Defect prediction and quality control method for high-strength aluminum alloy welding

Abstract

The invention provides a defect prediction and quality control method for high-strength aluminum alloy welding based on numerical simulation. The defect prediction and quality control method comprises the steps that a welding process finite element model is established according to the actual situation; inputting accurate heat source parameters, simulating a molten pool flow field, and revealing an influence rule of metal flow in the micro molten pool on formation of micro defects through visual simulation; phase field simulation and stress distribution simulation are conducted on the solidification behavior of the molten pool, the grain structure condition of a weld zone is obtained, and crack tendencies under different processes are evaluated in combination with stress distribution; post-welding deformation of the whole component is simulated, stress deformation of a key part is obtained, and post-welding deformation is inhibited by means of reversible deformation, pre-pressing and the like. The method belongs to the field of welding numerical simulation, and can help to adjust the welding process, reduce the crack occurrence rate during welding of the high-strength aluminum alloy and inhibit post-welding deformation.

Description

Technical Field

[0001] The invention belongs to the field of welding numerical simulation, and in particular relates to a defect prediction and quality control method for high-strength aluminum alloy welding. Background Art

[0002] High-strength aluminum alloys (such as 2-series and 7-series aluminum alloys) have the advantages of low density, high strength, and good machinability, and are widely used in the aerospace field. Welding is an important basic process for manufacturing high-strength aluminum alloy components. However, due to the physical and chemical properties of high-strength aluminum alloys, such as heat treatment strengthening characteristics and much larger thermal conductivity and linear expansion coefficient than ordinary steel materials, the welding quality problem is particularly prominent.

[0003] The fundamental reason for defects such as cracks in welding is the combined effect of metallurgical factors and mechanical factors. In the process of melting and welding of high-strength aluminum alloys, the solidification of the molten pool usually produces coarse dendrite structure and severe solute segregation. Under the action of welding stress, the weld will crack along the grain boundary, forming solidification cracks, which seriously damages the mechanical properties of the welded joint. In production, 4-series aluminum-silicon filler materials are often used for welding 2024-T4 high-strength aluminum alloys. The main reason is that the introduction of silicon elements can form a large number of low-melting eutectics with good fluidity and reduce crack sensitivity. However, due to the dilution of the matrix components of 2024-T4 high-strength aluminum alloy by aluminum-silicon filler materials, the strength of the welded joint is relatively low (strength coefficient is about 60%). The use of homogeneous second-series aluminum alloy wires can achieve equal strength matching, but the weld structure is coarse and prone to cracks. Therefore, how to reduce welding defects on the basis of ensuring strength and achieve crack-free welding of high-strength aluminum alloys is a major problem. Summary of the invention

[0004] In order to solve the defects of the prior art, the present invention provides a defect prediction and quality control method for high-strength aluminum alloy welding, including: establishing a finite element model of the welding process according to actual conditions; inputting precise heat source parameters to simulate the molten pool flow field, and visually simulating to reveal the influence of metal flow in the micro-molten pool on the formation of tiny defects; performing phase field simulation and stress distribution simulation on the molten pool solidification behavior to obtain the grain structure of the weld area, and evaluating the crack tendency under different processes in combination with the stress distribution; simulating the post-weld deformation of the overall component to obtain the stress deformation of key parts, and then using anti-deformation, pre-stressing and other means to suppress the post-weld deformation.

[0005] Preferably, the defect prediction and quality control method of high-strength aluminum alloy welding of the present invention specifically comprises the following steps: 1) Establish a finite element model of the welding process based on the welding process parameters and the actual conditions of the welding workpiece; 2) Input accurate heat source parameters to numerically simulate the molten pool flow field during welding, obtain the law of metal flow in the molten pool, and analyze the influence of molten pool flow on the formation of micro defects; 3) Perform phase field simulation on the solidification behavior of the molten pool during welding to obtain the grain structure distribution in the weld area; 4) Through stress distribution simulation analysis, evaluate the crack tendency of welded joints under different process parameters and the crack sensitivity of grain boundaries; 5) Perform deformation simulation on the whole component after the welding process to obtain the stress distribution of post-weld deformation; 6) Based on the analysis results of post-weld stress and deformation, anti-deformation and pre-stressing process methods are adopted to suppress the post-weld deformation of welded joints and components, and ensure the geometric accuracy and mechanical properties of welded joints.

[0006] Preferably, when establishing the finite element model of the welding process, it further includes experimentally acquiring the physical and mechanical property parameters of the aluminum alloy matrix material to ensure the accuracy of the model.

[0007] Preferably, when simulating the molten pool flow field, the heat conduction and interaction between the molten pool and the base material are considered, the heat source parameters are adjusted in real time, and the heat source is calibrated according to the exploratory experiment.

[0008] Preferably, in the phase field simulation, a grain growth model is used to simulate the solidification process of the molten pool during welding, and to analyze the solidification structure and defect distribution under different temperature fields.

[0009] Preferably, when evaluating the crack tendency of the weld joint, the stress-strain model is used to calculate the stress-strain distribution of the weld joint in combination with the thermal stress, cooling rate and alloy composition under different process parameters, and the critical stress / deformation value is set to determine the crack sensitivity area.

[0010] Preferably, multiple process simulations are performed to further optimize welding process parameters, including welding current, voltage, welding speed, selection of filler materials, etc., so as to reduce the incidence of welding defects and improve the strength of the welded joint.

[0011] Preferably, in the post-welding deformation simulation, the inverse deformation technology is used to predict and compensate for the plastic deformation caused by welding and optimize the workpiece deformation control during the welding process.

[0012] Preferably, based on the simulation results, appropriate welding parameter adjustment and process control are designed and implemented, and the welding process is monitored in real time to ensure welding quality.

[0013] The advantages and beneficial effects of the present invention are as follows: the present invention provides a defect prediction and quality control method for high-strength aluminum alloy welding based on numerical simulation, which belongs to the field of welding numerical simulation. The present invention can help adjust the welding process, reduce the crack incidence rate during high-strength aluminum alloy welding, and inhibit post-weld deformation. DETAILED DESCRIPTION

[0014] The specific implementation of the present invention is further described below in conjunction with the examples. The following examples are only used to more clearly illustrate the technical solutions of the present invention, and cannot be used to limit the protection scope of the present invention.

[0015] The technical solutions specifically implemented in the present invention are as follows: The present invention provides a defect prediction and quality control method for high-strength aluminum alloy welding, comprising: establishing a finite element model of the welding process according to actual conditions; inputting precise heat source parameters, simulating the molten pool flow field, and visually simulating to reveal the influence of metal flow in a micro-molten pool on the formation of tiny defects; performing phase field simulation and stress distribution simulation on the solidification behavior of the molten pool to obtain the grain structure of the weld zone, and evaluating the crack tendency under different processes in combination with the stress distribution; simulating the post-weld deformation of the overall component to obtain the stress deformation of key parts, and then using reverse deformation, pre-stressing and other means to suppress the post-weld deformation.

[0016] The defect prediction and quality control method of high-strength aluminum alloy welding of the present invention specifically comprises the following steps: 1) Establish a finite element model of the welding process based on the welding process parameters and the actual conditions of the welding workpiece; 2) Input accurate heat source parameters to numerically simulate the molten pool flow field during welding, obtain the law of metal flow in the molten pool, and analyze the influence of molten pool flow on the formation of micro defects; 3) Perform phase field simulation on the solidification behavior of the molten pool during welding to obtain the grain structure distribution in the weld area; 4) Through stress distribution simulation analysis, evaluate the crack tendency of welded joints under different process parameters and the crack sensitivity of grain boundaries; 5) Perform deformation simulation on the whole component after the welding process to obtain the stress distribution of post-weld deformation; 6) Based on the analysis results of post-weld stress and deformation, anti-deformation and pre-stressing process methods are adopted to suppress the post-weld deformation of welded joints and components, and ensure the geometric accuracy and mechanical properties of welded joints.

[0017] More specific: When establishing the finite element model of the welding process, it further includes experimentally acquiring the physical and mechanical property parameters of the aluminum alloy matrix material to ensure the accuracy of the model.

[0018] When simulating the molten pool flow field, the heat conduction and interaction between the molten pool and the base material are considered, the heat source parameters are adjusted in real time, and the heat source is calibrated according to the exploratory experiment.

[0019] In the phase field simulation, the grain growth model is used to simulate the solidification process of the molten pool during welding, and the solidification structure and defect distribution under different temperature fields are analyzed.

[0020] When evaluating the crack tendency of welded joints, the stress-strain model is used to calculate the stress-strain distribution of welded joints in combination with the thermal stress, cooling rate and alloy composition under different process parameters, and the critical stress / deformation value is set to determine the crack sensitivity area.

[0021] Conduct multi-process simulation to further optimize welding process parameters, including welding current, voltage, welding speed, selection of filler materials, etc., to reduce the incidence of welding defects and improve the strength of welded joints.

[0022] When simulating post-weld deformation, the inverse deformation technology is used to predict and compensate for the plastic deformation caused by welding and optimize the workpiece deformation control during the welding process.

[0023] Based on the simulation results, appropriate welding parameter adjustments and process controls are designed and implemented, and the welding process is monitored in real time to ensure welding quality.

[0024] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A defect prediction and quality control method for high-strength aluminum alloy welding, characterized in that: include: A finite element model of the welding process is established based on actual conditions. Accurate heat source parameters are input to simulate the molten pool flow field, and visual simulation reveals the influence of metal flow in the micro-molten pool on the formation of tiny defects. Phase field simulation and stress distribution simulation are performed on the molten pool solidification behavior to obtain the grain structure of the weld area, and the crack tendency under different processes is evaluated in combination with the stress distribution. The post-weld deformation of the overall component is simulated to obtain the stress deformation of key parts, and then anti-deformation, pre-stressing and other means are used to suppress post-weld deformation.

2. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 1, characterized in that: The specific steps include: 1) Establish a finite element model of the welding process based on the welding process parameters and the actual conditions of the welding workpiece; 2) Input accurate heat source parameters to numerically simulate the molten pool flow field during welding, obtain the law of metal flow in the molten pool, and analyze the influence of molten pool flow on the formation of micro defects; 3) Perform phase field simulation on the solidification behavior of the molten pool during welding to obtain the grain structure distribution in the weld area; 4) Through stress distribution simulation analysis, evaluate the crack tendency of welded joints under different process parameters and the crack sensitivity of grain boundaries; 5) Perform deformation simulation on the whole component after the welding process to obtain the stress distribution of post-weld deformation; 6) Based on the analysis results of post-weld stress and deformation, anti-deformation and pre-stressing process methods are adopted to suppress the post-weld deformation of welded joints and components, and ensure the geometric accuracy and mechanical properties of welded joints.

3. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 4 is characterized in that: When establishing the finite element model of the welding process, it further includes experimentally acquiring the physical and mechanical property parameters of the aluminum alloy matrix material to ensure the accuracy of the model.

4. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 3, characterized in that: When simulating the molten pool flow field, the heat conduction and interaction between the molten pool and the base material are considered, the heat source parameters are adjusted in real time, and the heat source is calibrated according to the exploratory experiment.

5. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 4, characterized in that: In the phase field simulation, the grain growth model is used to simulate the solidification process of the molten pool during welding, and the solidification structure and defect distribution under different temperature fields are analyzed.

6. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 5, characterized in that: When evaluating the crack tendency of welded joints, the stress-strain model is used to calculate the stress-strain distribution of welded joints in combination with the thermal stress, cooling rate and alloy composition under different process parameters, and the critical stress / deformation value is set to determine the crack sensitivity area.

7. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 6, characterized in that: Conduct multi-process simulation to further optimize welding process parameters, including welding current, voltage, welding speed, selection of filler materials, etc., to reduce the incidence of welding defects and improve the strength of welded joints.

8. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 7, characterized in that: When simulating post-weld deformation, the inverse deformation technology is used to predict and compensate for the plastic deformation caused by welding and optimize the workpiece deformation control during the welding process.

9. The defect prediction and quality control method for high-strength aluminum alloy welding according to claim 8, characterized in that: Based on the simulation results, appropriate welding parameter adjustments and process controls are designed and implemented, and the welding process is monitored in real time to ensure welding quality.