Welding process optimization design method

Abstract

The invention belongs to the technical field of welding processes, and discloses a welding process optimization design method which comprises the following steps: step 1, establishing a simulation to-be-welded workpiece model according to a real to-be-welded workpiece; 2, selecting a virtual material which is the same as the real to-be-welded workpiece material from a simulation welding material library of welding simulation software, and endowing the virtual material with the simulation to-be-welded workpiece model; wherein when the virtual material which is the same as the real to-be-welded workpiece material does not exist in the simulation welding material library, the virtual material, with the electromagnetic performance closest to that of the real to-be-welded workpiece material, in the simulation welding material library is selected to be given to the simulation to-be-welded workpiece model; thirdly, at least two welding process schemes are designed, and the designed welding process schemes are adopted for conducting welding process simulation on the simulation to-be-welded workpiece model; and fourthly, the welding process scheme with the best simulation welding effect is selected as the welding process scheme of the real to-be-welded workpiece.

Description

Technical Field

[0001] This invention belongs to the field of welding process technology, and specifically relates to a welding process optimization design method. Background Technology

[0002] With the development of modern industry, the application of new welding materials is becoming increasingly widespread, and the properties of these new materials bring new challenges to the design of new welding processes. In the optimization design of welding processes, CAE (Computer Aided Engineering) welding process analysis based on the welding process simulation analysis software Simufact-Welding can minimize trial and error costs and shorten the process development time.

[0003] To better utilize the Simufact-Welding software, process designers should ensure that the virtual materials used in the simulation are the same as the actual materials used. Otherwise, the simulation results will differ significantly from the actual results and will not be reliable.

[0004] However, in reality, the welding material library of welding process simulation analysis software cannot always cover new welding materials. For example, a certain heat-treatable die-casting aluminum alloy is a new type of vacuum die-casting material developed based on traditional die-casting aluminum alloys. It can directly obtain good comprehensive performance without heat treatment, effectively avoiding the adverse effects of heat treatment on part performance. However, it is not currently included in the Simufact-Welding software's material library. If material performance testing is conducted on the materials used and user-defined materials are created and included in the Simufact-Welding software's material library, it would require extensive and long-term material performance testing, consuming significant human and material resources and time.

[0005] Therefore, how to reasonably set up the simulation scheme so that the simulation process can be closer to the real welding process while ensuring research efficiency, so as to obtain more accurate optimization results, is an urgent problem to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a welding process optimization design method, which, by reasonably setting the simulation scheme and reasonably selecting the simulation welding materials, can make the simulation process closer to reality, thereby improving efficiency and obtaining accurate optimization results.

[0007] The technical solution provided by this invention is as follows: A welding process optimization design method includes the following steps: Step 1: Based on the actual workpiece to be welded, establish a simulated model of the workpiece to be welded; Step 2: Select a virtual material that is the same as the material of the real workpiece to be welded from the simulation welding material library of the welding simulation software and assign it to the simulation workpiece model; Wherein, when there is no virtual material in the simulation welding material library that is the same as the material of the real workpiece to be welded, the virtual material in the simulation welding material library that is closest to the electromagnetic properties of the material of the real workpiece to be welded is selected and assigned to the simulation workpiece model. Step 3: Design at least two welding process schemes, and use the designed welding process schemes to simulate the welding process of the simulated workpiece model to be welded; Step 4: Select the welding process scheme with the best simulated welding effect as the welding process scheme for the actual workpiece to be welded.

[0008] Preferably, in step one, a 3D model is created in Soildworks software and output as an STL format model as a simulation model of the workpiece to be welded.

[0009] Preferably, step one further includes: The STL format model is imported into Hypermesh software for mesh generation, so that the mesh ratio of the model is above 80%.

[0010] Preferably, the welding process includes: welding parameters, weld spot settings, spot welding sequence, joint type, and lap width; The welding parameters include welding current, electrode pressure, and energizing time.

[0011] Preferably, in step two, if the simulated welding material library contains multiple virtual materials whose electromagnetic properties are closest to those of the real workpiece material to be welded, then the virtual material whose electromagnetic properties and rheological stress-strain curve are closest to those of the real workpiece material to be welded is selected and assigned to the simulated workpiece model.

[0012] Preferably, step one further includes: Simulation modeling was performed on the support platform and welding fixture used for welding.

[0013] The beneficial effects of this invention are: The welding process optimization design method provided by this invention, by reasonably setting the simulation scheme and reasonably selecting the simulation welding materials, can make the simulation process closer to reality, thereby improving efficiency and obtaining accurate optimization results. Attached Figure Description

[0014] Figure 1 This is a flowchart of the welding process optimization design method described in this invention. Detailed Implementation

[0015] The present invention will now be described in further detail with reference to the accompanying drawings, so that those skilled in the art can implement it based on the description.

[0016] like Figure 1 As shown, the present invention provides a welding process optimization design method, and the specific implementation process is as follows.

[0017] S100. Establish a simulation model of the workpiece to be welded. Based on the actual structure and dimensions of the workpiece to be welded, a 3D model is created in Solidworks software and exported as an STL format model. The STL model is then imported into Hypermesh software for mesh generation. Mesh types can be categorized as solid meshes, shell meshes, and mid-surface meshes. In this embodiment, solid meshes are used for mesh generation. After generation, mesh checks and repairs are performed to ensure a mesh coverage ratio ≥ 80%, thus guaranteeing modeling accuracy.

[0018] In addition to creating a three-dimensional model of the workpiece to be welded, this invention also creates a support platform model and a fixture model. The support platform serves to support the workpiece to be welded, preventing it from falling during welding; the fixture serves to fasten and position the workpiece to be welded, preventing it from moving during welding.

[0019] S200. Select virtual materials for simulation and assign them to the simulated workpiece model. In the welding simulation software, select a virtual material that is the same as the material of the real workpiece to be welded from the simulation welding material library and assign it to the simulation workpiece model.

[0020] If the virtual material library of the welding simulation software does not contain a virtual material identical to the material of the actual workpiece to be welded, select a welding material from the virtual material library that is closest to the material of the actual workpiece to be welded and assign it to the simulated workpiece model.

[0021] Research revealed that electromagnetic properties are the most significant factor influencing the discrepancy between simulation and actual results among material characteristics. This is followed by the rheological stress-strain curve, which has a lesser impact on simulation results than electromagnetic properties. These electromagnetic properties include conductivity and resistivity; in practical applications, conductivity or resistivity can be chosen as the criterion for judging electromagnetic properties.

[0022] Therefore, if there is no virtual material in the simulation virtual material library that is the same as the material of the real workpiece to be welded, the present invention selects the virtual material in the simulation welding material library that is closest to the electromagnetic properties of the material of the real workpiece to be welded and assigns it to the simulation workpiece model.

[0023] If the simulated welding material library contains multiple virtual materials whose electromagnetic properties are closest to those of the real workpiece material to be welded, then the virtual material whose electromagnetic properties and rheological stress-strain curve are closest to those of the real workpiece material to be welded is selected and assigned to the simulated workpiece model.

[0024] In one embodiment, the simulation welding software uses Simufact-Welding software.

[0025] S300, Welding process scheme to be studied in design The welding process scheme to be studied includes at least two welding process schemes. Each welding process scheme includes welding parameters, weld spot settings, spot welding sequence, joint type, lap width, etc. The welding parameters include welding current, energizing time, and electrode pressure.

[0026] The welding process schemes to be studied were then used to simulate the welding process of the workpiece model.

[0027] S400. Set the simulation solver parameters to perform welding process simulation analysis. The simulation analysis of the welding process includes the following analysis indicators: weld nugget size, weld nugget position, total deformation, X-direction displacement, Y-direction displacement, Z-direction displacement, total contact area, temperature distribution, and current density distribution.

[0028] Based on the simulation analysis results of the welding process, the welding process scheme with the best results is selected as the optimal welding process scheme, and this optimal welding scheme is used as the welding scheme for the actual workpiece to be welded. In practical applications, an analysis index can be selected based on the test and analysis items to judge the quality of the simulation results. For example, when optimizing spot welding process parameters using simulation analysis, in order to obtain the ideal weld nugget size, the weld nugget diameter can be used as the simulation analysis result of the welding process. Example

[0029] This embodiment takes a heat-free die-cast aluminum alloy plate resistance spot welding product as an example to further illustrate the welding process optimization design method of the present invention.

[0030] Heat-treatable die-cast aluminum alloys are a new type of vacuum die-casting material developed based on traditional die-cast aluminum alloys. They can achieve good comprehensive properties directly without heat treatment, effectively avoiding the adverse effects of heat treatment on part performance. However, they are not currently included in the Simufact-Welding software material library.

[0031] The heat-free die-cast aluminum alloy plate is formed by integrated vacuum die-casting technology, with a width of 200mm, a thickness of 3mm, and a silver-white color.

[0032] The spot-welded die-cast aluminum alloy plate product without heat treatment was 3D modeled in Solidworks software and exported as an STL format model. During the modeling process, complete contact between the upper and lower plates should be avoided as much as possible. Complete contact can easily lead to mesh distortion and affect the judgment of contact conditions between the plates, resulting in failure of temperature field analysis. Research showed that the simulation results were best when the distance between the plates was controlled between 0.15mm and 0.25mm. In this embodiment, the distance between the plates was taken as 0.2mm.

[0033] The completed STL format model is imported into Hypermesh software for mesh generation. Mesh types can be categorized as solid meshes, shell meshes, and mid-surface meshes. In this embodiment, solid meshes are used for welding process analysis. After generation, mesh checks and repairs are performed to ensure a mesh coverage ratio ≥ 80%.

[0034] Next, virtual materials for simulation are obtained and assigned to the model of the workpiece to be welded.

[0035] Since the heat-free die-cast aluminum alloy used in this product is not included in the material library of the Simufact-Welding software, there are two ways to obtain virtual materials for simulation: First, perform material performance tests on the materials used and create user-defined materials to be included in the Simufact-Welding software's material library. The disadvantage of this method is that it relies on long-term and extensive material performance testing, requiring significant human and material resources and consuming a lot of time. Second, select a relatively close welding material based on the Simufact-Welding software's material library. However, due to the large range of material data and diverse material properties in the simulation virtual library, it is difficult to accurately select a suitable welding material based on experience.

[0036] In this embodiment, AlMgSi1 was selected as the virtual simulation material according to the method provided by the present invention. Three materials with different electromagnetic properties, stress-strain curves, and coefficients of thermal expansion compared to AlMgSi1 were selected as comparative material 1, comparative material 2, and comparative material 3, respectively. The results of the simulated maximum melt core size under different virtual materials are shown in Table 1. As can be seen from Table 1, the simulated maximum melt core size under the virtual material AlMgSi1 was 10.21 mm, with a deviation of 3.44% from the actual data. Compared with AlMgSi1, comparative material 1 had different electromagnetic properties but the same other properties, with a simulated maximum melt core size of 10.00 mm and a deviation of 5.74% from the actual data. Comparative material 2 had a different stress-strain curve but the same other properties, with a simulated maximum melt core size of 10.06 mm and a deviation of 5.11% from the actual data. Comparative material 3 had a different coefficient of thermal expansion but the same other properties, with a simulated maximum melt core size of 10.12 mm and a deviation of 4.48% from the actual data.

[0037] Table 1 Comparison of Simulation Results

[0038] Based on the above experiments, it can be seen that electromagnetic properties are the biggest factor affecting the deviation between simulation analysis results and actual results among material properties, followed by the rheological stress-strain curve, which has a lesser impact on the simulation analysis results than electromagnetic properties. In this embodiment, electrical conductivity is used as the electromagnetic performance index. The above experimental results fully demonstrate the rationality of the virtual simulation material method selected in this invention.

[0039] Therefore, in this embodiment, AlMgSi1 is selected as the virtual material for simulation.

[0040] In this embodiment, two welding process schemes to be studied are set (the first welding process scheme to be studied and the second welding process scheme to be studied). Compared with a single welding process scheme to be studied, increasing the number of welding process schemes to be studied can quickly select a better process scheme based on the results after simulation analysis, which can greatly reduce trial and error costs and shorten the process development cycle.

[0041] Both the first and second welding process schemes to be studied include welding parameters, weld point settings, spot welding sequence, joint type, and lap width.

[0042] In this embodiment, the first welding process to be studied is set as a lap joint with a lap width of 45mm, a weld point distance of 20mm from the edge of the plate, a weld point spacing of 40mm, and welding parameters set as welding current of 45KA, electrode pressure of 7.5KN, and energizing time of 100ms.

[0043] The second welding process scheme to be studied is set as a lap joint with a lap width of 45mm, a weld point distance of 10mm from the edge of the plate, a weld point spacing of 20mm, and welding parameters set as welding current of 45KA, electrode pressure of 7.5KN, and energizing time of 100ms.

[0044] The simulation analysis of the welding process includes the following analysis contents: weld nugget size, weld nugget location, total deformation, temperature distribution, and current density distribution.

[0045] Based on the heat-free die-cast aluminum alloy plate resistance spot welding product in this embodiment, the first and second welding process design schemes to be studied are analyzed as follows: The welding process of the first welding process design scheme was analyzed. In Simufact-Welding software, the Pardiso direct sparse solver was set, and the material grade AlMgSi1 was selected. Spot welding trajectory and parameters were set, and finally, welding process simulation analysis was performed. The analysis results show that the current density at each weld point is basically consistent, with the highest temperature ranging from 662.5℃ to 683.2℃, indicating that there is no interference between weld points and no current shunting occurs. The weld nugget is generated at the center of the plate, with a size ranging from 9.25mm to 9.76mm, which is within the acceptable weld nugget size range for a 3mm thick weld plate. The maximum total deformation is 0.29mm, less than the maximum indentation depth of a 3mm thick weld plate. Therefore, this scheme shows good forming and no obvious appearance defects.

[0046] The welding process of the second welding process design scheme was analyzed. The Pardiso direct sparse solver was set in Simufact-Welding software, and the material grade AlMgSi1 was selected. Spot welding trajectory and parameters were set, and then the welding process was simulated. The analysis results show that the current density at the first weld point is significantly higher than that at other weld points, and the current density at subsequent weld points gradually decreases. This indicates mutual interference and significant current shunting between weld points. The weld nuggets are generated at the center of the plate, with a maximum nugget size of 9.37 mm and a minimum of 8.65 mm, showing significant fluctuations in nugget size. The maximum total deformation is 0.15 mm, less than the maximum indentation depth of a 3 mm thick weld plate. It is evident that under this scheme, current shunting occurs between weld points, leading to inconsistent weld quality and significant fluctuations, making it difficult to guarantee a high weld pass rate.

[0047] Table 2 compares the welding process simulation results of the first and second welding process design schemes to be studied.

[0048] Table 2 Comparison of Simulation Results

[0049] Based on the comparison of the welding process simulation results of the first and second welding process design schemes, the first welding process design scheme is selected as the optimal welding process scheme.

[0050] As can be seen from the above embodiments, the present invention can make the simulation analysis results of the welding process closer to the actual welding results. When dealing with the design of new materials, it can ensure greater flexibility and accuracy, which is conducive to reducing trial and error costs, shortening the optimization design cycle, and improving product development and production efficiency.

[0051] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A welding process optimization design method, characterized in that, Includes the following steps: Step 1: Based on the actual workpiece to be welded, establish a simulated model of the workpiece to be welded; Step 2: Select a virtual material that is the same as the material of the real workpiece to be welded from the simulation welding material library of the welding simulation software and assign it to the simulation workpiece model; Wherein, when there is no virtual material in the simulation welding material library that is the same as the material of the real workpiece to be welded, the virtual material in the simulation welding material library that is closest to the electromagnetic properties of the material of the real workpiece to be welded is selected and assigned to the simulation workpiece model. Step 3: Design at least two welding process schemes, and use the designed welding process schemes to simulate the welding process of the simulated workpiece model to be welded; Step 4: Select the welding process scheme with the best simulated welding effect as the welding process scheme for the actual workpiece to be welded.

2. The welding process optimization design method according to claim 1, characterized in that, In step one, a 3D model is created in the Solidworks software and output as an STL format model, which serves as the simulation model of the workpiece to be welded.

3. The welding process optimization design method according to claim 2, characterized in that, Step one also includes: The STL format model is imported into Hypermesh software for mesh generation, so that the mesh ratio of the model is above 80%.

4. The welding process optimization design method according to claim 3, characterized in that, The welding process plan includes: welding parameters, weld point settings, spot welding sequence, joint type, and lap width; The welding parameters include welding current, electrode pressure, and energizing time.

5. The welding process optimization design method according to claim 3 or 4, characterized in that, In step two, if the simulated welding material library contains multiple virtual materials whose electromagnetic properties are closest to those of the real workpiece material to be welded, then the virtual material whose electromagnetic properties and rheological stress-strain curve are closest to those of the real workpiece material to be welded is selected and assigned to the simulated workpiece model.

6. The welding process optimization design method according to claim 5, characterized in that, Step one also includes: performing simulation modeling of the support platform and welding fixture used for welding.

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