Optimization control method and device for stamping die, electronic equipment and storage medium

Abstract

The invention provides an optimal control method and device for a stamping die, electronic equipment and a storage medium, and the method comprises the steps: carrying out the mean value operation of the plate inflow collected by each contact probe, and determining the average plate inflow; judging whether the average inflow amount of the plate is matched with a preset inflow amount range or not; when the average plate inflow amount is not matched with the preset inflow amount range, the average plate inflow amount is compared with the corresponding CAE simulation inflow amount, and a corresponding compensation value is determined; and based on the compensation value, generating a corresponding stamping die calibration instruction to guide optimization of the stamping die. It can be understood that by comparing the plate inflow quantity with the corresponding CAE simulation inflow quantity, plate stacking or excessive thinning of the stamping die can be fully reflected and quantified, and then the optimization precision of the stamping die and the optimization efficiency of the stamping die are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the stamping technical field, in particular to a stamping die optimization control method and device, electronic equipment and storage medium. BACKGROUND

[0002] The stamping forming process is a core link in the production of vehicle body cover in modern vehicle manufacturing, which directly determines the size accuracy, appearance quality and structural strength of the whole vehicle. As a key tooling of stamping production, the process state of the stamping die is directly related to the final quality of the stamping part, so the precise control and optimization of the stamping die is an important basis for guaranteeing the level of vehicle manufacturing.

[0003] In the related art, the optimization and rectification of the stamping die mainly rely on manual measurement and experience judgment after the stamping part is formed. Specifically, after completing a stamping cycle on the production line, the related technical personnel enters the stamping die, manually positions and fixes the drawn part, and then measures and records the profile, contour or hole position of the stamping part. The technical personnel compares the measurement data with the theoretical CAD model, and based on the deviation result and personal experience, formulates an adjustment scheme for the stamping die, such as supplementing the die profile, grinding or adjusting the blank holder force, and then performs a trial and measurement cycle again.

[0004] However, since the measurement result is distorted due to the positioning deviation of the stamping part and its own springback deformation, it is difficult to reflect the real data corresponding to the stamping die, thereby reducing the optimization accuracy of the stamping die; at the same time, since the manual measurement is low in efficiency and highly dependent on personnel experience, the optimization efficiency of the stamping die is also low.

[0005] It should be noted that the information disclosed in the background section of the present application is only intended to deepen the understanding of the general background of the present application, and should not be regarded as acknowledging or implying in any form that the information constitutes prior art known to those skilled in the art. SUMMARY

[0006] Therefore, the present application provides a stamping die optimization control method and device, electronic equipment and storage medium, so as to solve the problem that the measurement result is distorted due to the positioning deviation of the stamping part and its own springback deformation, it is difficult to reflect the real data corresponding to the stamping die, thereby reducing the optimization accuracy of the stamping die; at the same time, since the manual measurement is low in efficiency and highly dependent on personnel experience, the optimization efficiency of the stamping die is also low.

[0007] In a first aspect, an embodiment of the present application provides a stamping die optimization control method, a plurality of contact probes are arranged on a blank holder ring of the stamping die, each contact probe is used to detect the flow amount of sheet metal, and the method comprises: perform mean operation on the sheet metal inflow collected by each contact probe to determine the average sheet metal inflow; determine whether the average sheet metal inflow matches a preset inflow range; when the average sheet metal inflow does not match the preset inflow range, compare the average sheet metal inflow with a corresponding CAE simulation inflow to determine a corresponding compensation value; generate a corresponding stamping die calibration instruction based on the compensation value to guide optimization of the stamping die.

[0008] In the embodiments of the present application, first, mean operation is performed on the sheet metal inflow collected by each contact probe to determine the average sheet metal inflow; then, it is determined whether the average sheet metal inflow matches a preset inflow range; when the average sheet metal inflow does not match the preset inflow range, the average sheet metal inflow is compared with a corresponding CAE simulation inflow to determine a corresponding compensation value; and a corresponding stamping die calibration instruction is generated based on the compensation value to guide optimization of the stamping die. It can be understood that by comparing the sheet metal inflow with the corresponding CAE simulation inflow, the sheet metal accumulation or excessive thinning of the stamping die can be fully reflected and quantified, thereby improving the optimization accuracy of the stamping die; at the same time, since the corresponding sheet metal inflow of the stamping die during work can be monitored in real time and compared directly with the corresponding CAE simulation inflow, the optimization efficiency of the stamping die is improved.

[0009] In a possible implementation, a plurality of ultrasonic probes are arranged in the stamping die, each of the ultrasonic probes is used to detect a sheet metal thinning rate, and the method further includes: perform mean operation on the sheet metal thinning rate collected by each ultrasonic probe to determine an average sheet metal thinning rate; determine whether the average sheet metal thinning rate matches a preset thinning rate range; when the average sheet metal inflow does not match the preset inflow range, compare the average sheet metal inflow with a corresponding CAE simulation inflow to determine a corresponding compensation value, including: when the average sheet metal inflow does not match the preset inflow range and / or the average sheet metal thinning rate does not match the preset thinning rate range, compare the average sheet metal inflow and the average sheet metal thinning rate with the corresponding CAE simulation value respectively to determine a corresponding compensation value.

[0010] In the embodiment of the present application, firstly, the average value operation is performed on the sheet thickness reduction collected by each ultrasonic probe to determine the average sheet thickness reduction; then it is judged whether the average sheet thickness reduction matches the preset thickness reduction range; when the average sheet inflow and the preset inflow range do not match, and / or the average sheet thickness reduction and the preset thickness reduction range do not match, the average sheet inflow and the average sheet thickness reduction are compared with the corresponding CAE simulation values respectively to determine the corresponding compensation value. It can be understood that, since the sheet thickness reduction is closely related to the working performance of the stamping die, by simultaneously detecting the average sheet inflow and the average sheet thickness reduction, the sheet accumulation or excessive sheet thinning of the stamping die can be fully reflected and quantified, thereby further improving the optimization accuracy of the stamping die and greatly reducing the misjudgment rate caused by single parameter monitoring.

[0011] In a possible implementation, the contact probe and the ultrasonic probe collect the sheet inflow and the sheet thickness reduction in a measurement time period, and the measurement time period is the time period from the closing of the blank holder ring of the stamping die to the running of the slide to the bottom dead center.

[0012] In the embodiment of the present application, the contact probe and the ultrasonic probe collect the sheet inflow and the sheet thickness reduction in a measurement time period. The measurement time period is the time period from the closing of the blank holder ring of the stamping die to the running of the slide to the bottom dead center. It can be understood that, by limiting the measurement time period of the two probes to the key dynamic process of stamping forming, it is ensured that the collected inflow and thickness reduction can accurately reflect the accuracy of the stamping die, thereby improving the optimization accuracy of the stamping die.

[0013] In a possible implementation, the comparison of the average sheet inflow with the corresponding CAE simulation inflow to determine the corresponding compensation value comprises: determining the corresponding predicted springback amount according to the average sheet inflow, material mechanical performance parameters and stamping process state parameters, wherein the material mechanical performance parameters are used to represent the physical characteristic parameters of the sheet, and the stamping process state parameters are used to represent a parameter set of the dynamic relationship between the external load and the internal response of the sheet in the deformation process; determining the corresponding deviation coefficient according to the predicted springback amount and the CAE simulation springback amount; comparing the average sheet inflow with the corresponding CAE simulation inflow, and combining the deviation coefficient to determine the corresponding compensation value.

[0014] In the embodiments of the present application, the corresponding predicted springback amount is determined according to the average flow of the sheet metal, the material mechanical property parameters and the stamping process state parameters; the corresponding deviation coefficient is determined according to the predicted springback amount and the CAE simulation springback amount; and the average flow of the sheet metal is compared with the corresponding CAE simulation flow, and the corresponding compensation value is determined in combination with the deviation coefficient. It can be understood that the deviation coefficient is obtained by introducing the predicted springback amount and comparing it with the CAE simulation springback amount, so as to realize the quantitative calibration of the system error of the CAE model. Then, the deviation coefficient is integrated into the compensation value calculation process, so that the finally determined compensation value not only reflects the local difference of the flow, but also corrects the inherent deviation of the simulation model itself, thereby significantly improving the accuracy and reliability of the compensation value when used for the rectification of the stamping die surface.

[0015] In a possible implementation manner, the material mechanical property parameters include sheet metal stiffness, sheet metal toughness, Poisson's ratio, hardening index and thickness anisotropy ratio; and the stamping process state parameters include stamping speed, friction coefficient, stamping time and contact pressure. The corresponding predicted springback amount is determined according to the average flow of the sheet metal, the material mechanical property parameters and the stamping process state parameters, and includes: The corresponding predicted springback amount is determined according to the formula: Wherein, δ predicted springback amount, σ is the sheet metal toughness, L is the average flow of the sheet metal, μ is the friction coefficient, N is the contact pressure, E is the sheet metal stiffness, α is the preset friction influence coefficient, and k is the comprehensive correction coefficient. The comprehensive correction coefficient k is determined according to the formula: , Wherein, β 0 is a preset reference constant term, and is a preset weighting coefficient, V is the normalized stamping speed, t is the normalized stamping time, v is the normalized Poisson's ratio, n is the normalized hardening index, and r is the normalized thickness anisotropy ratio.

[0016] In the embodiments of the present application, the material mechanical property parameters include sheet metal stiffness, sheet metal toughness, Poisson's ratio, hardening index and thickness anisotropy ratio; and the stamping process state parameters include stamping speed, friction coefficient, stamping time and contact pressure.

[0017] In a specific implementation, the predicted springback amount can be determined according to the following formula: ; .

[0018] ​Specific analysis as follows, plate toughness σ represents the threshold stress of the material to occur permanent deformation, the greater the plate toughness σ, the more strong and tough plate, the corresponding threshold stress to occur permanent deformation is also greater, the corresponding plate is more prone to springback. L represents the average flow of plate, representing the amount of plate drawn into the mold cavity, indicating the degree of deformation of the plate. When the average flow of plate is greater, the amount of plate drawn into the mold cavity is greater, and the degree of deformation of the plate is greater. The friction coefficient μ represents the roughness of the mold and the plate surface, the greater the value, the greater the friction resistance; the contact pressure N represents the pressure applied by the blank holder, the greater the value, the tighter the pressure; the friction influence coefficient α is used to quantify the comprehensive influence of friction on springback; therefore, to represent the difficulty of plate flow in the stamping process; when the greater the value, the more difficult the plate flow, the greater the resistance that the plate flow needs to overcome, and the greater the stress in the plate, corresponding to the plate is more prone to springback. The stiffness E of the plate represents the ability of the plate to resist deformation, and the greater the stiffness of the plate, the stronger the ability of the plate to resist deformation, corresponding to the plate is less prone to springback.

[0019] When the stamping process and the plate material are determined, the corresponding Poisson's ratio, hardening index, thickness anisotropy ratio, stamping speed and stamping time are usually fixed, so a fixed comprehensive correction coefficient k can be determined based on the above parameters. Specifically, β0 is a constant term, representing the basic correction value when all other factors are in the reference state. represents the influence of stamping speed on the predicted springback amount of plate; represents the influence of stamping time on the predicted springback amount of plate; represents the influence of Poisson's ratio on the predicted springback amount of plate; represents the influence of hardening index on the predicted springback amount of plate; represents the influence of thickness anisotropy ratio on the predicted springback amount of plate; represents the influence of the coupling effect between stamping speed and hardening index on the predicted springback amount of plate; represents the influence of the coupling effect between stamping time and thickness anisotropy ratio on the predicted springback amount of plate; represents the influence of the synergistic effect between Poisson's ratio and hardening index on the predicted springback amount of plate.

[0020] It can be understood that by accurately introducing the internal attribute parameters that determine the elastic-plastic deformation behavior of the material and the process parameters that completely characterize the external load, the prediction accuracy of the springback behavior is significantly improved, laying a foundation for generating high-credibility compensation values.

[0021] In one possible implementation, the generating, based on the compensation value, corresponding stamping die calibration instructions to guide the optimization of the stamping die comprises: generate a corresponding stamping die calibration instruction based on the compensation value and the predicted springback amount, to guide optimization of the stamping die.

[0022] In the embodiments of the present application, the corresponding stamping die calibration instruction is generated by combining the compensation value reflecting the geometric size deviation with the predicted springback amount representing the stress-strain state, which significantly improves the stability of the optimized die.

[0023] In a possible implementation, the method further includes: establishing a sheet production database according to the sheet average flow-in amount, the sheet average thinning rate, and the corresponding sheet eligibility; determining a preset flow-in amount range and a preset thinning rate range based on a corresponding sheet eligibility fluctuation interval of the sheet production database.

[0024] In the embodiments of the present application, the sheet production database is established according to the sheet average flow-in amount, the sheet average thinning rate, and the corresponding sheet eligibility, and the preset flow-in amount range and the preset thinning rate range are determined based on a corresponding sheet eligibility fluctuation interval of the sheet production database. It can be understood that, by systematically accumulating the sheet average flow-in amount and the average thinning rate and associating them with the eligibility result, the system can autonomously learn the parameter distribution law of the eligible sheet, and then accurately determine the statistical boundary of the preset range, which significantly improves the accuracy and reliability of the preset flow-in amount range and the preset thinning rate range, and provides a data basis for continuous optimization of the stamping die.

[0025] In a second aspect, the embodiments of the present application provide an optimization control device of a stamping die, the pressure pad ring of the stamping die is provided with a plurality of contact probes, each of the contact probes is used to detect a sheet flow-in amount, and the device includes: a sheet average flow-in amount determination module, configured to perform mean value operation on the sheet flow-in amount collected by each of the contact probes, to determine a sheet average flow-in amount; a judgment module, configured to judge whether the sheet average flow-in amount matches a preset flow-in amount range; a compensation value determination module, configured to, when the sheet average flow-in amount does not match the preset flow-in amount range, compare the sheet average flow-in amount with a corresponding CAE simulation flow-in amount, to determine a corresponding compensation value; a calibration instruction generation module, configured to generate a corresponding stamping die calibration instruction based on the compensation value, to guide optimization of the stamping die.

[0026] In a third aspect, the embodiments of the present application provide an electronic device, including: a processor; a memory; and a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, which, when executed by the processor, cause the electronic device to perform the method in any one of the first aspect.

[0027] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which includes a stored program, wherein the program, when executed, controls a device where the computer-readable storage medium is located to perform the method in any one of the first aspect.

[0028] It can be understood that the stamping die optimization control device provided in the second aspect, the electronic device provided in the third aspect, and the computer-readable storage medium provided in the fourth aspect are all used to execute part or all of the methods provided in the present application. Therefore, the beneficial effects that can be achieved thereby can refer to the beneficial effects in the corresponding methods, which will not be described here again. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0030] Figure 1 An application scenario diagram provided by an embodiment of the present application.

[0031] Figure 2 A flowchart of a stamping die optimization control method provided by an embodiment of the present application.

[0032] Figure 3 A schematic diagram of a contact probe distribution in a stamping die provided by an embodiment of the present application.

[0033] Figure 4 A structural schematic diagram of an ultrasonic probe arrangement position provided by an embodiment of the present application.

[0034] Figure 5 A flowchart of another stamping die optimization control method provided by an embodiment of the present application.

[0035] Figure 6 A structural schematic diagram of a stamping die optimization control device provided by an embodiment of the present application.

[0036] Figure 7 A structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION For better understanding of the technical solutions of the present application, the embodiments of the present application are described in detail below with reference to the drawings.

[0037] It should be clear that the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0038] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0039] It should be understood that the term "and / or" used herein is only to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship.

[0040] The stamping forming process is the core link of producing the body cover of the modern vehicle, which directly determines the size precision, appearance quality and structural strength of the whole vehicle. As a key tooling of stamping production, the process state of the stamping die is directly related to the final quality of the stamping part, so realizing the precise control and optimization of the stamping die is an important basis to guarantee the level of vehicle manufacturing. In order to facilitate understanding, the stamping die in specific application scenarios is first described by way of example.

[0041] Referring to Figure 1 , a schematic diagram of an application scenario provided by the embodiments of the present application is shown. As Figure 1 shown, the application scenario shows a schematic diagram of a vehicle cover stamping die, wherein the stamping die comprises a lower die seat 101, a guide rod 102, a fixed plate 103, a power cylinder 104 and an upper die seat 105. Specifically, the surface of the lower die seat 101 is provided with four groups of guide rods 102; the top of the guide rod 102 is provided with a fixed plate 103; the surface of the fixed plate 103 is provided with a power cylinder 104, and the output end of the power cylinder 104 penetrates through the fixed plate 103 and is connected with the upper die seat 105; the upper die seat 105 is penetrated by the guide rod 102.

[0042] In particular, the upper die holder 105 is driven downward by the press slide, and at this time, the guide rod 102 installed on the upper die is first precisely matched with the guide sleeve on the lower die holder 101, thereby ensuring accurate centering during the closing of the upper and lower dies and preventing lateral deviation. As the upper die continues to move downward, the blank holder installed on the fixed plate 103 begins to contact the sheet metal, and at this time, the power cylinder 104 begins to act, providing a controllable blank holder force to press the sheet metal against the die surface of the die, thereby accurately restricting the material flow. Under the action of the blank holder force, the sheet metal deforms plastically in the cavity formed by the punch and the die, fills the cavity, and forms the required part shape. After the forming is completed, the press slide drives the upper die holder 105 and all the components fixed thereon to return, and the power cylinder 104 usually also drives the ejection mechanism to eject the formed part from the cavity, thereby completing a complete stamping cycle.

[0043] It should be noted that, Figure 1 The illustrated stamping die is only an exemplary description and should not be considered as limiting the scope of protection of the present application. For example, the stamping die can refer to a process equipment for achieving sheet metal separation or plastic forming, including but not limited to a drawing die, a trimming die, a punching die, a flanging die, a shaping die, a bending die, a blanking die, a compound die, a progressive die, a fine blanking die, a thermoforming die, and a continuous die or a multi-station automatic transfer die integrating multiple functions in a single set of devices. Meanwhile, Figure 1 Only part of the structure of the stamping die is shown, and in actual design, the stamping die can also include a sheet metal positioning device and a fastening device for reliably connecting and fixing various die parts, etc., which are not limited in the present application.

[0044] In the related art, the optimization and rectification of the stamping die mainly rely on manual measurement and experience judgment after the stamping part is formed. Specifically, after one stroke is completed on the production line, the related technical personnel enter the stamping die, manually position and fix the retained drawing part, and then measure and record the profile, contour or hole position of the stamping part. The technical personnel compare the measurement data with the theoretical CAD model, and based on the deviation result and personal experience, develop an adjustment scheme for the stamping die, such as supplementing the die profile, grinding or adjusting the blank holder force, and then perform a trial and measurement cycle again.

[0045] However, since the measurement result is distorted due to the positioning deviation of the stamping part and the springback deformation thereof, it is difficult to reflect the real data corresponding to the stamping die, thereby reducing the optimization accuracy of the stamping die; at the same time, since the manual measurement is low in efficiency and highly dependent on personnel experience, the optimization efficiency of the stamping die is also low.

[0046] To solve the above problems, in the embodiment of the present application, first, the average of the sheet inflow quantity collected by each contact probe is calculated to determine the average sheet inflow quantity; then it is judged whether the average sheet inflow quantity matches the preset inflow quantity range; when the average sheet inflow quantity does not match the preset inflow quantity range, the average sheet inflow quantity is compared with the corresponding CAE simulation inflow quantity to determine the corresponding compensation value; based on the compensation value, the corresponding stamping die calibration instruction is generated to guide the optimization of the stamping die. It can be understood that by comparing the sheet inflow quantity with the corresponding CAE simulation inflow quantity, the sheet accumulation or excessive thinning of the stamping die can be fully reflected and quantified, thereby improving the optimization accuracy of the stamping die; at the same time, since the corresponding sheet inflow quantity of the stamping die during operation can be monitored in real time and compared directly with the corresponding CAE simulation inflow quantity, the optimization efficiency of the stamping die is improved. Specifically, the following will be described in detail in combination with the drawings and specific embodiments.

[0047] Referring to Figure 2 A flowchart of a stamping die optimization control method provided by the embodiment of the present application is shown. The method can be applied to Figure 1 the application scenario shown, as shown in Figure 2 , which mainly includes the following steps.

[0048] Step S201: Calculate the average of the sheet inflow quantity collected by each contact probe to determine the average sheet inflow quantity.

[0049] In the embodiment of the present application, a plurality of contact probes are arranged on the blank holder ring of the stamping die, and each contact probe is used to detect the sheet inflow quantity. For ease of understanding, referring to Figure 3 A schematic diagram of the distribution of contact probes in a stamping die provided by the embodiment of the present application is shown. As shown in the figure, the stamping die 300 is shown. A plurality of contact probes 301-308 are arranged on the blank holder ring of the stamping die 300.

[0050] It should be noted that Figure 3 The eight contact probes shown in

[0051] In the embodiment of the present application, after the sheet inflow quantity collected by each contact probe is completed, the average of the sheet inflow quantity collected by each contact probe is calculated to determine the average sheet inflow quantity.

[0052] For example, when the collected plate material inflow amounts are {A1, A2, A3, A4, A5, A6, A7, A8}, the average plate material inflow amount A is (A1+A2+A3+A4+A5+A6+A7+A8) / 8.

[0053] Of course, in actual use, since the positions of each contact probe are not the same, the plate material inflow amounts collected by each contact probe can represent different meanings. For example, when the plate material inflow amount collected by the contact probe at the middle position is the same as the plate material inflow amount collected by the contact probe at the edge position, it is possible that the plate material at the middle position is normally shaped by stamping, while the plate material at the edge position has a possibility of wrinkling. Therefore, in a possible implementation, the plate material inflow amounts collected by each contact probe are subjected to weighted operation to determine the average plate material inflow amount.

[0054] It should be further noted that the plate material inflow amount refers to the displacement length of the plate material held by the blank holder under the constraint of the die to flow into the die cavity during the stamping forming process. This parameter directly reflects the degree of material filling the cavity. In other words, when the inflow amount is too small, it is easy to cause the stamping part to crack, thereby causing the material to lose stability and defects during the forming process; when the inflow amount is too large, it will cause the stamping part to wrinkle, thereby causing the material to lose stability and defects during the forming process.

[0055] The plate material inflow amount is usually controlled by the setting parameters of the stamping die and the specific material of the plate material. In other words, when the material of the plate material is fixed, the stamping die corresponding to the plate material inflow amount can be optimized.

[0056] Step S202: determining whether the average plate material inflow amount matches the preset inflow amount range.

[0057] In the embodiments of the present application, after the average plate material inflow amount is determined, it is determined whether the average plate material inflow amount matches the preset inflow amount range.

[0058] The preset inflow amount range is used to represent the plate material inflow amount range corresponding to the case that the stamping die can normally produce stamping parts. In specific implementation, the user can obtain the plate material inflow amount range based on a large amount of experimental data. Of course, the related personnel in the field can also set the plate material inflow amount range as a dynamic adjustable plate material inflow amount range based on the specific process parameters of the stamping die according to actual needs, and the present application does not make specific limitations thereto.

[0059] It can be understood that when the average plate material inflow amount matches the preset inflow amount range, it means that the working result of the stamping die meets the user's demand, and the current stamping die will usually be continued to be used to perform stamping production work.

[0060] Step S203: When the average plate inflow amount does not match the preset inflow amount range, compare the average plate inflow amount with the corresponding CAE simulation inflow amount to determine the corresponding compensation value.

[0061] In the embodiments of the present application, when the average plate inflow amount does not match the preset inflow amount range, compare the average plate inflow amount with the corresponding CAE simulation inflow amount to determine the corresponding compensation value.

[0062] It can be understood that CAE refers to a stamping forming simulation software. In specific applications, first open the CAE on the terminal device, and establish a virtual stamping die and a virtual plate. At the same time, set the virtual stamping machine parameters, such as stamping speed and pressure, etc. Finally, run the virtual stamping die, and the CAE will simulate the entire process of the plate being stretched, bent and formed by the stamping die, while collecting the corresponding simulation inflow amount. When the virtual stamping die of the CAE simulation meets the user's requirements, the simulation inflow amount collected at this time is the CAE simulation inflow amount.

[0063] In other words, the CAE simulation inflow amount is the standard plate inflow amount corresponding to the target stamping die. At this time, compare the actual average plate inflow amount corresponding to the current stamping die with the standard plate inflow amount to infer the gap between the current stamping die and the target stamping die.

[0064] Specifically, difference value operation is performed on the average plate inflow amount and the corresponding CAE simulation inflow amount, and the difference value is taken as the compensation value. It can be understood that the difference value of the average plate inflow amount and the corresponding CAE simulation inflow amount can fully reflect the gap between the current stamping die and the target stamping die, so that the optimization of the stamping die can be realized based on the difference value.

[0065] In actual applications, relying only on the single parameter of the average plate inflow amount to evaluate the stamping die may exist in the scene of evaluation failure, thereby affecting the optimization of the stamping die. In view of this problem, the change of the plate thickness can be monitored at the same time, and the plate thinning rate and the average plate inflow amount are combined to comprehensively evaluate the stamping die.

[0066] Specifically, in one possible implementation, first, the plate thinning rate collected by each ultrasonic probe is subjected to mean value operation to determine the average plate thinning rate. Then, it is judged whether the average plate thinning rate matches the preset thinning rate range. When the average plate inflow amount does not match the preset inflow amount range, and / or the average plate thinning rate does not match the preset thinning rate range, compare the average plate inflow amount and the average plate thinning rate with the corresponding CAE simulation values respectively to determine the corresponding compensation values.

[0067] It can be understood that by detecting the average thinning rate of the sheet metal, the quality of the stamped part can be grasped in real time, and then the optimization direction of the stamping die can be inferred. Specifically, when the gap of the stamping die is too small, the thinning rate of the sheet metal increases, and the stamped part will produce necking or even cracking; when the gap of the stamping die is too large, the thinning rate of the sheet metal decreases, and the material flow increases during the forming process, which causes local material stacking and thickening, and then the stamped part will produce wrinkling defects. Therefore, by detecting the thinning rate of the sheet metal, the optimization direction of the stamping die can be inferred.

[0068] First of all, it needs to be pointed out that first, a plurality of ultrasonic probes are arranged in the stamping die, and each ultrasonic probe is used to detect the thinning rate of the sheet metal. Specifically, the area where the stamped part thins the most can be determined through CAE simulation analysis or based on the technical experience of those skilled in the art, and the ultrasonic probe is arranged in this area. For example, the middle range of the hinge mounting surface of the side door inner panel usually thins greatly, and the ultrasonic probe can be arranged in the corresponding area position of the concave die in the lower die seat.

[0069] For the sake of understanding, see Figure 4 A structural schematic diagram of an arrangement position of an ultrasonic probe provided by the embodiment of the present application is shown. As shown in the figure, the lower die seat and the ultrasonic probe 401 are shown in the side view.

[0070] It should be pointed out that, Figure 3 The ultrasonic probe shown in the figure is only an exemplary illustration. Those skilled in the art can set any number of ultrasonic probes according to actual needs, which is not specifically limited in the present application.

[0071] It can be understood that when a plurality of ultrasonic probes are arranged, the thinning rate of the sheet metal collected by each ultrasonic probe usually needs to be subjected to mean value operation to determine the average thinning rate of the sheet metal.

[0072] For example, when the collected thinning rate of the sheet metal is {B1, B2, B3, B4, B5, B6, B7, B8}, the average thinning rate B of the sheet metal is (B1+B2+B3+B4+B5+B6+B7+B8) / 8.

[0073] Of course, in actual use, since the positions of each ultrasonic probe are not the same, the thinning rate of the sheet metal collected by each ultrasonic probe may represent different meanings. For example, when the thinning rate of the sheet metal collected by the ultrasonic probe at the middle position is the same as that collected by the ultrasonic probe at the edge position, the sheet metal at the middle position may be normally stamped, while the sheet metal at the edge position may have the possibility of cracking. Therefore, in one possible implementation, the thinning rate of the sheet metal collected by each ultrasonic probe is subjected to weighted operation to determine the average thinning rate of the sheet metal.

[0074] It can be understood that, since the sheet metal reduction rate is closely related to the working performance of the stamping die, by simultaneously detecting the average sheet metal inflow and the average sheet metal reduction rate, the sheet metal accumulation or excessive thinning of the stamping die can be fully reflected and quantified, and the optimization accuracy of the stamping die is further improved, and the misjudgment rate caused by single parameter monitoring is greatly reduced.

[0075] In a possible implementation, the contact probe and the ultrasonic probe collect the sheet metal inflow and the sheet metal reduction rate in a measurement time period. The measurement time period is the time period from the closing of the blank holder ring of the stamping die to the running of the slide to the bottom dead center.

[0076] It can be understood that, by limiting the measurement time period of the two probes to the key dynamic process of stamping forming, it is ensured that the collected inflow and reduction rate can accurately reflect the accuracy of the stamping die, and the optimization accuracy of the stamping die is improved.

[0077] In actual application, the CAE model system may also have system errors, which affects the optimization accuracy of the stamping die. To solve this problem, the springback amount of the stamping part can be compared with the CAE simulation springback amount, and then the CAE model system is optimized. Specifically, the details are described below in combination with the drawings and specific embodiments.

[0078] Referring to Figure 5 , another flowchart of the optimization control method of the stamping die provided in the embodiments of the present application is shown. As Figure 5 shown, the method further includes the following steps S203 based on the method shown in Figure 2 .

[0079] Step S2031: determining the corresponding predicted springback amount according to the average sheet metal inflow, the material mechanical performance parameter, and the stamping process state parameter.

[0080] In the embodiments of the present application, the material mechanical performance parameter is used to represent the physical characteristic parameter of the sheet metal. Specifically, in a possible implementation, the material mechanical performance parameter includes: sheet metal stiffness, sheet metal toughness, Poisson's ratio, hardening index, and thickness anisotropy ratio. The stamping process state parameter is used to represent a parameter set of the dynamic relationship between the external load and the internal response of the sheet metal during deformation. Specifically, in a possible implementation, the stamping process state parameter includes: stamping speed, friction coefficient, stamping time, and contact pressure.

[0081] It can be understood that, by accurately introducing the internal attribute parameters that determine the elastic-plastic deformation behavior of the material and the process parameters that fully characterize the external load, the prediction accuracy of the springback behavior is significantly improved, which lays a foundation for generating high-credibility compensation values.

[0082] The predicted springback amount is a theoretical springback deformation of the stamped part calculated by the data processing system. Specifically, the predicted springback amount of the stamped part is generally related to the residual stress of the sheet metal after stamping and the sheet metal stiffness. It can be understood that the greater the residual stress of the sheet metal after stamping, the more likely the sheet metal is to springback; the greater the sheet metal stiffness, the less likely the sheet metal is to springback. Based on the above principle, the predicted springback amount of the stamped part is positively correlated with the ratio of the residual stress of the sheet metal to the sheet metal stiffness. In one possible implementation, the predicted springback amount = the residual stress of the sheet metal / the sheet metal stiffness.

[0083] Specifically, the predicted springback amount It can be understood that is used to characterize the residual stress of the sheet metal; E is the stiffness of the sheet metal.

[0084] wherein σ is the toughness of the sheet metal, L is the average flow of the sheet metal, μ is the friction coefficient, N is the contact pressure, E is the stiffness of the sheet metal, α is a preset friction influence coefficient, and k is a comprehensive correction coefficient.

[0085] The comprehensive correction coefficient k is used to correct the predicted springback amount of the stamped part. , wherein β0 is a preset reference constant term, and is a preset weighting coefficient, V is the normalized stamping speed, t is the normalized stamping time, ν is the normalized Poisson's ratio, n is the normalized hardening index, and r is the normalized thickness anisotropy ratio.

[0086] Specific analysis is as follows. The toughness σ of the sheet metal represents the threshold stress at which the material permanently deforms. The greater the toughness σ of the sheet metal, the more tenacious the sheet metal, and the greater the threshold stress at which the material permanently deforms. The greater the toughness of the sheet metal, the more likely the sheet metal is to springback. L represents the average flow of the sheet metal, which characterizes the amount of sheet metal drawn into the mold cavity, and represents a measure of the degree of deformation of the sheet metal. The greater the average flow of the sheet metal, the more sheet metal is drawn into the mold cavity, and the greater the degree of deformation of the sheet metal. The greater the degree of deformation of the sheet metal, the more likely the sheet metal is to springback. The friction coefficient μ represents the roughness of the mold and the surface of the sheet metal. The greater the value, the greater the frictional resistance. The contact pressure N represents the pressure applied by the blank holder. The greater the value, the tighter the pressure. The friction influence coefficient α is used to quantify the comprehensive influence of friction on springback. Therefore, 1 + α × μ × N is used to represent the degree of difficulty of the flow of the sheet metal during stamping. The greater the value of 1 + α × μ × N, the more difficult the flow of the sheet metal, the greater the resistance that the flow of the sheet metal needs to overcome, and the greater the stress within the sheet metal, which makes the sheet metal more likely to springback. The stiffness E of the sheet metal represents the ability of the sheet metal to resist deformation. The greater the stiffness of the sheet metal, the stronger the ability of the sheet metal to resist deformation, and the less likely the sheet metal is to springback.

[0087] When the stamping process and the sheet material are determined, the corresponding Poisson's ratio, hardening index, thickness anisotropy ratio, stamping speed and stamping time are usually fixed, so a fixed comprehensive correction coefficient k can be determined based on the above parameters. Specifically, β0 is a constant term, representing the basic correction value when all other factors are in the reference state. represents the influence of the stamping speed on the predicted springback amount of the sheet; represents the influence of the stamping time on the predicted springback amount of the sheet; represents the influence of the Poisson's ratio on the predicted springback amount of the sheet; represents the influence of the hardening index on the predicted springback amount of the sheet; represents the influence of the thickness anisotropy ratio on the predicted springback amount of the sheet; represents the influence of the coupling effect between the stamping speed and the hardening index on the predicted springback amount of the sheet; represents the influence of the coupling effect between the stamping time and the thickness anisotropy ratio on the predicted springback amount of the sheet; represents the influence of the synergistic effect between the Poisson's ratio and the hardening index on the predicted springback amount of the sheet.

[0088] Of course, in actual application, relevant technicians in the field can determine the predicted springback amount of the sheet through other ways according to actual needs, for example, in order to simplify the algorithm difficulty, relevant technicians in the field can determine the predicted springback amount of the sheet only by using part of the above parameters; or in order to improve the calculation accuracy of the predicted springback amount, relevant technicians in the field can add more relevant parameters to determine the predicted springback amount of the sheet, which is not limited in the present application.

[0089] Of course, relevant technicians in the field can also determine the predicted springback amount directly based on the above parameters by training a relevant model according to actual needs, which is not limited in the present application.

[0090] Step S2032: determining the corresponding deviation coefficient according to the predicted springback amount and the CAE simulation springback amount.

[0091] It can be understood that the deviation coefficient is a deviation correction coefficient for correcting the CAE model.

[0092] In one possible implementation, the deviation coefficient is the difference between the predicted springback amount and the CAE simulation springback amount. Of course, relevant technicians in the field can also set the deviation coefficient as the ratio of the predicted springback amount to the CAE simulation springback amount, etc. according to actual needs, which is not limited in the present application.

[0093] Step S2033: comparing the average flow amount of the sheet with the corresponding CAE simulation flow amount, and determining the corresponding compensation value in combination with the deviation coefficient.

[0094] In the embodiments of the present application, first, the CAE model is corrected based on the deviation coefficient; then, more accurate CAE simulation inflow is determined according to the corrected CAE model; finally, the plate average inflow is compared with the corresponding CAE simulation inflow to determine the corresponding compensation value.

[0095] Of course, in a possible implementation, the plate average inflow can also be compared with the corresponding CAE simulation inflow first to determine the corresponding compensation value; then, the compensation value is corrected based on the deviation coefficient.

[0096] In the embodiments of the present application, the deviation coefficient is obtained by introducing the predicted springback amount and comparing it with the CAE simulation springback amount, which realizes the quantitative calibration of the system error of the CAE model. Subsequently, the deviation coefficient is integrated into the compensation value calculation process, so that the finally determined compensation value not only reflects the local difference of the inflow, but also corrects the inherent deviation of the simulation model itself, thereby significantly improving the accuracy and reliability of the compensation value when used for the rectification of the stamping die surface.

[0097] Step S204: generating a corresponding stamping die calibration instruction based on the compensation value to guide the optimization of the stamping die.

[0098] In the embodiments of the present application, when the compensation value is determined, a corresponding stamping die calibration instruction is generated based on the compensation value to guide the optimization of the stamping die.

[0099] In a possible implementation, a corresponding stamping die calibration instruction can be generated based on the compensation value and the predicted springback amount to guide the optimization of the stamping die.

[0100] In the embodiments of the present application, by combining the compensation value reflecting the geometric size deviation with the predicted springback amount characterizing the stress-strain state to generate a corresponding stamping die calibration instruction, the stability of the optimized die is significantly improved.

[0101] In actual applications, in addition to the preset inflow range and the preset thinning rate range determined by the related technical personnel in the field through a large number of experiments as described above, the system can also automatically determine the reliable boundary range corresponding to the preset inflow range and the preset thinning rate range according to historical data. Specifically, the specific embodiments are described in detail below.

[0102] In a possible implementation, a plate production database is established according to the plate average inflow, the plate average thinning rate and the corresponding plate eligibility; the preset inflow range and the preset thinning rate range are determined based on the plate eligibility fluctuation interval corresponding to the plate production database.

[0103] It can be understood that, by systematically accumulating the average flow-in amount of the sheet metal and the average thinning rate and associating them with the eligibility results, the system can autonomously learn the parameter distribution law corresponding to the eligible sheet metal, thereby accurately determining the statistical boundary of the preset range, significantly improving the accuracy and reliability of the preset flow-in amount range and the preset thinning rate range, and providing a data basis for the continuous optimization of the stamping die.

[0104] In the embodiment of the application, first, the average flow-in amount of the sheet metal is determined by performing mean operation on the sheet metal flow-in amount collected by each contact probe; then it is judged whether the average flow-in amount of the sheet metal matches the preset flow-in amount range; when the average flow-in amount of the sheet metal does not match the preset flow-in amount range, the corresponding compensation value is determined by comparing the average flow-in amount of the sheet metal with the corresponding CAE simulation flow-in amount; and based on the compensation value, the corresponding stamping die calibration instruction is generated to guide the optimization of the stamping die. It can be understood that, by comparing the sheet metal flow-in amount with the corresponding CAE simulation flow-in amount, the sheet metal accumulation or excessive thinning of the stamping die can be fully reflected and quantified, thereby improving the optimization accuracy of the stamping die; at the same time, since the corresponding sheet metal flow-in amount during the operation of the stamping die can be monitored in real time and directly compared with the corresponding CAE simulation flow-in amount, the optimization efficiency of the stamping die is improved.

[0105] Corresponding to the above-mentioned embodiments, the application also provides an optimization control device of a stamping die. Specifically, referring to Figure 6 A structural diagram of an optimization control device of a stamping die is provided in the embodiment of the application. As shown in the figure, the optimization control device 600 of the stamping die is shown in the figure. The optimization control device 600 of the stamping die specifically includes: a sheet metal average flow-in amount determination module 601, a judgment module 602, a compensation value determination module 603, and a calibration instruction generation module 604. Specifically, the sheet metal average flow-in amount determination module 601 is configured to perform mean operation on the sheet metal flow-in amount collected by each contact probe to determine the average flow-in amount of the sheet metal; the judgment module 602 is configured to judge whether the average flow-in amount of the sheet metal matches the preset flow-in amount range; the compensation value determination module 603 is configured to compare the average flow-in amount of the sheet metal with the corresponding CAE simulation flow-in amount to determine the corresponding compensation value when the average flow-in amount of the sheet metal does not match the preset flow-in amount range; and the calibration instruction generation module 604 is configured to generate the corresponding stamping die calibration instruction based on the compensation value to guide the optimization of the stamping die.

[0106] For specific implementation, reference can be made to the corresponding method embodiment part described above. In order to express concisely, the application will not be described here. Corresponding to the above-mentioned embodiments, the application also provides a structural diagram of an electronic device. Referring to Figure 7A structural schematic diagram of an electronic device is provided for an embodiment of the present application. The electronic device 700 can include a processor 701, a memory 702, and a communication unit 703. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiments of the present application. It can be a bus structure or a star structure. It can also include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0107] The communication unit 703 is configured to establish a communication channel, so that the electronic device can communicate with other devices. It receives user data from other devices or sends user data to other devices.

[0108] The processor 701 is the control center of the electronic device. It connects various parts of the electronic device through various interfaces and lines, executes software programs, instructions, and / or modules stored in the memory 702, and calls data stored in the memory, to perform various functions of the electronic device and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs connected together. For example, the processor 701 can only include a central processing unit (CPU). In the embodiments of the present application, the CPU can be a single operation core or can include multiple operation cores.

[0109] The memory 702 is configured to store execution instructions for the processor 701. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0110] When the execution instructions in the memory 702 are executed by the processor 701, the electronic device 700 can perform Figure 2 some or all of the steps in the illustrated embodiments.

[0111] In specific implementation, the present application further provides a computer storage medium, wherein the computer storage medium can store a program, and the program can include some or all steps in each embodiment of the simulation scene generation method provided by the present application when executed. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM) and the like.

[0112] In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. The "and / or" describes the association relationship of the associated objects, which means that there can be three kinds of relationships, for example, A and / or B, which can represent the cases of A alone, A and B together, and B alone. Wherein A and B can be singular or plural. The character " / " generally represents that the associated objects before and after it are in an "or" relationship. "At least one of the following" and the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b and c can represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b and c can be single or multiple.

[0113] Those skilled in the art can realize that the units and algorithm steps described in the embodiments disclosed in the present application can be realized by electronic hardware, computer software and combination of electronic hardware and computer software. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0114] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0115] In several embodiments provided in the present application, any function, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or in part or parts of the technical solutions that make contributions to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0116] The same or similar parts among the various embodiments in the specification can be referred to each other. Especially, for the device embodiments and the terminal embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

Claims

1. An optimized control method for stamping dies, characterized in that, The stamping die has multiple contact probes on its blank holder ring. Each contact probe is used to detect the amount of sheet metal flowing in. The method includes: The average inflow rate of the sheet material collected by each of the contact probes is calculated to determine the average inflow rate of the sheet material. Determine whether the average inflow rate of the sheet material matches the preset inflow rate range; When the average inflow of the sheet material does not match the preset inflow range, the average inflow of the sheet material is compared with the corresponding CAE simulation inflow to determine the corresponding compensation value. Based on the compensation value, a corresponding stamping die calibration instruction is generated to guide the optimization of the stamping die.

2. The method according to claim 1, characterized in that, The stamping die is equipped with multiple ultrasonic probes, each of which is used to detect the sheet metal thinning rate. The method further includes: The average sheet thinning rate is determined by averaging the sheet thinning rates collected by each ultrasonic probe. Determine whether the average thinning rate of the sheet material matches the preset thinning rate range; When the average inflow of the sheet material does not match the preset inflow range, the average inflow of the sheet material is compared with the corresponding CAE simulation inflow to determine the corresponding compensation value. This includes: when the average inflow of the sheet material does not match the preset inflow range, and / or the average thinning rate of the sheet material does not match the preset thinning rate range, the average inflow of the sheet material and the average thinning rate of the sheet material are compared with the corresponding CAE simulation values ​​to determine the corresponding compensation values.

3. The method according to claim 2, characterized in that, The contact probe and the ultrasonic probe collect the sheet material inflow and sheet material thinning rate during the measurement time period, which is the time period from the closing of the blank holder of the stamping die to the slide reaching the bottom dead center.

4. The method according to claim 1, characterized in that, The step of comparing the average inflow of the sheet metal with the corresponding CAE simulation inflow to determine the corresponding compensation value includes: Based on the average inflow of the sheet metal, the material mechanical properties parameters, and the stamping process state parameters, the corresponding predicted springback amount is determined. The material mechanical properties parameters are used to characterize the physical properties of the sheet metal, and the stamping process state parameters are a set of parameters used to characterize the dynamic relationship between the external load and the internal response of the sheet metal during the deformation process. Based on the predicted rebound amount and the CAE simulated rebound amount, determine the corresponding deviation coefficient; The average inflow of the sheet material is compared with the corresponding CAE simulation inflow, and the corresponding compensation value is determined by combining the deviation coefficient.

5. The method according to claim 4, characterized in that, The material mechanical properties parameters include: sheet stiffness, sheet toughness, Poisson's ratio, hardening index, and thickness anisotropy ratio; the stamping process parameters include: stamping speed, coefficient of friction, stamping time, and contact pressure. The step of determining the corresponding predicted springback amount based on the average inflow rate of the sheet metal, material mechanical property parameters, and stamping process state parameters includes: According to the formula: Determine the corresponding predicted rebound amount; Among them, δ is the predicted rebound amount, σ is the sheet toughness, L is the average inflow amount of the sheet, μ is the friction coefficient, N is the contact pressure, E is the sheet stiffness, α is the preset friction influence coefficient, and k is the comprehensive correction coefficient. The comprehensive correction coefficient ， Where β0 is a preset reference constant term, as well as ν is the preset weighting coefficient, V is the normalized stamping speed, t is the normalized stamping time, ν is the normalized Poisson's ratio, n is the normalized hardening index, and r is the normalized thickness anisotropy ratio.

6. The method according to claim 4, characterized in that, The step of generating a corresponding stamping die calibration instruction based on the compensation value to guide the optimization of the stamping die includes: Based on the compensation value and the predicted springback amount, a corresponding stamping die calibration instruction is generated to guide the optimization of the stamping die.

7. The method according to claim 2, characterized in that, The method further includes: A sheet material production database is established based on the average sheet material inflow, the average sheet material thinning rate, and the corresponding sheet material qualification. Based on the qualified fluctuation range of the sheet material corresponding to the sheet material production database, a preset inflow range and a preset thinning rate range are determined.

8. An optimized control device for stamping dies, characterized in that, The stamping die has multiple contact probes on its blank holder ring. Each contact probe is used to detect the amount of sheet metal flowing in. The device includes: The average inflow rate of sheet material is determined by performing an average calculation on the inflow rate of sheet material collected by each of the contact probes to determine the average inflow rate of sheet material. The judgment module is used to determine whether the average inflow amount of the sheet material matches the preset inflow amount range; The compensation value determination module is used to compare the average inflow of the sheet material with the corresponding CAE simulation inflow when the average inflow of the sheet material does not match the preset inflow range, and determine the corresponding compensation value. The calibration instruction generation module is used to generate corresponding stamping die calibration instructions based on the compensation value, so as to guide the optimization of the stamping die.

9. An electronic device, characterized in that, include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, the computer program including instructions that, when executed by the processor, cause the electronic device to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 7.

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