An automatic flexible spot welding system for identifying 3D features

Abstract

The present invention discloses an automatic flexible spot welding system for identifying 3D features, which relates to the technical field of welding. In order to solve the problems in the prior art that it takes a certain amount of time for tooling change during product welding, and on the basis of tooling change, it is also necessary to program and teach the robot welding according to the sizes of different welded products, which affects the production efficiency of product welding. A four-axis positioning mechanism is installed above the main tooling frame, an X-direction translation cross beam is arranged inside the main tooling frame, and a positioning component is arranged above the X-direction translation cross beam; The system flow of the automatic flexible spot welding system for identifying 3D features includes the following steps: Step 1: Import product data into the system and analyze it; Step 2: Judge the positioning point information of the product according to the positioning rules of the tooling for the product, and generate the layout program of the tooling.

Description

Technical Field

[0001] The present invention relates to the technical field of welding, and particularly to an automatic flexible spot welding system for identifying 3D features. Background Art

[0002] Welding, also known as fusion welding, is a metal joining process that uses heat, high temperature, or high pressure. With the continuous development of cities, the demand for various equipment products is increasing. Many equipment products need to be welded during the production process. With the continuous development of intelligent factories, the processing mode of small batches and multiple batches of products is increasing. For frame welding, traditional proprietary tooling is still used for welding. Different positioning tooling fixtures need to be used according to different product sizes, and there are two situations: one is that there are many types of tooling, which occupy a large area and can quickly switch tooling fixtures; the other is that flexible tooling is used, and the positioning of the tooling fixture needs to be adjusted according to different products.

[0003] However, it takes a certain amount of time to switch the tooling during product welding. On the basis of tooling switching, it is also necessary to program and teach the robot welding according to the sizes of different welded products, which affects the production efficiency of product welding. Therefore, there is an urgent need in the market to develop an automatic flexible spot welding system for identifying 3D features to help people solve existing problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an automatic flexible spot welding system for identifying 3D features to solve the problems mentioned in the above background art, that is, it takes a certain amount of time to switch the tooling during product welding, and on the basis of tooling switching, it is also necessary to program and teach the robot welding according to the sizes of different welded products, which affects the production efficiency of product welding.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An automatic flexible spot welding system for identifying 3D features, including a main tooling frame, a four-axis positioning mechanism is installed above the main tooling frame, an X-direction translation cross beam is arranged inside the main tooling frame, and a positioning component is arranged above the X-direction translation cross beam;

[0006] The system process of the automatic flexible spot welding system for identifying 3D features includes the following steps:

[0007] Step 1: Import product data into the system and analyze it;

[0008] Step 2: Judge the positioning point information of the product according to the positioning rule of the tooling for the product, generate the layout program of the tooling, and drive different driving components in the main tooling frame through the action of the four-axis positioning mechanism to adjust the positions of the X-direction translation cross beam and the positioning component, and then fix the product to be welded in the main tooling frame;

[0009] Step 3: Based on the matching of the product image, extract the product welding features, identify the points corresponding to the welds of the product, and select the welding posture;

[0010] Step 4: The system then verifies the interference of the generated robot trajectory according to Steps 2 and 3. If there is no interference, generate the robot welding path trajectory; otherwise, return to Steps 2 and 3 for recalculation and optimization;

[0011] Step 5: Generate welding parameters by retrieving the corresponding information from the welding parameter table or the data in the welding process library;

[0012] Step 6: The robot executes the welding program.

[0013] Preferably, the process of extracting the product welding features in Step 3 of the system process includes the following steps:

[0014] Step 1: Import the 3D model, the STP file of the entire welded product;

[0015] Step 2: The internal algorithm program identifies the STP file;

[0016] Step 3: Split the product to obtain individual parts;

[0017] Step 4: Identify the volume, surface area, number of faces, holes, chamfers, length, width, height, and wall thickness of each individual part;

[0018] Step 5: With the help of the welding knowledge base, perform feature screening and classification on the individual parts and complete the matching detection of the product to be welded;

[0019] Step 6: Find the welding target surface;

[0020] Step 7: Identify the weld seam by combining the found welding target surface with the normal vector contact determination;

[0021] Step 8: Output the point position information of the weld seam.

[0022] Preferably, a driving component for the X-direction translation cross beam is provided inside the main fixture frame.

[0023] Preferably, a driving component for the positioning component is provided inside the X-direction translation cross beam.

[0024] Preferably, a fixture positioning monitoring module is provided inside the four-axis positioning mechanism.

[0025] Preferably, a sliding vertical plate is provided above the main fixture frame, and a translation cross plate is installed on one side of the sliding vertical plate, and the sliding vertical plate and the translation cross plate are fixedly connected by bolts.

[0026] Preferably, a collection camera is installed below the translation cross plate, and the translation cross plate is fixedly connected to the collection camera by bolts.

[0027] Preferably, in step five of the process of extracting the welding characteristics of the product, the product matching detection process includes the following steps:

[0028] Step 1: Through the function of the collection camera, image collection is performed on the product to be welded.

[0029] Step 2: Through mathematical morphology, a non-linear filtering method is used to process the collected image, suppressing the noise contained in the original collected image caused by machine vibration and other factors, and increasing the clarity of the original image.

[0030] Step 3: Then, masking processing is performed to block the parts of the collected image that are not the product to be welded, display the edge line features of the product to be welded, and extract the image of the product to be welded part.

[0031] Step 4: Then, binary processing is performed on the image of the product to be welded, and it is compared and matched with the image of the imported welding product file to observe whether the image of the product to be welded is the same as the imported product image, and defect detection is performed on the image of the product to be welded.

[0032] Step 5: Then, the matching detection result is output.

[0033] Preferably, the collection camera uses a area array CCD camera.

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] 1. The invention imports and identifies the features of 3D files, and relies on the internal algorithm of the system. Through the confirmation of product features, weld positions, positioning points, interference verification, and feasibility analysis of robot trajectories, it automatically plans the welding path points of the robot, and coordinates with the program programming of the servo stitch welding tooling to complete the welding system. The internal algorithm can calculate the positioning point information, welding points, welding postures, and robot trajectory interference verification of the product based on the imported product data, weld the overlapping parts of the product parts, and can identify the relevant electrophoresis holes at the welding positions and avoid welding them. During the welding process of the product, according to the combination of different product part lengths and specifications, the system can identify the welds at the overlapping parts, identify relevant data such as electrophoresis holes, and perform welding program avoidance, ultimately realizing the welding function without teaching programming, improving the flexibility and practicality of welding, increasing the welding efficiency. At the same time, the introduction of the four-axis positioning mechanism can quickly realize the switching and adjustment of the positioning fixture of the tooling, better realizing the switching of welding different products, thus solving the problems of single traditional special tooling, insufficient flexibility, large space occupation, and low production efficiency, and being more suitable for the production of small-batch and multi-batch welding frame types.

[0036] 2. The invention is equipped with a collection camera that can collect images of the welded product. Then, the collected images are processed respectively and sequentially through mathematical morphology, masking, and binarization to extract the product part images, increasing the clarity of the product images. Then, the product images are compared and matched with the imported welded product images to observe whether the product images are the same as the imported product images, preventing the wrong parts in the product from being taken and resulting in welding errors. At the same time, defect detection is carried out on the product to prevent defective parts from being welded into the product, improving the product production quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is the product welding system flow chart of an automatic flexible spot stitch welding system for identifying 3D features of the present invention;

[0038] Figure 2 It is the extraction welding feature flow chart of an automatic flexible spot stitch welding system for identifying 3D features of the present invention;

[0039] Figure 3 It is the product matching detection flow chart of an automatic flexible spot stitch welding system for identifying 3D features of the present invention;

[0040] Figure 4 It is the top view of the welding tooling of the present invention;

[0041] Figure 5 It is the side view of the translation cross plate of the present invention.

[0042] In the figure: 1. Main fixture frame; 2. X-direction translation cross beam; 3. Positioning component; 4. Four-axis positioning mechanism; 5. Sliding vertical plate; 6. Translation cross plate; 7. Acquisition camera. Detailed implementation mode

[0043] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0044] Please refer to Figures 1-5 , an embodiment provided by the present invention: An automatic flexible spot welding system for identifying 3D features, including a main fixture frame 1. Above the main fixture frame 1, a four-axis positioning mechanism 4 is installed. Inside the main fixture frame 1, there are multiple X-direction translation cross beams 2, which increase the stability of the product to be welded. Above the X-direction translation cross beam 2, there is a positioning component 3. The positioning component 3 is set as a fixture, and the positioning component 3 is movably arranged on the X-direction translation cross beam 2. Inside the main fixture frame 1, there is a driving component for the X-direction translation cross beam 2, which increases the convenience of moving and adjusting the X-direction translation cross beam 2. Inside the X-direction translation cross beam 2, there is a driving component for the positioning component 3, which increases the convenience of moving and adjusting the positioning component 3;

[0045] The system process of the automatic flexible spot welding system for identifying 3D features includes the following steps:

[0046] Step 1: Import the product data into the system and analyze it;

[0047] Step 2: Judge the positioning point information of the product according to the positioning rule of the fixture for the product, and generate the layout program of the fixture. Through the action of the four-axis positioning mechanism 4, drive different driving components in the main fixture frame 1 to adjust the positions of the X-direction translation cross beam 2 and the positioning component 3, and then fix the product to be welded in the main fixture frame 1;

[0048] Step 3: Extract the welding features of the product based on the product image matching, identify the points corresponding to the welds of the product, and select the welding posture;

[0049] Step 4: The system then verifies the interference of the generated robot trajectory according to the second and third steps. If there is no interference, generate the robot welding path trajectory. Otherwise, return to the second and third steps to calculate and optimize again;

[0050] Step 5: Generate welding parameters by retrieving the corresponding information in the welding parameter table or the data in the welding process library;

[0051] Step 6: The robot executes the welding program.

[0052] Based on the imported product data through an internal algorithm, data analysis is carried out to calculate the positioning point information, welding points, welding postures of the product, and verify the interference of the robot trajectory. Welding is performed at the overlapping parts of the parts, and the electrophoresis holes related to the welding parts can be identified and welding is avoided for them. This enables the system to be flexibly changed, eliminating the need for teaching programming when welding different products, facilitating the production and use of welding frames for small batches and multiple batches of different products, significantly improving production efficiency, and reducing production costs.

[0053] Furthermore, the process of extracting product welding features in step 3 of the system process includes the following steps:

[0054] Step 1: Import the 3D model, the STP file of the entire welded product;

[0055] Step 2: The internal algorithm program identifies the STP file;

[0056] Step 3: Split the product to obtain individual parts;

[0057] Step 4: Identify the volume, surface area, number of faces, holes, chamfers, length, width, height, and wall thickness of each individual part;

[0058] Step 5: Use the welding knowledge base to screen and classify the features of individual parts and complete the matching detection of the product to be welded;

[0059] Step 6: Find the welding target surface;

[0060] Step 7: Identify the weld seam by combining the found welding target surface with the normal vector contact determination;

[0061] Step 8: Output the point position information of the weld seam.

[0062] By importing the STP file of the product, the welded products in the file can be automatically identified and processed, and the welding surfaces and the point positions of the weld seams on the surfaces in the product can be found. Thus, the X-direction translation cross beam 2 and the positioning component 3 in the tooling main frame 1 can be adjusted, facilitating the fixation of the product and the welding work of the welding robot, reducing the time consumed by manual programming, and improving the welding efficiency.

[0063] Further, a fixture positioning monitoring module is provided inside the four-axis positioning mechanism 4. The setting of the fixture positioning monitoring module can monitor and adjust the positions of the X-direction translation cross beam 2 and the positioning component 3 on the tooling main frame 1, improving the practicability and flexibility of product welding. Above the tooling main frame 1, a sliding vertical plate 5 is provided. On one side of the sliding vertical plate 5, a translation cross plate 6 is installed, and the sliding vertical plate 5 and the translation cross plate 6 are fixedly connected by bolts. Inside the tooling main frame 1, a driving component for driving the sliding vertical plate 5 to move is provided, enabling the sliding vertical plate 5 to drive the translation cross plate 6 to translate, so that the acquisition camera 7 can move above the product to be welded, improving the convenience of acquiring product images. Below the translation cross plate 6, an acquisition camera 7 is installed, and the translation cross plate 6 and the acquisition camera 7 are fixedly connected by bolts. The setting of the acquisition camera 7 can perform image acquisition on the product to be welded, facilitating the matching detection of the product to be welded and improving practicability.

[0064] Further, in step five of the process of extracting product welding features, the product matching detection process includes the following steps:

[0065] Step 1: Through the function of the acquisition camera 7, perform image acquisition on the product to be welded;

[0066] Step 2: Through mathematical morphology, use a non-linear filtering method to process the acquired image, suppress the noise contained in the original acquired image caused by machine vibration and other factors, and increase the clarity of the original image;

[0067] Step 3: Then perform masking processing to block the parts of the acquired image that are not the product to be welded, display the edge line features of the product to be welded, and extract the image of the product to be welded part;

[0068] Step 4: Then perform binaryzation processing on the image of the product to be welded, and compare and match it with the image of the imported welding product file, observe whether the image of the product to be welded is the same as the imported product image, and perform defect detection on the image of the product to be welded;

[0069] Step 5: Then output the matching detection result.

[0070] By sequentially processing the acquired image through mathematical morphology, masking, and binaryzation, the image of the product part can be extracted, the clarity of the product image can be increased, and then the product image is compared and matched with the imported welding product image to observe whether the product image is the same as the imported product image, preventing the wrong parts from being taken in the product, resulting in welding errors. At the same time, defect detection is performed on the product to prevent defective parts from being welded into the product, improving the product production quality. The alarm module externally connected to the detection module facilitates sound alarm prompts.

[0071] Furthermore, the acquisition camera 7 adopts an area array CCD camera. Through the setting of the area array CCD sensor, images with a large amount of information can be acquired, improving the accuracy of the matching detection of the product to be welded.

[0072] Working principle: When in use, import the product data into the system and analyze it. Determine the positioning point information of the product according to the positioning rules of the tooling for the product, and generate the layout program of the tooling. Through the action of the four-axis positioning mechanism 4, drive different driving components on the tooling main frame 1 to adjust the positions of the X-direction translation cross beam 2 and the positioning component 3. Then fix the product to be welded inside the tooling main frame 1. Extract the welding features of the product based on the image matching of the product. Identify the STP file of the entire welded product in the imported 3D model through the internal algorithm program, split the product to obtain individual parts, and then identify the volume, surface area, number of faces, holes, chamfers, length, width, height, and wall thickness of each individual part. Screen and classify the features of the individual parts with the help of the welding knowledge base. At the same time, through the action of the acquisition camera 7, collect images of the product to be welded. Use mathematical morphology to perform non-linear filtering on the collected images to suppress the noise contained in the original collected images caused by machine vibration and other factors, increase the clarity of the original images, and then perform masking processing to block the parts of the collected images that are not the product to be welded, display the edge line features of the product to be welded, and extract the image of the product to be welded part. Then perform binary processing on the image of the product to be welded and compare and match it with the image of the imported welded product file to observe whether the image of the product to be welded is the same as the imported product image, and perform defect detection on the image of the product to be welded. If there are differences or defects, give a sound alarm prompt through the external alarm module. Then find the welding target surface according to the result of the feature screening and classification. Then, combined with the normal vector contact determination of the found welding target surface, identify the point position information of the weld seam and the electrophoresis holes related to the welding position. Then, according to the identified point positions and electrophoresis holes corresponding to the weld seam of the product, select the welding posture to avoid welding the electrophoresis holes. The system then verifies the interference of the generated robot trajectory according to the second and third steps. If there is no interference, generate the robot welding path trajectory. Otherwise, return to the second and third steps to calculate and optimize again. Generate welding parameters by retrieving the corresponding information in the welding parameter table or the data in the welding process library, and the robot executes the welding program to weld the product.

[0073] It is obvious to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any respect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. An automatic flexible spot welding system for identifying 3D features, including a main tooling frame (1), characterized in that: A four-axis positioning mechanism (4) is installed above the tooling main frame (1), an X-direction translation beam (2) is arranged inside the tooling main frame (1), and a positioning component (3) is arranged above the X-direction translation beam (2); The system flow of the automatic flexible spot welding system for recognizing 3D features includes the following steps: Step 1: Import product data into the system and analyze it; Step 2: Determine the positioning point information of the product according to the positioning rule of the tooling for the product, and generate a layout program of the tooling, drive different driving components in the tooling main frame (1) through the action of the four-axis positioning mechanism (4), adjust the position of the X-axis translation beam (2) and the positioning component (3), and then fix the product to be welded in the tooling main frame (1); Step 3: Based on the matching of product images, extract the product welding features, identify the points corresponding to the product welds, and select the welding posture; Step 4: The system verifies the interference of the generated robot trajectory according to the second and third steps. If there is no interference, the robot welding path trajectory is generated. Otherwise, it returns to the second and third steps for calculation and optimization again. Step 5: Generate welding parameters by retrieving corresponding information in the welding parameter table or welding process library data; Step 6: The robot executes the welding procedure; The process of extracting product welding characteristics in step 3 of the system process includes the following steps: Step 1: Import the 3D model and the STP file of the entire welding product; Step 2: The internal algorithm program identifies the STP file; Step 3: Disassemble the product and obtain individual parts; Step 4: Identify the volume, surface area, number of faces, holes, chamfers, length, width, height and wall thickness of each individual part; Step 5: Use the welding knowledge base to perform feature screening and classification of individual parts and complete matching detection of products to be welded; Step 6: Find the target surface for welding; Step 7: Identify the weld by finding the welding target surface and judging the normal vector contact; Step 8: Output the point information of the weld; A fixture positioning monitoring module is provided inside the four-axis positioning mechanism (4); A sliding vertical plate (5) is arranged above the tooling main frame (1), a translational horizontal plate (6) is installed on one side of the sliding vertical plate (5), and the sliding vertical plate (5) and the translational horizontal plate (6) are fixedly connected by bolts; A collection camera (7) is installed below the translational transverse plate (6), and the translational transverse plate (6) and the collection camera (7) are fixedly connected by bolts.

2. The automatic flexible spot welding system for identifying 3D features according to claim 1, characterized in that: A driving component for the X-direction translational crossbeam (2) is arranged inside the tooling main frame (1).

3. An automatic flexible spot welding system for identifying 3D features according to claim 2, characterized in that: A driving component of a positioning assembly (3) is arranged inside the X-direction translation crossbeam (2).

4. The automatic flexible spot welding system for identifying 3D features according to claim 1, characterized in that: The product matching detection process in step 5 of the process of extracting product welding features includes the following steps: Step 1: Capture an image of the product to be welded by using a collection camera (7); Step 2: Through mathematical morphology, a nonlinear filtering method is used to process the collected image to suppress the noise contained in the original image collected due to the influence of machine vibration and other factors, thereby increasing the clarity of the original image; Step 3: Then perform masking processing to block the parts of the acquired image that are not the products to be welded, display the edge line features of the products to be welded, and extract the images of the parts of the products to be welded; Step 4: Then perform binarization processing on the images of the products to be welded, and perform comparison and matching detection with the images of the imported welding product files, observe whether the images of the products to be welded are the same as the imported product images, and perform defect detection on the images of the products to be welded; Step 5: Then output the matching detection results.

5. The automatic flexible spot welding system for identifying 3D features according to claim 1, characterized in that: The acquisition camera (7) is a area array CCD camera.

Images