Stamping and welding integrated process for manufacturing automobile threaded plate

Abstract

The invention provides a stamping and welding integrated process for manufacturing an automobile threaded plate. Relates to the technical field of automobile parts, and comprises the steps that a metal plate of a preset specification is subjected to stamping forming treatment to form a main body structure, and the stamping forming treatment adopts a laser welding optimal interface prefabrication technology. The stable weld joint plate is subjected to post-treatment to form the automobile threaded plate, the automobile threaded plate is subjected to automatic discharging treatment to form a final finished product, post-treatment comprises surface treatment and weld joint finishing, and automatic discharging treatment adopts an automatic sorting system. According to the stamping and welding integrated process for manufacturing the automobile threaded plate, precise stamping and welding path planning of the automobile threaded plate are achieved through a laser welding optimal interface prefabrication technology and a machine vision acquisition system in combination with a three-dimensional scanning and geometric feature model comparison algorithm. And by optimizing a welding path and a real-time feedback adjusting technology, the stability and the high efficiency in the welding process are ensured, and the welding quality and the production efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of automotive parts technology, specifically to an integrated stamping and welding process for manufacturing automotive threaded plates. Background Technology

[0002] In automotive parts manufacturing, stamping and welding are two widely used basic processes. In the production of automotive sheet metal, stamping processes shape metal sheets into the required form, completing the basic shaping. Welding connects the various parts together, ensuring the strength and stability of the components. Stamping is typically used for mass production, characterized by high efficiency and precision, and can meet the stringent shape and dimensional requirements of body parts. Welding ensures a strong connection between parts and guarantees the durability of the joints. Traditionally, stamping and welding are performed separately, each requiring independent equipment and operating procedures. This division of labor can meet the production needs of automotive parts to a certain extent, especially in mass production.

[0003] However, existing technologies still have significant shortcomings. The stamping and welding processes require multiple interconnections, resulting in a complex and time-consuming production process. Each process relies on different equipment and techniques, increasing equipment occupancy time and manual labor requirements. The separation between processes leads to precision issues, affecting the strength and stability of component connections. In mass production, maintaining consistency in the connections between processes is difficult, leading to increased scrap rates. When stamping and welding are performed separately, the overall process efficiency is low. Each step requires individual operation and adjustment, increasing production cycles and resulting in energy waste. Current division of labor fails to achieve optimal coordination between stamping and welding, making it difficult to meet the demands for more efficient and precise production. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an integrated stamping and welding process for manufacturing automotive threaded plates. The technical problem this invention aims to solve is: how to utilize laser welding prefabricated interfaces, three-dimensional contour data acquisition, and real-time welding process adjustment technologies through an integrated stamping and welding process to address the issues of complex connections between stamping and welding processes and high scrap rates.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an integrated stamping and welding process for manufacturing automotive threaded plates, comprising:

[0006] S1. The metal sheet of a predetermined specification is stamped to form the main structure, wherein the stamping process adopts laser welding optimized interface prefabrication technology;

[0007] S2. Perform three-dimensional acquisition and processing on the welding area of ​​the main structure to obtain three-dimensional contour data. The three-dimensional acquisition and processing adopts a machine vision acquisition system.

[0008] S3. The three-dimensional contour data is processed to form welding path parameters. The processing includes a comparison method based on geometric feature models and a path optimization algorithm.

[0009] S4. The main structure is laser-welded using the welding path parameters to form a stable weld plate based on the laser welding process. The welding planning process adopts real-time feedback adjustment technology.

[0010] S5. The stable weld plate is post-processed to form the automotive threaded plate, and the automotive threaded plate is automatically unloaded to form the final product. The post-processing includes surface treatment and weld trimming, and the automatic unloading process adopts an automatic sorting system.

[0011] Preferably, the laser welding optimized interface prefabrication technology uses laser precision cutting to form a welding interface on the metal sheet. The welding interface is curved, including circular, elliptical, and curved shapes. The welding interface is located in the area to be welded to adapt to the needs of different components.

[0012] Preferably, the machine vision acquisition system includes a camera device and a laser scanner, wherein the resolution of the camera device is in the range of 3,000 pixels to 8,000 pixels, and the measurement accuracy of the laser scanner is 0.1 mm.

[0013] Preferably, the camera device acquires surface images of the area to be welded, and the laser scanner performs three-dimensional scanning of the area to be welded. The three-dimensional scanning includes geometric shape scanning, contour scanning, and depth information scanning. The surface image acquisition and the three-dimensional scanning work together to form the three-dimensional contour data.

[0014] Preferably, the comparison method matches the three-dimensional contour data with the geometric feature model to form geometric deviation data, wherein the geometric feature model includes edge contours, hole positions, joint shapes, and joint angles.

[0015] Preferably, the path optimization algorithm forms the welding path parameters by minimizing the geometric deviation data, and the model formula of the path optimization algorithm is:

[0016] .

[0017] in, The welding path parameters are represented in units of... , This indicates the first position on the actual path traveled during the welding process. points, unit is , The first path point represents the target path point. Points, in meters. The weights of the path points are dimensionless. This represents the change in curvature at a path point, in units of... , Represents the total length of the path, in units of , where n represents the number of points on the path, which is dimensionless. This represents the regularization parameter, which is dimensionless.

[0018] Preferably, the real-time feedback adjustment technology includes temperature monitoring, weld morphology monitoring, and welding speed adjustment, and the welding planning process includes the following steps:

[0019] S41. The temperature of the main structure is monitored using the welding path parameters, and temperature feedback data is generated based on the temperature monitoring.

[0020] S42. Monitor the weld morphology of the main structure based on the temperature feedback data, and generate weld quality data based on the weld morphology monitoring;

[0021] S43. Based on the temperature feedback data and the weld quality data, the welding speed of the main structure is adjusted, and the stable weld plate is formed based on the welding speed adjustment.

[0022] Preferably, the surface treatment includes removing the oxide layer and applying an anti-corrosion coating, and the weld finishing includes weld finishing grinding and weld crack inspection.

[0023] Preferably, the automated sorting system includes a sensor subsystem and a robotic arm control subsystem, wherein the sensor subsystem includes a vision sensor and a force sensor.

[0024] Preferably, the vision sensor performs imaging position recognition on the automotive threaded plate to form spatial coordinate data, the force sensor adjusts the grasping force on the spatial coordinate data to form grasping data, and the robotic arm control subsystem performs planning and adjustment processing based on the grasping data to form the final product. The planning and adjustment processing includes path planning and grasping action adjustment.

[0025] This invention provides an integrated stamping and welding process for manufacturing automotive threaded plates. It offers the following advantages:

[0026] This integrated stamping and welding process for manufacturing automotive threaded plates utilizes laser welding optimized interface prefabrication technology and a machine vision acquisition system, combined with 3D scanning and geometric feature model comparison algorithms, to achieve precise stamping and welding path planning for automotive threaded plates. By optimizing the welding path and employing real-time feedback adjustment technology, the stability and efficiency of the welding process are ensured, improving welding quality and production efficiency.

[0027] By employing real-time feedback adjustment technology, temperature monitoring, weld morphology monitoring, and welding speed are adjusted, enabling temperature control and weld quality monitoring during the welding process, resulting in stable weld plates. The automated sorting system optimizes post-processing and finished product unloading, improving production automation and product consistency. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the overall process of this invention.

[0029] Figure 2 This is a schematic diagram of the stamping process of the present invention;

[0030] Figure 3 This is a schematic diagram of the three-dimensional acquisition system of the present invention;

[0031] Figure 4 This is a flowchart of the welding path planning process of the present invention;

[0032] Figure 5 This is a flowchart of the laser welding feedback system of the present invention;

[0033] Figure 6 This is a flowchart of the post-processing and automatic feeding system of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Example 1

[0036] like Figure 1-6As shown, this embodiment of the invention provides an integrated stamping and welding process for manufacturing automotive threaded plates, including: S1. Stamping a metal sheet of predetermined specifications to form a main structure, wherein the stamping process employs laser welding prefabrication technology. Laser welding prefabrication technology involves precisely laser-cutting the metal sheet to form a welding interface. The welding interface is curved, including circular, elliptical, and bent shapes. The welding interface is located in the area to be welded to accommodate different component requirements.

[0037] S2. Three-dimensional data acquisition and processing are performed on the welding area of ​​the main structure to obtain three-dimensional contour data. This three-dimensional acquisition and processing utilizes a machine vision system. The machine vision system includes a camera and a laser scanner. The camera has a resolution range of 3000 to 8000 pixels, and the laser scanner has a measurement accuracy of 0.1 mm. The camera acquires surface images of the welding area, while the laser scanner performs a three-dimensional scan. The three-dimensional scan includes geometric shape scanning, contour scanning, and depth information scanning. The surface image acquisition and three-dimensional scanning work together to form three-dimensional contour data.

[0038] S3. The 3D contour data is processed to form welding path parameters. This processing includes a comparison method based on geometric feature models and a path optimization algorithm. The comparison method matches the 3D contour data with the geometric feature models to generate geometric deviation data. The geometric feature models include edge contours, hole positions, joint shapes, and joint angles. The path optimization algorithm minimizes the geometric deviation data to form the welding path parameters. The model formula for the path optimization algorithm is:

[0039] .

[0040] in, This indicates the welding path parameters, in units of... , This indicates the first position on the actual path traveled during the welding process. points, unit is , The first path point represents the target path point. Points, in meters. The weights of the path points are dimensionless. This represents the change in curvature at a path point, in units of... , Represents the total length of the path, in units of , where n represents the number of points on the path, which is dimensionless. This represents the regularization parameter, which is dimensionless.

[0041] S4. Laser welding is performed on the main structure using welding path parameters to form a stable weld plate. The welding planning process employs real-time feedback adjustment technology. This technology includes temperature monitoring, weld morphology monitoring, and welding speed adjustment. The welding planning process includes the following steps:

[0042] S41. Temperature monitoring of the main structure is performed using welding path parameters, and temperature feedback data is generated based on the temperature monitoring.

[0043] S42. Monitor the weld morphology of the main structure based on temperature feedback data, and generate weld quality data based on the weld morphology monitoring.

[0044] S43. The welding speed of the main structure is adjusted based on temperature feedback data and weld quality data, and a stable weld plate is formed based on the welding speed adjustment.

[0045] S5. Post-processing of the stabilized weld plate forms automotive threaded plates. The automotive threaded plates undergo automated unloading to form the final product. Post-processing includes surface treatment and weld finishing. Automated unloading utilizes an automated sorting system. Surface treatment includes oxide layer removal and anti-corrosion coating application. Weld finishing includes weld grinding and weld crack inspection. The automated sorting system includes a sensor subsystem and a robotic arm control subsystem. The sensor subsystem includes vision sensors and force sensors. The vision sensors image and identify the position of the automotive threaded plates to generate spatial coordinate data. The force sensors adjust the gripping force based on the spatial coordinate data to generate gripping data. The robotic arm control subsystem performs planning and adjustment based on the gripping data to form the final product. The planning and adjustment process includes path planning and gripping motion adjustment.

[0046] Laser welding prefabrication technology uses precise laser cutting to create circular, elliptical, or curved welding interfaces, reducing stress concentration in the weld joint area and minimizing welding defects caused by uneven joints. This technology provides a more stable mating surface, maintaining good joint quality under high loads and temperatures, and improving the strength and stability of the welded structure.

[0047] After acquiring 3D contour data, the geometric feature model is compared with the actual data to accurately capture deviations. The generation of geometric deviation data helps optimize the welding path, enabling better matching of the preset geometric features during welding and reducing welding errors. The path optimization algorithm ensures that the welding path matches the actual welding requirements by minimizing the deviation data, improving welding accuracy and stability.

[0048] The real-time feedback adjustment mechanism dynamically adjusts welding parameters through temperature monitoring, weld morphology monitoring, and welding speed adjustment. When the temperature data exceeds the set range, the welding speed is automatically adjusted to avoid overheating or undercooling, ensuring weld quality. Simultaneously, weld morphology monitoring provides real-time data on weld quality, and welding speed adjustment is optimized in real-time based on the feedback information, ensuring that weld quality is always at its best.

[0049] The automated unloading system accurately identifies and positions automotive threaded plates of different specifications through the collaboration of vision and force sensors. The vision sensors identify the spatial position of the product, while the force sensors sense the weight and gripping force of the item, adjusting the gripping force to ensure precise grasping and positioning. Based on this information, the robotic arm control subsystem plans the path and adjusts the gripping actions to ensure accurate unloading and sorting of each component.

[0050] In the post-processing stage, weld finishing and surface treatment improve the appearance quality and service life of automotive threaded plates. Weld finishing, through grinding and crack inspection, eliminates welding defects, ensuring a smooth, crack-free weld surface and improving weld strength. Surface treatment, by removing the oxide layer and applying an anti-corrosion coating, enhances the product's corrosion resistance and wear resistance, ensuring long-term stability in various harsh environments.

[0051] Example 2

[0052] This embodiment is based on a stamping and welding integrated process for manufacturing automotive threaded plates. By applying a path optimization algorithm and combining it with three-dimensional contour data, the laser welding path is precisely optimized to improve the accuracy and efficiency of the welding process. The specific implementation method is as follows:

[0053] 1. Acquisition and processing of 3D contour data

[0054] A machine vision acquisition system was used to acquire three-dimensional data of the automotive threaded plate to be welded.

[0055] The camera equipment has a resolution of 5000 pixels, and the laser scanner has a measurement accuracy of 0.1 mm. All data was acquired directly through the on-site laser scanner and camera acquisition equipment.

[0056] The acquired image data is 5000×3000 pixels, and the precision of the geometric shape and depth information provided by the laser scanner is 0.1 mm. The acquired three-dimensional contour data provides the basis for the accurate three-dimensional contour of the welding area.

[0057] 2. Comparison between geometric feature model and 3D contour data

[0058] Based on actual 3D data acquired from 3D scanners and cameras, CAD software is used to compare the data with geometric feature models.

[0059] The geometric feature model is provided by the on-site design engineer, and the model data accurately reflects the expected component design.

[0060] Edge profile: The target is a circle with a radius of 50mm, and the actual measurement result is 50.2mm. Therefore, the geometric deviation of the edge profile is 0.2mm.

[0061] Hole diameter: The target is 10mm, and the actual measurement result is 10.1mm. Therefore, the geometric deviation of the hole is 0.1mm.

[0062] Joint angle: The target is 45°, and the actual measurement result is 45.5°. Therefore, the deviation of the joint angle is 0.5°.

[0063] The above deviation values ​​are derived from the comparison between the actual welding area on site and the design model, ensuring the accuracy of the data.

[0064] 3. Application of path optimization algorithms and calculation of welding path parameters

[0065] The data for the 10 path points on the welding path comes from the automatic path planning function of the laser scanner and machine vision system, and the total path length is calculated from this data. .

[0066] The curvature change is obtained through geometric analysis of the welding path, specifically by calculating the curvature at each point on the path using mathematical modeling tools.

[0067] The deviation data for each path point is based on measurement results during the actual welding process. The deviation value for each path point is dynamically measured by on-site measuring equipment and calculated by comparing the actual welding path with the target path.

[0068] The curvature change and path point deviation data are shown in the table below:

[0069] Table 1: Curvature change and path point deviation data.

[0070]

[0071] Path point weights and regularization parameters:

[0072] To ensure even distribution, the weight data is set during the engineering design, with each path point having a weight of 1.

[0073] The regularization parameter is set to 0.5 based on the accuracy requirements and control strategies of the actual welding process.

[0074] The path optimization algorithm forms welding path parameters by minimizing geometric deviation data. The model formula for the path optimization algorithm is:

[0075] .

[0076] in, This indicates the welding path parameters, in units of... , This indicates the first position on the actual path traveled during the welding process. points, unit is , The first path point represents the target path point. Points, in meters. The weights of the path points are dimensionless. This represents the change in curvature at a path point, in units of... , Represents the total length of the path, in units of , where n represents the number of points on the path, which is dimensionless. This represents the regularization parameter, which is dimensionless.

[0077] Sum of squared deviations at path points:

[0078] The calculation is as follows:

[0079]

[0080]

[0081]

[0082] The path point deviation data obtained from measurements during the actual welding process is in mm. For the calculation in the formula, the unit of the path point deviation data needs to be converted to m, 1mm = 0.001m. Therefore, the sum of squares of path point deviations, 0.3366mm², is converted to 0.0000003366m².

[0083] Sum of curvature changes:

[0084] .

[0085]

[0086] Optimized path parameters:

[0087]

[0088] 4. Welding path parameter output

[0089] The objective function value for welding path optimization obtained through the optimization algorithm will be used for the actual planning of the welding path. The calculation result is as follows: To obtain the precise waypoints It is output as a control signal to guide the laser welding equipment to weld along the optimal path.

[0090] By optimizing the algorithm, the welding path was improved, ensuring high precision and efficiency in the welding process and reducing welding defects caused by path mismatch.

[0091] By collecting 3D contour data, comparing the geometric feature model with actual data, and applying a path optimization algorithm, the optimal welding path parameters were obtained. The optimization results show that the deviation and curvature variation of the welding path were controlled, ensuring accuracy and efficiency in the welding process. The path optimization algorithm reduced the occurrence of welding defects, improved product quality, and provided reliable data support and theoretical basis for practical welding path planning.

[0092] Example 3

[0093] This embodiment is based on a stamping and welding integrated process for manufacturing automotive threaded plates. It optimizes the laser welding process through real-time feedback adjustment technology, ensuring precise control of welding temperature, weld morphology, and welding speed, thereby improving the welding quality of automotive threaded plates. The specific implementation method is as follows:

[0094] 1. Application of welding path parameters

[0095] In this embodiment, the metal sheet used is a 2mm thick cold-rolled steel sheet with dimensions of 1000mm x 500mm. The laser welding path is optimized by a computer control system and customized according to the workpiece geometry and welding requirements. The total length of the welding path is 50 meters, with 5000 path points. The curvature change at each path point is 0.02m. -1 The weight of the path point is set to 0.8 to ensure the smoothness and accuracy of the welding path.

[0096] The planning and optimization of the welding path is a dynamic process. When the system detects a geometric deviation on the path, it corrects it by comparing it with the geometric feature model. The coordinates of the path points are fine-tuned based on real-time feedback to ensure that the laser welding process accurately adapts to the shape of the workpiece.

[0097] 2. Implementation of real-time feedback adjustment technology

[0098] Temperature monitoring: A K-type thermocouple temperature sensor with an accuracy of 0.1℃ is used during the welding process, and the temperature data of the welding area is recorded every 1 second.

[0099] In actual production, the target welding temperature is 2000℃, and the actual welding process maintains a temperature range between 1900℃ and 2100℃. When the temperature exceeds the set range, the system automatically adjusts the welding speed. The following are temperature data recorded by the temperature monitoring system:

[0100] Table 2: Temperature monitoring data.

[0101]

[0102] Data shows that the welding temperature is stable and always remains within a reasonable fluctuation range of the target temperature, with a change of less than 5%.

[0103] Weld morphology monitoring:

[0104] The welding process uses a high-definition camera with a resolution of 6,000 pixels and a laser scanner with an accuracy of 0.1 mm to monitor the weld morphology in real time.

[0105] The system records 60 frames per second and automatically calculates the weld width, depth, and surface quality. When the weld width exceeds the set range, the system automatically adjusts the welding parameters. The following are the actual monitored weld width data:

[0106] Table 3: Weld width monitoring data.

[0107]

[0108] The weld width was consistently maintained between 5.0 mm and 5.2 mm, and there were no cracks or excessive melting, meeting the quality requirements.

[0109] Welding speed adjustment:

[0110] The welding speed is dynamically adjusted based on real-time temperature and weld morphology data. During actual welding, the welding speed varies between 15 mm / min and 20 mm / min. The following are the recorded welding speed data:

[0111] Table 4: Welding speed data.

[0112]

[0113] Through feedback adjustment, the welding speed will automatically decrease when the welding temperature approaches or exceeds the upper limit of 2100℃. When the temperature returns to normal, the welding speed will gradually recover.

[0114] 3. Welding process control

[0115] Throughout the welding process, temperature, weld morphology, and welding speed are controlled in a closed-loop manner using real-time feedback data to ensure precise adjustments at every stage. The specific control method is as follows:

[0116] Temperature control: The temperature of the welding area is recorded by a sensor every second and uploaded to the central control system. The system adjusts the welding speed according to the set temperature range to ensure that the temperature fluctuation does not exceed ±50℃.

[0117] Weld morphology control: Weld morphology data is uploaded to the system every second. Image analysis is used to determine whether welding parameters need to be adjusted to ensure that the weld width is kept within the range of 5.0mm ± 0.5mm.

[0118] Welding speed adjustment: The welding speed will automatically decrease when the temperature exceeds the limit, and will automatically increase again after the temperature returns to normal, ensuring a balance between welding quality and production efficiency.

[0119] 4. Quality inspection after welding is completed

[0120] After welding is completed, the product will enter the quality inspection stage. The specific inspection methods are as follows:

[0121] Ultrasonic testing: Non-destructive testing is performed using ultrasonic flaw detectors with a probe frequency of 5MHz and a detection depth of 25mm to detect defects such as porosity and cracks inside the weld. Ultrasonic flaw detectors ensure that the internal quality of the weld meets requirements.

[0122] X-ray imaging: For critical welds, X-rays are used for further inspection with an imaging resolution of 0.2 mm and an exposure time of 2 seconds to ensure that the welds are free of defects such as porosity and cracks.

[0123] 5. Production Efficiency and Optimization

[0124] In addition to quality control, improving production efficiency is also crucial in the welding process. In this embodiment, the automated control system optimizes production line operation through real-time data feedback. Automatic adjustment of welding speed, dynamic temperature monitoring, and instantaneous adjustment of weld morphology all contribute to improving production efficiency while ensuring welding quality, thus avoiding human intervention.

[0125] By monitoring the time of each welding process, the system automatically optimizes the parameters of the next process based on feedback data, maximizing production efficiency.

[0126] By implementing real-time feedback adjustment technology, precise control of temperature, weld morphology, and welding speed during the welding process was achieved. The welding temperature was maintained within the range of 2000℃±50℃, the weld width remained stable at 5.0mm±0.5mm, and no cracks or over-melting were observed on the weld surface. All parameters were optimized through real-time monitoring and dynamic adjustment during the welding process, ensuring consistent welding quality and improved production efficiency. This technical solution improves the stability of the welding process, is suitable for the automotive manufacturing industry, and has high application value and promising prospects for promotion.

[0127] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A stamping and welding integrated process for manufacturing automotive threaded plates, characterized in that, include: S1. The metal sheet of a predetermined specification is stamped to form the main structure, wherein the stamping process adopts laser welding optimized interface prefabrication technology; S2. Perform three-dimensional acquisition and processing on the welding area of ​​the main structure to obtain three-dimensional contour data. The three-dimensional acquisition and processing adopts a machine vision acquisition system. S3. The three-dimensional contour data is processed to form welding path parameters. The processing includes a comparison method based on geometric feature models and a path optimization algorithm. S4. The main structure is laser-welded using the welding path parameters to form a stable weld plate based on the laser welding process. The welding planning process adopts real-time feedback adjustment technology. S5. The stable weld plate is post-processed to form the automotive threaded plate, and the automotive threaded plate is automatically unloaded to form the final product. The post-processing includes surface treatment and weld trimming, and the automatic unloading process adopts an automatic sorting system.

2. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The laser welding optimized interface prefabrication technology uses laser precision cutting to form a welding interface on the metal sheet. The welding interface is curved, including circular, elliptical, and curved shapes, and is located in the area to be welded.

3. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The machine vision acquisition system includes a camera device and a laser scanner. The resolution of the camera device ranges from 3,000 pixels to 8,000 pixels, and the measurement accuracy of the laser scanner is 0.1 mm.

4. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 3, characterized in that: The camera device acquires surface images of the area to be welded, and the laser scanner performs three-dimensional scanning of the area to be welded. The three-dimensional scanning includes geometric shape scanning, contour scanning, and depth information scanning. The surface image acquisition and the three-dimensional scanning work together to form the three-dimensional contour data.

5. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The comparison method matches the three-dimensional contour data with the geometric feature model to form geometric deviation data. The geometric feature model includes edge contours, hole positions, joint shapes, and joint angles.

6. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 5, characterized in that: The path optimization algorithm forms the welding path parameters by minimizing the geometric deviation data. The model formula of the path optimization algorithm is: ， in, This indicates the welding path parameters. This indicates the first position on the actual path traveled during the welding process. One point, The first path point represents the target path point. One point, Represents the weight of the path points. This represents the change in curvature at a path point. The path length is represented by n, and the number of points on the path is represented by n. This represents the regularization parameter.

7. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The real-time feedback adjustment technology includes temperature monitoring, weld morphology monitoring, and welding speed adjustment. The welding planning process includes the following steps: S41. The temperature of the main structure is monitored using the welding path parameters, and temperature feedback data is generated based on the temperature monitoring. S42. Monitor the weld morphology of the main structure based on the temperature feedback data, and generate weld quality data based on the weld morphology monitoring; S43. Based on the temperature feedback data and the weld quality data, the welding speed of the main structure is adjusted, and the stable weld plate is formed based on the welding speed adjustment.

8. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The surface treatment includes removing the oxide layer and applying an anti-corrosion coating, and the weld finishing includes weld finishing grinding and weld crack inspection.

9. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 1, characterized in that: The automated sorting system includes a sensor subsystem and a robotic arm control subsystem. The sensor subsystem includes a vision sensor and a force sensor.

10. The stamping and welding integrated process for manufacturing automotive threaded plates according to claim 9, characterized in that: The vision sensor images and identifies the position of the car threaded plate to form spatial coordinate data. The force sensor adjusts the gripping force based on the spatial coordinate data to form gripping data. The robotic arm control subsystem performs planning and adjustment processing based on the gripping data to form the final product. The planning and adjustment processing includes path planning and gripping action adjustment.

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