A method for optimizing a welding process design

Abstract

The present application belongs to the technical field of welding process, and discloses a welding process optimization design method, comprising the following steps: step one, establishing a simulation to-be-welded workpiece model according to a real to-be-welded workpiece; step two, selecting a virtual material identical to the material of the real to-be-welded workpiece from a simulation welding material library of welding simulation software and assigning the virtual material to the simulation to-be-welded workpiece model; wherein, when the simulation welding material library does not contain a virtual material identical to the material of the real to-be-welded workpiece, a virtual material closest to the real to-be-welded workpiece in electromagnetic performance is selected from the simulation welding material library and assigned to the simulation to-be-welded workpiece model; step three, designing at least two welding process schemes, and respectively adopting the designed welding process schemes to perform welding process simulation on the simulation to-be-welded workpiece model; and step four, selecting a welding process scheme with the best simulation welding effect as the welding process scheme of the real to-be-welded workpiece.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of welding process, and particularly relates to a welding process optimization design method. BACKGROUND

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

[0003] In order to better play the role of the Simufact-Welding software, the process designer should try to ensure that the virtual material used for simulation is the same as the actual material used, otherwise the simulation result and the actual result will be quite different, which will not be of reference.

[0004] However, in fact, the welding material library of the welding process simulation analysis software cannot cover new welding materials in time. For example: a heat treatment-free die-casting aluminum alloy is a new type of vacuum die-casting material developed on the basis of traditional die-casting aluminum alloy, which can directly obtain good comprehensive performance without heat treatment, and effectively avoid the adverse effects of heat treatment on the performance of the part. However, it is not included in the current Simufact-Welding software material library. If the material performance test is carried out on the used material and the user-defined material is established to be included in the material library of the Simufact-Welding software, it needs to be based on a long-term and large amount of material performance test, which requires a lot of manpower and material resources and takes a lot of time.

[0005] Therefore, how to reasonably set the simulation scheme can make the simulation process closer to the real welding process under the premise of ensuring the research efficiency, so as to obtain more accurate optimization results, which is a problem to be solved at present. SUMMARY

[0006] The purpose of the application is to provide a welding process optimization design method, which can make the simulation process closer to the actual situation by reasonably setting the simulation scheme and reasonably selecting the simulation welding material, so as to obtain accurate optimization results while improving the efficiency.

[0007] The technical scheme provided by the application is as follows:

[0008] A welding process optimization design method comprises the following steps:

[0009] Step 1: According to the real workpiece to be welded, a simulation workpiece model is established;

[0010] Step two, selecting a virtual material identical to the material of the real to-be-welded workpiece from a simulation welding material library of a welding simulation software and assigning the virtual material to the simulation to-be-welded workpiece model;

[0011] When the virtual material identical to the material of the real to-be-welded workpiece does not exist in the simulation welding material library, a virtual material closest to the material of the real to-be-welded workpiece in electromagnetic performance is selected from the simulation welding material library and assigned to the simulation to-be-welded workpiece model.

[0012] Step three, designing at least two welding process schemes and performing welding process simulation on the simulation to-be-welded workpiece model by using the designed welding process schemes respectively.

[0013] Step four, selecting a welding process scheme with the best simulation welding effect as the welding process scheme of the real to-be-welded workpiece.

[0014] Preferably, in the step one, three-dimensional modeling is performed in the Soildworks software and an STL format model is output as the simulation to-be-welded workpiece model.

[0015] Preferably, in the step one, the step further comprises:

[0016] The STL format model is imported into the Hypermesh software to perform meshing, so that the meshing ratio of the model is above 80%.

[0017] Preferably, the welding process scheme comprises welding parameters, welding spot setting, spot welding sequence, joint type and overlap width.

[0018] The welding parameters comprise welding current, electrode pressure and welding time.

[0019] Preferably, in the step two, if there are multiple virtual materials closest to the material of the real to-be-welded workpiece in electromagnetic performance in the simulation welding material library, a virtual material closest to the material of the real to-be-welded workpiece in electromagnetic performance and closest to the flow stress strain curve is selected and assigned to the simulation to-be-welded workpiece model.

[0020] Preferably, in the step one, the step further comprises:

[0021] A simulation model of a support table and a welding fixture used for welding is established.

[0022] The welding process optimization design method provided by the application has the advantages that:

[0023] The welding process optimization design method provided by the application has the advantages that: BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 This is a flowchart of the welding process optimization design method described in this invention. Detailed Implementation

[0025] 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.

[0026] like Figure 1 As shown, the present invention provides a welding process optimization design method, and the specific implementation process is as follows.

[0027] S100. Establish a simulation model of the workpiece to be welded.

[0028] 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.

[0029] 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.

[0030] S200. Select virtual materials for simulation and assign them to the simulated workpiece model.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Therefore, if a virtual material identical to the real material of the workpiece to be welded does not exist in the virtual material library, the present application selects a virtual material in the virtual welding material library that is closest to the real material of the workpiece to be welded in electromagnetic properties to assign to the simulation workpiece model.

[0035] If multiple virtual materials closest to the real material of the workpiece to be welded in electromagnetic properties exist in the virtual welding material library, a virtual material closest to the real material of the workpiece to be welded in electromagnetic properties and closest to the real material of the workpiece to be welded in rheological stress-strain curve is selected to assign to the simulation workpiece model.

[0036] In an embodiment, the simulation welding software is Simufact-Welding software.

[0037] S300, designing a welding process scheme to be studied

[0038] The welding process scheme to be studied includes at least two welding process schemes, each of which includes welding parameters, spot setting, spot welding sequence, joint type, overlap width, etc., and the welding parameters include welding current, welding time, electrode pressure.

[0039] The welding process scheme to be studied is then used for simulation welding process of the simulation workpiece model.

[0040] S400, setting simulation solver parameters for welding process simulation analysis

[0041] The welding process simulation analysis includes the following analysis indexes: nugget size, nugget position, total deformation, X-direction displacement, Y-direction displacement, Z-direction displacement, total contact area, temperature distribution, and current density distribution.

[0042] According to the welding process simulation analysis result, the welding process scheme to be studied with the best result is selected as the optimal welding process scheme, and the optimal welding scheme is used as the welding scheme of the real workpiece to be welded. In actual application, one analysis index can be selected according to the test analysis project to judge the pros and cons of the simulation result. For example, when the spot welding process parameters are optimized by simulation analysis, in order to obtain an ideal nugget size, the nugget diameter can be used as the welding process simulation analysis result. Embodiment

[0043] This embodiment takes a hot-treatment-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 application.

[0044] The heat treatment-free die casting aluminum alloy is a new type of vacuum die casting material developed on the basis of traditional die casting aluminum alloy, which can directly obtain good comprehensive performance without heat treatment, and effectively avoids the adverse effects of heat treatment on the performance of parts. However, it is not included in the current Simufact-Welding software material library.

[0045] The heat treatment-free die casting aluminum alloy plate is formed by an integrated vacuum die casting technology, has a width of 200 mm, a thickness of 3 mm, and a silver-white color.

[0046] The heat treatment-free die casting aluminum alloy plate spot-welded product is modeled in Soildworks software and output as an STL format model. In the modeling process, the upper plate and the lower plate should be prevented from being in complete contact as much as possible. Complete contact can easily cause distortion of the mesh and affect the judgment of the contact conditions between the plates, leading to failure of temperature field analysis. It is found through research that the simulation result is best when the distance between the plates is controlled at 0.15 mm to 0.25 mm. In this embodiment, the distance between the plates is 0.2 mm.

[0047] The built STL format model is imported into Hypermesh software for mesh division. The mesh type can be classified as solid mesh, shell mesh, and mid-surface mesh. In this embodiment, solid mesh is used for mesh division in the welding process analysis. After division, mesh inspection and mesh repair are performed to ensure that the mesh ratio is ≥80%.

[0048] Next, a virtual material for simulation is obtained and assigned to the to-be-welded workpiece model.

[0049] Since the heat treatment-free die casting aluminum alloy used for this product is not included in the material library of Simufact-Welding software, there are two ways to obtain the virtual material for simulation: one is to test the material performance and establish a user-defined material in the material library of Simufact-Welding software, which has the disadvantage of requiring a large amount of manpower and material resources and taking a long time; the other is to select a similar welding material based on the material library of Simufact-Welding software, but since the material data range in the simulation virtual library is large and the material performance is diverse, it is difficult to accurately select the appropriate welding material based on experience.

[0050] In this embodiment, AlMgSi1 is selected as the simulation virtual material according to the method provided in the application, three materials different from the virtual simulation material AlMgSi1 in electromagnetic performance, stress-strain curve and thermal expansion coefficient are selected as comparative material 1, comparative material 2 and comparative material 3 respectively, and the simulation maximum nugget size results of the simulation virtual materials with different performances are shown in Table 1. As can be seen from Table 1, through test verification, the simulation maximum nugget size of the simulation virtual material AlMgSi1 is 10.21 mm, and the relative deviation from the true data is 3.44%; compared with AlMgSi1, the comparative material 1 is different in electromagnetic performance and consistent in other performances, the simulation maximum nugget size is 10.00 mm, and the relative deviation from the true data is 5.74%, the comparative material 2 is different in stress-strain curve and consistent in other performances, the simulation maximum nugget size is 10.06 mm, and the relative deviation from the true data is 5.11%, and the comparative material 3 is different in thermal expansion coefficient and consistent in other performances, the simulation maximum nugget size is 10.12 mm, and the relative deviation from the true data is 4.48%.

[0051] Table 1 simulation result comparison

[0052]

[0053] As can be seen from the above test, the electromagnetic performance in the material properties is the largest factor affecting the deviation between the simulation analysis result and the actual result, and the rheological stress-strain curve in the material properties is the second largest factor affecting the simulation analysis result. In this embodiment, the conductivity is used as the electromagnetic performance index. The above test results fully prove the rationality of the method for selecting the virtual simulation material.

[0054] Therefore, the material with the brand AlMgSi1 is selected as the simulation virtual material in this embodiment.

[0055] In this embodiment, two welding process schemes to be studied (a first welding process scheme to be studied and a second welding process scheme to be studied) are set. 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 according to the result after simulation analysis, and can greatly reduce the trial and error cost and shorten the process development cycle.

[0056] The first welding process scheme to be studied and the second welding process scheme to be studied both include welding parameters, spot setting, spot welding sequence, joint type and overlap width.

[0057] In this embodiment, the first welding process scheme to be studied is set as a lap joint, the overlap width is 45 mm, the spot distance from the edge of the plate is 20 mm, the spot pitch is 40 mm, and the welding parameters are set as a welding current of 45 KA, an electrode pressure of 7.5 KN and an electric conduction time of 100 ms.

[0058] The second welding process to be studied is designed as a lap joint with a lap width of 45 mm, a distance of 10 mm from the welding spot to the edge of the plate, a spot spacing of 20 mm, and welding parameters set as a welding current of 45 KA, an electrode pressure of 7.5 KN, and an on-time of 100 ms.

[0059] The welding process simulation analysis includes the following analysis contents: nugget size, nugget position, total deformation, temperature distribution, and current density distribution.

[0060] Based on the non-heat-treated die-cast aluminum alloy plate resistance spot welding product in this embodiment, the first welding process to be studied and the second welding process to be studied are analyzed as follows:

[0061] The welding process of the first welding process to be studied is analyzed, the Pardiso direct sparse solver is set in the Simufact-Welding software, the material grade AlMgSi1 is selected, the spot welding track and spot welding parameters are set, and finally the welding process simulation analysis is performed. According to the analysis result, at this time, the current density at each welding spot position is basically the same, the highest temperature is between 662.5℃ and 683.2℃, which indicates that each welding spot does not interfere with each other and does not occur the shunt phenomenon; the nugget is generated at the center between the plates, the nugget size is between 9.25mm and 9.76mm, which meets the qualified nugget size range of 3mm thick welding plate; the maximum total deformation is 0.29mm, which is less than the maximum indentation depth of 3mm thick welding plate. It can be seen that the forming is good under this scheme, and there is no obvious appearance defect.

[0062] The welding process of the second welding process to be studied is analyzed, the Pardiso direct sparse solver is set in the Simufact-Welding software, the material grade AlMgSi1 is selected, the spot welding track and spot welding parameters are set, and finally the welding process simulation analysis is performed. According to the analysis result, at this time, the current density at the first welding spot position is significantly higher than that at the remaining welding spot positions, and the current density at the subsequent welding spot positions gradually decreases, which indicates that each welding spot interferes with each other and obvious shunt phenomenon occurs; the nugget is generated at the center between the plates, the maximum nugget size is 9.37mm, and the minimum nugget size is 8.65mm, the nugget size fluctuates greatly; the maximum total deformation is 0.15mm, which is less than the maximum indentation depth of 3mm thick welding plate. It can be seen that under this scheme, shunt phenomenon occurs between each welding spot, resulting in uneven quality of each welding spot, large fluctuation, and difficulty in ensuring the qualified rate of welding spots.

[0063] Table 2 is a comparison of the welding process simulation results of the first welding process to be studied and the second welding process to be studied.

[0064] Table 2 is a comparison of the simulation results

[0065]

[0066] According to 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.

[0067] As can be seen from the above examples, the welding process simulation analysis result is closer to the actual welding result, higher flexibility and accuracy can be ensured in the design of new materials, the trial and error cost is reduced, the optimization design cycle is shortened, and the product development and production efficiency are improved.

[0068] Although the embodiments of the present application have been disclosed as above, it is not limited to the application listed in the specification and the embodiments, and can be fully applied to various fields suitable for the present application, and other modifications can be easily realized by those skilled in the art, and therefore the present application is not limited to specific details and the figures shown and described herein, without departing from the general concept defined by the claims and the equivalent scope.

Claims

1. A method of designing a welding process optimization, characterized by, The method comprises the following steps: Step one, according to the real workpiece to be welded, a simulation workpiece model is established; Step two, a virtual material identical to the material of the real workpiece to be welded is selected from a simulation welding material library of a welding simulation software and is given to the simulation workpiece model; When the simulation welding material library does not have a virtual material identical to the material of the real workpiece to be welded, a virtual material closest to the real workpiece to be welded in electromagnetic performance is selected from the simulation welding material library and is given to the simulation workpiece model; Step three, at least two welding process schemes are designed, and the simulation workpiece model is simulated by using the designed welding process schemes respectively; Step four, a welding process scheme with the best simulation welding effect is selected as the welding process scheme of the real workpiece to be welded. In the step two, if the simulation welding material library has multiple virtual materials closest to the real workpiece to be welded in electromagnetic performance, a virtual material closest to the real workpiece to be welded in electromagnetic performance and closest to the real workpiece to be welded in rheological stress-strain curve is selected and is given to the simulation workpiece model.

2. The method of claim 1, wherein, In the step one, three-dimensional modeling is performed in Soildworks software and an STL format model is output as the simulation workpiece model.

3. The method of claim 2, wherein, In the step one, the following steps are further included: The STL format model is imported into Hypermesh software to perform meshing, so that the meshing ratio of the model is more than 80%.

4. The method of claim 3, wherein, The welding process scheme includes welding parameters, welding spot setting, spot welding sequence, joint type and overlap width. The welding parameters include welding current, electrode pressure and welding time.

5. The welding process optimization design method according to claim 3 or 4, characterized by, In the step one, the following steps are further included: The support table and the welding fixture used for welding are simulated and modeled.

Images