module based on dynamic sensing data to obtain a target cleaning parameter set. It is evident that this invention considers the differences in insulation layer type and thickness on the surfaces of different welding points, making fixed cleaning parameters unsuitable for diverse working conditions. Therefore, by querying a process parameter mapping table, it obtains the basic laser power, basic scanning speed, and basic spot overlap rate to match the current surface state of the welding point, achieving adaptive correction of the process parameters. Next, based on the dynamic compensation planning scheme and the target cleaning parameter set, this invention performs fixed-point laser cleaning on the welding point to obtain the cleaned welding point. It is evident that this invention considers the need for laser cleaning to scan point-by-point within the micro-area of ​​the welding point while simultaneously addressing wire bounce; therefore, it utilizes... The coordinated operation of galvanometer deflection control and defocus compensation precisely guides the laser pulse to each scanning node and dynamically maintains the focal position. Combined with the calculation of the spot movement rate, stable peeling of surface coverings within the micro-area of ​​the weld joint is achieved. Furthermore, this invention utilizes a surface condition detection module to detect the surface condition of the weld joint after cleaning, obtaining surface condition data. This surface condition data is input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. It is evident that this invention considers the fluctuations in cleaning effect, and that a fixed welding power is difficult to adapt to different post-cleaning surface conditions. Therefore, by performing dual detection of surface roughness and residual oxygen content of the weld joint after cleaning, and substituting this data into the cleaning-welding mapping model... The model is processed to dynamically adapt the welding power to the actual surface condition. Finally, the invention sends the adjusted welding power to the downstream welding equipment through the control module to perform welding on the cleaned welding points, obtaining the target welding points. The target welding points are then summarized to obtain n target welding points, completing the preprocessing of high-speed line welding points based on laser cleaning. It can be seen that the invention links laser cleaning with welding parameters, enabling each welding point to obtain welding parameters that are precisely matched with its surface condition, ensuring the reliability of the target welding points. Therefore, the invention can achieve precise laser cleaning of welding points on high-speed moving wires through dynamic sensing and spatiotemporal synchronous compensation, and adaptively adjust the cleaning parameters by the surface condition after cleaning, ensuring the reliability of the cleaning effect. Attached Figure Description

[0021] Figure 1 This is a schematic flowchart of a high-speed line welding joint pretreatment method based on laser cleaning provided in an embodiment of the present invention; Figure 2 This is a functional block diagram of a high-speed line welding joint pretreatment system based on laser cleaning provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of an electronic device that implements the laser cleaning-based high-speed line welding joint pretreatment method according to an embodiment of the present invention.

[0022] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0023] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] This application provides a high-speed wire bonding joint preprocessing method based on laser cleaning. The execution entity of this laser-cleaning-based high-speed wire bonding joint preprocessing method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the laser-cleaning-based high-speed wire bonding joint preprocessing method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0026] Reference Figure 1 The diagram shown is a schematic flowchart of a high-speed wire bonding joint pretreatment method based on laser cleaning according to an embodiment of the present invention. In this embodiment, the high-speed wire bonding joint pretreatment method based on laser cleaning includes: S1. Receive a preprocessing start command, and determine the high-speed line to be processed and the preprocessing execution system based on the preprocessing start command. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment.

[0027] Understandably, the preprocessing start command is a start command issued by the operator to initiate the pre-welding preprocessing procedure for the high-speed wire welding points. The high-speed wire to be processed is a metal wire in a state of high-speed continuous motion and with a surface coating. For example, enameled flat wire in a new energy vehicle motor. The preprocessing execution system is a hardware and software integrated system for performing pre-welding preprocessing on the high-speed wire to be processed.

[0028] It should be understood that the sensing module is a hardware unit integrating speed detection, visual imaging, and spectral analysis functions, used to acquire dynamic sensing data of the high-speed line to be processed. Optionally, a laser Doppler velocimeter, a coaxial vision camera, and a LIBS spectral probe can be used to construct the sensing module. The control module is used to receive the dynamic sensing data acquired by the sensing module, perform spatiotemporal synchronization compensation processing and calculation of the target cleaning parameter set, and coordinate the control of the laser cleaning module and the surface state detection module. Optionally, an STM32 series microcontroller based on the ARM architecture can be used as the control module. The laser cleaning module is an execution unit including a laser source, a two-dimensional galvanometer scanning head, and a Z-axis focusing mechanism, used to perform fixed-point laser cleaning on the solder joint. The laser source is used to emit high-energy-density laser pulses to clean the surface covering within the micro-area of ​​the solder joint. Optionally, a pulsed fiber laser with an average power of 100 watts and a wavelength of 1064 nanometers can be used as the laser source. The two-dimensional galvanometer scanning head is used to quickly and accurately locate each scanning point within the micro-area of ​​the solder joint and accurately guide the laser pulse to each scanning point within the micro-area of ​​the solder joint. Optionally, a high-speed scanning galvanometer with a maximum scanning speed of not less than 2000 mm / s is used as the two-dimensional galvanometer scanning head. The Z-axis focusing mechanism is used to adjust the position of the laser cleaning module in the Z-axis direction, so that the focus of the laser pulse is dynamically maintained at the point to be welded, thereby achieving stable peeling of the surface coating. Optionally, a high-speed Z-axis actuator with a step resolution of not more than 0.01 mm is used as the Z-axis focusing mechanism, which works in conjunction with the control module to achieve real-time defocus compensation.

[0029] It should be clarified that the surface condition detection module is a hardware unit for evaluating the cleaning effect of the weld joints after cleaning. It comprehensively judges whether the cleaning effect meets the standards by acquiring surface images of the weld joints after cleaning and detecting the residual oxygen content. For example, a coaxial vision camera can be used to perform coaxial vision imaging of the weld joints after cleaning, and a LIBS spectral probe can be used to detect the residual oxygen content to comprehensively judge whether the cleaning effect meets the standards. The downstream welding equipment is used to receive the adjusted welding power and perform welding operations on the cleaned weld joints. Optionally, a laser welding machine can be used as the downstream welding equipment, and data communication with the control module can be achieved via industrial Ethernet.

[0030] S2. Using the sensing module, determine n welding points from the high-speed line to be processed. For each of the n welding points, perform the following operations: acquire the dynamic sensing data of the welding point, perform spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic sensing data, and generate a dynamic compensation planning scheme.

[0031] It should be explained that the weld point is a specific location on the high-speed line that requires laser cleaning. The dynamic sensing data is a set of data collected by the sensing module to describe the real-time status information of the weld point. The dynamic compensation planning scheme is a complete control scheme generated after performing spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic sensing data. It is used to control the laser cleaning module to perform precise fixed-point laser cleaning on the weld point in high-speed motion.

[0032] Specifically, acquiring the dynamic sensing data of the weld point includes: Determine the center point of the light outlet of the laser cleaning module, and construct a three-dimensional rectangular coordinate system with the center point of the light outlet as the origin; Doppler velocity detection and coaxial vision imaging were performed on the high-speed line to be processed to obtain the initial motion velocity and the image of the line surface, respectively. Subpixel-level corner detection is performed on the wire surface image to determine the coordinates of the point to be welded in the three-dimensional Cartesian coordinate system; The image of the area to be welded is extracted from the wire surface image based on the coordinates of the point to be welded. The structured light velocity value is calculated based on the image of the area to be welded, and the initial motion velocity and the structured light velocity value are cross-validated to obtain the real-time motion velocity. Based on the coordinates of the point to be welded, the surface covering material of the point to be welded is collected. Spectral analysis and spectral thickness measurement of the surface covering material are performed to obtain the insulation layer type and insulation layer thickness. The insulation layer type and insulation layer thickness are summarized to obtain the surface covering material information. By summarizing real-time motion speed, coordinates of the welding point, and surface covering information, dynamic sensing data is obtained.

[0033] Understandably, the center point of the light outlet is the geometric center of the laser pulse emission position in the laser cleaning module, serving as the origin to construct a three-dimensional Cartesian coordinate system between the point to be welded and the laser cleaning module. The initial motion velocity is the preliminary velocity value of the high-speed wire to be processed. The wire surface image is a two-dimensional image of the surface of the high-speed wire to be processed. The coordinates of the point to be welded are the spatial coordinates of the point to be welded in the three-dimensional Cartesian coordinate system, obtained by locating it in the wire surface image using sub-pixel-level corner detection technology. Doppler velocity detection, coaxial vision imaging, and sub-pixel-level corner detection technology are all existing technologies, and their specific processes will not be elaborated here. The image of the area to be welded is a partial image cropped from the wire surface image based on the coordinates of the point to be welded, containing only the point to be welded and its surrounding adjacent areas. The purpose of cropping the image of the area to be welded is to reduce the image processing range, ensuring that subsequent structured light velocimetry calculations are performed only on the point to be welded and its surrounding adjacent areas, avoiding interference from information from other areas, and improving computational efficiency and accuracy. For example, a 40-pixel × 40-pixel rectangular area is extracted from the wire surface image, centered on the coordinates of the point to be soldered. This rectangular area contains only the point to be soldered and its surrounding adjacent areas. The surrounding adjacent areas are obtained by removing the point to be soldered from the rectangular area.

[0034] It should be understood that the structured light velocimetry value is a velocity value calculated based on the phase shift of the structured light stripes in the image of the area to be welded. The calculation principle of the structured light velocimetry value is as follows: a structured light stripe of known spatial frequency is projected onto the surface of the high-speed line to be processed. When the high-speed line moves at high speed, the structured light stripe will undergo phase shift. By analyzing the phase shift of the structured light stripe in the image of the area to be welded, combined with the spatial frequency of the structured light stripe, the instantaneous velocity of the high-speed line at the welding point can be calculated. The specific calculation process is existing technology and will not be elaborated here. The real-time motion velocity is the final velocity value obtained by cross-validating the initial motion velocity with the structured light velocimetry value. The cross-validation process is as follows: the absolute difference between the initial motion velocity and the structured light velocimetry value is calculated, and the absolute difference is compared with a preset velocity deviation threshold. If the absolute difference is less than the velocity deviation threshold, the average of the absolute difference and the velocity deviation threshold is taken as the real-time motion velocity; otherwise, the data is determined to be abnormal, and the dynamic sensing data of the welding point is reacquired. The speed deviation threshold is a critical value set manually based on the hardware characteristics of the sensing module and the actual operating conditions of the high-speed line to be processed, in order to improve the accuracy of real-time motion speed.

[0035] It should be clarified that the surface coating is a non-metallic coating layer attached to the surface of the high-speed line to be treated, such as an insulating layer, oxide film, or oil. The insulating layer type refers to the type of surface coating. The insulating layer thickness refers to the thickness value of the surface coating.

[0036] Specifically, the step of performing spatiotemporal synchronization compensation processing on the laser cleaning module based on dynamic sensing data to generate a dynamic compensation planning scheme includes: Based on the real-time motion speed and the coordinates of the point to be welded, the time required for the point to be welded to reach the center point of the light outlet is calculated, and the synchronization delay of the weld point is obtained. The triggering time and scanning frequency of the laser cleaning module are calculated based on the micro-area range of the solder joint, the preset spot diameter, and the synchronous delay of the solder joint. By combining the trigger time and the scanning frequency, the galvanometer timing parameter set is obtained; The range of the micro-area of ​​the solder joint is determined based on the coordinates of the solder joint to be welded. The scanning path of the laser cleaning module is planned within the range of the micro-area of ​​the solder joint to obtain the solder joint scanning path. Collect the surface height of the high-speed line to be processed at the coordinates of the welding point, and calculate the defocus compensation amount based on the surface height and the preset focal length; By summarizing the galvanometer timing parameter set, solder joint scanning path, and defocus compensation amount, a dynamic compensation planning scheme is obtained.

[0037] It should be explained that the solder joint synchronization delay is the time required for the solder joint to travel from its corresponding coordinates to the center point of the light outlet at a real-time speed. The calculation process for the solder joint synchronization delay is as follows: In a three-dimensional Cartesian coordinate system, calculate the Euclidean distance between the coordinates of the solder joint and the center point of the light outlet; divide this Euclidean distance by the real-time speed to obtain the solder joint synchronization delay. The trigger time is the time when the laser source of the laser cleaning module begins to output laser pulses. The calculation process for the trigger time is as follows: Obtain the current system time of the control module; calculate the sum of the current system time and the solder joint synchronization delay; this sum is the trigger time. The scanning frequency is the rate at which the two-dimensional galvanometer scanning head of the laser cleaning module scans within the micro-area of ​​the solder joint. The scanning frequency is calculated as follows: The side length of the solder joint micro-area along the scanning direction is divided by the spot diameter, and rounded up to obtain the number of spots per scanning line. The side length of the solder joint micro-area perpendicular to the scanning direction is divided by the spot diameter, and rounded up to obtain the total number of scanning lines. The product of the number of spots and the total number of scanning lines is calculated to obtain the total number of spots. The total number of spots is then divided by the solder joint synchronization delay to obtain the scanning frequency. The spot diameter is an inherent optical parameter of the laser source, and its value is determined by the laser source's factory specifications.

[0038] For example, assuming the solder joint micro-area is a square region with a side length of 2 mm and the spot diameter is 0.05 mm, then each scan line contains 40 spots, the total number of scan lines is 40, and the total number of spots is 1600. If the solder joint synchronization delay is 0.1 seconds, then the calculated scanning frequency is 16000 Hz.

[0039] Understandably, the laser spot is a single laser irradiation point formed on the surface of the high-speed line to be processed after the laser pulse output by the laser cleaning module is focused; it is the smallest unit of laser cleaning. The laser spot diameter is the effective width of the laser spot on the surface of the high-speed line to be processed, and its value is determined by the inherent optical parameters of the laser source, used to characterize the size of the area that a single laser pulse can cover. Optionally, a pulsed fiber laser with an average power of 100 watts and a wavelength of 1064 nanometers is used as the laser source, and its laser spot diameter is approximately 0.05 millimeters. The basic laser spot overlap rate is the ratio of the length of the overlapping portion of two adjacent laser spots in the scanning direction to the laser spot diameter within a single scan line. The solder joint micro-area range is a spatial region centered on the coordinates of the point to be soldered. The size of this spatial region is determined according to the type and thickness of the insulation layer, used to ensure that the coverage area of ​​laser cleaning is slightly larger than the point to be soldered itself, so as to fully clean the surface covering at the point to be soldered. For example, if the insulation layer is polyurethane and its thickness is 0.05 mm, the solder joint micro-area can be set as a square region with a side length of 2 mm, centered on the coordinates of the point to be soldered. The solder joint scanning path is the trajectory of the laser spot planned by the laser cleaning module within the solder joint micro-area. The scanning path consists of multiple parallel scanning lines and multiple scanning points. Each scanning line is composed of multiple scanning points arranged sequentially in the horizontal direction, with adjacent scanning lines evenly spaced in the vertical direction. Each scanning line contains the same number of laser spots, and the length of each scanning line is equal to the side length of the solder joint micro-area along the scanning direction. A scanning point is a position where the laser spot stops within the solder joint micro-area. The laser spot moves point by point along the scanning line according to the arrangement of the scanning points. After completing the scanning of a single scanning line, it jumps to the first scanning point of the next scanning line to continue scanning, until all scanning points have been traversed. The scanning direction is the direction in which the laser spot moves point by point along the scanning line. The center-to-center distance between two adjacent laser spots is the distance between the centers of two adjacent laser spots along or perpendicular to the scanning direction. Since the overlap rate of the basic spot is uniformly set in all directions within the micro-area of ​​the solder joint, the center-to-center distance of the spot along the scanning direction and perpendicular to the scanning direction is numerically equal.

[0040] It should be understood that the galvanometer timing parameter set is a set of control parameters composed of trigger time and scanning frequency, used to control the output timing of laser pulses and the deflection rate of the two-dimensional galvanometer scanning head. The trigger time determines when the laser pulse starts to be output, and the scanning frequency determines the rate at which the two-dimensional galvanometer scanning head scans the micro-area of ​​the solder joint. The surface height is the vertical distance between the coordinates of the point to be soldered and the center point of the light outlet. The focal length is, under ideal conditions, the distance from the focal point of the laser pulse to the center point of the light outlet after the laser source of the laser cleaning module is focused. The focal length is set based on the inherent optical parameters of the laser source, ensuring that the spot diameter at the focal point is minimized and the energy density is maximized at this focal length. The defocus compensation amount is the Z-axis displacement compensation value calculated based on the surface height and focal length. The calculation process for the defocus compensation amount is as follows: calculate the absolute difference between the surface height and the focal length. If the absolute difference is greater than a preset defocus dead zone threshold, then the absolute difference is used as the defocus compensation amount; otherwise, the defocus compensation amount is zero. The defocus dead zone threshold is a manually set maximum allowable difference between the surface height and the focal length. Its setting is based on a comprehensive consideration of the laser cleaning module's precision and the characteristics of the high-speed line being processed. By introducing the defocus dead zone threshold, the frequent adjustment of the Z-axis direction due to jumps during the high-speed line's movement can be avoided, thereby improving the stability of the preprocessing execution system.

[0041] S3. Calculate the process parameters of the laser cleaning module based on the dynamic sensing data to obtain the target cleaning parameter set.

[0042] It should be clarified that the target cleaning parameter set is a set of process parameters used to control the laser cleaning module to perform targeted laser cleaning.

[0043] Specifically, the step of calculating the process parameters of the laser cleaning module based on dynamic sensing data to obtain the target cleaning parameter set includes: The base laser power and base scanning speed are determined based on the type and thickness of the insulating layer. Calculate the ratio of the insulation layer thickness to the preset reference thickness to obtain the thickness normalization coefficient; Multiply the thickness normalization coefficient by the preset overlap rate benchmark value to obtain the basic spot overlap rate; The target cleaning parameter set is obtained by summarizing the basic laser power, basic scanning speed, and basic spot overlap rate.

[0044] It should be explained that the basic laser power is the reference power value of the laser pulse. The basic scanning speed is the reference rate at which the laser spot moves along the scanning line. The basic laser power and basic scanning speed are determined by consulting a pre-constructed process parameter mapping table based on the insulating layer type and thickness. The specific process of constructing the process parameter mapping table is as follows: multiple sets of standard samples with different insulating layer types, insulating layer thicknesses, laser power, and scanning speeds are set up. Multi-factor orthogonal experiments are conducted on these standard samples to obtain multiple experimental results. The surface cleaning effect of the weld joint after cleaning is used as the judgment standard. Multiple sample scores are obtained based on the multiple experimental results. The standard samples, experimental results, and sample scores correspond one-to-one. The laser power and scanning speed corresponding to the highest score among the multiple sample scores are taken as the standard laser power and standard scanning speed. The insulating layer type, insulating layer thickness, standard laser power, and standard scanning speed are summarized to construct the process parameter mapping table and store it in the control module.

[0045] Understandably, the reference thickness is a manually set thickness benchmark value used to normalize different insulation layer thicknesses into a dimensionless proportionality coefficient. The reference thickness is set based on the median value of common thickness ranges corresponding to different insulation layer types. The thickness normalization coefficient is used to quantify the deviation of the insulation layer thickness at the welding point from the reference thickness and is a dimensionless quantity. The overlap rate benchmark value is a manually set benchmark value for the basic spot overlap rate. It is set based on: setting multiple sets of standard samples with different reference thicknesses and spot overlap rates; conducting cleaning experiments on these standard samples to obtain multiple experimental results; using the surface cleaning effect of the welding point after cleaning as the evaluation criterion; and evaluating multiple sample scores based on the multiple experimental results. Each standard sample, experimental result, and sample score corresponds one-to-one. The spot overlap rate corresponding to the highest score among the multiple sample scores is taken as the overlap rate benchmark value. By multiplying the thickness normalization coefficient by the overlap rate benchmark value, the overlap rate benchmark value is corrected, allowing the basic spot overlap rate to adaptively adjust according to the insulation layer thickness.

[0046] S4. Based on the dynamic compensation planning scheme and the target cleaning parameter set, perform fixed-point laser cleaning on the welding point to obtain the cleaned welding point.

[0047] It should be understood that the weld points mentioned after cleaning are the locations where the surface covering on the high-speed line to be treated has been peeled off.

[0048] Specifically, the step of performing targeted laser cleaning on the welding points according to the dynamic compensation planning scheme and the target cleaning parameter set to obtain the cleaned welding points includes: The laser cleaning module is controlled to output laser pulses based on the trigger time and the basic laser power to obtain a laser pulse signal; Determine m scan points from the solder joint scan path, and perform the following operation on each of the m scan points: The laser cleaning module is controlled to deflect the galvanometer based on the scanning point and scanning frequency, thereby obtaining the galvanometer deflection control value. The laser cleaning module is adjusted according to the defocus compensation amount to obtain the focus position; By associating the galvanometer deflection control value with the focus position, the scanning node is obtained; Summarize the scanning nodes to obtain m scanning nodes. Calculate the movement rate of m-1 light spots based on the m scanning nodes, the basic scanning speed, and the basic spot overlap rate. Based on the laser pulse signal, m scanning nodes, and m-1 spot movement rates, a fixed-point laser cleaning is performed on the welding point to be welded, resulting in a cleaned welding point.

[0049] It should be clarified that the laser pulse signal is a sequence of m laser pulses used to strip the surface covering at the scanning node. Each laser pulse corresponds one-to-one with a scanning node; the trigger time determines the start time of the laser pulse signal output; and the base laser power determines the energy of each laser pulse. The galvanometer deflection control parameter is the deflection parameter required to guide the laser pulse to the scanning point using the two-dimensional galvanometer scanning head. The focus position is the actual height position of the focal point of the laser pulse. The spot movement rate is the movement speed of the spot as it moves from the current scanning node to the next scanning node. The calculation process for the spot movement rate is as follows: calculate the Euclidean distance between two adjacent scanning nodes; determine the center-to-center distance of the spots based on the base spot overlap rate; divide the Euclidean distance by the base scanning speed to obtain the movement time; and divide the center-to-center distance of the spots by the movement time to obtain the spot movement rate.

[0050] Specifically, the step of controlling the laser cleaning module to deflect the galvanometer based on the scanning point and scanning frequency to obtain the galvanometer deflection control amount includes: Obtain the galvanometer axis spacing and calibration working distance of the laser cleaning module; Determine the X-axis and Y-axis components of the scanning point in a three-dimensional rectangular coordinate system; The X-axis deflection angle and Y-axis deflection angle are calculated based on the galvanometer axis spacing, calibration working distance, X-axis component, and Y-axis component, using the following formulas:

[0051] in, This indicates the X-axis deflection angle. This represents the X-axis component. This indicates the calibrated working distance. This indicates the Y-axis deflection angle. This represents the Y-axis component. Indicates the galvanometer axis spacing. Represents the arctangent function. Represents the cosine function; The laser cleaning module is controlled to deflect the galvanometer based on the scanning frequency, X-axis deflection angle, and Y-axis deflection angle, thereby obtaining the galvanometer deflection control value.

[0052] It should be explained that the two-dimensional galvanometer scanning head includes an X-axis deflecting mirror and a Y-axis deflecting mirror. The galvanometer axis spacing is the physical distance between the rotation axes of the X-axis and Y-axis deflecting mirrors in the two-dimensional galvanometer scanning head. The calibrated working distance is the distance between the center point of the laser cleaning module's output port and the focal point of the laser pulse. The X-axis and Y-axis components are the coordinate values ​​of the scanning point along the X-axis and Y-axis directions in a three-dimensional rectangular coordinate system. The X-axis deflection angle is the angle by which the X-axis deflecting mirror needs to rotate. The Y-axis deflection angle is the angle by which the Y-axis deflecting mirror needs to rotate. The calculation process for the X-axis deflection angle is as follows: divide the X-axis component by the calibrated working distance and take the arctangent of the result, which is the X-axis deflection angle. The calculation process for the Y-axis deflection angle is as follows: Calculate the cosine value of the X-axis deflection angle, and then calculate the product of the Y-axis component and the cosine value. Calculate the sum of the calibration working distance and the galvanometer axis spacing. Divide the product by the sum, and then take the arctangent of the result, which is the Y-axis deflection angle. The purpose of introducing the galvanometer axis spacing is to ensure that the laser pulse, after being reflected by the X-axis and Y-axis deflection mirrors, can accurately point to the scanning point. The scanning frequency, in the galvanometer deflection control parameters, is used to characterize the deflection rate of the two-dimensional galvanometer scanning head between adjacent scanning points.

[0053] S5. Use the surface condition detection module to detect the surface condition of the weld points after cleaning, obtain surface condition data, input the surface condition data into the pre-built cleaning-welding mapping model, and obtain the adjusted welding power according to the cleaning-welding mapping model.

[0054] Understandably, the surface condition data is a set of indicators used to quantify the cleaning effect. The cleaning-welding mapping model is a mathematical model pre-built in the control module, used to calculate the adjusted welding power based on the surface condition data. The cleaning-welding mapping model includes a welding parameter correction formula and three model parameters: a base welding power, a roughness correction coefficient, and an oxygen content correction coefficient. The construction process of the cleaning-welding mapping model is as follows: multiple sets of standard samples with different surface roughness and residual oxygen content are set, and welding tensile tests are performed on these standard samples to obtain multiple sets of test data related to surface roughness, residual oxygen content, and welding power. Linear regression is used to fit these multiple sets of test data to obtain the three model parameters. These three model parameters are then substituted into the welding parameter correction formula to construct the cleaning-welding mapping model and store it in the control module. The adjusted welding power is a process parameter used to control the downstream welding equipment to perform welding operations on the cleaned welding points.

[0055] Specifically, the surface condition detection module is used to detect the surface condition of the weld joints after cleaning to obtain surface condition data, including: Coaxial visual imaging was performed on the weld points after cleaning to obtain an image of the cleaned surface. Gray-scale features were extracted from the cleaned surface image to obtain surface gray-scale distribution data; Surface roughness is calculated based on surface grayscale distribution data; LIBS spectral analysis was performed on the cleaned weld joints to obtain the characteristic spectral lines of oxygen. The residual oxygen content was calculated based on the characteristic spectral lines of oxygen. By summarizing the surface roughness and residual oxygen content, surface condition data are obtained.

[0056] It should be understood that the surface image after cleaning is a two-dimensional image of the weld point surface after cleaning. The surface grayscale distribution data is used to reflect the changes in brightness in different areas of the weld point surface after cleaning. The surface roughness is a quantified value calculated from the standard deviation of multiple grayscale values ​​in the surface grayscale distribution data, with units of micrometers, used to characterize the unevenness of the weld point surface after cleaning. The calculation process of surface roughness is as follows: multiple grayscale values ​​are obtained from the surface grayscale distribution data, the standard deviation of the multiple grayscale values ​​is calculated, and the standard deviation is converted into surface roughness through a preset grayscale-roughness calibration curve. The grayscale-roughness calibration curve is a manually set mapping relationship between grayscale values ​​and surface roughness. Its setting process is as follows: multiple sets of standard samples with different surface roughness are set, coaxial visual imaging and grayscale analysis are performed on the multiple sets of standard samples to obtain multiple sets of test data, and linear fitting is performed on the multiple sets of test data to obtain the grayscale-roughness calibration curve.

[0057] It should be clarified that the oxygen element characteristic spectral lines are used to characterize the spectral characteristics of residual oxygen on the surface of the weld joint after cleaning. The residual oxygen content is used to characterize the degree of oxide film residue on the surface of the weld joint after cleaning. The calculation process of the residual oxygen content is as follows: obtain the characteristic wavelength and intensity of oxygen from the oxygen element characteristic spectral lines, determine the molar absorptivity based on the characteristic wavelength, and calculate the residual oxygen content based on the intensity and molar absorptivity. The calculation process related to the molar absorptivity is prior art and will not be elaborated here.

[0058] Specifically, the step of performing LIBS spectral analysis on the cleaned weld joints to obtain the characteristic spectral lines of oxygen includes: The surface condition detection module excites the weld points after cleaning to generate plasma plumes. Collect raw spectral data of plasma plume; The characteristic wavelengths of oxygen are identified from the raw spectral data, and the intensity of the oxygen spectral lines is determined based on these characteristic wavelengths. The characteristic spectral lines of oxygen are constructed based on the characteristic wavelength and intensity of oxygen spectral lines.

[0059] It should be explained that the plasma plume is a plasma cloud formed when the surface of the weld point is bombarded by a laser pulse after cleaning. The original spectral data is used to characterize the correspondence between wavelength and spectral intensity values. For example, the original spectral data can be expressed as follows: a spectral intensity value of 3500 at a wavelength of 777 nm, a spectral intensity value of 1800 at a wavelength of 780 nm, and a spectral intensity value of 2800 at a wavelength of 844 nm. Here, 777 nm and 844 nm are characteristic wavelength positions of oxygen, and the spectral intensity value at these positions is the subsequent spectral line intensity of oxygen. The characteristic wavelength of oxygen is a specific wavelength value of oxygen identified from the original spectral data. The spectral line intensity of oxygen is the spectral intensity value at the position corresponding to the characteristic wavelength of oxygen in the original spectral data.

[0060] Specifically, the step of inputting surface state data into a pre-constructed cleaning-welding mapping model and obtaining the adjusted welding power based on the cleaning-welding mapping model includes: Set acceptable thresholds for surface roughness and oxygen content; The basic welding power, roughness correction factor, and oxygen content correction factor are obtained from the cleaning-welding mapping model. If the surface roughness is not greater than the acceptable roughness threshold and the residual oxygen content is not greater than the acceptable oxygen content threshold, the adjusted welding power is calculated based on the basic welding power, surface roughness, roughness correction coefficient, oxygen content correction coefficient, and the pre-constructed welding parameter correction formula. The welding parameter correction formula is as follows:

[0061] in, This indicates the adjusted welding power. This indicates the basic welding power. This represents the roughness correction coefficient. This indicates the surface roughness. This represents the oxygen content correction factor. This indicates the content of residual oxygen.

[0062] Understandably, the roughness qualification threshold is used to determine whether the surface roughness of the weld point is qualified after cleaning. Its setting basis is as follows: multiple sets of cleaned standard samples with different surface roughness are set, and the multiple sets of cleaned standard samples are sorted in ascending order of surface roughness. Standard welding parameters are set sequentially, and welding tests are performed on the cleaned standard samples according to the standard welding parameters. The weld strength obtained from the tests is recorded. When the weld strength is not greater than the weld strength benchmark value for the first time, if the current cleaned standard sample's position is 1, then the surface roughness corresponding to the current cleaned standard sample is taken as the roughness qualification threshold; otherwise, the surface roughness of the previous set of cleaned standard samples is taken as the roughness qualification threshold. The oxygen content qualification threshold is a critical value for determining whether the residual oxygen element content on the surface of the weld point after cleaning is qualified. Its setting basis is similar to that of the roughness qualification threshold, except that the roughness qualification threshold is set using multiple sets of cleaned standard samples with different surface roughness, while the oxygen content qualification threshold is set using multiple sets of cleaned standard samples with different residual oxygen element contents.

[0063] It should be understood that the weld strength is the maximum tensile force that the target weld point can withstand before breaking during the welding test, measured in megapascals (MPa). The weld strength benchmark value is the critical value for determining whether the weld strength meets the standard. It is set based on the welding process qualification standards followed by the downstream welding equipment. For example, ISO 15614-2 specifies that the weld strength after laser cleaning must reach at least 60% of the rated tensile strength of the metal wire. If the rated tensile strength of the metal wire is 300 MPa, then the weld strength benchmark value is 180 MPa.

[0064] It should be clarified that the base welding power, roughness correction coefficient, and oxygen content correction coefficient are all model parameters obtained from the cleaning-welding mapping model. Specifically, the base welding power is used to determine the starting point for calculating the adjusted welding power, the roughness correction coefficient is used to quantify the influence of surface roughness on the welding power, and the oxygen content correction coefficient is used to quantify the influence of residual oxygen content on the welding power. The adjusted welding power is a welding power value adapted to the actual surface condition of the weld point after cleaning. By substituting the surface roughness and residual oxygen content into the welding parameter correction formula, the adjusted welding power can dynamically adapt to the actual surface condition of the weld point after cleaning.

[0065] S6. The adjusted welding power is sent to the downstream welding equipment through the control module to perform welding on the cleaned welding points, obtain the target welding points, summarize the target welding points, obtain n target welding points, and complete the high-speed line welding point preprocessing based on laser cleaning.

[0066] It should be explained that the target welding point is the final qualified welding point formed on the high-speed line to be processed after pre-welding treatment and welding operation.

[0067] To address the problems described in the background section, this invention first receives a preprocessing start command. Based on this command, it determines the high-speed wire to be processed and the preprocessing execution system. The preprocessing execution system includes a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. This invention considers the characteristics of high-speed wires moving continuously on the production line and the discrete distribution of welding points. Through a modular system architecture, it achieves precise processing of each welding point on the high-speed wire, avoiding damage to non-welding areas and resource waste caused by the overall processing of the wire in traditional solutions.Then, this invention uses a sensing module to determine n welding points from the high-speed wire to be processed. For each of the n welding points, the following operations are performed: acquiring dynamic sensing data of the welding point, performing spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic sensing data, and generating a dynamic compensation planning scheme. It is evident that this invention considers the real-time changes in the spatial position of the welding points during the movement of the high-speed wire, and the problem that traditional static cleaning schemes cannot lock onto the moving target. Therefore, by collecting real-time motion speed and welding point coordinates and performing spatiotemporal synchronization compensation, a dynamic compensation planning scheme is generated, including welding point synchronization delay, galvanometer timing parameter set, and defocus compensation amount. This enables the laser cleaning module to accurately track the welding points moving at high speed. Secondly... This invention calculates the process parameters of the laser cleaning module based on dynamic sensing data to obtain a target cleaning parameter set. It is evident that this invention considers the differences in insulation layer type and thickness on the surfaces of different welding points, making fixed cleaning parameters unsuitable for diverse working conditions. Therefore, by querying a process parameter mapping table, it obtains the basic laser power, basic scanning speed, and basic spot overlap rate to match the current surface state of the welding point, achieving adaptive correction of the process parameters. Next, based on the dynamic compensation planning scheme and the target cleaning parameter set, this invention performs fixed-point laser cleaning on the welding point to obtain the cleaned welding point. It is evident that this invention considers the need for laser cleaning to scan point-by-point within the micro-area of ​​the welding point while simultaneously addressing wire bounce; therefore, it utilizes... The coordinated operation of galvanometer deflection control and defocus compensation precisely guides the laser pulse to each scanning node and dynamically maintains the focal position. Combined with the calculation of the spot movement rate, stable peeling of surface coverings within the micro-area of ​​the weld joint is achieved. Furthermore, this invention utilizes a surface condition detection module to detect the surface condition of the weld joint after cleaning, obtaining surface condition data. This surface condition data is input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. It is evident that this invention considers the fluctuations in cleaning effect, and that a fixed welding power is difficult to adapt to different post-cleaning surface conditions. Therefore, by performing dual detection of surface roughness and residual oxygen content of the weld joint after cleaning, and substituting this data into the cleaning-welding mapping model... The model is processed to dynamically adapt the welding power to the actual surface condition. Finally, the invention sends the adjusted welding power to the downstream welding equipment through the control module to perform welding on the cleaned welding points, obtaining the target welding points. The target welding points are then summarized to obtain n target welding points, completing the preprocessing of high-speed line welding points based on laser cleaning. It can be seen that the invention links laser cleaning with welding parameters, enabling each welding point to obtain welding parameters that are precisely matched with its surface condition, ensuring the reliability of the target welding points. Therefore, the invention can achieve precise laser cleaning of welding points on high-speed moving wires through dynamic sensing and spatiotemporal synchronous compensation, and adaptively adjust the cleaning parameters by the surface condition after cleaning, ensuring the reliability of the cleaning effect.

[0068] like Figure 2 The diagram shown is a functional block diagram of a high-speed line welding joint pretreatment system based on laser cleaning provided in an embodiment of the present invention.

[0069] The high-speed line welding joint pretreatment system 100 based on laser cleaning described in this invention can be installed in an electronic device. Depending on the functions implemented, the high-speed line welding joint pretreatment system 100 based on laser cleaning may include an instruction receiving and system determination module 101, a dynamic sensing and planning generation module 102, a parameter calculation and cleaning execution module 103, and a quality inspection and welding execution module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device. The instruction receiving and system determination module 101 is used to receive a preprocessing start instruction and determine the high-speed line to be processed and the preprocessing execution system based on the preprocessing start instruction. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. The dynamic perception and planning generation module 102 is used to determine n welding points from the high-speed line to be processed using the sensing module, and to perform the following operations on each of the n welding points: acquire the dynamic perception data of the welding point, perform spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic perception data, and generate a dynamic compensation planning scheme. The parameter calculation and cleaning execution module 103 is used to calculate the process parameters of the laser cleaning module based on dynamic sensing data, obtain the target cleaning parameter set, and perform fixed-point laser cleaning on the welding point to be welded according to the dynamic compensation planning scheme and the target cleaning parameter set, so as to obtain the cleaned welding point. The quality inspection and welding execution module 104 is used to perform surface condition detection on the weld points after cleaning using the surface condition detection module, obtain surface condition data, input the surface condition data into a pre-constructed cleaning-welding mapping model, obtain the adjusted welding power according to the cleaning-welding mapping model, send the adjusted welding power to the downstream welding equipment through the control module, perform welding on the weld points after cleaning, obtain target weld points, summarize the target weld points, obtain n target weld points, and complete the high-speed line welding point preprocessing based on laser cleaning.

[0070] In detail, the modules in the high-speed wire bonding joint pretreatment system 100 based on laser cleaning described in this embodiment of the invention employ the same methods as described above. Figure 1 The method described herein is the same as the laser cleaning-based high-speed line welding point pretreatment method and can produce the same technical effect, so it will not be repeated here.

[0071] like Figure 3The diagram shown is a structural schematic of an electronic device that implements a high-speed line welding joint pretreatment method based on laser cleaning, according to an embodiment of the present invention.

[0072] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a laser-based high-speed wire bonding joint pretreatment method program.

[0073] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a high-speed wire bonding joint pretreatment method program based on laser cleaning, but also to temporarily store data that has been output or will be output.

[0074] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a high-speed wire bonding joint pretreatment method program based on laser cleaning), and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0075] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0076] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0077] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0078] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0079] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0080] The program for the high-speed wire bonding joint preprocessing method based on laser cleaning, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: The system receives a preprocessing start command and determines the high-speed line to be processed and the preprocessing execution system based on the preprocessing start command. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. Using a sensing module, n points to be soldered are identified from the high-speed line to be processed. For each of the n points to be soldered, the following operation is performed: Acquire dynamic sensing data of the point to be welded, perform spatiotemporal synchronous compensation processing on the laser cleaning module based on the dynamic sensing data, and generate a dynamic compensation planning scheme. The process parameters of the laser cleaning module are calculated based on the dynamic sensing data to obtain the target cleaning parameter set; Based on the dynamic compensation planning scheme and the target cleaning parameter set, the welding point to be welded is subjected to fixed-point laser cleaning to obtain the cleaned welding point. The surface condition detection module is used to detect the surface condition of the weld points after cleaning to obtain surface condition data. The surface condition data is then input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. The adjusted welding power is sent to the downstream welding equipment through the control module, and welding is performed on the cleaned welding points to obtain the target welding points. The target welding points are summarized to obtain n target welding points, thus completing the high-speed line welding point preprocessing based on laser cleaning.

[0081] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0082] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0083] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: The system receives a preprocessing start command and determines the high-speed line to be processed and the preprocessing execution system based on the preprocessing start command. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. Using a sensing module, n points to be soldered are identified from the high-speed line to be processed. For each of the n points to be soldered, the following operation is performed: Acquire dynamic sensing data of the point to be welded, perform spatiotemporal synchronous compensation processing on the laser cleaning module based on the dynamic sensing data, and generate a dynamic compensation planning scheme. The process parameters of the laser cleaning module are calculated based on the dynamic sensing data to obtain the target cleaning parameter set; Based on the dynamic compensation planning scheme and the target cleaning parameter set, the welding point to be welded is subjected to fixed-point laser cleaning to obtain the cleaned welding point. The surface condition detection module is used to detect the surface condition of the weld points after cleaning to obtain surface condition data. The surface condition data is then input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. The adjusted welding power is sent to the downstream welding equipment through the control module, and welding is performed on the cleaned welding points to obtain the target welding points. The target welding points are summarized to obtain n target welding points, thus completing the high-speed line welding point preprocessing based on laser cleaning.

[0084] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0085] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0086] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0087] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A pretreatment method for high-speed wire bonding joints based on laser cleaning, characterized in that, The method includes: The system receives a preprocessing start command and determines the high-speed line to be processed and the preprocessing execution system based on the preprocessing start command. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. Using a sensing module, n points to be soldered are identified from the high-speed line to be processed. For each of the n points to be soldered, the following operation is performed: Acquire dynamic sensing data of the point to be welded, perform spatiotemporal synchronous compensation processing on the laser cleaning module based on the dynamic sensing data, and generate a dynamic compensation planning scheme. The process parameters of the laser cleaning module are calculated based on the dynamic sensing data to obtain the target cleaning parameter set; Based on the dynamic compensation planning scheme and the target cleaning parameter set, the welding point to be welded is subjected to fixed-point laser cleaning to obtain the cleaned welding point. The surface condition detection module is used to detect the surface condition of the weld points after cleaning to obtain surface condition data. The surface condition data is then input into a pre-constructed cleaning-welding mapping model, and the adjusted welding power is obtained based on the cleaning-welding mapping model. The adjusted welding power is sent to the downstream welding equipment through the control module, and welding is performed on the cleaned welding points to obtain the target welding points. The target welding points are summarized to obtain n target welding points, thus completing the high-speed line welding point preprocessing based on laser cleaning.

2. The high-speed line welding joint pretreatment method based on laser cleaning as described in claim 1, characterized in that, The acquisition of dynamic sensing data of the weld point includes: Determine the center point of the light outlet of the laser cleaning module, and construct a three-dimensional rectangular coordinate system with the center point of the light outlet as the origin; Doppler velocity detection and coaxial vision imaging were performed on the high-speed wire to be processed to obtain the initial motion velocity and the wire surface image, respectively. Subpixel-level corner detection is performed on the wire surface image to determine the coordinates of the point to be welded in the three-dimensional Cartesian coordinate system; The image of the area to be welded is extracted from the wire surface image based on the coordinates of the point to be welded. The structured light velocity value is calculated based on the image of the area to be welded, and the initial motion velocity and the structured light velocity value are cross-validated to obtain the real-time motion velocity. Based on the coordinates of the point to be welded, the surface covering material of the point to be welded is collected. Spectral analysis and spectral thickness measurement of the surface covering material are performed to obtain the insulation layer type and insulation layer thickness. The insulation layer type and insulation layer thickness are summarized to obtain the surface covering material information. By summarizing real-time motion speed, coordinates of the welding point, and surface covering information, dynamic sensing data is obtained.

3. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 2, characterized in that, The step of performing spatiotemporal synchronization compensation processing on the laser cleaning module based on dynamic sensing data to generate a dynamic compensation planning scheme includes: Based on the real-time motion speed and the coordinates of the point to be welded, the time required for the point to be welded to reach the center point of the light outlet is calculated, and the synchronization delay of the weld point is obtained. The triggering time and scanning frequency of the laser cleaning module are calculated based on the micro-area range of the solder joint, the preset spot diameter, and the synchronous delay of the solder joint. By combining the trigger time and the scanning frequency, the galvanometer timing parameter set is obtained; The range of the solder joint micro-area is determined based on the coordinates of the solder joint to be welded. The scanning path of the laser cleaning module is planned within the range of the solder joint micro-area to obtain the solder joint scanning path. Collect the surface height of the high-speed line to be processed at the coordinates of the welding point, and calculate the defocus compensation amount based on the surface height and the preset focal length; By summarizing the galvanometer timing parameter set, solder joint scanning path, and defocus compensation amount, a dynamic compensation planning scheme is obtained.

4. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 3, characterized in that, The process parameters of the laser cleaning module are calculated based on dynamic sensing data to obtain the target cleaning parameter set, including: The base laser power and base scanning speed are determined based on the type and thickness of the insulating layer. Calculate the ratio of the insulation layer thickness to the preset reference thickness to obtain the thickness normalization coefficient; Multiply the thickness normalization coefficient by the preset overlap rate benchmark value to obtain the basic spot overlap rate; The target cleaning parameter set is obtained by summarizing the basic laser power, basic scanning speed, and basic spot overlap rate.

5. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 4, characterized in that, The process involves performing targeted laser cleaning on the welding points based on a dynamic compensation planning scheme and a target cleaning parameter set, resulting in cleaned welding points, including: The laser cleaning module is controlled to output laser pulses based on the trigger time and the basic laser power to obtain a laser pulse signal; Determine m scan points from the solder joint scan path, and perform the following operation on each of the m scan points: The laser cleaning module is controlled to deflect the galvanometer based on the scanning point and scanning frequency, thereby obtaining the galvanometer deflection control value. The laser cleaning module is adjusted according to the defocus compensation amount to obtain the focus position; By associating the galvanometer deflection control value with the focus position, the scanning node is obtained; Summarize the scanning nodes to obtain m scanning nodes. Calculate the movement rate of m-1 light spots based on the m scanning nodes, the basic scanning speed, and the basic spot overlap rate. Based on the laser pulse signal, m scanning nodes, and m-1 spot movement rates, a fixed-point laser cleaning is performed on the welding point to be welded, resulting in a cleaned welding point.

6. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 5, characterized in that, The step of controlling the laser cleaning module to deflect the galvanometer based on the scanning point and scanning frequency to obtain the galvanometer deflection control quantity includes: Obtain the galvanometer axis spacing and calibration working distance of the laser cleaning module; Determine the X-axis and Y-axis components of the scanning point in a three-dimensional rectangular coordinate system; The X-axis deflection angle and Y-axis deflection angle are calculated based on the galvanometer axis spacing, calibration working distance, X-axis component, and Y-axis component, using the following formulas: in, This indicates the X-axis deflection angle. This represents the X-axis component. This indicates the calibrated working distance. This indicates the Y-axis deflection angle. This represents the Y-axis component. Indicates the axial spacing of the galvanometer. Represents the arctangent function. Represents the cosine function; The laser cleaning module is controlled to deflect the galvanometer based on the scanning frequency, X-axis deflection angle, and Y-axis deflection angle, thereby obtaining the galvanometer deflection control value.

7. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 6, characterized in that, The surface condition detection module is used to detect the surface condition of the weld points after cleaning, and surface condition data is obtained, including: Coaxial visual imaging was performed on the weld points after cleaning to obtain an image of the cleaned surface. Gray-scale features were extracted from the cleaned surface image to obtain surface gray-scale distribution data; Surface roughness is calculated based on surface grayscale distribution data; LIBS spectral analysis was performed on the cleaned weld joints to obtain the characteristic spectral lines of oxygen. The residual oxygen content was calculated based on the characteristic spectral lines of oxygen. By summarizing the surface roughness and residual oxygen content, surface condition data are obtained.

8. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 7, characterized in that, The LIBS spectral analysis of the cleaned weld joints to obtain the characteristic spectral lines of oxygen includes: The surface condition detection module excites the weld points after cleaning to generate plasma plumes. Collect raw spectral data of plasma plume; The characteristic wavelengths of oxygen are identified from the raw spectral data, and the intensity of the oxygen spectral lines is determined based on these characteristic wavelengths. The characteristic spectral lines of oxygen are constructed based on the characteristic wavelength and intensity of oxygen spectral lines.

9. The high-speed wire bonding joint pretreatment method based on laser cleaning as described in claim 8, characterized in that, The step of inputting surface condition data into a pre-constructed cleaning-welding mapping model and obtaining the adjusted welding power based on the cleaning-welding mapping model includes: Set acceptable thresholds for surface roughness and oxygen content; The basic welding power, roughness correction factor, and oxygen content correction factor are obtained from the cleaning-welding mapping model. If the surface roughness is not greater than the acceptable roughness threshold and the residual oxygen content is not greater than the acceptable oxygen content threshold, the adjusted welding power is calculated based on the basic welding power, surface roughness, roughness correction coefficient, oxygen content correction coefficient, and the pre-constructed welding parameter correction formula. The welding parameter correction formula is as follows: in, This indicates the adjusted welding power. This indicates the basic welding power. This represents the roughness correction coefficient. This indicates the surface roughness. This represents the oxygen content correction factor. This indicates the content of residual oxygen.

10. A high-speed wire bonding joint pretreatment system based on laser cleaning, characterized in that, The system includes: The instruction receiving and system determination module is used to receive a preprocessing start instruction and determine the high-speed line to be processed and the preprocessing execution system based on the preprocessing start instruction. The preprocessing execution system includes: a sensing module, a control module, a laser cleaning module, a surface condition detection module, and downstream welding equipment. The dynamic perception and planning generation module is used to determine n welding points from the high-speed line to be processed using the sensing module. For each of the n welding points, the following operations are performed: acquire the dynamic perception data of the welding point, perform spatiotemporal synchronization compensation processing on the laser cleaning module based on the dynamic perception data, and generate a dynamic compensation planning scheme. The parameter calculation and cleaning execution module is used to calculate the process parameters of the laser cleaning module based on dynamic sensing data, obtain the target cleaning parameter set, and perform fixed-point laser cleaning on the welding point to be welded according to the dynamic compensation planning scheme and the target cleaning parameter set, so as to obtain the welded point after cleaning. The quality inspection and welding execution module is used to detect the surface condition of the weld points after cleaning using the surface condition detection module, obtain surface condition data, input the surface condition data into a pre-built cleaning-welding mapping model, obtain the adjusted welding power according to the cleaning-welding mapping model, and send the adjusted welding power to the downstream welding equipment through the control module to perform welding on the cleaned weld points, obtain the target weld points, summarize the target weld points, obtain n target weld points, and complete the high-speed line welding point preprocessing based on laser cleaning.

Images