CN110695477B - Eutectic welding parameter selection method based on stress-penetration rate sequential simulation - Google Patents
Eutectic welding parameter selection method based on stress-penetration rate sequential simulation Download PDFInfo
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- CN110695477B CN110695477B CN201910994469.4A CN201910994469A CN110695477B CN 110695477 B CN110695477 B CN 110695477B CN 201910994469 A CN201910994469 A CN 201910994469A CN 110695477 B CN110695477 B CN 110695477B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K1/00—Soldering, e.g. brazing, or unsoldering
Abstract
The invention provides a eutectic welding parameter selection method based on stress-penetration rate sequential simulation, which comprises the following steps of: a, setting a plurality of groups of stress simulation parameters; b, constructing a geometric model and inputting stress simulation parameters; c, comparing the simulated residual stress with the standard stress, and determining the process parameter range according to the qualified stress simulation parameters; if all simulation results do not meet the requirements of standard stress, returning to the step A; d, setting a plurality of groups of drill penetration rate simulation parameters; e, inputting the penetration simulation parameters and the solder property parameters for simulation; f, comparing the simulated penetration rate with the standard penetration rate, selecting qualified penetration rate simulation parameters, and returning to D if all the penetration rates are unqualified. The invention has the advantages that: the process parameters and the material parameters meeting the requirements are determined by sequentially simulating the stress and the penetration rate, so that the experiment cost and the material consumption are greatly reduced.
Description
Technical Field
The invention relates to the technical field of eutectic brazing, in particular to a method for selecting eutectic welding parameters based on stress-braze penetration rate sequential simulation.
Background
The eutectic brazing is to form a binary system by utilizing metal with a higher melting point and another metal with a lower melting point, the temperature in the processing process is higher than the melting point of the eutectic brazing filler metal, a solid solution is formed under isothermal condition, and the melting point of a final joint is higher than the welding temperature. The eutectic brazing has the advantages that: the joint is smooth and flat, the deformation is small, and the size of the workpiece is accurate; the welding can be carried out on the same metal and different materials, and the thickness difference of the workpiece is not strictly limited; the eutectic brazing of metal and metal effectively reduces ohmic resistance and effectively improves heat conduction efficiency. Meanwhile, the connection of different metals, metals and non-metal materials can be easily solved by brazing, and the power output and the stability of the device with high frequency and high power can be ensured by adopting eutectic brazing.
In the actual eutectic brazing process, residual stress and braze penetration are two important factors regarding the quality of the weld. Welding together of materials with different coefficients of thermal expansion necessarily results in residual stresses inside the object, the magnitude of these residual stresses in the housing directly affecting the reliability of the packaged device. If the residual stress of the shell is too large, the packaged device is deformed, cracked and leaked, the reliability of the device is seriously influenced, and even the device fails. The brazing penetration rate is the percentage of the welded area to the required welding area, and low brazing penetration rate means more holes, and the existence of the holes greatly reduces the electrical conductivity and the thermal conductivity of the welding layer, thereby causing circuit crosstalk, insertion loss and additional capacitance and oscillation. The reliability of the weld is also greatly affected. In the traditional manufacturing process, the development of a new eutectic welding process mainly needs to realize effective control of residual stress and brazing penetration rate, and a large number of trial and error experiments are needed. However, trial and error experiments for eutectic brazing are costly and have a long experimental period. And the adoption of a simulation method to scientifically optimize the penetration rate of eutectic brazing can reduce the loss of experimental materials and greatly improve the process efficiency and the welding quality. However, if simulation optimization is performed on the penetration rate and the residual stress at the same time, the calculation difficulty of simulation is high, two parameter variables are set simultaneously in the simulation process, the parameter set needing simulation is heavy, and the optimization process is difficult to obtain quickly.
Disclosure of Invention
The invention aims to provide a eutectic brazing parameter selection method which can give consideration to both residual stress and brazing penetration rate and reduce data operation complexity.
The invention solves the technical problems through the following technical scheme:
a eutectic welding parameter selection method based on stress-penetration rate sequential simulation comprises the following steps:
step A: determining the technological parameter range of eutectic brazing and setting a plurality of groups of stress simulation parameters;
and B: building a geometric model based on dimensional data of welding materials and welding fluxes, and inputting the stress simulation parameters for simulation;
and C: comparing the simulated residual stress with the standard stress, selecting stress simulation parameters meeting the requirements, and determining the qualified process parameter range of the stress; if all simulation results do not meet the requirements of standard stress, returning to the step A, and re-determining stress simulation parameters;
step D: setting a plurality of groups of penetration simulation parameters based on the stress qualified process parameter range;
step E: inputting the penetration simulation parameter and the solder property parameter for simulation;
step F: and D, comparing the simulated penetration rate obtained by simulation with the standard penetration rate, selecting qualified penetration rate simulation parameters, and returning to the step D to re-determine the penetration rate simulation parameters if all the penetration rates are unqualified.
Preferably, the stress simulation parameters in the step a include a eutectic soldering maximum temperature, a holding time, a solder thickness and a soldering pressure.
Preferably, the calculation model for stress simulation in the step B is
Wherein T is solder temperature, the input value of the initial moment is the highest temperature in the process parameters, T is time corresponding to the holding time in the process parameters, epsilon is solder strain, sigma is residual stress after welding, F is yield strength of the material, K is isotropic hardening factor, sigma is the yield strength of the material, and0is the subsequent yield stress; rho is solder density, c is solder specific heat capacity, kxIs the thermal conductivity in the x direction, kyIs the thermal conductivity in the y direction, kzIs the thermal conductivity in the z direction, V is the volume of the integration region, S is the integralThe area of the region.
Preferably, the material property parameters of step E include density, viscosity, surface tension coefficient and melting point.
Preferably, the calculation model for the penetration simulation in the step E is as follows:
wherein the content of the first and second substances,
in order to melt the flow rate of the solder, ρ is the density of the solder, t is the time, μ is the viscosity, p is the pressure, corresponding to the soldering pressure,
Is the gravity acceleration, T is the solder temperature, K is the Darcy factor when solidified,
Surface tension and thermal capillary force, c is specific heat capacity of the solder, k is a thermal conductivity coefficient, and F is volume fraction of the solder in each grid, wherein F is 0 to represent that the grids are all gas, and F is 1 to represent that the grids are all solder;
the penetration rate eta of the brazing rod is
Wherein, VgasV is the total volume of the region contained in the solder, and V is the total volume of the region where F is 0 inside the solder.
Preferably, the step C further includes the step of applying the stress simulation parameters meeting the requirements to the welding test, comparing the test residual stress after the test with the standard stress, rejecting the parameters not meeting the requirements, determining the range of the qualified stress process parameters based on the qualified stress process parameters, and returning to the step a to re-determine the stress simulation parameters if all the parameters do not meet the requirements.
Preferably, the step F further comprises the step of applying the qualified penetration rate simulation parameters to the welding test, comparing the results of the test penetration rate and the standard penetration rate, eliminating the unqualified penetration rate simulation parameters, determining the proper welding process parameter range, and returning to the step D to re-determine the penetration rate simulation parameters if all the penetration rate simulation parameters are not qualified.
Preferably, the method for re-determining the stress simulation parameter and/or the drill penetration simulation parameter adopts a bisection method to obtain a middle value of an original parameter or an extrapolation method to obtain a larger value or a smaller value.
The eutectic welding parameter selection method based on stress-penetration rate sequential simulation provided by the invention has the advantages that: through carrying out the order simulation to stress, borer penetration rate, confirm process parameter and the material parameter that accords with the requirement gradually to carry out actual welding to the parameter that obtains to the simulation and verify, very big reduction experiment cost and material consumption, reduced the complexity of data operation, can confirm suitable welding parameter fast, improve the brazing quality.
Drawings
FIG. 1 is a flow chart of a eutectic welding parameter selection method based on stress-braze penetration sequence simulation provided by an embodiment of the present invention;
FIG. 2 is a diagram of a predicted welding residual stress result provided by an embodiment of the present invention
FIG. 3 is a graph showing the results of penetration prediction according to the embodiment of the present invention
FIG. 4 is a statistical chart of penetration results of different processes provided in the examples of the present invention
FIG. 5 is a graph showing the detection of the penetration rate of a sample actually manufactured by the preferred process according to the embodiment of the present invention
Detailed Description
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
As shown in fig. 1, the present embodiment provides a method for selecting parameters of a eutectic soldering process based on stress-penetration sequence simulation, which is described as eutectic soldering connection between a kovar alloy plate and a molybdenum-copper alloy plate, and the selected solder is Au80Sn 20; the method specifically comprises the following steps:
kovar plate size: 3.05mm 1.8mm 0.1 mm;
the size of the molybdenum-copper alloy plate is as follows: 3.8mm 2.4mm 0.5 mm;
solder (Au80Sn20) size: 3.05mm 1.8mm 0.05 mm.
Step A: determining the technological parameter range of eutectic brazing and setting a plurality of groups of stress simulation parameters;
based on the material type and size data selected in the embodiment, in order to ensure the reliability of the joint and establish a sufficient heat dissipation channel, it is necessary to ensure that the solder is completely liquefied, sufficiently spread and completely wet the surface of the parent metal to obtain a high penetration rate, and for Au80Sn20 solder, the melting point is about 280 ℃, and the thermal conductivity is 57 W.m-1·K-1(ii) a The range of the parameters of the eutectic brazing process preliminarily determined by the method comprises the maximum temperature of 290-320 ℃, the holding time of 10-20S, the welding pressure of 0-5g, the thickness of the solder of 0.04-0.08 mm, and the thickness of the solder selected by the embodiment of 0.05 mm.
Stress simulation parameters set based on the ranges are shown in table 1;
table 1: stress simulation process parameters
And B: building a geometric model based on dimensional data of welding materials and welding fluxes, and inputting the stress simulation parameters for simulation;
during specific operation, any known simulation software can be used for constructing an aggregate model, the finite element software ABAQUS or ANSYS is selected for constructing the aggregate model in the embodiment, and then stress simulation parameters are input for simulation, wherein the specific simulation calculation model is as follows:
wherein T is the solder temperature, the input value of the T at the initial moment is the highest temperature in the process parameters, T is the time corresponding to the holding time in the process parameters, epsilon is the solder strain, sigma is the residual stress after welding, F is the yield strength of the material, K is the isotropic hardening factor, sigma is the isotropic hardening factor0Stresses associated with hardening of the material; rho is solder density, c is solder specific heat capacity, kxIs the thermal conductivity in the x direction, kyIs the thermal conductivity in the y direction, kzIs the thermal conductivity in the z direction, V is the volume of the integration zone and S is the area of the integration zone. Carrying out simulation by using finite element software to calculate the residual stress sigma; the simulation result of the residual stress field obtained by simulation is shown in fig. 2.
And C: comparing the simulated residual stress with the standard stress, wherein the tensile strength of the solder Au80Sn20 used in the embodiment is 104MPa, so that the standard stress is set to be 104MPa, and if all simulation results do not meet the requirement of the standard stress, returning to the step A and re-determining stress simulation parameters; the method for re-determining the stress simulation parameters is to adopt a bisection method to obtain a middle value of the original stress simulation parameters or an extrapolation method to obtain a larger value or a smaller value.
Comparing with standard stress, selecting a simulation result meeting the stress requirement, and in order to ensure parameter effectiveness, the embodiment also comprises a step of using stress simulation parameters meeting the stress requirement to perform an actual welding test; referring to table 2, the groups 1 to 7 of the stress simulation parameters given in table 1 meet the requirements through simulation and actual tests, and the qualified process parameters of the stress confirmed based on this embodiment are welding temperature 300 ℃ to 320 ℃, heat preservation time 10S to 14S, and welding pressure 0 g.
Table 2: stress simulation and actual detection results
Step D: and setting a plurality of groups of simulation parameters of the penetration rate based on the stress qualified process parameter range, wherein the range of the determined simulation parameters comprises the solder temperature of 300-320 ℃, the heat preservation time of 10-14S, the welding pressure of 0g and the solder thickness of 0.05 mm.
The penetration simulation parameters set based on the ranges are shown in table 3;
table 3: simulation technological parameter of penetration rate of drill rod
Step E: inputting the penetration simulation parameter and the solder property parameter for simulation;
the material property parameters comprise density, viscosity, surface tension coefficient and melting point; specific values are shown in Table 4;
table 4: solder property parameters
The calculation model of the penetration simulation is as follows:
wherein the content of the first and second substances,
the flow rate of the molten solder is defined as ρ is the density of the solder and t isMu is viscosity, p is pressure, corresponding to welding pressure in the process parameters,
Is the gravity acceleration, T is the solder temperature, K is the Darcy factor when solidified,
Surface tension and thermal capillary force, c is specific heat of the solder, k is a thermal conductivity coefficient, and F is the volume fraction of the solder in each grid, wherein F is 0 to represent that the grids are all gas, and F is 1 to represent that the grids are all solder;
the penetration rate eta of the brazing rod is
Wherein, VgasV is the total volume of the region contained in the solder, and V is the total volume of the region where F is 0 inside the solder.
Through simulation, the distribution diagram of the air holes shown in fig. 3 and the simulation diagram of the penetration rate under different penetration rate simulation parameters shown in fig. 4 are calculated.
Step F: comparing the simulated penetration rate obtained by simulation with the standard penetration rate, wherein the result of the penetration rate is shown in FIG. 4, the standard penetration rate is set to 85% in the embodiment, and if all the penetration rates are unqualified, the step D is returned to re-determine the penetration rate simulation parameters; selecting qualified penetration rate simulation parameters, namely obtaining the parameter range of the eutectic brazing process qualified through simulation, and obtaining the simulation result of the 3 rd to 7 th parameters from the graph of figure 4 to meet the requirement of penetration rate.
Similarly, in the step of performing the actual welding test on the qualified penetration rate simulation parameters provided in this embodiment, the relationship between the penetration rate of the shell and the standard penetration rate is compared after welding, the unqualified penetration rate simulation parameters are removed, and the appropriate welding process parameter range is determined, and certainly, if all the penetration rate simulation parameters are not satisfactory, the step D needs to be returned to determine the penetration rate simulation parameters again. Referring to table 5, it can be seen that the brazing rates of the groups 6 and 7 are the best, and the welding time of the group 6 process is shorter than that of the group 7, so that the optimal parameters are combined into the group 6 process to improve the manufacturing efficiency.
| Serial number | The penetration rate of the drill rod is measured by experiments | Whether it meets the |
| 3 | 93.5％ | Is that |
| 4 | 95.6％ | Is that |
| 4 | 97.8 | Is that |
| 6 | 100％ | Is that |
| 7 | 100％ | Is that |
Table 5: stress simulation and actual detection results
In this embodiment, the optimal parameters selected based on the above method are temperature 315 ℃, welding time 12S, welding pressure 0g, and the parameters are used to perform a welding test and the result is detected, so as to obtain a braze penetration rate detection diagram shown in fig. 5.
Claims (8)
1. A eutectic welding parameter selection method based on stress-penetration rate sequential simulation is characterized by comprising the following steps: the method comprises the following steps:
step A: determining the technological parameter range of eutectic brazing and setting a plurality of groups of stress simulation parameters;
and B: building a geometric model based on dimensional data of welding materials and welding fluxes, and inputting the stress simulation parameters for simulation;
and C: comparing the simulated residual stress with the standard stress, selecting stress simulation parameters meeting the requirements, and determining the qualified process parameter range of the stress; if all simulation results do not meet the requirements of standard stress, returning to the step A, and re-determining stress simulation parameters;
step D: setting a plurality of groups of penetration simulation parameters based on the stress qualified process parameter range;
step E: inputting the penetration simulation parameter and the solder property parameter for simulation;
step F: and D, comparing the simulated penetration rate obtained by simulation with the standard penetration rate, selecting qualified penetration rate simulation parameters, and returning to the step D to re-determine the penetration rate simulation parameters if all the penetration rates are unqualified.
2. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 1, wherein: the stress simulation parameters in the step A comprise the highest eutectic welding temperature, the heat preservation time, the solder thickness and the welding pressure.
3. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 2, wherein: the calculation model for stress simulation in the step B is
Wherein T is solder temperature, the input value of the initial moment is the highest temperature in the process parameters, T is time corresponding to the holding time in the process parameters, epsilon is solder strain, sigma is residual stress after welding, F is yield strength of the material, K is isotropic hardening factor, sigma is the yield strength of the material, and0is the subsequent yield stress; rho is solder density, c is solder specific heat capacity, kxIs the thermal conductivity in the x direction, kyIs the thermal conductivity in the y direction, kzIs the thermal conductivity in the z direction, V is the volume of the integration zone and S is the area of the integration zone.
4. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 3, wherein: and E, the solder property parameters comprise density, viscosity, surface tension coefficient and melting point.
5. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 4, wherein: and E, performing penetration simulation on the drill rod by using a calculation model as follows:
wherein the content of the first and second substances,
in order to melt the flow rate of the solder, ρ is the density of the solder, t is the time, μ is the viscosity, p is the pressure, corresponding to the soldering pressure,
Is the gravity acceleration,T is the solder temperature, K is the Darcy factor at solidification,
Surface tension and thermal capillary force, c is specific heat capacity of the solder, k is a thermal conductivity coefficient, and F is volume fraction of the solder in each grid, wherein F is 0 to represent that the grids are all gas, and F is 1 to represent that the grids are all solder;
the penetration rate eta of the brazing rod is
Wherein, VgasV is the total volume of the region contained in the solder, and V is the total volume of the region where F is 0 inside the solder.
6. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 1, wherein: and step C, applying the stress simulation parameters meeting the requirements to a welding test, comparing the tested residual stress with the standard stress after the test, removing the parameters which do not meet the requirements, determining the range of the qualified process parameters of the stress based on the qualified process parameters of the stress, and returning to the step A to re-determine the stress simulation parameters if the parameters do not meet the requirements.
7. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation of claim 1, wherein: and step F, applying the qualified penetration rate simulation parameters to the welding test, comparing the results of the test penetration rate and the standard penetration rate, eliminating unqualified penetration rate simulation parameters, determining a proper welding process parameter range, and returning to the step D to re-determine the penetration rate simulation parameters if all the penetration rate simulation parameters are not in accordance with the requirements.
8. The eutectic welding parameter selection method based on stress-braze penetration sequence simulation according to any one of claims 1 to 7, wherein: the method for re-determining the stress simulation parameters and/or the penetration simulation parameters adopts a bisection method to obtain the middle value of the original parameters or an extrapolation method to obtain a larger value or a smaller value.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103273207A (en) * | 2013-04-12 | 2013-09-04 | 广东工业大学 | Press machine body welding deformation eliminating method based on residual stress quantitative analysis |
| CN104809291A (en) * | 2015-04-27 | 2015-07-29 | 江苏金通灵流体机械科技股份有限公司 | ANSYS-based duplex stainless steel and dissimilar steel welding deformation prediction method |
| JP2015188928A (en) * | 2014-03-28 | 2015-11-02 | 三菱日立パワーシステムズ株式会社 | Lifetime evaluation method and lifetime evaluation device |
| CN105965179A (en) * | 2016-06-01 | 2016-09-28 | 江苏科技大学 | Auxiliary programming system and method for hull welding technology |
| WO2016208204A1 (en) * | 2015-06-26 | 2016-12-29 | Neturen Co., Ltd. | Direct resistance heating simulation method |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103273207A (en) * | 2013-04-12 | 2013-09-04 | 广东工业大学 | Press machine body welding deformation eliminating method based on residual stress quantitative analysis |
| JP2015188928A (en) * | 2014-03-28 | 2015-11-02 | 三菱日立パワーシステムズ株式会社 | Lifetime evaluation method and lifetime evaluation device |
| CN104809291A (en) * | 2015-04-27 | 2015-07-29 | 江苏金通灵流体机械科技股份有限公司 | ANSYS-based duplex stainless steel and dissimilar steel welding deformation prediction method |
| WO2016208204A1 (en) * | 2015-06-26 | 2016-12-29 | Neturen Co., Ltd. | Direct resistance heating simulation method |
| CN105965179A (en) * | 2016-06-01 | 2016-09-28 | 江苏科技大学 | Auxiliary programming system and method for hull welding technology |
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