Automatic welding loading and unloading method and equipment based on flexible control

Abstract

The present invention relates to the field of welding control technology, and in particular to an automatic welding loading and unloading method and equipment based on flexible control. The method screens out weld edge combinations based on the uniformity of the distance between adjacent edge lines, further determines the welding super-rotation angle by analyzing the local trends of the edge lines in the weld edge combination, uses the welding super-rotation angle to characterize the structural stability of the weld, and finally obtains the welding stability in combination with the welding length. Based on the initial weight of the welding stability adjustment algorithm, the optimal welding path can be found based on the final path pheromone weight, and then the welding loading and unloading control is performed based on the parameter information of the optimal welding path. The present invention improves the optimization efficiency and the accuracy of the results by optimizing the pheromone weight of the ant colony algorithm in the process of welding path optimization, and facilitates the effective control of automatic welding loading and unloading.

Description

Technical Field

[0001] The present invention relates to the technical field of welding control, and in particular to an automatic welding loading and unloading method and equipment based on flexible control. Background Art

[0002] Flexible control refers to the ability of an automatic welding system to flexibly adjust the control strategies for the welding and loading and unloading processes based on variations in workpiece specifications, shapes, and sizes. This flexibility reduces equipment switching and setup time, improving the system's ability to adapt to diverse production needs. Through flexible control, the equipment can automatically adjust welding paths and parameters to accommodate workpieces of varying types and sizes, thereby achieving efficient and stable automated production. In the automatic welding process, loading and unloading involves the automatic introduction of the workpieces into the welding equipment and their removal after welding. This process is typically performed by a robotic arm, conveyor belt, or other automated equipment. The goal of automated loading and unloading is to improve production efficiency, reduce manual labor, and enhance welding accuracy and consistency. Loading and unloading control must be synchronized with the welding process to ensure a continuous and smooth production flow.

[0003] Among them, during the automatic welding process, the existing technology for identifying and positioning the workpiece is mainly carried out through two-dimensional image recognition, and the image processing algorithm is used to identify several parameters of the workpiece, thereby guiding the robotic arm to perform precise loading and unloading. In order to achieve the purpose of accurately controlling loading and unloading and smoothly switching the workpiece to be welded, it is selected to add pre-preparation to the welding process, reasonably arrange the preparation time of the next workpiece, reduce waiting time, achieve seamless connection, and improve welding efficiency. Among them, when identifying welding parameters, there are multiple welding paths on the surface of the material. The existing technology will use the ant colony algorithm to optimize the welding path, and then determine the optimal welding path for automatic welding and loading and unloading control. During the optimization process, each welding path can be set with an initial weight based on the ant colony algorithm. However, there is noise information such as deviation and rust in the weld information, which leads to a lot of time wasted in these noise information during the optimization process, affecting the efficiency of the optimization algorithm, and also affecting the accuracy of the optimal welding path finally obtained, thereby failing to perform accurate loading and unloading control. Summary of the Invention

[0004] In order to solve the technical problem that the prior art uses ant colony algorithm to optimize the weld path, which is affected by noise, resulting in low algorithm efficiency and accuracy, and inability to effectively control loading and unloading, the purpose of the present invention is to provide an automatic welding loading and unloading method and equipment based on flexible control. The technical solutions adopted are as follows:

[0005] The present invention proposes an automatic welding loading and unloading method based on flexible control, the method comprising:

[0006] Acquire a surface image of a workpiece to be welded, extract edge lines from the surface image, and screen out weld edge combinations based on the uniformity of distances between adjacent edge lines;

[0007] According to the local trend of the edge line in the weld edge combination, the set of in-seam angles of each weld edge combination is obtained; the welding super-rotation angle is screened out from the in-seam angles; and the welding stability of each weld edge combination is obtained according to the distribution of the welding super-rotation angles in the weld edge combination and the welding length of the weld edge combination;

[0008] Performing welding path planning on the surface image according to an ant colony algorithm, adjusting the initial algorithm weight for each weld edge combination according to welding stability in the ant colony algorithm to obtain a final path pheromone weight, and planning an optimal welding path based on the final path pheromone weight;

[0009] Welding loading and unloading is controlled according to the path length, path direction and welding time of the optimal welding path.

[0010] Furthermore, screening out the weld edge combination according to the distance between adjacent edge lines includes:

[0011] The edge merging property of two adjacent edges is obtained according to the uniformity of the distance between the two adjacent edge lines at different local positions; the two edge lines whose edge merging property is greater than a preset merging property threshold are regarded as the weld edge combination.

[0012] Furthermore, the method for obtaining the edge merging property includes:

[0013] Any edge line between two adjacent edge lines is used as the target edge line, and the other edge line is used as the comparison edge line. Multiple sampling points are uniformly sampled on the target edge line, and the distance between each sampling point and the comparison edge line is used as the comparison distance of the sampling point; the comparison distance difference between adjacent sampling points is negatively correlated to obtain local distance uniformity, and the average value of all local distance uniformities is used as the edge merging property.

[0014] Furthermore, the method for obtaining the set of angles within the seam includes:

[0015] The angle between the line between two adjacent sampling points on the target edge line and the horizontal direction is taken as the local angle, and the angle difference between adjacent local angles is calculated to obtain the intra-slit angle in the intra-slit angle set.

[0016] Furthermore, the welding super-rotation angle is an in-seam angle in the set of in-seam angles that is greater than a preset angle threshold.

[0017] Furthermore, the method for obtaining welding stability includes:

[0018] The proportion of the welding super-rotation angle in the seam angle set is negatively correlated and normalized, and then multiplied by the welding length to obtain the welding stability of the weld edge combination.

[0019] Furthermore, the method for obtaining the final path pheromone weight includes:

[0020] The welding stability is normalized and then added to the positive integer 1 to obtain an adjustment coefficient, and the adjustment coefficient is multiplied by the initial weight of the algorithm to obtain the final path pheromone weight.

[0021] Furthermore, the method for obtaining the welding time of the optimal welding path includes:

[0022] In a historical database, the welding length and welding time in each historical welding process are fitted to obtain a welding length-time model; the path length of the optimal welding path is input into the welding length-time model to obtain the welding time of the optimal welding path.

[0023] Furthermore, the edge line is obtained by processing the surface image using a Canny edge detection algorithm.

[0024] The present invention also proposes an automatic welding loading and unloading device based on flexible control, the device comprising:

[0025] A welding image recognition module is used to obtain a surface image of a workpiece to be welded, extract edge lines in the surface image, and screen out weld edge combinations based on the distance between adjacent edge lines;

[0026] A weld information extraction module is used to obtain a set of seam angles for each weld edge combination based on the local trends of the edge lines in the weld edge combination; screen out welding super-rotation angles from the seam angles; and obtain the welding stability of each weld edge combination based on the distribution of the welding super-rotation angles in the weld edge combination and the welding length of the weld edge combination;

[0027] An optimal welding path planning module is used to plan the welding path based on the surface image according to the ant colony algorithm. In the ant colony algorithm, for each weld edge combination, the initial algorithm weight is adjusted according to the welding stability to obtain the final path pheromone weight, and the optimal welding path is planned based on the final path pheromone weight;

[0028] The welding loading and unloading control module is used to control the welding loading and unloading according to the path length of the optimal welding path and the welding time.

[0029] The present invention has the following beneficial effects:

[0030] The present invention takes into account that a good weld should be a weld with obvious structural stability and regularity. Therefore, the weld edge combination is first screened out based on the uniformity of the distance between adjacent edge lines, that is, the weld edge combination is a combination of two edge lines with a relatively regular distance distribution, which is more likely to be a relatively excellent weld. Further, the welding super-rotation angle is determined by analyzing the local trend of the edge lines in the weld edge combination, and the welding super-rotation angle is used to characterize the structural stability of the weld, and finally the welding stability is obtained in combination with the welding length. Welding stability can characterize the welding stability of the weld during the welding process, so the initial weight of the algorithm can be adjusted based on the welding stability, and the optimal welding path can be found based on the final path pheromone weight, and then the welding loading and unloading control is performed based on the parameter information of the optimal welding path, which is convenient for effective control of automatic welding loading and unloading. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 This is a flow chart of an automatic welding loading and unloading method based on flexible control provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0033] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a flexible-controlled automatic welding loading and unloading method and apparatus proposed by the present invention. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0035] The present invention aims to optimize the welding path optimization process using the ant colony algorithm during the automatic welding process. The ant colony algorithm is a bionics-based optimization algorithm that optimizes the welding path by simulating the process of ants searching for food. Its basic principle is:

[0036] (1) Pheromone mechanism: Ants release pheromones along the path, and the concentration of pheromones along the path reflects the quality of the path. During welding path planning, the initial path is randomly generated by virtual "ants" based on the weld information in the image.

[0037] (2) Path selection: When ants choose a path at each step, they tend to choose a path with a higher pheromone concentration and conduct random exploration based on a certain probability to avoid falling into a local optimal solution.

[0038] (3) Pheromone update: Each time an ant completes a path, it updates its pheromone based on the quality of the path. The shortest path retains more pheromone, while the pheromone of the poorer path gradually evaporates. Through multiple rounds of iteration, the algorithm gradually finds the optimal welding path.

[0039] The specific algorithm of the ant colony algorithm for optimizing the welding path is a technical means well known to those skilled in the art and will not be described in detail here. The embodiment of the present invention mainly focuses on updating the initial weights in the algorithm.

[0040] The scenario in which the embodiment of the present invention is implemented is an automatic welding scenario. When performing automatic welding, a pre-prepared workbench is required to prevent the workpiece to be welded, and a fixing device is used to ensure the stability of the workpiece during image capture and posture adjustment. A posture adjustment robotic arm and a depth camera are provided to capture and obtain the workpiece image.

[0041] (1) The workbench parameters include: aluminum material to ensure high strength and durability; the specific size can be set based on the size of the workpiece to be welded; the maximum load weight is set to 500 kg.

[0042] (2) The parameters of the mechanical part for posture adjustment include: six degrees of freedom, which can flexibly adjust the position and angle of the workpiece; repeated positioning accuracy of ±0.05 mm; maximum load of 50 kg; and a range of motion radius of 1.5 meters.

[0043] (3) The parameters of the depth camera include: resolution of 1280×720; field of view of 70 degrees; depth range of 0.3 meters to 2 meters; frame rate of 30 frames.

[0044] The following describes in detail a specific solution of an automatic welding loading and unloading method and equipment based on flexible control provided by the present invention in conjunction with the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart of an automatic welding loading and unloading method based on flexible control provided by one embodiment of the present invention, the method comprising:

[0046] Step S1: Acquire a surface image of a workpiece to be welded, extract edge lines in the surface image, and select weld edge combinations based on the uniformity of distances between adjacent edge lines.

[0047] As described in the preceding scenario, the present invention uses a depth camera to capture a surface image of a welded workpiece. The pixel values ​​in the surface image represent the distance of the corresponding workpiece location from the camera. Because welds have distinct depth information compared to other surface locations, the pixel values ​​in the surface image also differ from those in other surface areas. Therefore, edge lines in the surface image can be extracted based on the pixel values ​​for further analysis.

[0048] In the embodiment of the present invention, after obtaining the surface image, it is subjected to image preprocessing to improve the image quality. The image preprocessing operation includes grayscale conversion, mean filtering and other operations, which are technical means well known to those skilled in the art and will not be described in detail here.

[0049] In the embodiment of the present invention, a canny edge detection method is used to identify edge lines in a surface image. Canny edge detection is a technical means well known to those skilled in the art and will not be described in detail here.

[0050] Because a weld has a certain width, it can be considered to be composed of two edges, and the distance between these two edges is relatively uniform, forming a weld with a certain width. Therefore, weld edge combinations can be screened based on the uniformity of the distance between adjacent edges. In the subsequent analysis process, only these weld edge combinations are analyzed, avoiding interference from information such as the pattern on the workpiece surface.

[0051] Preferably, in one embodiment of the present invention, screening out weld edge combinations based on the distance between adjacent edge lines includes:

[0052] The edge merging properties of two adjacent edges are determined based on the uniformity of the distances between them at different local locations. Two edge lines with an edge merging property greater than a preset merging property threshold are considered a weld edge combination. In this embodiment of the present invention, the edge merging property is normalized and the merging property threshold is set to 0.9.

[0053] Furthermore, the edge merging property acquisition method includes:

[0054] Any edge line between two adjacent edge lines is used as the target edge line, and the other edge line is used as the comparison edge line. Multiple sampling points are uniformly sampled on the target edge line, and the distance between each sampling point and the comparison edge line is used as the comparison distance of the sampling point. It should be noted that the distance between the sampling point and the comparison edge line is the minimum distance between the sampling point and each edge point on the comparison edge line. If these two edge lines are the edge lines of a weld, the comparison distance should show a uniform distribution feature, and the comparison distance between different sampling points will not vary significantly. Therefore, the comparison distance difference between adjacent sampling points is further negatively correlated to obtain the local distance uniformity, that is, the greater the difference in comparison distance between a sampling point and its adjacent sampling points, the greater the abnormality in the comparison distance distribution of the local position, and the smaller the local distance uniformity. The average value of all local distance uniformities is used as the edge merging property.

[0055] As an example, edge mergeability is formulated as:

[0056]

[0057] in, is the edge merging property between two adjacent edge lines in the kth group, is the number of sampling points, is the comparison distance of the nth sampling point, is the comparison distance of the n+1th sampling point.

[0058] In the edge merging formula, the contrast distance difference is negatively correlated in the form of an inverse. At the same time, in order to avoid the denominator being 0, a positive integer 1 is added to the denominator. That is, the closer the final edge merging is to 1, the more the two edge lines are a weld edge combination.

[0059] In the embodiment of the present invention, the sampling points are 100 points evenly arranged on the target edge line.

[0060] Step S2: According to the local trend of the edge line in the weld edge combination, the set of in-seam angles of each weld edge combination is obtained; the welding super-rotation angle is screened out from the in-seam angles; and the welding stability of each weld edge combination is obtained according to the distribution of the welding super-rotation angle in the weld edge combination and the welding length of the weld edge combination.

[0061] The workpiece to be welded has a relatively complete geometric structure, and the shape and structure of the area to be welded are relatively regular. For example, straight welds are commonly used for plate splicing, bracket structure connection, etc., and are common in steel structures and frame structures; curved welds are commonly used for pipes, body structures, flange connections, etc., and require welding around a circumference or complex curved surface. During the automatic welding process, regardless of the structural shape of the workpiece area to be welded, the optimized welding method must ensure the smoothness of the entire automatic welding process. The smoother the weld, the higher the stability of the entire welding process and the higher the welding efficiency. Conversely, the lower the smoothness, the more complex the welding process, the higher the requirements for the robot arm during the welding process, and the greater the risk of welding errors. Therefore, the embodiment of the present invention further obtains the set of seam angles for each weld edge combination based on the local trend of the edge line in the weld edge combination, and then screens out the welding super-angle. That is, at the welding super-angle position, the automatic welding robot arm will perform a more difficult welding posture transition. The more welding super-angles in the weld edge combination, the worse the smoothness of the path. Further combined with the welding length of the weld edge combination, the longer the welding length, the more margin the robotic arm has for adjustment control, and the stronger the welding stability, thereby obtaining the welding stability of each weld edge combination.

[0062] Preferably, in an embodiment of the present invention, the method for obtaining a set of angles within a seam includes:

[0063] The angle between the line connecting two adjacent sampling points on the target edge line and the horizontal direction is used as the local angle. The angular difference between adjacent local angles is calculated to obtain the intra-seam angle in the intra-seam angle set. In other words, the greater the angular difference between the local angles, the greater the amplitude of welding control performed by the robotic arm at that location. It should be noted that because there are 100 sampling points in this embodiment of the present invention, 99 local angles are generated, with 98 angular differences, meaning that the number of elements in the intra-seam angle set is 98.

[0064] In the embodiment of the present invention, the welding super-rotation angle is an angle within the seam that is greater than a preset angle threshold in the set of seam angles. The angle threshold is set to 90 degrees.

[0065] Preferably, in an embodiment of the present invention, the method for obtaining welding stability includes:

[0066] The proportion of the welding super-rotation angle in the seam angle set is negatively correlated and normalized, and then multiplied by the welding length to obtain the welding stability of the weld edge combination.

[0067] It should be noted that in this embodiment of the present invention, the proportion of non-welding super-rotation angles in the set of seam angles can be directly selected as a negative correlation mapping of the proportion of welding super-rotation angles in the set of seam angles, and the normalized result can be used. That is, the smaller the proportion of welding super-rotation angles, the larger the proportion of non-welding super-rotation angles, indicating smoother control of the robot arm during automated welding and greater welding stability.

[0068] Step S3: Perform welding path planning on the surface image according to the ant colony algorithm. In the ant colony algorithm, for each weld edge combination, adjust the initial weight of the algorithm according to the welding stability to obtain the final path pheromone weight, and plan the optimal welding path based on the final path pheromone weight.

[0069] After the above steps, each weld edge combination corresponds to a welding stability, which can then be used to adjust the initial weights in the ant colony algorithm. Compared with traditional ant colony optimization algorithms, using the final path pheromone weights for optimization can improve the convergence speed and accuracy of the optimal welding path based on the basic characteristics of the workpiece to be welded.

[0070] Preferably, in one embodiment of the present invention, the method for obtaining the final path pheromone weight includes:

[0071] The welding stability is normalized and added to the positive integer 1 to obtain the adjustment coefficient, which is then multiplied by the initial weight of the algorithm to obtain the final path pheromone weight.

[0072] It should be noted that the normalization in the embodiment of the present invention adopts a linear normalization method, and may also adopt a method such as a sigmoid function mapping, which will not be elaborated or limited here.

[0073] Step S4: Preliminary preparations for welding loading and unloading are performed according to the path length, path direction, and welding time of the optimal welding path.

[0074] After obtaining the optimal welding path, the welding length and the main direction corresponding to the path can be intuitively obtained. In the subsequent automatic welding process, the main direction can be used as a reference value for posture adjustment, greatly improving the steering effectiveness during the welding process.

[0075] In the loading and unloading control during the automatic welding process, welding time is also a relatively important welding parameter. By determining the path length, path direction and welding time of the optimal welding path, the preliminary preparation work of automatic welding is completed. During the automatic welding process, automatic welding can be directly performed using these welding parameters to control the loading and unloading parameters and welding direction during the welding process.

[0076] Preferably, the method for obtaining the welding time of the optimal welding path in the embodiment of the present invention includes:

[0077] In the historical database, the welding length and welding time of each historical welding process are fitted to obtain a welding length-time model. The path length of the optimal welding path is input into the welding length-time model to obtain the welding time of the optimal welding path. In this embodiment of the present invention, the fitting method uses the least squares method to perform linear fitting to obtain the welding length-time model.

[0078] In summary, the present invention first screens out the weld edge combination based on the uniformity of the distance between adjacent edge lines, further determines the welding super-rotation angle by analyzing the local trend of the edge lines in the weld edge combination, uses the welding super-rotation angle to characterize the structural stability of the weld, and finally obtains the welding stability in combination with the welding length. Based on the initial weight of the welding stability adjustment algorithm, the optimal welding path can be found based on the final path pheromone weight, and then the welding loading and unloading control is performed based on the parameter information of the optimal welding path. The present invention improves the optimization efficiency and the accuracy of the results by optimizing the pheromone weight of the ant colony algorithm in the process of welding path optimization, and facilitates the effective control of automatic welding loading and unloading.

[0079] Based on the same inventive concept, the present invention also proposes an automatic welding loading and unloading device based on flexible control, the device comprising:

[0080] The welding image recognition module is used to obtain the surface image of the workpiece to be welded, extract the edge lines in the surface image, and screen the weld edge combination based on the distance between adjacent edge lines;

[0081] The weld information extraction module is used to obtain the set of seam angles within each weld edge combination based on the local trend of the edge line in the weld edge combination; screen out the welding super-rotation angles from the seam angles; and obtain the welding stability of each weld edge combination based on the distribution of the welding super-rotation angles within the weld edge combination and the welding length of the weld edge combination;

[0082] The optimal welding path planning module is used to plan the welding path based on the surface image according to the ant colony algorithm. In the ant colony algorithm, for each weld edge combination, the initial algorithm weight is adjusted according to the welding stability to obtain the final path pheromone weight. The optimal welding path is planned based on the final path pheromone weight;

[0083] The welding loading and unloading control module is used to control the welding loading and unloading according to the path length of the optimal welding path and the welding time.

[0084] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. An automatic welding loading and unloading method based on flexible control, characterized in that: The method comprises: Acquire a surface image of a workpiece to be welded, extract edge lines from the surface image, and screen out weld edge combinations based on the uniformity of distances between adjacent edge lines; According to the local trend of the edge line in the weld edge combination, the set of in-seam angles of each weld edge combination is obtained; the welding super-rotation angle is screened out from the in-seam angles; and the welding stability of each weld edge combination is obtained according to the distribution of the welding super-rotation angles in the weld edge combination and the welding length of the weld edge combination; Performing welding path planning on the surface image according to an ant colony algorithm, adjusting the initial algorithm weight for each weld edge combination according to welding stability in the ant colony algorithm to obtain a final path pheromone weight, and planning an optimal welding path based on the final path pheromone weight; Welding loading and unloading is controlled according to the path length, path direction and welding time of the optimal welding path.

2. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The method of screening out the weld edge combination according to the distance between adjacent edge lines includes: The edge merging property of two adjacent edges is obtained according to the uniformity of the distance between the two adjacent edge lines at different local positions; the two edge lines whose edge merging property is greater than a preset merging property threshold are regarded as the weld edge combination.

3. The method for automatic welding loading and unloading based on flexible control according to claim 2, characterized in that: The method for obtaining the edge merging property includes: Any edge line between two adjacent edge lines is used as the target edge line, and the other edge line is used as the comparison edge line. Multiple sampling points are uniformly sampled on the target edge line, and the distance between each sampling point and the comparison edge line is used as the comparison distance of the sampling point; the comparison distance difference between adjacent sampling points is negatively correlated to obtain local distance uniformity, and the average value of all local distance uniformities is used as the edge merging property.

4. The method for automatic welding loading and unloading based on flexible control according to claim 3 is characterized in that: The method for obtaining the set of angles within the seam includes: The angle between the line between two adjacent sampling points on the target edge line and the horizontal direction is taken as the local angle, and the angle difference between adjacent local angles is calculated to obtain the intra-slit angle in the intra-slit angle set.

5. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The welding super-rotation angle is an in-seam angle in the in-seam angle set that is greater than a preset angle threshold.

6. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The method for obtaining welding stability includes: The proportion of the welding super-rotation angle in the seam angle set is negatively correlated and normalized, and then multiplied by the welding length to obtain the welding stability of the weld edge combination.

7. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The method for obtaining the final path pheromone weight includes: The welding stability is normalized and then added to the positive integer 1 to obtain an adjustment coefficient, and the adjustment coefficient is multiplied by the initial weight of the algorithm to obtain the final path pheromone weight.

8. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The method for obtaining the welding time of the optimal welding path includes: In a historical database, the welding length and welding time in each historical welding process are fitted to obtain a welding length-time model; the path length of the optimal welding path is input into the welding length-time model to obtain the welding time of the optimal welding path.

9. The method for automatic welding loading and unloading based on flexible control according to claim 1, characterized in that: The edge line is obtained by processing the surface image using a Canny edge detection algorithm.

10. An automatic welding loading and unloading equipment based on flexible control, characterized in that: The device comprises: A welding image recognition module is used to obtain a surface image of a workpiece to be welded, extract edge lines in the surface image, and screen out weld edge combinations based on the distance between adjacent edge lines; A weld information extraction module is used to obtain a set of seam angles for each weld edge combination based on the local trends of the edge lines in the weld edge combination; screen out welding super-rotation angles from the seam angles; and obtain the welding stability of each weld edge combination based on the distribution of the welding super-rotation angles in the weld edge combination and the welding length of the weld edge combination; An optimal welding path planning module is used to plan the welding path based on the surface image according to the ant colony algorithm. In the ant colony algorithm, for each weld edge combination, the initial algorithm weight is adjusted according to the welding stability to obtain the final path pheromone weight, and the optimal welding path is planned based on the final path pheromone weight; The welding loading and unloading control module is used to control the welding loading and unloading according to the path length of the optimal welding path and the welding time.

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