Method for processing a sample for tensile testing of a cold rolled sheet containing a hardened layer

Abstract

The application discloses a processing method of a cold-rolled plate tensile test sample containing a hardened layer, which comprises the following steps: grouping the samples to be processed; processing the same positions of different samples in any group of samples by punching and milling and laser processing respectively, and obtaining corresponding mechanical property data; taking the data obtained by punching and milling as a control group, and taking the data obtained by laser processing as an experimental group; calculating the deviation of the mechanical property data of the experimental group and the control group under different laser processing parameter combinations respectively; establishing a calculation model by taking the deviation as a dependent variable and different laser processing parameters as independent variables; setting corresponding expected weights according to product requirements, solving the calculation model, and obtaining the independent variable combination meeting the preset conditions. The method effectively suppresses the material edge hardening problem in the processing process, and does not need secondary processing such as a milling machine to reduce the work-hardened layer.

Description

Technical Field

[0001] This invention relates to the field of tensile testing technology for cold-rolled steel sheets, and more particularly to a method for processing samples for tensile testing of cold-rolled steel sheets containing a hardened layer. Background Technology

[0002] Cold-rolled steel sheets are key raw materials for forming in the automotive and home appliance industries due to their excellent mechanical and stamping properties. In order to obtain stamped parts of a certain size and shape, manufacturers usually need to accurately evaluate the mechanical properties of the original coil in order to select the appropriate stamping dies.

[0003] In existing technologies, a punching and milling technique is used for processing. This involves first machining the sample to a specified size using a shearing and punching machine, leaving a certain margin, and then milling away the work-hardened zone. This work-hardened zone significantly affects the mechanical properties of the cold-rolled sheet; in extreme cases, the strength may be more than 30 MPa higher than the original result. The principle is as follows: Shearing and punching machines primarily use dies for cutting. When the sheet is sheared, the metal at the cut edge undergoes plastic deformation during shearing, causing the upper surface to bend downwards and the lower surface to bulge downwards, forming burrs. The sheared surface forms a collapsed corner area, a sheared surface area, a fracture surface area formed by tearing, and a burr area. The collapsed corner area and sheared surface area are relatively regular and flat, while the fracture surface area, due to tearing force, has an irregular fracture surface with many bright spots, exhibiting obvious crystalline fracture characteristics. The plastic deformation at the cut edge in the cold state increases its hardness and decreases its plasticity, resulting in work-hardening. This phenomenon is more pronounced for high-strength steels. The hardening range at the cut edge increases with the thickness of the sheared material. The punched sample is then machined on a milling machine, which uses a multi-toothed milling cutter to cut the sample while simultaneously using an emulsion for cooling to reduce work hardening (e.g., ...). Figure 2 As shown, the milling cutter uses the torque generated by its high-speed rotation to mill the sample. The brittle material being cut is subjected to force and forms small, short, irregularly broken chips. The burrs generated during the milling process mainly include burrs on both sides of the main cutting edge, burrs cut out in the cutting direction from the side edge, burrs cut out in the cutting direction from the bottom edge, and burrs in the feed directions of entry and exit.

[0004] The milling cutter and the workpiece have relative linear motion, while the milling cutter itself rotates, continuously machining the workpiece. The entire process produces alternating, scaly transition tool marks (such as...) from the tool's cutting edge. Figure 3 (As shown). If the material has high strength and hardness, it will accelerate the wear of the cutting tool, easily causing chipping of the cutting edge and affecting the quality of the machined surface (e.g., Figure 4(The shaded strip in the middle of the sample is shown). The problem is that the work-hardened zone of the punched sample cross-section averages 200-500 μm. Therefore, a milling space of about 1 mm is reserved in the sample. During milling, the area to be milled of about 1 mm needs to be removed, and the work-hardened zone needs to be ensured to be no more than 30 μm. The process is complicated and inefficient. Moreover, currently, there are many types of cold-rolled steel, from IF steel to 780 grade deep-drawing steel, from galvanized to alloyed, etc. The quality of the milling cutter and related process parameters directly determine the processing quality of the sample, which needs to be adjusted at any time according to different sample types. The adjustment operation is complicated. Summary of the Invention

[0005] This application provides a processing method for a cold-rolled sheet sample with a hardened layer for tensile testing. This method at least partially solves the technical problems of complex and inefficient removal of the hardened layer in the prior art during cold-rolled sheet processing. It effectively curbs edge hardening of the material during processing and reduces the need for secondary processing such as milling to remove the hardened layer.

[0006] Firstly, to solve the above-mentioned technical problems, embodiments of the present invention provide the following technical solutions:

[0007] A method for processing a cold-rolled sheet sample for tensile testing containing a hardened layer, comprising:

[0008] The samples to be processed are grouped; within any group of samples, different samples are processed at the same location using punching and milling and laser processing respectively, and the corresponding mechanical property data are obtained; the data obtained from punching and milling is used as the control group, and the data obtained from laser processing is used as the experimental group; the deviation of the mechanical property data of the experimental group and the control group under different combinations of laser processing parameters is calculated; a calculation model is established with the deviation as the dependent variable and different laser processing parameters as independent variables; the expected weights are set according to product requirements, and the calculation model is solved to obtain the combination of independent variables that meets the preset conditions.

[0009] Optionally, the steps of obtaining the mechanical property data of the sampling sites of the control group and the experimental group respectively further include:

[0010] The yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening index of the sampling sites in the control group and the experimental group were obtained by tensile testing machine.

[0011] Optionally, the above calculation model includes:

[0012]

[0013] Where ΔX is the deviation of any one of the parameters among yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening exponent; a1, a2, b1, b2, c1, c2, d1, d2, d3, e, and f are correlation coefficients; the correlation coefficients are different when different parameters are selected for the dependent variable ΔX; y1 is the average laser power; y2 is the laser cutting speed; y3 is the laser focal defocus; y4 is the laser processing auxiliary gas pressure; y5 is the laser focal radius; C is a constant term; the above-mentioned average laser power, laser cutting speed, laser focal defocus, laser processing auxiliary gas pressure, and laser focal radius must all satisfy the formula corresponding to the deviation of any parameter in ΔX.

[0014] Optionally, the steps for establishing the computational model described above also include:

[0015] The above calculation model is established using the least squares method.

[0016] Optionally, before calculating the different combinations of laser processing parameters, the above method further includes:

[0017] The response surface methodology is used to select laser processing parameter combinations according to a preset scheme;

[0018] The least squares method is used to filter based on preset screening factors;

[0019] Based on the obtained goodness of fit and predicted expression, the optimal solution is obtained to obtain the combination of target laser processing parameters.

[0020] Optionally, the above-mentioned step of grouping the samples to be treated includes:

[0021] The samples to be treated were grouped according to steel type, coating, and thickness.

[0022] Optionally, the above laser processing uses a fiber laser to process the sample.

[0023] Secondly, a processing system for a cold-rolled sheet tensile test specimen containing a hardened layer is provided, the system comprising:

[0024] The grouping module is used to group the samples to be processed.

[0025] The separate processing module is used to process the same position of different samples in any group of the above samples using punching and milling and laser processing respectively, and obtain the corresponding mechanical property data; the data obtained by punching and milling is used as the control group, and the data obtained by laser processing is used as the experimental group;

[0026] The deviation calculation module is used to calculate the deviation of the mechanical property data of the experimental group and the control group under different combinations of laser processing parameters.

[0027] The model building module is used to establish a calculation model with the above-mentioned deviation as the dependent variable and different laser processing parameters as independent variables.

[0028] The results module is used to set the corresponding expected weights according to product requirements, solve the above calculation model, and obtain the combination of independent variables that meet the preset conditions.

[0029] Thirdly, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the steps corresponding to the method described in the first aspect.

[0030] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, performs the steps corresponding to the method described in the first aspect.

[0031] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0032] Tensile test specimens were processed using both laser processing and punching / shearing / milling methods, with each sampling location corresponding to the previous one. The mechanical property data measured using the punching / shearing / milling method served as a reference. An established model was then used to obtain the optimal laser processing parameters, which were then applied to the specimens using laser processing. This effectively curbs edge hardening of the material during processing and eliminates the need for secondary milling to remove the hardened layer. The milling step is eliminated, shortening the processing cycle for specimens with small hardened layers in tensile tests and improving production efficiency. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 A flowchart illustrating a processing method for a cold-rolled sheet sample containing a hardened layer for tensile testing, provided in this application;

[0035] Figure 2 This is a schematic diagram of the prior art milling process for brittle materials in this application;

[0036] Figure 3 This is a cross-sectional view of the prior art milling machine used in this application;

[0037] Figure 4 This is another schematic diagram of the cross-section processed by the prior art milling machine in this application;

[0038] Figure 5 This is a schematic diagram showing the predicted and actual goodness-of-fit values ​​in this application.

[0039] Figure 6 This is a schematic diagram showing the result of optimizing the expression in this application;

[0040] Figure 7 A schematic diagram of the processing system for a cold-rolled sheet sample with a hardened layer for tensile testing provided in this application;

[0041] Figure 8 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0043] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0044] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0045] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the term "setup" should be interpreted broadly. For example, it can refer to a fixed setup, a detachable setup, or an integral setup; it can refer to a mechanical setup or an electrical setup; it can refer to a direct connection or an indirect connection through an intermediate medium; it can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0046] It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. Unless otherwise specified, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0047] This application provides a processing method for a cold-rolled sheet sample with a hardened layer for tensile testing. This method improves upon the technical problems of complex and inefficient removal of the hardened layer in the existing cold-rolled sheet processing process. It effectively curbs edge hardening of the material during processing and reduces the need for secondary processing such as milling to remove the hardened layer.

[0048] The technical solution of this application embodiment is to solve the above-mentioned technical problems, and the general idea is as follows:

[0049] Tensile test samples were processed using both laser processing and punching / shearing / milling methods, with each sampling location corresponding to the previous one. The mechanical property data measured using the punching / shearing / milling method served as a reference. An established model was then used to obtain the optimal laser processing parameters, which were then applied to the samples using laser processing. This effectively curbs edge hardening of the material during processing and eliminates the need for secondary milling to remove a hardened layer.

[0050] In the embodiments of this application, the following are provided: Figure 1 The method shown is a processing method for a cold-rolled sheet sample for tensile testing containing a hardened layer, the method comprising steps S101 to S105:

[0051] Step S101: Group the samples to be processed;

[0052] It should be noted that the sample grouping is mainly based on: steel type (composition), coating (hot-dip galvanizing, electro-galvanizing, alloying, etc.) and thickness.

[0053] In step S102, for any group of the above samples, the same position of different samples is processed by punching and milling and laser processing respectively, and the corresponding mechanical property data are obtained; the data obtained by punching and milling is used as the control group, and the data obtained by laser processing is used as the experimental group.

[0054] It should be noted that for the same group of samples, tensile test samples were processed using both laser processing and punching / shearing / milling methods, and the sampling locations for laser processing and punching / shearing / milling must correspond one-to-one. Furthermore, during laser processing, different combinations of laser processing parameters should be configured, with response surface methodology used for parameter combination design, and at least 28 parameter combinations performed. Additionally, to ensure that the performance of the laser-processed products is consistent with or better than that of the traditional punching / shearing / milling processed products, the data obtained from punching / shearing / milling is used as the control group, and the data obtained from laser processing is used as the experimental group.

[0055] Step S103: Calculate the deviation of the mechanical property data of the experimental group and the control group under different combinations of laser processing parameters;

[0056] It should be noted that the purpose of calculating the deviation is to obtain the specific deviation factor and the specific difference between the punching and milling technique and laser processing under the current laser processing parameters.

[0057] Step S104: Using the above deviation as the dependent variable and different laser processing parameters as independent variables, establish a calculation model;

[0058] It should be noted that the calculation model is established using the least squares method.

[0059] Step S105: Set the corresponding expected weights according to product requirements, solve the above calculation model, and obtain the combination of independent variables that meets the preset conditions.

[0060] It should be noted that, because this calculation model is a multi-variable mathematical model, the expected weights of the corresponding indicators are set according to the product's performance requirements. If a requirement must be met, the weight is set to 1; if not, it is set to 0. Other performance weights can be set to any value between 0 and 1, depending on the requirements. The optimal solution for this calculation model is then obtained, yielding the best combination of laser processing parameters.

[0061] Furthermore, the steps of obtaining the mechanical property data of the sampling sites of the control group and the experimental group respectively also include: obtaining the yield strength, tensile strength, elongation after fracture, plastic strain ratio and strain hardening index of the sampling sites of the control group and the experimental group respectively by using a tensile testing machine.

[0062] It should be noted that when determining the yield strength, one of the yield strength, upper yield strength, and lower yield strength at a non-proportional elongation of 2% is used.

[0063] Furthermore, the above calculation model includes:

[0064]

[0065] Where ΔX is the deviation of any one of the parameters among yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening exponent; a1, a2, b1, b2, c1, c2, d1, d2, d3, e, and f are correlation coefficients; the correlation coefficients are different when different parameters are selected for the dependent variable ΔX; y1 is the average laser power; y2 is the laser cutting speed; y3 is the laser focal defocus; y4 is the laser processing auxiliary gas pressure; y5 is the laser focal radius; C is a constant term; the above-mentioned average laser power, laser cutting speed, laser focal defocus, laser processing auxiliary gas pressure, and laser focal radius must all satisfy the formula corresponding to the deviation of any parameter in ΔX.

[0066] It should be noted that ΔX represents multiple parameters, therefore its formula is essentially:

[0067] Yield strength deviation ΔR at a non-proportional elongation of 2% p0.2 for:

[0068]

[0069] Lower yield strength deviation ΔR eL for:

[0070]

[0071] Lower yield strength deviation ΔR eH for:

[0072]

[0073] Tensile strength deviation ΔR m for:

[0074]

[0075] The post-fracture elongation deviation ΔA is:

[0076]

[0077] The plastic strain ratio deviation Δr is:

[0078]

[0079] The strain hardening exponent deviation Δn is:

[0080]

[0081] The correlation coefficients are obtained from the correspondence of data in laser processing, which is the result of response surface design as described above. Therefore, the correlation coefficients are different when the parameters selected for the dependent variable ΔX are different; however, the average laser power y1, laser cutting speed y2, laser focal defocus y3, laser processing auxiliary gas pressure y4, and laser focal radius y5 must all satisfy formulas (1) to (7).

[0082] After substituting the required data, the optimal solution is obtained as follows:

[0083]

[0084]

[0085] Furthermore, before calculating the different combinations of laser processing parameters, the above method also includes:

[0086] The response surface methodology is used to select laser processing parameter combinations according to a preset scheme;

[0087] As shown in the table below:

[0088] model X1 X2 X3 X4 X5 -+--+ -1 1 -1 -1 1 0000A 0 0 0 0 1 000a0 0 0 0 -1 0 ++++- 1 1 1 1 -1 … … … … … …

[0089] Where X1, X2, X3, X4, and X5 are parameter variables, namely, average laser power y1, laser cutting speed y2, laser focal defocus y3, laser processing auxiliary gas pressure y4, and laser focal radius y5. -1 represents the minimum value, 1 represents the maximum value, and 0 represents the average value. This preset scheme uses different random permutations and combinations.

[0090] The least squares method is used to filter based on preset screening factors;

[0091] It should be noted that this embodiment uses Matlab or JMP to perform simulation fitting using data mining methods, and the selection factors are as follows:

[0092]

[0093]

[0094] Logworth is a p-value transformation based on the Pearson chi-square test.

[0095] Based on the obtained goodness of fit and predicted expression, the optimal solution is obtained to obtain the combination of target laser processing parameters.

[0096] It should be noted that the prediction expression is as follows:

[0097] y = -0.011857273 + 3.8623944e-6·laser power + 0.0002723607·

[0098] Laser speed +0.0004295622 · Focal position +0.0026477278 · Nitrogen pressure +

[0099] (laser power - 1500)·((laser power - 1500)·4.2150929e -9 )+(laser power-1500))·((laser speed-30.277777778)·-4.243719e -9 )+(laser velocity-30.277777778)·((laser velocity-30.277777778)·-0.000065254)+

[0100] (Laser power -1500)·((Focus position -(-0.055555556))·-2.947388e -6 )+(laser velocity-30.277777778)·((focal position-(-0.055555556))·

[0101] 0.0003425582)+(focal position-(-0.055555556|))·(focal position-

[0102] (-0.055555556))-0.000514379)+(laser power-1500)·((nitrogen pressure-1.2722222222)·-1.840915e -5 )+(laser velocity-30.277777778)·

[0103] ((Nitrogen pressure -1.2722222222)·-0.000550982)+(Focus position -

[0104] (-0.055555556))·((Nitrogen pressure-1.2722222222)·0.0029944296)+(

[0105] Nitrogen pressure -1.2722222222)·((Nitrogen pressure -1.2722222222).0077943408)

[0106] Its predicted values ​​and goodness of fit are as follows: Figure 5 As shown, the optimization solution is performed based on the expression. Figure 6 As shown.

[0107] Furthermore, the above-mentioned laser processing uses a fiber laser to process the sample.

[0108] It should be noted that the average laser power of fiber lasers ranges from 1000 to 4000W, the laser focal radius is 1 to 3μm, the laser focal defocus is -1 to 1mm, the laser cutting speed is 20 to 50m / min, and the laser processing auxiliary gas is N2, with a pressure level generally between 1.0 and 2.0Mpa.

[0109] Based on the same inventive concept, embodiments of this application provide a processing system for cold-rolled sheet samples used in tensile testing containing a hardened layer, such as... Figure 7 As shown, it includes:

[0110] Grouping module 201 is used to group the samples to be processed;

[0111] The separate processing module 202 is used to process the same position of different samples in any group of the above samples using punching and milling and laser processing respectively, and obtain the corresponding mechanical property data; the data obtained by punching and milling is used as the control group, and the data obtained by laser processing is used as the experimental group;

[0112] The deviation calculation module 203 is used to calculate the deviation of the mechanical property data of the above experimental group and the above control group under different combinations of laser processing parameters.

[0113] The model building module 204 is used to build a calculation model with the above-mentioned deviation as the dependent variable and different laser processing parameters as independent variables.

[0114] The results module 205 is used to set the corresponding expected weights according to product requirements, solve the above calculation model, and obtain the combination of independent variables that meet the preset conditions.

[0115] Based on the same inventive concept, embodiments of this application provide an electronic device, such as... Figure 8 As shown, it includes: a memory 302, a processor 301, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, it implements a method for processing a cold-rolled sheet sample for tensile testing containing a hardened layer.

[0116] Based on the same inventive concept, this embodiment provides a computer-readable storage medium storing a computer program, characterized in that, when executed by processor 301, the program implements a processing method for a cold-rolled sheet sample for tensile testing containing a hardened layer.

[0117] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0118] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0119] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0120] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for processing a cold-rolled sheet sample for tensile testing containing a hardened layer, characterized in that, The method includes: Group the samples to be processed; In any group of samples, the same position of different samples was processed by punching and milling and laser processing respectively, and the corresponding mechanical property data were obtained; the data obtained by punching and milling was used as the control group, and the data obtained by laser processing was used as the experimental group. The deviations in mechanical property data between the experimental group and the control group under different combinations of laser processing parameters were calculated respectively. A calculation model is established using the aforementioned deviation as the dependent variable and different laser processing parameters as independent variables; Based on the product requirements, set the corresponding expected weights, solve the calculation model, and obtain the combination of independent variables that meets the preset conditions; The step of obtaining mechanical property data of the sampling sites of the control group and the experimental group respectively further includes: The yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening index of the sampling sites in the control group and the experimental group were obtained by tensile testing machine, respectively. The computational model includes: in, The deviation is the deviation of any one of the following parameters: yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening exponent. , , , , , , , , e and f are correlation coefficients; when the dependent variable Different parameters result in different correlation coefficients; The average power of the laser; This refers to the laser cutting speed; This refers to the defocusing amount of the laser focus; The pressure of the auxiliary gas for laser processing; Where C is the laser focal radius; C is a constant; the average laser power, laser cutting speed, laser focal defocus, laser processing auxiliary gas pressure, and laser focal radius must all meet the following requirements. The formula corresponding to the deviation of any parameter in the formula.

2. The method as described in claim 1, characterized in that, The step of establishing the computational model also includes: The computational model is established using the least squares method.

3. The method as described in claim 1, characterized in that, Before calculating the different combinations of laser processing parameters, the method further includes: The response surface methodology is used to select laser processing parameter combinations according to a preset scheme; The least squares method is used to filter based on preset screening factors; Based on the obtained goodness of fit and predicted expression, the optimal solution is obtained to obtain the combination of target laser processing parameters.

4. The method as described in claim 1, characterized in that, The step of grouping the samples to be processed includes: The samples to be treated were grouped according to steel type, coating, and thickness.

5. The method as described in claim 1, characterized in that, The laser processing uses a fiber laser to process the sample.

6. A processing system for a cold-rolled sheet sample for tensile testing containing a hardened layer, characterized in that, The system includes: The grouping module is used to group the samples to be processed. The separate processing module is used to process the same position of different samples in any group of samples using punching and milling and laser processing respectively, and obtain the corresponding mechanical property data; the data obtained by punching and milling is used as the control group, and the data obtained by laser processing is used as the experimental group; The separate processing module is also used to obtain the yield strength, tensile strength, elongation after fracture, plastic strain ratio and strain hardening index of the sampling parts of the control group and the experimental group respectively through a tensile testing machine; The deviation calculation module is used to calculate the deviation of the mechanical property data of the experimental group and the control group under different combinations of laser processing parameters. The model building module is used to establish a calculation model with the deviation as the dependent variable and different laser processing parameters as independent variables. The computational model includes: in, The deviation is the deviation of any one of the following parameters: yield strength, tensile strength, elongation after fracture, plastic strain ratio, and strain hardening exponent. , , , , , , , , e and f are correlation coefficients; when the dependent variable Different parameters result in different correlation coefficients; The average power of the laser; This refers to the laser cutting speed; This refers to the defocusing amount of the laser focus; The pressure of the auxiliary gas for laser processing; Where C is the laser focal radius; C is a constant; the average laser power, laser cutting speed, laser focal defocus, laser processing auxiliary gas pressure, and laser focal radius must all meet the following requirements. The formula corresponding to the deviation of any parameter in the formula; The results module is used to set corresponding expected weights according to product requirements, solve the calculation model, and obtain a combination of independent variables that meets preset conditions.

7. An electronic device, characterized in that, The electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps corresponding to the method as described in any one of claims 1 to 5.

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