A method and system for optimizing process parameters of laser or ultrasonic vibration assisted milling

Abstract

The present application belongs to the technical field of multi-energy field assisted cutting machining, and discloses a method and system for optimizing laser or ultrasonic vibration assisted milling machining process parameters. The method comprises the following steps: S1, calculating the total stress of the workpiece end in laser or ultrasonic vibration assisted milling machining; S2, using the total stress of the workpiece end to solve the stress and the corresponding equivalent stress borne by the reinforcing particles in the workpiece; S3, calculating the current damage probability of the reinforcing particles, comparing the current damage probability with the preset critical damage probability, and when the current damage probability is less than or equal to the preset critical damage probability, determining the machining parameters in the laser or ultrasonic vibration assisted milling machining according to the current cutting force and cutting temperature; otherwise, adjusting the preset cutting force and cutting temperature, returning to step S1 until the current damage probability is less than or equal to the preset critical damage probability. Through the present application, low-damage machining of complex trajectory particle reinforced metal matrix composites is realized.

Description

Technical Field

[0001] This invention belongs to the technical field of multi-energy field assisted cutting, and more specifically, relates to a method and system for optimizing process parameters of laser or ultrasonic vibration assisted milling. Background Technology

[0002] The application of particle-reinforced metal matrix composites in key components of aerospace and military applications is becoming increasingly widespread. As the requirements for high-quality and high-efficiency manufacturing of major equipment become increasingly stringent, multi-energy-field assisted manufacturing processes, such as laser-assisted cutting and ultrasonic-assisted cutting, offer breakthroughs for achieving near-zero-damage machining. Utilizing energy fields such as heat and vibration to alter the physical and mechanical properties of materials in the area to be processed improves material machinability and is currently a hot topic in international advanced manufacturing technology research, as well as an important component of intelligent manufacturing technology.

[0003] The presence of reinforcing particles significantly increases the processing difficulty of particle-reinforced metal matrix composites. Conventional cutting processes suffer from rapid tool wear and low processing efficiency, and the workpiece surface often exhibits a processing damage layer composed of defects such as cracks, pits, and holes, failing to meet the requirements for component use. Therefore, subsequent grinding and polishing processes of more than 12 hours are still required to remove the processing damage layer. Multi-energy field assisted cutting technology has the technical advantages of high efficiency and low damage. Lasers soften the matrix material and interface by heating, thereby improving the material flowability in the cutting area and greatly improving the cutting efficiency and processing quality. Currently, in conventional laser-assisted cutting processes, the laser is usually fixed on the spindle, the laser spot size is fixed, and it moves simultaneously with the spindle. Under this heating method, the heat-affected zone at the workpiece end exhibits an uneven distribution with a high temperature in the middle and a low temperature on both sides, affecting the consistency of damage. Moreover, it can usually only use fixed tools or processing parameters, resulting in poor processing flexibility and inability to perform complex trajectory machining. It is generally only suitable for linear machining with a fixed cutting width. By combining a galvanometer with a laser, a galvanometer-type laser-assisted heating method is introduced. Combined with the machine tool feed motion, the material in the area to be processed is heated and modified in front of the tool in the form of small spot and line scanning. This solves the problem of limited preheating area, energy distribution range and uniformity under the above conventional heating methods.

[0004] Meanwhile, ultrasonic vibration reduces crack propagation in particles through high-frequency vibration cutting, thereby reducing the damage depth of the workpiece surface. The laser-ultrasonic vibration coupling method combines the characteristics of both energy fields, resulting in highly efficient and extremely low-damage machining. Currently, no platform can simultaneously meet the requirements of real-time in-situ information acquisition during the cutting process under laser galvanometer and ultrasonic coupling assisted machining conditions. Furthermore, the two-dimensional spatial laser heating method combining galvanometer and laser allows for matching different cutting tools and machining parameters according to the structural characteristics of the workpiece, ensuring the uniformity and consistency of the heated area. Therefore, there is an urgent need to invent a device and process method for low-damage machining of particle-reinforced metal matrix composites, suitable for low-damage machining of particle-reinforced metal matrix composites with complex trajectories, guiding the selection of process parameters to maximize the reduction of workpiece surface damage depth. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a method and system for optimizing the process parameters of laser or ultrasonic vibration assisted milling, and solves the problem of optimizing process parameters in the processing of particle-reinforced metal matrix composites.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for optimizing process parameters in laser or ultrasonic vibration-assisted milling is provided, the method comprising the following steps:

[0007] In laser or ultrasonic vibration assisted milling, S1 calculates the mechanical stress and thermal stress on the workpiece end using preset cutting force and cutting temperature, and sums the mechanical stress and thermal stress to obtain the total stress on the workpiece end.

[0008] S2 uses the total stress at the workpiece end to solve for the stress and corresponding equivalent stress borne by the reinforcing particles in the workpiece;

[0009] S3 calculates the current damage probability of the reinforcing particles using the equivalent stress of the reinforcing particles, compares the current damage probability with the preset critical damage probability, and determines the processing parameters in laser or ultrasonic vibration assisted milling based on the current cutting force and cutting temperature. These processing parameters are the optimal processing parameters. Otherwise, the preset cutting force and cutting temperature are adjusted, and the process returns to step S1 until the current damage probability is less than or equal to the preset critical damage probability.

[0010] More preferably, in step S1, the formula for calculating the mechanical stress is as follows:

[0011]

[0012] in,( x s , zs () represents the coordinates of a point on the workpiece in the shear plane coordinate system. Let x represent the mechanical stress components in the x-direction of the shear plane coordinate system. Let z be the mechanical stress component in the z-direction of the shear plane coordinate system. Let x and z be the mechanical stress components in the shear plane coordinate system. l s The length of the shear plane. q s and p s These are the normal stress and tangential stress on the shear plane, respectively.

[0013] More preferably, in step S2, the formula for calculating the thermal stress is as follows:

[0014]

[0015] Where (x,z) are the coordinates of a point on the workpiece in the workpiece coordinate system. Let x be the thermal stress component in the x-direction of the workpiece coordinate system. Let Z be the thermal stress component in the z-direction of the workpiece coordinate system. Let be the thermal stress components in the x and z directions of the workpiece coordinate system, α be the thermal diffusivity of the material, E be the elastic modulus of the material, ν be the Poisson's ratio of the material, and T(x,z) be the temperature distribution in the x and z directions of the workpiece. , and These represent the corresponding responses in the x, z, and xz directions after a unit load is applied along the horizontal direction. , and These represent the corresponding responses in the x, z, and xz directions after a unit load is applied along the vertical direction. g (s) represents the hydrostatic pressure at that coordinate position.

[0016] More preferably, in step S1, the formula for calculating the total stress at the workpiece end is as follows:

[0017]

[0018] Where (x,z) are the coordinates of a point on the workpiece in the workpiece coordinate system. Let x represent the total stress component in the x-direction of the workpiece coordinate system. Let Z be the total stress component in the z-direction of the workpiece coordinate system. Let be the total stress component in the y-direction in the workpiece coordinate system. Let x be the total stress components in the xz direction of the workpiece coordinate system. The total stress components in the xy direction in the workpiece coordinate system. Let α be the total stress component in the yz direction in the workpiece coordinate system, E be the material's thermal expansion coefficient, E be the material's elastic modulus, ν be the material's Poisson's ratio, and T(x,z) be the temperature distribution in the x and z directions of the workpiece.

[0019] More preferably, in step S2, the formula for calculating the stress borne by the reinforcing particles is as follows:

[0020]

[0021] in, The stress borne by the particles Total stress at the workpiece end This represents the volume fraction of the particles. Let the stiffness tensor of the matrix be... For Eshelby tensors, It is the identity matrix. The transformation strain of the matrix material. Let be the stiffness tensor of the particle. is the coefficient of thermal expansion of the particles. The coefficient of thermal expansion of the matrix is ​​denoted as . This represents the temperature difference.

[0022] More preferably, in step S2, the formula for calculating the equivalent stress borne by the reinforcing particles is as follows:

[0023]

[0024] in, The equivalent stress borne by the particles. , , , , and The stress borne by the particles The stress matrix has components in X, Y, Z, XY, YZ, and XZ.

[0025] More preferably, in step S3, the formula for calculating the enhanced particle damage probability is as follows:

[0026]

[0027] in, Let be the probability of particle breakage. For particle equivalent stress, The reference fracture stress for the particles, For particle reference diameter, denoted as particle diameter, and m as the Weibull coefficient.

[0028] More preferably, in step S3, the processing parameters include laser power, laser scanning speed, ultrasonic amplitude, spindle speed, and feed rate.

[0029] According to another aspect of the present invention, a laser or ultrasonic vibration-assisted milling machining system for optimizing machining process parameters using the above-described optimization method is provided. The machining system includes a milling machining unit, a laser-assisted unit, an ultrasonic vibration-assisted unit, and an in-situ acquisition and control unit, wherein:

[0030] The milling unit is used to process the workpiece;

[0031] The laser-assisted unit is used to soften the workpiece using a laser while milling;

[0032] The ultrasonic vibration auxiliary unit is used to soften the workpiece by ultrasonic vibration during milling.

[0033] The in-situ acquisition and control unit includes an in-situ information recognition module and a control module. The in-situ information recognition module is used to acquire the processing parameters of the processing process and optimize the acquired processing parameters. At the same time, it generates corresponding processing instructions based on the optimized processing parameters and feeds them back to the control module. The control module is used to control the processing of the milling unit, the laser-assisted unit, and the ultrasonic vibration-assisted unit according to the instructions issued by the in-situ information recognition module.

[0034] According to another aspect of the present invention, a process method for machining using the laser or ultrasonic vibration-assisted milling system described above is provided, the process method comprising:

[0035] The selection of one or a combination of two of the laser-assisted unit and the ultrasonic vibration-assisted unit as auxiliary processing depends on the material of the workpiece.

[0036] The in-situ acquisition and control unit determines the optimal machining process parameters and controls the milling unit, laser-assisted unit, and ultrasonic vibration-assisted unit to perform machining according to the optimal machining parameters.

[0037] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0038] 1. The process parameter optimization method adopted in this invention calculates the equivalent stress of the reinforcing particles by calculating the total stress at the workpiece end, then calculates the damage probability using the equivalent stress, and finally adjusts the processing parameters using the damage probability. This helps to reduce the depth of workpiece processing damage and achieve low-damage processing of particle-reinforced metal matrix composites.

[0039] 2. This invention utilizes the equivalent stress of reinforcing particles to calculate the damage probability and then determine the subsurface particle damage depth, which is beneficial for understanding particle damage phenomena in particle-reinforced metal matrix composites and guides the selection of process parameters for low-damage processing.

[0040] 3. This invention uses a combination of laser and galvanometer to heat the workpiece, which solves the problems of limited preheating area, energy distribution range and uniformity under traditional laser heating methods. At the same time, the combination of coaxial positioning and temperature feedback module helps to ensure the consistency of the laser heating area under free trajectory conditions.

[0041] 4. This invention couples the laser energy field and the ultrasonic vibration energy field to the same processing platform, which can simultaneously realize laser-assisted cutting, ultrasonic vibration-assisted cutting, and laser-ultrasonic-assisted cutting, combining the advantages of both laser-assisted and ultrasonic vibration-assisted cutting, and is conducive to selecting the optimal processing method according to processing requirements.

[0042] 5. The process method provided by this invention takes into account the structural characteristics of materials and components, and combines damage depth prediction with intelligent algorithms to achieve reverse optimization of process parameters, thereby realizing low-damage processing of particle-reinforced metal matrix composites. Attached Figure Description

[0043] Figure 1 This is a process parameter optimization flow constructed according to a preferred embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of a low-damage processing apparatus for particle-reinforced metal matrix composites constructed according to a preferred embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of a laser-assisted unit structure constructed according to a preferred embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of an ultrasonic vibration auxiliary unit constructed according to a preferred embodiment of the present invention;

[0047] Figure 5 This is a schematic diagram of the laser galvanometer heating trajectory constructed according to a preferred embodiment of the present invention, and its advantages in temperature distribution compared with conventional laser heating. In this diagram, (a) is the laser spot trajectory of galvanometer laser preheating, (b) is the laser spot trajectory of conventional laser preheating, (c) is the surface temperature distribution of the workpiece under galvanometer laser preheating, and (d) is the surface temperature distribution of the workpiece under conventional laser preheating.

[0048] In all the accompanying drawings, the same reference numerals are used to denote the same elements or structures, wherein:

[0049] 1-In-situ information recognition module, 2-Floor-mounted mineral casting bed, 3-Three-axis high-precision motion module, 4-Spindle module, 5-Ultrasonic tool holder, 6-Tool, 7-Galvanometer module, 8-Laser, 9-UW-axis precision motion guide rail, 10-Coupled interface, 11-Coaxial positioning and temperature feedback module, 12-Control module. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0051] Reference Figures 2-5 This invention provides a device for low-damage processing of particle-reinforced metal matrix composites, comprising a milling unit, a laser-assisted unit, an ultrasonic vibration-assisted unit, and an in-situ acquisition and control unit, wherein...

[0052] In one embodiment of the present invention, the milling unit includes a floor-mounted mineral casting bed 2, a three-axis high-precision motion module 3, and a spindle module 4. The three-axis precision motion module 3 is respectively installed in the X, Y, and Z directions of the floor-mounted mineral casting bed 2, and the spindle module 4 is installed in the Z direction of the three-axis precision motion module 3. Figure 3 As shown;

[0053] In one embodiment of the present invention, the laser-assisted unit includes a laser 8, a coupling interface 10, a galvanometer module 7, and a coaxial positioning and temperature feedback module 11. The laser 8, galvanometer module 7, and coaxial positioning and temperature feedback module 11 are connected through the coupling interface 10. The coupling interface 10 ensures that the measurement optical path of the coaxial positioning and temperature feedback module 11 is coaxial with the laser optical path. Figure 3 As shown;

[0054] In one embodiment of the present invention, the ultrasonic vibration auxiliary unit includes an ultrasonic tool holder 5 and a cutting tool 6. The cutting tool 6 is mounted on the ultrasonic tool holder 5, and the ultrasonic tool holder 5 is mounted on the spindle module 4 for cutting operations, such as... Figure 4 As shown;

[0055] In one embodiment of the present invention, the in-situ acquisition and control unit includes an in-situ information identification module 1 and a control module 12. The control module 12 is used to control the laser energy field, the ultrasonic vibration energy field and the cutting process, optimize the processing parameters according to the physical signals acquired by the in-situ information identification module 1 and issue corresponding processing commands.

[0056] In one embodiment of the present invention, the laser-assisted unit is provided with a UW-axis precision motion guide rail 9. The laser-assisted unit is mounted on the floor-mounted mineral casting bed 2 via the UW-axis precision motion guide rail 9 and is located next to the spindle module 4. It is used to adjust the size of the laser spot and the relative position of the laser spot and the tool 6.

[0057] In one embodiment of the present invention, the galvanometer module 7 enables the laser spot to perform rapid two-dimensional scanning on the workpiece surface, achieving uniform heating of any workpiece area for different structural features of the parts and different types of cutting tools. Figure 5 This indicates that compared with conventional linear laser heating, the galvanometer-type laser heating method can achieve a more uniform temperature distribution. The coaxial positioning and temperature feedback module can track the laser spot position in real time to determine the trajectory position of the laser spot. At the same time, the temperature at the heating position is measured in real time through a measurement optical path coaxial with the laser beam, and then compared with the predefined target temperature. The feedback control signal adjusts the laser power to ensure the uniformity and consistency of the temperature in the entire laser heating area.

[0058] In one embodiment of the present invention, the in-situ information identification module 1 can collect force, temperature and deformation data of the cutting area during the machining process in real time, so as to optimize the machining parameters.

[0059] A process method for low-damage processing of the above-mentioned particle-reinforced metal matrix composite material includes the following steps:

[0060] (1) Determine the type of auxiliary energy field according to the type of processing material and processing conditions, and adjust each module to the corresponding position;

[0061] (2) Optimize processing parameters based on the physical quantities collected by the in-situ information identification module;

[0062] (3) The optimized processing parameters are sent to each unit by the control module to complete the low-damage processing of particle-reinforced metal matrix composites.

[0063] Furthermore, the laser energy field is mainly used to soften the metal matrix and interface strength, while ultrasonic vibration assistance can reduce the propagation of particle cracks and achieve particle refinement and removal. Therefore, different energy fields need to be selected for auxiliary processing for different material types. For low volume fraction particle-reinforced metal matrix composites, a laser-assisted unit can be selected to soften the metal matrix. For high volume fraction particle-reinforced metal matrix composites, an ultrasonic vibration assistance unit and a laser-ultrasonic coupling assistance unit can be selected. The volume fraction range that distinguishes between high and low volume fractions is determined by using 50% volume fraction as the criterion. A volume fraction higher than 50% is considered high volume fraction, and vice versa.

[0064] In one embodiment of the present invention, the method for optimizing process parameters under low-damage conditions is as follows: Figure 1 As shown, it includes the following steps:

[0065] (1) Using particle damage depth as the evaluation index of damage, and based on the forward modeling idea of ​​particle damage depth, establish the mapping relationship between processing parameters and damage depth.

[0066] The approach to positively predicting particle damage depth is as follows:

[0067] First, the mechanical stress and thermal stress on the workpiece are calculated separately. Regarding mechanical stress, based on the cutting force and temperature data collected by the in-situ information recognition module, the mechanical stress in the shear plane coordinate system is calculated using contact mechanics theory. After coordinate transformation, the mechanical stress in the workpiece coordinate system is obtained. The calculation process is shown in the following equations:

[0068]

[0069] in, , and For mechanical stress in the shear plane coordinate system, ( x s , z s () represents the coordinates of any point on the workpiece in the shear plane coordinate system. l s Shear length, q s and p s The normal and tangential stresses on the shear surface are obtained from the cutting force collected by the in-situ information recognition module.

[0070]

[0071] in, , and This represents the mechanical stress in the workpiece coordinate system.

[0072] Regarding thermal stress, based on the theories of heat conduction and elasticity, the thermal stress is calculated by collecting physical quantities using the in-situ information identification module, as shown in the following formula:

[0073]

[0074] in, , and Thermal stress at the workpiece end, , and These are the coefficient of thermal expansion, elastic modulus, and Poisson's ratio of the composite material, respectively. , , , , and For plane strain Green's function, g (s) represents the hydrostatic pressure at that coordinate position.

[0075] Secondly, based on the calculated mechanical and thermal stresses, the stress at the workpiece end is calculated as follows:

[0076]

[0077] Next, the equivalent stress borne by the reinforcing particles is calculated. Based on the calculated workpiece end stress, the stress borne by the reinforcing particles is calculated according to Eshelby inclusion theory, as shown in the following formula:

[0078]

[0079] in, The total stress borne by the material. f To increase particle volume fraction, C M and C P These are the stiffness tensors of the matrix and the reinforcing particles, respectively. S For Eshelby tensors, I It is the identity matrix. and These are the coefficients of thermal expansion of the reinforcing particles and the matrix, respectively.

[0080] According to Von Mise's theory, the equivalent stress borne by the reinforced particles is obtained as shown in the following formula:

[0081]

[0082] in, , , , , and For (2.5) The amount.

[0083] Finally, the damage probability of the enhanced particles was calculated based on the Weibull distribution model. P fra When the workpiece depth position P fra The depth is considered the damage depth if it exceeds the critical damage probability of the particle. H fra The formula for calculating the probability of damage is as follows:

[0084]

[0085] (2) Based on the positive prediction of damage depth, the iterative gradient search method based on Kalman filtering is adopted. The low particle damage depth is used as the target value to capture the trend in the iterative process. The damage depth under different processing parameters is calculated continuously and compared with the target value to determine whether it is within the error range. If the error requirement is met, the process parameters corresponding to the damage depth at this time are output. If the error requirement is not met, the next loop is entered until the calculated damage depth is close to the target value.

[0086] (3) After obtaining the optimized processing parameters in the above steps, the control module is used to send the optimized processing parameter instructions to each unit to complete the low-damage processing of particle-reinforced metal matrix composites.

[0087] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing process parameters in laser or ultrasonic vibration-assisted milling, characterized in that, The method includes the following steps: In laser or ultrasonic vibration assisted milling, S1 calculates the mechanical stress and thermal stress on the workpiece end using preset cutting force and cutting temperature, and sums the mechanical stress and thermal stress to obtain the total stress on the workpiece end. S2 uses the total stress at the workpiece end to solve for the stress and corresponding equivalent stress borne by the reinforcing particles in the workpiece; S3 calculates the current damage probability of the reinforcing particles using equivalent stress, compares the current damage probability with the preset critical damage probability, and determines the processing parameters in laser or ultrasonic vibration assisted milling based on the current cutting force and cutting temperature. These processing parameters are the optimal processing parameters. Otherwise, the preset cutting force and cutting temperature are adjusted, and the process returns to step S1 until the current damage probability is less than or equal to the preset critical damage probability. In step S2, the formula for calculating the stress borne by the reinforcing particles is as follows: in, The stress borne by the particles Total stress at the workpiece end This represents the volume fraction of the particles. Let the stiffness tensor of the matrix be... For Eshelby tensors, It is the identity matrix. The transformation strain of the matrix material. Let be the stiffness tensor of the particle. is the coefficient of thermal expansion of the particles. The coefficient of thermal expansion of the matrix is ​​denoted as . This is the temperature difference value; In step S2, the formula for calculating the equivalent stress is as follows: in, The equivalent stress borne by the particles. , , , , and The stress borne by the particles The stress matrix has components in X, Y, Z, XY, YZ, and XZ; In step S3, the formula for calculating the current damage probability of the reinforcing particle is as follows: in, Let be the probability of particle breakage. For particle equivalent stress, The reference fracture stress for the particles, For particle reference diameter, denoted as particle diameter, and m as the Weibull coefficient.

2. The method for optimizing process parameters in laser or ultrasonic vibration-assisted milling as described in claim 1, characterized in that, In step S1, the formula for calculating the mechanical stress is as follows: in,( x s , z s () represents the coordinates of a point on the workpiece in the shear plane coordinate system. Let x represent the mechanical stress components in the x-direction of the shear plane coordinate system. Let z be the mechanical stress component in the z-direction of the shear plane coordinate system. Let x and z be the mechanical stress components in the shear plane coordinate system. l s The length of the shear plane. q s and p s These are the normal stress and tangential stress on the shear plane, respectively.

3. The method for optimizing process parameters in laser or ultrasonic vibration-assisted milling as described in claim 1 or 2, characterized in that, In step S1, the formula for calculating the thermal stress is as follows: Where (x,z) are the coordinates of a point on the workpiece in the workpiece coordinate system. Let x be the thermal stress component in the x-direction of the workpiece coordinate system. Let Z be the thermal stress component in the z-direction of the workpiece coordinate system. Let be the thermal stress components in the x and z directions of the workpiece coordinate system, α be the thermal diffusivity of the material, E be the elastic modulus of the material, ν be the Poisson's ratio of the material, and T(x,z) be the temperature distribution in the x and z directions of the workpiece. , and These represent the corresponding responses in the x, z, and xz directions after a unit load is applied along the horizontal direction. , and These represent the corresponding responses in the x, z, and xz directions after a unit load is applied along the vertical direction. g (s) represents the hydrostatic pressure at that coordinate position.

4. The method for optimizing process parameters in laser or ultrasonic vibration-assisted milling as described in claim 3, characterized in that, In step S1, the formula for calculating the total stress at the workpiece end is as follows: Where (x,z) are the coordinates of a point on the workpiece in the workpiece coordinate system. Let x represent the total stress component in the x-direction of the workpiece coordinate system. Let Z be the total stress component in the z-direction of the workpiece coordinate system. Let be the total stress component in the y-direction in the workpiece coordinate system. Let x be the total stress components in the xz direction of the workpiece coordinate system. The total stress components in the xy direction in the workpiece coordinate system. Let α be the total stress component in the yz direction in the workpiece coordinate system, E be the material's thermal expansion coefficient, E be the material's elastic modulus, ν be the material's Poisson's ratio, and T(x,z) be the temperature distribution in the x and z directions of the workpiece.

5. The method for optimizing process parameters in laser or ultrasonic vibration-assisted milling as described in claim 1, characterized in that, In step S3, the processing parameters include laser power, laser scanning speed, ultrasonic amplitude, spindle speed, and feed rate.

6. A laser or ultrasonic vibration-assisted milling system for optimizing machining process parameters using the optimization method described in any one of claims 1-5, characterized in that, The machining system includes a milling unit, a laser-assisted unit, an ultrasonic vibration-assisted unit, and an in-situ acquisition and control unit, wherein: The milling unit is used to process the workpiece; The laser-assisted unit is used to soften the workpiece using a laser while milling; The ultrasonic vibration auxiliary unit is used to soften the workpiece by ultrasonic vibration during milling. The in-situ acquisition and control unit includes an in-situ information identification module and a control module. The in-situ information identification module is used to acquire the processing parameters of the processing process and optimize the acquired processing parameters using the optimization method described in claims 1-5. At the same time, it generates corresponding processing instructions based on the optimized processing parameters and feeds them back to the control module. The control module is used to control the processing of the milling unit, the laser-assisted unit, and the ultrasonic vibration-assisted unit according to the instructions issued by the in-situ information identification module.

7. A process method for machining using the laser or ultrasonic vibration-assisted milling system as described in claim 6, characterized in that, The process includes: The selection of one or a combination of two of the laser-assisted unit and the ultrasonic vibration-assisted unit as auxiliary processing depends on the material of the workpiece. The in-situ acquisition and control unit determines the optimal machining process parameters and controls the milling unit, laser-assisted unit, and ultrasonic vibration-assisted unit to perform machining according to the optimal machining parameters.

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