Liquid metal bearing surface laser processing technological parameter simulation optimization method

Abstract

The invention belongs to the technical field of machining process simulation optimization, and particularly discloses a liquid metal bearing surface laser machining process parameter simulation optimization method, which comprises the following steps of: constructing a temperature field model of femtosecond laser ablation liquid metal, and respectively carrying out single-factor simulation tests of energy density, equivalent pulse number and scanning number under the model to obtain a temperature field model of the femtosecond laser ablation liquid metal; therefore, the optimal energy density, the equivalent pulse number and the scanning frequency are determined by measuring the ablation effect parameter and the heat influence parameter under the simulation test, optimization of the femtosecond laser processing technology is achieved, and the femtosecond laser processing effect is guaranteed. Meanwhile, after the optimal energy density, the equivalent pulse number and the scanning number are obtained through a simulation test, an environmental factor multivariable test carried out under the process condition is added, so that the ablation effect and the ablation aging under different environmental conditions are evaluated, the adaptive environmental condition is determined, and efficient exertion of the optimal process condition can be ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of machining process simulation optimization, and specifically discloses a method for simulating and optimizing process parameters of laser machining of a liquid metal bearing surface. Background Art

[0002] Liquid metal bearings are bearings that use liquid metal as a lubricant. Liquid metal has extremely high thermal conductivity and low viscosity, and can provide excellent lubrication at high speeds while effectively conducting heat to prevent the bearing from overheating. This type of bearing is particularly suitable for high-speed, high-load mechanical equipment, such as modern CT machines and other medical equipment.

[0003] When using liquid metal bearings as lubricants, tiny grooves or holes need to be formed on the bearing surface to better store and distribute the liquid metal lubricant, ensuring that the lubricant can evenly cover the entire contact surface during high-speed rotation, reducing friction. This process is the process of surface texturing of liquid metal bearings.

[0004] Traditional methods for processing liquid metal bearing surface textures include mechanical processing, chemical corrosion, electrospark machining, and long-pulse laser processing. These methods have obvious disadvantages: First, the processing accuracy is insufficient, and it is difficult to achieve micron or nanometer-level fine textures, especially on hard materials (such as metal molybdenum). The processing error is large, which affects the ability to lubricate and store liquid metal. In addition, thermal effects are a major challenge. Laser and electrospark machining will form a heat-affected zone on the surface, resulting in material recasting, surface microcracks and thermal damage, thereby reducing the friction performance and durability of the bearing. At the same time, chemical corrosion will cause environmental pollution and put forward higher requirements for waste liquid treatment. In addition, traditional methods are difficult to control the uniformity and consistency of complex textures, have low processing efficiency, and are not suitable for large-area surface treatment. Summary of the invention

[0005] In order to solve the problems of low processing accuracy, large processing errors and significant heat-affected zones in the prior art, it is proposed here to use femtosecond laser technology to perform high-precision processing of liquid metal bearing surface textures. Femtosecond lasers have extremely short pulse widths and can achieve micron or even nanometer-level fine processing without producing significant heat-affected zones. However, the effect of femtosecond laser processing is affected by a variety of process parameters, including energy density, pulse frequency, and scanning speed. Different combinations of process parameters will lead to significant differences in processing effects, so determining the optimal process parameters is crucial to ensuring processing quality. To this end, the present invention proposes a method for simulating and optimizing process parameters for laser processing of liquid metal bearing surfaces, which aims to optimize femtosecond laser processing technology by constructing a simulation model and combining experimental data to evaluate the effects of different process parameter combinations on processing effects.

[0006] The objective of the present invention can be achieved by the following technical solution: A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing, comprising the following steps: (1) constructing a dual-temperature model of femtosecond laser processing of liquid metal, and predicting the ablation threshold of liquid metal by numerical simulation.

[0007] (2) A single-factor simulation test of energy density is performed based on the ablation threshold while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat-affected parameters under different energy densities are measured, where the ablation effect parameters include ablation performance parameters and ablation morphology parameters, to determine the optimal energy density.

[0008] (3) A single-factor simulation test of the equivalent pulse number is carried out while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat influence parameters under different equivalent pulse numbers are measured to determine the optimal equivalent pulse number.

[0009] (4) A single-factor simulation test of the number of scans is performed while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat impact parameters under different scan times are measured to determine the optimal scan times.

[0010] (5) Conduct multivariate tests on environmental factors under the process conditions of optimal energy density, equivalent pulse number, and scan number to evaluate the ablation effect and ablation time under different environmental conditions to determine the suitable environmental conditions.

[0011] The above-mentioned technical scheme provided by the embodiment of the present application has the following advantages compared with the prior art: 1. The present invention constructs a temperature field model of femtosecond laser ablation of liquid metal, and conducts single-factor simulation tests of energy density, equivalent number of pulses and number of scans under this model. By measuring the ablation effect parameters and heat influence parameters under the simulation test, the optimal energy density, equivalent number of pulses and number of scans are determined, thereby realizing the optimization of the femtosecond laser processing technology and facilitating the femtosecond laser processing effect.

[0012] 2. After obtaining the optimal energy density, equivalent pulse number and scanning times through simulation experiments, the present invention also adds a multivariate test of environmental factors under this process condition, thereby evaluating the ablation effect and ablation time under different environmental conditions to determine the suitable environmental conditions, which can ensure the efficient use of the optimal process conditions, help avoid process fluctuations caused by environmental changes, and improve the stability and reliability of the overall process. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0014] Figure 1 The present invention is a flowchart of the steps for implementing the method.

[0015] Figure 2 This is a linear fitting diagram of the ablation threshold test experiment of femtosecond laser ablation of metal molybdenum in the present invention.

[0016] Figure 3 This is the processing optical path diagram of the single factor process parameter test in the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention proposes a method for simulating and optimizing process parameters of liquid metal bearing surface laser processing, comprising the following steps: (1) constructing a dual-temperature model of femtosecond laser processing of liquid metal, and predicting the ablation threshold of the liquid metal through numerical simulation.

[0019] The dual-temperature model used to construct femtosecond laser processing of liquid metal is shown in the following process: In the model, it is assumed that the electrons and lattices of the liquid metal can be regarded as two independent thermal systems in a short period of time, and energy is exchanged between them through phonon-electron coupling.

[0020] The core equations of the model include the electron temperature equation and the lattice temperature equation, where the expression of the electron temperature equation is , in the model is the electron heat capacity, , represent the electronic and lattice temperatures respectively, is the electronic thermal conductivity, represents the acoustic-electric coupling coefficient, represents the laser heat source term, Represents the gradient operator.

[0021] The expression of the lattice temperature equation is , in the model represents the lattice heat capacity, represents the lattice thermal conductivity.

[0022] In the femtosecond laser ablation process, the laser heat source term can be expressed as , where Represents the reflectivity of the metal surface. represents the energy density, represents the radiation depth, Indicates the distance in the depth direction, Represents a natural constant.

[0023] It is important to know that during femtosecond laser processing, the electrons and lattices inside the material absorb and transfer energy at different time scales. Electrons quickly absorb laser energy within a femtosecond timeframe, while the lattice takes a longer time to respond to the electron energy transfer. Therefore, the traditional single-temperature model cannot accurately describe this rapid energy transfer process. The dual-temperature model can more accurately describe the energy transfer process between the femtosecond laser and the liquid metal by simulating the electron temperature separately. Since the pulse width of the femtosecond laser is extremely short, there is a significant time lag effect in the temperature changes of the electrons and the lattice. The dual-temperature model can better capture this non-equilibrium heat conduction process, thereby more accurately predicting the ablation behavior of the material.

[0024] Once again, it is important to know that the ablation threshold refers to the minimum laser energy density at which significant material removal begins. For liquid metal, the ablation threshold is a key parameter to ensure processing quality. If the laser energy is lower than the ablation threshold, the material will not be effectively removed; if the energy is too high, it may lead to excessive ablation, unnecessary heat-affected zones or material damage. Therefore, determining the ablation threshold under the dual-temperature model can provide a scientific basis for the selection of process parameters to ensure that the laser energy just reaches the critical point for material removal. This helps to achieve high-precision micro-nanostructure processing, avoid processing defects caused by insufficient or excessive energy, while minimizing the heat-affected zone and maintaining the microstructural integrity of the material.

[0025] Further applied to the above scheme, the ablation threshold of liquid metal is predicted as follows: the dual temperature model is solved by setting the initial conditions and boundary conditions, where the initial condition is that the temperature of the electron and the lattice are both the ambient temperature before laser irradiation. ,Right now The boundary condition is that the temperature distribution in the laser irradiation area can be obtained by the laser heat source term To describe, while outside the laser irradiation area, the temperature is kept at ambient temperature .

[0026] Gradually increasing the laser energy density in the numerical solution of the two-temperature model , and monitor the lattice temperature When the lattice temperature reaches the melting point of the liquid metal or evaporation temperature The energy density corresponding to the ablation threshold is , the specific calculation formula is ,in Represents a temperature distribution function that varies with time and spatial position.

[0027] It should be pointed out that the melting temperature of liquid metal refers to the temperature at which the liquid metal begins to undergo a phase change and enters a molten state.

[0028] The evaporation temperature of liquid metal refers to the temperature at which the material begins to transform directly from solid or liquid to gas, that is, evaporation occurs.

[0029] In the above-mentioned solution of the dual-temperature model, since the dual-temperature model is a set of nonlinear partial differential equations, numerical methods (such as finite difference method, finite element method, Monte Carlo simulation, etc.) are usually required to solve it.

[0030] The specific numerical solution steps include: Discretization: discretize time and space, and transform the continuous partial differential equation into discrete algebraic equation.

[0031] Iterative solution: The changes in electron temperature and lattice temperature are gradually solved through iterative algorithms (such as Runge-Kutta method, Euler method, etc.).

[0032] Convergence judgment: Set convergence conditions to ensure the accuracy and stability of the numerical solution.

[0033] Furthermore, after predicting the ablation threshold of liquid metal, it can also be verified through experiments. The specific operations are as follows: select laser equipment indicators suitable for liquid metal processing, where laser equipment indicators include laser wavelength, pulse width, repetition frequency, spot size, etc.

[0034] In the above examples, the laser wavelength can be 515 nm, 1030 nm or 266 nm, depending on the absorption characteristics of the material.

[0035] The pulse width is specifically to ensure that the laser pulse width is at the femtosecond level (usually 100fs to 1ps) to achieve a "cold ablation" effect and reduce the heat affected zone.

[0036] The repetition frequency can be selected according to the experimental requirements.

[0037] Spot size: Control the laser spot size (e.g. 10μm to 100μm) to ensure uniformity of the ablation area.

[0038] Fix the liquid metal sample on the sample stage, use laser alignment to ensure that the laser beam is accurately focused on the sample surface, and adjust the laser equipment indicators to meet the selected values.

[0039] The first ablation experiment was performed by controlling the energy density to be lower than the predicted ablation threshold, and keeping other process parameters unchanged. Then, the radius of the ablation area was measured after the ablation experiment.

[0040] It should be added that the radius of the ablated area can be measured using an optical microscope or a scanning electron microscope.

[0041] In the example of the above operation, the first ablation experiment starts below the predicted ablation threshold. Assuming the predicted ablation threshold is 0.4 J / cm², you can start at 0.1 J / cm².

[0042] After the first ablation experiment, the energy density was controlled to increase and the step length was set to conduct the next ablation experiment, and the radius of the ablation area corresponding to each ablation experiment was recorded.

[0043] The step size in the above setting can be 0.05J / cm².

[0044] The energy density and the radius of the ablation area corresponding to each ablation experiment are plotted in a coordinate system with the energy density as the horizontal axis and the radius of the ablation area as the vertical axis. A linear fit is performed on the plotted curve, and the slope is read from the fitting curve to calculate the experimental ablation threshold of the liquid metal.

[0045] It should be understood that the radial distribution of laser energy density in the spot can be expressed as According to this formula, we can deduce , where represents the ablation threshold of liquid metal material, Expressed as the ablation radius, represents the peak energy density, The distance from the center of the light spot is represents the spot radius, Indicates the distance from the center of the light spot The laser energy density at .

[0046] In the example of femtosecond laser ablation of metal molybdenum, the fitting and The linear relationship between Figure 2 shown.

[0047] The experimental ablation threshold of the liquid metal is compared with the predicted ablation threshold to calculate the proximity. Specifically, the experimental ablation threshold and the predicted ablation threshold can be subtracted by taking the absolute value and then divided by the experimental ablation threshold, and then the value 1 and the division result are subtracted to obtain the proximity. The calculated result is compared with the preset effective proximity. For example, the effective proximity is 0.8. If the proximity reaches the effective proximity, the experimental verification is successful. Otherwise, the ablation threshold verification experiment is repeated.

[0048] The factors that may affect the processing effect in femtosecond laser processing mainly include energy density, equivalent pulse number and repeated scanning times. The influence of these three parameters on the experimental results is independent of each other. The present invention conducts single factor experiments on the three parameters respectively. The specific processing optical path diagram is as follows: Figure 3 shown.

[0049] (2) A single-factor simulation test of energy density is performed based on the ablation threshold while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat-affected parameters under different energy densities are measured, where the ablation effect parameters include ablation performance parameters and ablation morphology parameters, to determine the optimal energy density.

[0050] In the preferred implementation of the above scheme, the single-factor simulation test of energy density based on the ablation threshold refers to the following process: the upper limit energy density is extracted from the curve of the change of ablation radius with energy density, thereby the ablation threshold and the upper limit energy density of the liquid metal constitute the energy density test range.

[0051] The above-mentioned upper and lower energy densities refer to the energy density at which the ablation effect reaches the expected maximum value. By way of example, the upper limit energy density extraction can perform a linear fit on the fast-growing segment of the ablation radius versus energy density curve. The slope of the fitting straight line will gradually decrease until it approaches zero. The upper limit energy density usually appears near the point where the slope decreases significantly.

[0052] As another example, if the ablation radius versus energy density curve is S-shaped, a Sigmoid function can be used for fitting. The specific function expression is: , where represents the maximum ablation radius, represents the growth rate, represents the upper limit energy density, represents the natural constant. By fitting the parameters The upper limit energy density can be obtained.

[0053] It should be noted that the energy density test interval covers the entire energy density range from when the liquid metal begins to be effectively removed to when the ablation effect is maximized.

[0054] Several single-point energy densities are obtained in the energy density test range according to the set step length, and each single-point energy density corresponds to an energy density test.

[0055] In each energy density test, ensure that the applied energy density meets the corresponding single-point energy density and keep other process parameters unchanged.

[0056] In a further preferred implementation of the above scheme, the ablation effect parameters and the heat influence parameters refer to the following measurement process: after the test, the ablation image is collected using a visual detection terminal, wherein the visual detection terminal can be an electron microscope, to ensure that the collected image can clearly display the edge contour and surface morphology of the ablation area, and the collected ablation image is edge detected by image processing software, thereby extracting the ablation depth and ablation width as ablation performance parameters.

[0057] Focus the lens of the visual inspection terminal on the surface of the ablation area to obtain a high-resolution surface morphology image, and use non-contact measurement technology such as white light interferometry or atomic force microscopy to calculate the surface roughness as the ablation morphology parameter.

[0058] It should be added that the surface roughness mentioned above can be the arithmetic mean variance or the root mean square roughness, which is dimensional. The unit of measurement is usually the unit of length, and its dimension reflects the height characteristics of the surface microstructure of the liquid metal material.

[0059] Ultrasonic waves are emitted to the ablation area, and the thickness of the heat-affected zone, the number of internal defects and residual stress are obtained as heat-affected parameters based on the intensity and propagation time of the reflected waves.

[0060] It should be added that the thickness of the heat-affected zone can be calculated based on the propagation speed of the ultrasonic wave in the material and the time difference of the reflected wave. This helps to evaluate the degree of heat diffusion during laser processing.

[0061] Internal defects can be identified by analyzing the intensity changes of reflected waves to determine whether there are cracks, holes or other microscopic defects in the heat affected zone and to count the number of internal defects, which helps to assess the integrity of the material and potential structural damage.

[0062] Residual stress can be evaluated in the heat affected zone by the phase change or propagation velocity change of ultrasonic waves. This helps to evaluate the mechanical properties of the material and possible stress concentration areas.

[0063] In a further preferred implementation of the above scheme, the optimal energy density is determined by referring to the following process: the ablation performance parameters under different energy densities are compared with the expected ablation performance parameters to calculate the ablation performance at different energy densities. The specific calculation formula is: , where Indicates that the ablation performance meets the standard. , Represent the ablation depth and ablation width respectively. , They represent the expected ablation depth and the expected ablation width, respectively.

[0064] Substituting the ablation performance and surface roughness at different energy densities into the formula Obtain the ablation effect coefficient at different energy densities , where Indicates the surface roughness, Indicates the allowable surface roughness.

[0065] The heat effect parameters under different energy densities are expressed as Calculate the heat impact coefficient at different energy densities , where , , They represent the thickness of the heat affected zone, the number of internal defects in the heat affected zone, and the residual stress, respectively. , , They represent the allowable thickness of the heat affected zone, the allowable number of internal defects in the heat affected zone, and the allowable residual stress. Represents a natural constant.

[0066] It should be pointed out that the expected ablation performance parameters, allowable surface roughness, allowable heat-affected zone thickness, allowable number of internal defects in the heat-affected zone, and allowable residual stress mentioned above can be based on experimental design and material properties reference.

[0067] It should be explained that when calculating the ablation effect coefficient and the heat influence coefficient, these values ​​are amplified by multiplying the calculation results by 10. This amplification process can avoid the problem of unclear or difficult to interpret curves due to the original calculation results being too small.

[0068] The ablation effect coefficient and the heat influence coefficient under different energy densities are respectively used to generate an ablation effect curve and a heat influence curve in a coordinate system with energy density as the horizontal axis and the ablation effect coefficient and the heat influence coefficient as the vertical axis.

[0069] The energy density comparison corresponding to the maximum ablation effect coefficient and the minimum heat influence coefficient is captured in the ablation effect curve and the heat influence curve respectively to identify whether they are close. If they are close, the average of the two energy densities is taken as the optimal energy density. If they are not close, it is judged whether there is an intersection between the ablation effect curve and the heat influence curve. If there is an intersection, the energy density corresponding to the intersection in the curve is taken as the optimal energy density. If there is no intersection, the change rate of the ablation effect curve and the heat influence curve is obtained respectively, and then the absolute value of the change rate is used as the weight factor of the ablation effect coefficient and the heat influence coefficient. Therefore, the ablation effect coefficient and the heat influence coefficient under different energy densities are combined with the weight factor to perform weighted average calculation to obtain the ablation performance under different energy densities, and then the energy density corresponding to the maximum ablation performance is taken as the optimal energy density.

[0070] It should be added that the above-mentioned curve change rate refers to the slope of the curve at each energy density.

[0071] It should be further added that 10-minimum heat impact coefficient is used when performing weighted average calculation of ablation performance. This is because the smaller the heat impact coefficient, the better the ablation performance.

[0072] In the above, to identify whether the energy densities corresponding to the maximum ablation effect coefficient and the minimum heat influence coefficient are close, the difference between the energy densities corresponding to the maximum ablation effect coefficient and the minimum heat influence coefficient can be taken as the absolute value and then divided by the energy density corresponding to the maximum ablation effect coefficient, and then the value 1 is subtracted from the division result to obtain the proximity, and compared with the preset effective proximity. When the effective proximity is reached, it is identified as close, otherwise it is identified as not close.

[0073] It should be understood that when the energy densities corresponding to the maximum ablation effect coefficient and the minimum thermal influence coefficient are close, the average of the two can be directly taken as the optimal energy density. In this case, the energy density can minimize the thermal influence while ensuring the best ablation effect. When the two are not close, it is necessary to further analyze whether there is an intersection. If there is an intersection, the energy density corresponding to the intersection is used as the optimal energy density. The existence of the intersection means that at this energy density, the ablation effect and thermal influence have reached the best balance. When there is no intersection, the rate of change needs to be introduced as a weighting factor. This is because the rate of change reflects the degree of influence of energy density on the ablation effect and thermal influence.

[0074] (3) A single-factor simulation test of the equivalent pulse number is carried out while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat influence parameters under different equivalent pulse numbers are measured to determine the optimal equivalent pulse number.

[0075] (4) A single-factor simulation test of the number of scans is performed while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat impact parameters under different scan times are measured to determine the optimal scan times.

[0076] The above process of determining the optimal equivalent pulse number and the optimal scanning number is similar to the process of determining the optimal energy density.

[0077] It should be emphasized that the environmental conditions need to be consistent when conducting single-factor experiments on energy density, equivalent pulse number and scan number.

[0078] (5) Conduct multivariate tests on environmental factors under the process conditions of optimal energy density, equivalent pulse number, and scan number to evaluate the ablation effect and ablation time under different environmental conditions to determine the suitable environmental conditions.

[0079] Preferably, the multivariate test of environmental factors is implemented as follows: the environmental factors to be tested are selected, and the test level of each environmental factor is determined.

[0080] Common environmental factors mentioned above include but are not limited to temperature, humidity, air pressure, etc. For each selected environmental factor, determine its test level (i.e. different values), usually three levels (low, medium, high) are selected to capture nonlinear effects. For example: temperature: 20°C, 25°C, 30°C; humidity: 30%, 50%, 70%; air pressure: standard atmospheric pressure, 0.8 times standard atmospheric pressure, 1.2 times standard atmospheric pressure.

[0081] One test level is selected from the test levels of each environmental factor in turn and combined to form several environmental level groups.

[0082] In the above example where there are 3 environmental factors and each environmental factor has 3 levels, there will be a total of 27 environmental level groups.

[0083] When conducting environmental tests, the environmental conditions in the test are controlled to meet the environmental conditions in the corresponding environmental level group, and the environmental tests are carried out under the process conditions of optimal energy density, equivalent pulse number and scanning number under control.

[0084] Further preferably, the evaluation of the ablation effect and ablation time under different environmental conditions is implemented as follows: measuring ablation effect parameters under different environmental level group tests, thereby calculating ablation effect coefficients corresponding to the different environmental level group tests.

[0085] The ablation time was measured under different environmental level group tests and substituted into the formula Obtain the ablation time coefficient corresponding to the test of different environmental level groups , where Indicates the ablation time, It represents the sum of the ablation time under all environmental level group tests.

[0086] Furthermore, the adaptive environmental conditions are determined as follows: the ablation effect coefficient and ablation time-effect coefficient corresponding to the tests of different environmental level groups are compared, and the environmental level groups corresponding to the maximum ablation effect coefficient and the ablation time-effect coefficient are extracted respectively, and it is analyzed whether they are the same environmental level group. If they are the same environmental level group, the environmental level corresponding to the environmental level group is taken as the adaptive environmental condition. If they are not the same environmental level group, the ablation effect coefficient and the ablation time-effect coefficient corresponding to the tests of different environmental level groups are comprehensively evaluated, and then the environmental level corresponding to the environmental level group to which the maximum comprehensive evaluation belongs is taken as the adaptive environmental condition.

[0087] It needs to be explained that when the maximum ablation effect coefficient and the minimum ablation aging coefficient correspond to the same environmental level group, then the environmental level group can be directly used as the adaptation environmental condition. This shows that under this condition, both the best ablation effect and the highest ablation efficiency can be obtained. If the maximum ablation effect coefficient and the minimum ablation aging coefficient correspond to different environmental level groups, it means that there is a trade-off between the two aspects. At this time, we cannot simply choose one of the environmental conditions, but need to conduct further comprehensive evaluation to find the optimal balance point. Specifically, the comprehensive evaluation can set the weight factors of the ablation effect coefficient and the ablation aging coefficient. If the ablation quality is critical, the ablation effect should be given a higher weight; if production efficiency is the main concern, the ablation aging should be given a higher weight.

[0088] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing, characterized in that: The following steps are involved: (1) Construct a dual-temperature model for femtosecond laser processing of liquid metal and predict the ablation threshold of liquid metal through numerical simulation; (2) A single-factor simulation test of energy density is performed based on the ablation threshold while keeping other process parameters unchanged. After the test, the ablation effect parameters and heat-affected parameters under different energy densities are measured, where the ablation effect parameters include ablation performance parameters and ablation morphology parameters, to determine the optimal energy density. (3) Carry out a single factor simulation test of equivalent pulse number while keeping other process parameters unchanged, and measure the ablation effect parameters and heat influence parameters under different equivalent pulse numbers after the test to determine the optimal equivalent pulse number; (4) Carry out a single factor simulation test on the number of scans while keeping other process parameters unchanged, and measure the ablation effect parameters and heat impact parameters under different scan times after the test to determine the optimal scan times; (5) Conduct multivariate tests on environmental factors under the process conditions of optimal energy density, equivalent pulse number, and scan number to evaluate the ablation effect and ablation time under different environmental conditions to determine the suitable environmental conditions.

2. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 1, characterized in that: The dual-temperature model for femtosecond laser processing of liquid metal is constructed as follows: In the model, it is assumed that the electrons and lattice of the liquid metal can be regarded as two independent thermal systems for a short time, and energy is exchanged between them through phonon-electron coupling; The core equations of the model include the electron temperature equation and the lattice temperature equation, where the expression of the electron temperature equation is , in the model is the electron heat capacity, , represent the electronic and lattice temperatures respectively, is the electronic thermal conductivity, represents the acoustic-electric coupling coefficient, represents the laser heat source term, represents the gradient operator; The expression of the lattice temperature equation is , in the model represents the lattice heat capacity, represents the lattice thermal conductivity; In the femtosecond laser ablation process, the laser heat source term can be expressed as , where Represents the reflectivity of the metal surface. represents the energy density, represents the radiation depth, Indicates the distance in the depth direction, Represents a natural constant.

3. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing as claimed in claim 2, characterized in that: The prediction of the ablation threshold of liquid metal is implemented as follows: The dual-temperature model is solved by setting initial conditions and boundary conditions, where the initial condition is that the temperature of the electrons and the lattice are both at ambient temperature before laser irradiation. ,Right now ; The boundary condition is that the temperature distribution in the laser irradiation area can be obtained by the laser heat source term To describe, while outside the laser irradiation area, the temperature is kept at ambient temperature ; Gradually increasing the laser energy density in the numerical solution of the two-temperature model , and monitor the lattice temperature When the lattice temperature reaches the melting point of the liquid metal or evaporation temperature The energy density corresponding to the ablation threshold is , the specific calculation formula is ,in Represents a temperature distribution function that varies with time and spatial position.

4. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 1, characterized in that: The predicted ablation threshold of the liquid metal can be verified by experiments, and the specific operations are as follows: Indications for selecting laser equipment suitable for liquid metal processing; Fix the liquid metal sample on the sample stage, use laser alignment to ensure that the laser beam is accurately focused on the sample surface, and adjust the laser equipment indicators to meet the selected values; The energy density is controlled to be lower than the predicted ablation threshold to start the first ablation experiment, and other process parameters are kept unchanged, and then the radius of the ablation area is measured after the ablation experiment; After the first ablation experiment, the energy density is controlled to increase and the step length is set to conduct the next ablation experiment, and the radius of the ablation area corresponding to each ablation experiment is recorded; The energy density and the radius of the ablation area corresponding to each ablation experiment are plotted in a coordinate system with the energy density as the horizontal coordinate and the radius of the ablation area as the vertical coordinate. A linear fit is performed on the plotted curve, and then the slope is read from the fitting curve to calculate the experimental ablation threshold of the liquid metal. The experimental ablation threshold of the liquid metal is compared with the predicted ablation threshold to calculate the proximity, and compared with the preset effective proximity. If the proximity reaches the effective proximity, the experimental verification is successful, otherwise the ablation threshold verification experiment is carried out again.

5. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing as claimed in claim 4, characterized in that: The single factor simulation test of energy density based on ablation threshold is as follows: The upper limit energy density is extracted from the curve of ablation radius changing with energy density, and thus the ablation threshold of liquid metal and the upper limit energy density constitute the energy density test range; In the energy density test range, a number of single-point energy densities are obtained according to the set step length, and each single-point energy density corresponds to an energy density test; In each energy density test, ensure that the applied energy density meets the corresponding single-point energy density and keep other process parameters unchanged.

6. The method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 1, characterized in that: The ablation effect parameters and heat influence parameters refer to the following measurement process: After the test, the visual detection terminal is used to collect the ablation image, and the ablation depth and ablation width are extracted from the image as ablation performance parameters; The visual inspection terminal is focused on the surface topography image of the ablation area, and the surface roughness is extracted as the ablation topography parameter; Ultrasonic waves are emitted to the ablation area, and the thickness of the heat-affected zone, the number of internal defects and residual stress are obtained as heat-affected parameters based on the intensity and propagation time of the reflected waves.

7. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 6, characterized in that: The optimal energy density is determined by referring to the following process: The ablation performance parameters at different energy densities are compared with the expected ablation performance parameters to calculate the ablation performance at different energy densities. The specific calculation formula is: , where Indicates that the ablation performance meets the standard. , Represent the ablation depth and ablation width respectively. , They represent the expected ablation depth and the expected ablation width respectively; Substituting the ablation performance and surface roughness at different energy densities into the formula Obtain the ablation effect coefficient under different energy densities , where Indicates the surface roughness, Indicates the allowable surface roughness; The heat effect parameters under different energy densities are expressed as Calculate the heat impact coefficient at different energy densities , where , , They represent the thickness of the heat affected zone, the number of internal defects, and the residual stress, respectively. , , They represent the allowable thickness of the heat affected zone, the allowable number of internal defects in the heat affected zone, and the allowable residual stress. represents a natural constant; The ablation effect coefficient and the heat influence coefficient under different energy densities are respectively used to generate an ablation effect curve and a heat influence curve in a coordinate system with energy density as the horizontal axis and ablation effect coefficient and heat influence coefficient as the vertical axis; The energy density comparison corresponding to the maximum ablation effect coefficient and the minimum heat influence coefficient is captured in the ablation effect curve and the heat influence curve respectively to identify whether they are close. If they are close, the average of the two energy densities is taken as the optimal energy density. If they are not close, it is judged whether there is an intersection between the ablation effect curve and the heat influence curve. If there is an intersection, the energy density corresponding to the intersection in the curve is taken as the optimal energy density. If there is no intersection, the change rate of the ablation effect curve and the heat influence curve is obtained respectively, and then the absolute value of the change rate is used as the weight factor of the ablation effect coefficient and the heat influence coefficient. Therefore, the ablation effect coefficient and the heat influence coefficient under different energy densities are combined with the weight factor for weighted average calculation to obtain the ablation performance under different energy densities, and then the energy density corresponding to the maximum ablation performance is taken as the optimal energy density.

8. The method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 1, characterized in that: The multivariate test of environmental factors is implemented as follows: Select the environmental factors that need to be tested and determine the test level for each environmental factor; Select one test level from the test levels of each environmental factor in turn and combine them to form several environmental level groups; When conducting environmental tests, the environmental conditions in the test are controlled to meet the environmental conditions in the corresponding environmental level group.

9. A method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 8, characterized in that: The evaluation of the ablation effect and ablation aging under different environmental conditions is carried out as follows: The ablation effect parameters were measured under different environmental level group tests, and the ablation effect coefficient was calculated accordingly; The ablation time was measured under different environmental level group tests and substituted into the formula Obtain the ablation time coefficient corresponding to the test of different environmental level groups , where Indicates the ablation time, It represents the sum of the ablation time under all environmental level group tests.

10. The method for simulating and optimizing process parameters of liquid metal bearing surface laser processing according to claim 9, characterized in that: The process of determining the adaptation environment conditions is as follows: The ablation effect coefficient and ablation time-effect coefficient corresponding to the tests in different environmental level groups are compared, and the environmental level groups corresponding to the maximum ablation effect coefficient and ablation time-effect coefficient are extracted respectively to analyze whether they are the same environmental level group. If they are the same environmental level group, the environmental level corresponding to the environmental level group is taken as the adaptive environmental condition. Otherwise, the ablation effect coefficient and ablation time-effect coefficient corresponding to the tests in different environmental level groups are comprehensively evaluated, and then the environmental level corresponding to the environmental level group to which the maximum comprehensive evaluation belongs is taken as the adaptive environmental condition.

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