Stamping part slippage defect control method, device and equipment based on coating evaluation

Abstract

The invention discloses a stamping part slippage defect control method, device and equipment based on coating evaluation, and the method comprises the steps: after a target die carries out stamping forming on a target stamping part, if the target stamping part after stamping forming has a slippage line, obtaining the dependent variable of the target stamping part after stamping forming; inputting the dependent variable of the target stamping part after stamping forming and the fillet radius of the target die into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples comprises historical dependent variables of a sample stamping part after stamping forming, a fillet radius of a sample mold and an actual result; and if the first prediction result is normal, the target stamping part obtained after stamping forming is coated. According to the invention, the technical problem that the evaluation accuracy of the influence of the severity of the slip line on the appearance quality of the stamped part after coating is low is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of sheet metal stamping, and in particular relates to a method, device and equipment for controlling slip defects of stamping parts based on coating evaluation. Background Art

[0002] During the sheet metal stamping process, slip line defects are a major quality issue for stamped parts and directly impact the visual quality after painting. Stamped parts are considered acceptable if the slip line defects can be completely covered by the paint film without affecting the appearance. If the slip line defects cannot be completely covered by the paint film, the painted stamped part is considered unacceptable.

[0003] Prior art methods used to assess the impact of slip lines on the painted appearance of stamped parts solely through manual experience before painting. This resulted in low accuracy in assessing the impact of slip line severity on the painted appearance of stamped parts. This in turn led to a high probability of unqualified painted stamped parts, rendering them unusable and wasting materials. Therefore, the low accuracy of assessing the impact of slip line severity on the painted appearance of stamped parts is a technical problem that urgently needs to be addressed. Summary of the Invention

[0004] The embodiments of the present invention provide a method, device and equipment for controlling slip defects of stamping parts based on painting evaluation, which solve the technical problem of low accuracy in evaluating the impact of the severity of slip lines on the appearance quality of stamping parts after painting.

[0005] In the first aspect, an embodiment of the present invention provides a method for controlling slip defects of stamping parts based on painting evaluation, comprising: after a target stamping part is stamped by a target mold, if a slip line exists on the target stamping part after stamping, obtaining the strain of the target stamping part after stamping; inputting the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, each group of samples in the multiple groups of samples includes the strain of historical sample stamping parts after stamping, the fillet radius of the sample mold and the actual results; if the first prediction result is normal, painting the target stamping part after stamping; the first prediction result is normal, indicating that the slip line does not affect the appearance quality of the target stamping part after painting.

[0006] In combination with the first aspect of the present invention, in some embodiments, obtaining the strain of the target stamping part after stamping includes: obtaining the maximum height of the contour of the slip line of the target stamping part after stamping, the maximum height of the contour of the slip line being the maximum distance between a point on the slip line and the plane where the slip line is located; inputting the maximum height of the contour of the slip line and the fillet radius of the target mold into a preset first corresponding relationship to obtain the strain of the target stamping part after stamping; the first corresponding relationship is the correspondence between the maximum height of the contour of the slip line, the fillet radius of the mold and the strain of the stamping part after stamping.

[0007] In combination with the first aspect of the present invention, in some embodiments, obtaining the maximum height of the slip line profile of the target stamping part after stamping includes: obtaining the maximum height of the slip line profile of the target stamping part after stamping through a roughness meter.

[0008] In combination with the first aspect of the present invention, in some embodiments, the quality prediction model is pre-established through the following steps: obtaining the multiple groups of samples; inputting the strain of the sample stamping parts of each group of samples in the multiple groups of samples after stamping and the fillet radius of the sample mold into the machine learning model to obtain a second prediction result; determining the loss function of the second prediction result and the actual result; based on the loss function of the second prediction result and the actual result, iteratively optimizing the machine learning model to obtain the quality prediction model.

[0009] In combination with the first aspect of the present invention, in some embodiments, the data of each group of samples in the multiple groups of samples are pre-acquired through the following steps: the sample stamping part is stamped by the sample mold of the group of samples so that the strain of the sample stamping part after stamping reaches the target strain, and a slip line exists on the sample stamping part after stamping; the sample stamping part after stamping is sprayed with a hanging piece to obtain the sample stamping part after painting; the sample stamping part after painting is subjected to surface visual analysis to obtain an actual result for characterizing the appearance quality of the sample stamping part after painting; the data of the group of samples are obtained based on the target strain of the sample stamping part after stamping, the fillet radius of the sample mold and the actual result of characterizing the appearance quality of the sample stamping part after painting.

[0010] In combination with the first aspect of the present invention, in some embodiments, the sample stamping part is stamped and formed by the sample mold of the group of samples so that the strain of the sample stamping part after stamping and forming reaches the target strain, including: inputting the target strain into a preset second corresponding relationship to obtain a target forming height; the second corresponding relationship is the correspondence between the forming height and the strain of the sample stamping part when the sample stamping part is stamped and formed; based on the target forming height, the sample mold is controlled to stamp and form the sample stamping part so that the strain of the sample stamping part after stamping and forming reaches the target strain.

[0011] In combination with the first aspect of the present invention, in some embodiments, the surface visual analysis of the sample stamping part after painting is performed to obtain an actual result for characterizing the appearance quality of the sample stamping part after painting, including: performing a surface visual analysis on the sample stamping part after painting through a visual analysis system to determine whether there are ridges on the surface of the sample stamping part after painting; if there are no ridges on the surface of the sample stamping part after painting, determining that the actual result is normal; if there are ridges on the surface of the sample stamping part after painting, determining that the actual result is abnormal.

[0012] In combination with the first aspect of the present invention, in some embodiments, the method further includes: if the first prediction result is abnormal, marking the surface slip line profile height of the target stamping part after stamping as abnormal.

[0013] In the second aspect, an embodiment of the present invention provides a stamping part slip defect control device based on painting evaluation, including: a strain acquisition unit, which is used to obtain the strain of the target stamping part after stamping if a slip line exists on the target stamping part after stamping; a prediction unit, which is used to input the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples includes the strain of historical sample stamping parts after stamping, the fillet radius of the sample mold and the actual results; a painting unit, which is used to paint the target stamping part after stamping if the first prediction result is normal; the first prediction result is normal, which indicates that the slip line does not affect the appearance quality of the target stamping part after painting.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the methods described in the first aspect when executing the computer program.

[0015] The one or more technical solutions provided by the embodiments of the present invention achieve at least the following technical effects or advantages:

[0016] The embodiment of the present invention obtains the strain of the target stamping part after stamping by the target mold if there is a slip line in the target stamping part after stamping; inputs the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples includes the strain of the historical sample stamping part after stamping, the fillet radius of the sample mold and the actual result; if the first prediction result is normal, the target stamping part after stamping is painted; the first prediction result is normal, indicating that the slip line does not affect the appearance quality of the target stamping part after painting. Since the strain of the target stamping part after stamping and the fillet radius of the target mold are strongly correlated with the deformation of the stamping part, and the deformation of the stamping part affects the slip degree of the slip line. Therefore, a first prediction result can be determined based on the strain, fillet radius, and quality prediction model to characterize whether slip lines affect the appearance quality of the target stamped part after painting. This allows for judging appearance quality based on actual data, avoiding relying solely on manual experience. This in turn improves the accuracy of assessing the impact of slip line severity on the appearance quality of stamped parts after painting.

[0017] In addition, judging whether to paint the target stamping part based on the first prediction result reduces the possibility that the target stamping part after painting will be a substandard product, thereby achieving the beneficial effect of reducing material waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 Flowchart of a method for controlling slip defects of stamping parts based on coating evaluation in an embodiment of the present invention;

[0020] Figure 2 Schematic diagram of a mold in an embodiment of the present invention;

[0021] Figure 3 Schematic diagram of a sample stamping part in an embodiment of the present invention;

[0022] Figure 4Schematic diagram of the measurement direction of the roughness meter in an embodiment of the present invention;

[0023] Figure 5 This is a schematic diagram of the contour curve data of the slide line before correction in an embodiment of the present invention;

[0024] Figure 6 Schematic diagram of the corrected contour curve data of the slide line in an embodiment of the present invention;

[0025] Figure 7 : This is a corresponding curve of the maximum height of the profile and the strain at different fillet radii in an embodiment of the present invention;

[0026] Figure 8 1 is a functional module diagram of a stamping part slip defect control device based on coating evaluation in an embodiment of the present invention;

[0027] Figure 9 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] In the present invention, descriptions such as "first" and "second" are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions of various embodiments may be combined with each other, but this must be based on the fact that they can be implemented by a person of ordinary skill in the art. If the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0030] The embodiment of the present invention provides a method for controlling slip defects of stamping parts based on coating evaluation, referring to Figure 1 As shown, the method includes the following steps S101 to S103:

[0031] S101: After a target stamping part is stamped by a target die, if a slip line exists in the target stamping part after stamping, a strain amount of the target stamping part after stamping is obtained.

[0032] In some embodiments, obtaining the strain of the target stamping part after stamping can include: obtaining the maximum height of the contour of the slip line of the target stamping part after stamping, the maximum height of the contour of the slip line being the maximum distance between a point on the slip line and the plane where the slip line is located; inputting the maximum height of the contour of the slip line and the fillet radius of the target mold into a preset first corresponding relationship to obtain the strain of the target stamping part after stamping; the first corresponding relationship is the correspondence between the maximum height of the contour of the slip line, the fillet radius of the mold and the strain of the stamping part after stamping.

[0033] It should be noted that the strain can be obtained indirectly by measuring the maximum height of the profile, or it can be obtained by direct calculation. However, direct calculation of the strain is more complicated and time-consuming. In this case, the strain is obtained indirectly by measuring the maximum height of the slide line profile, which makes it more convenient to obtain the strain data.

[0034] In some embodiments, obtaining the maximum height of the slip line profile of the target stamping part after stamping may include: obtaining the maximum height of the slip line profile of the target stamping part after stamping using a roughness meter.

[0035] S102: Input the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples includes the strain of the historical sample stamping part after stamping, the fillet radius of the sample mold and the actual results.

[0036] It should be noted that the actual results are used to indicate whether the slip lines affect the appearance quality of the sample stamping parts after painting. Specifically, a normal actual result indicates that the slip lines do not affect the appearance quality of the sample stamping parts after painting, while an abnormal actual result indicates that the slip lines do affect the appearance quality of the sample stamping parts after painting.

[0037] In some embodiments, the quality prediction model can be pre-established through the following steps: obtaining multiple groups of samples; inputting the strain of the sample stamping parts of each group of samples in the multiple groups of samples after stamping and the fillet radius of the sample mold into the machine learning model to obtain a second prediction result; determining the loss function of the second prediction result and the actual result; based on the loss function of the second prediction result and the actual result, iteratively optimizing the machine learning model to obtain a quality prediction model.

[0038] In some embodiments, the data of each sample group in the plurality of sample groups may be pre-acquired through the following steps, including steps A to D:

[0039] Step A: stamping the sample stamping part using the sample die of the group of samples so that the strain of the sample stamping part reaches the target strain after stamping, and a slip line exists on the sample stamping part after stamping.

[0040] In some embodiments, stamping the sample stamping part by the sample mold of the group of samples so that the strain of the sample stamping part after stamping reaches the target strain, can include: inputting the target strain into a preset second corresponding relationship to obtain a target forming height; the second corresponding relationship is the correspondence between the forming height and the strain of the sample stamping part when the sample stamping is stamped; based on the target forming height, controlling the sample mold to stamp the sample stamping part so that the strain of the sample stamping part after stamping reaches the target strain.

[0041] It should be noted that, during the stamping process of the sample stamping part, it is relatively complicated to directly calculate the strain amount, but the strain amount has a corresponding relationship with the forming height. By controlling the forming height, the strain amount of the sample stamping part can be accurately controlled, thereby improving the data accuracy of each group of samples in multiple groups.

[0042] Step B: performing sheet spraying on the stamped sample stamping part to obtain the painted sample stamping part.

[0043] Step C: Performing a surface visual analysis on the painted sample stamping part to obtain actual results for characterizing the appearance quality of the painted sample stamping part.

[0044] In some embodiments, performing a surface visual analysis on the sample stamping part after painting to obtain an actual result for characterizing the appearance quality of the sample stamping part after painting may include: performing a surface visual analysis on the sample stamping part after painting through a visual analysis system to determine whether there are ridges on the surface of the sample stamping part after painting; if there are no ridges on the surface of the sample stamping part after painting, determining the actual result is normal; if there are ridges on the surface of the sample stamping part after painting, determining the actual result is abnormal.

[0045] It should be noted that the height of the slip line profile can also be obtained through surface visual analysis.

[0046] Step D: Based on the target strain of the sample stamping part after stamping, the fillet radius of the sample die, and the actual results characterizing the appearance quality of the sample stamping part after painting, the data of the group of samples are obtained.

[0047] It should be noted that the data of this group of samples may also include the height of the slide line profile.

[0048] S103: If the first prediction result is normal, the target stamped part after stamping is painted; the first prediction result being normal indicates that the slip line does not affect the appearance quality of the target stamped part after painting.

[0049] In some embodiments, the method for controlling slip defects of stamping parts based on coating evaluation may further include: if the first prediction result is abnormal, marking the height of the slip line profile on the surface of the target stamping part after stamping as abnormal.

[0050] It should be noted that the first prediction result is an abnormal representation that the slip line affects the appearance quality of the target stamping part after painting.

[0051] Specifically, the slip line does not affect the appearance quality of the target stamping part after painting, which may mean that the slide line profile height does not affect the appearance quality of the target stamping part after painting. The slip line affects the appearance quality of the target stamping part after painting, which may mean that the slide line profile height affects the appearance quality of the target stamping part after painting.

[0052] It should be noted that the above embodiment mainly discusses the situation where the stamping parts have already been produced, and whether the stamping parts should be painted can be determined based on the quality prediction model. Different from the above embodiment, before the stamping parts are produced, the process parameters are determined by the quality prediction model. For example, the fillet radius and strain amount are input into the quality prediction model. If the first prediction result is normal, the fillet radius, strain amount and other process parameters can be adopted. If the height of the slip line of the stamping part exceeds the maximum threshold that meets the requirements for painting, the quality prediction model can be used to optimize the mold fillet radius and material strain.

[0053] It should be noted that slip lines are common surface defects in the stamping process of automotive panels, seriously affecting the surface quality and appearance of stamped parts. However, the complex shapes of automotive parts and the increasing number of characteristic ridges on the body make hardening and slippage inevitable when the die radius contacts the sheet metal. To more accurately assess slip defects, it is necessary to conduct in-depth research on the strain, ridge profile, and coating results after sheet metal slip, and establish a corresponding relationship between the three to prevent slip defects from being introduced into subsequent processes.

[0054] It should be noted that during the sheet metal stamping process, as the sheet passes through areas such as the punch radius and characteristic edges, it can undergo localized hardening and thinning due to bending, reverse bending, and stretching, leaving marks on the sheet surface. As the material flows unevenly on both sides of the die during stamping, these marks can slip and enter the part's molded area, thereby affecting the quality of the final product. Slipline defects are a major concern for surface quality defects in automotive panels and directly impact the visual appearance of the finished vehicle after painting. Therefore, measuring and evaluating the slipline of stamped parts during the process design phase enables accurate on-site assessment and evaluation, while also guiding the optimization of slipline defect control, which is of great practical value to automotive parts stamping. Furthermore, AutoForm simulation software uses three methods: slip distance, maximum contact compressive stress, and reverse bending strain to determine whether slipline defects, which could impact product appearance quality, will occur when the sheet passes through the die radius. However, this software cannot quantify slipline height, and changes in resistance due to die wear can cause simulation results to differ from actual stamping conditions. Therefore, simulation evaluation is primarily used during the product development phase. Human visual inspection is significantly influenced by subjective factors. The technical skill level, on-site lighting, and changes in stamping conditions can all contribute to assessment errors. The severity of slip lines is directly related to the size of the punch radius where the sheet metal contacts the die, sheet metal properties, and the strain at the radius. Therefore, establishing a correspondence between die radius, strain, slip line profile values, and appearance quality allows for rapid assessment of slip defects in stamped parts. Furthermore, based on the correspondence between profile curves and strain, production lines can be guided to optimize stamping process parameters, thereby minimizing the impact of slip lines on coating.

[0055] It should be noted that, in order to solve the problem of slip line defects caused by the die fillet and material flow during the stamping process, the embodiment of the present invention can obtain the surface profile curve of the sample with hardened ridges under different strains through the ridge forming and DIC (Digital Image Correlation) online measurement system, and form a corresponding relationship between the die fillet radius, steel type, forming strain and slip line profile morphology. At the same time, a sample coupon spraying test is carried out to realize the surface defect evaluation of the sample after coating, and form a corresponding relationship between strain and slip defects. Based on this, the minimum strain and ridge profile fluctuation threshold that affect the surface quality of the stamping part can be obtained, thereby effectively guiding the evaluation of slip line defects in the forming process and providing a basis for the optimization control of the slip line. Specifically, first, based on the mechanism of slip line generation, a tensile bending die with different fillet radii is developed. The die fillet radius r can be 1.5mm to 6.5mm, the step distance is 1mm, and the die angle is ≥90°. Secondly, a forming test machine is used to simulate stamping to prepare ridge samples with different fillet radii. Then, a cup tensile test was performed on the existing edge sample. Before the test began, speckles were sprayed on the sample surface, and the strain state of the sample was measured and recorded based on the DIC online detection equipment. The strain was controlled by the forming height. According to the forming height and strain comparison table, the test was repeated on the sample without spraying speckles to obtain tensile specimens with different radii and different strains. The roughness meter was used to perform contour scanning analysis on the tensile specimen after strain in the direction perpendicular to the edge to obtain the contour curve at the edge. Through data processing, the maximum value of the edge profile fluctuation after different strains was obtained, which was recorded as H. max Finally, the evaluation of surface slip line defects is completed by spraying the coupons, and the corresponding relationship between steel type, mold corner radius, strain and evaluation results is established. When the defect at the edge of the sample is no longer visible after spraying, the corresponding strain is the minimum strain ε caused by the plate slip defect under the mold corner. min That is, when this type of steel is formed under this mold radius, when the strain is greater than ε min When the hardened edge line produced after the sheet metal contacts the mold can be covered by the paint film, which will not affect the surface quality. max It can be regarded as the maximum critical height. When the edge profile height after the mold and the plate impact is less than H max When the impact is detected, it can be determined that the sliding ridges after impact will not affect the coating surface.

[0056] To enhance understanding of the first correspondence, the second correspondence, and the process of determining multiple groups of samples, the following example illustrates steps 1 to 5:

[0057] Step 1: Slip edge mold development and sample preparation. Figure 2 As shown, Figure 2This is a schematic diagram of the mold in the embodiment of the present invention. A tensile bending mold with different fillet radii and angles is developed. The fillet radii are selected from 1.5mm to 6.5mm. The slip ridge perpendicular to the tensile direction is prepared by a forming test machine. In order to ensure uniform deformation of the center area of the sample stamping during the stretching process, the sample stamping is designed to be "dumbbell-shaped". Figure 3 As shown, Figure 3 Schematic diagram of the sample stamping part in the embodiment of the present invention, a=45mm, b=70mm, d=260mm.

[0058] Step 2: Edge Tensile Strain Measurement and Analysis. The surface of the sample stamping with edge patterns is speckle-sprayed and a cup tensile test is performed using a DIC measurement system. The strain and thinning curves for the material edge region are obtained, and a table is established for forming height and strain. A second correspondence can be derived from this table. The table for forming height and strain can be referenced in Table 1. Repeat the test on the sample without speckle patterns based on Table 1.

[0059] Table 1:

[0060] Forming height h(mm) 10 13 17 23 28 32 Strain (%) 5 10 15 20 25 30

[0061] Step 3: Edge height measurement and data fitting correction. Use the roughness meter to measure the stretched sample stamping along the vertical edge direction, with a measurement stroke of 15mm, to obtain the contour curve data, refer to Figure 4 and Figure 5 As shown, Figure 4 Schematic diagram of the measurement direction of the roughness meter in an embodiment of the present invention, Figure 5 This is a schematic diagram of the contour curve data of the slip line before correction in the embodiment of the present invention. In order to accurately obtain the maximum height of the contour at the ridge line, the original data must be corrected so that the sample plane coincides with or is parallel to the X-axis. The original data of the plane area can be fitted using Excel to obtain the angle between the fitting curve and the X-axis, and the coordinate conversion can be performed using the following formulas (1) and (2) to obtain the optimized contour curve. Figure 6 As shown, Figure 6 Schematic diagram of the corrected contour curve data of the sliding line in the embodiment of the present invention. The correction method of the contour curve can be: first, calculate the rotation angle, the rotation angle corresponding to the slope a of the fitting curve is: θ = arctan (a); then, calculate the coordinates of the data points after rotation, for each data point (X i ,Y i ), the new coordinate after rotation (X i ',Y i ').

[0062] X′ i =X i cos(θ)+Yi sin(θ) (1);

[0063] Y i ′=-X i sin(θ)+Y i ·cos(θ) (2);

[0064] Step 4: Establish the corresponding relationship between strain and ridge contour height. According to the corrected contour line, select the absolute value of the distance from the highest or lowest point of the contour to the X axis as H max , that is, the maximum height of the contour of the slip line, establish the radius of each fillet, strain and H max Refer to Table 2 for the corresponding table, and then get the first corresponding relationship, the corresponding strain variable is recorded as ε min The first correspondence is illustrated by an example. From Table 2, it can be seen that when the fillet radius is 1.5mm and the maximum profile height is 34mm, the strain is 15%. In addition, you can refer to Figure 7 As shown, Figure 7 1 is a corresponding curve of the maximum height of the profile and the strain at different fillet radii in an embodiment of the present invention.

[0065] Table 2:

[0066]

[0067] Step 5: Threshold Determination and Slip Defect Assessment. After measurement, the tensile specimens are sprayed with coupons. Under sufficient lighting, the surface quality of the specimens is assessed by light reflection. A visual analysis system can be used to analyze whether the slip edges on the substrate surface are completely covered by the paint film and record these results. Multiple sets of samples are obtained, as shown in Table 3. Finally, a relationship is established between the mold radius, strain, and assessment results.

[0068] Table 3:

[0069]

[0070] Among them, in Table 3, ε represents the strain amount, and the spraying evaluation of "yes" may represent that the height of the slip line profile affects the appearance quality of the stamping part after painting, and the corresponding actual result is abnormal; the spraying evaluation of "slight" may represent that the height of the slip line profile affects the appearance quality of the stamping part after painting, and the corresponding actual result is abnormal; the spraying evaluation of "no" may represent that the height of the slip line profile does not affect the appearance quality of the stamping part after painting, and the corresponding actual result is normal. Specifically, one group of samples has a fillet radius of 1.5mm and a strain amount of 5%, and the corresponding actual result is abnormal. It should be emphasized that Table 3 is only a defect evaluation correspondence table for one type of steel after slip. Other steel types and strain detection evaluation methods are the same as the above methods and will not be repeated here.

[0071] It should be noted that by obtaining a table that compares edge strain and surface quality assessment for specific steel grades after forming with different die corner radiuses, in actual stamping production, the impact of slip edges on the final sprayed surface quality can be determined based on the die corner radius and the strain after forming. Furthermore, based on the evaluation results of this table, the stamping process and sheet metal strain state can be adjusted to optimize the control of slip defects.

[0072] The embodiment of the present invention obtains the strain of the target stamping part after stamping by the target mold if there is a slip line in the target stamping part after stamping; inputs the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples includes the strain of the historical sample stamping part after stamping, the fillet radius of the sample mold and the actual result; if the first prediction result is normal, the target stamping part after stamping is painted; the first prediction result is normal, indicating that the slip line does not affect the appearance quality of the target stamping part after painting. Since the strain of the target stamping part after stamping and the fillet radius of the target mold are strongly correlated with the deformation of the stamping part, and the deformation of the stamping part affects the slip degree of the slip line. Therefore, a first prediction result can be determined based on the strain, fillet radius, and quality prediction model to characterize whether the slip line affects the appearance quality of the target stamping part after painting. This allows for judging appearance quality based on actual data, avoiding judgment based solely on manual experience, thereby achieving the beneficial effect of improving the accuracy of the assessment of the impact of the severity of the slip line on the appearance quality of the stamping part after painting. In addition, determining whether to paint the target stamping part based on the first prediction result reduces the possibility that the painted target stamping part will be a substandard product, thereby achieving the beneficial effect of reducing material waste.

[0073] Based on the same invention concept, Figure 8As shown, an embodiment of the present invention provides a stamping part slip defect control device 10 based on painting evaluation, including: a strain acquisition unit 110, which is used to obtain the strain of the target stamping part after stamping if a slip line exists in the target stamping part after stamping; a prediction unit 120, which is used to input the strain of the target stamping part after stamping and the fillet radius of the target mold into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, and each group of samples in the multiple groups of samples includes the strain of the historical sample stamping parts after stamping, the fillet radius of the sample mold and the actual results; a painting unit 130, which is used to paint the target stamping part after stamping if the first prediction result is normal; the first prediction result is normal, which indicates that the slip line does not affect the appearance quality of the target stamping part after painting.

[0074] It can be understood that the strain acquisition unit 110 is specifically used to: obtain the maximum height of the contour of the slip line of the target stamping part after stamping, the maximum height of the contour of the slip line is the maximum distance between a point on the slip line and the plane where the slip line is located; input the maximum height of the contour of the slip line and the fillet radius of the target mold into a preset first corresponding relationship to obtain the strain of the target stamping part after stamping; the first corresponding relationship is the correspondence between the maximum height of the contour of the slip line, the fillet radius of the mold and the strain of the stamping part after stamping. Among them, obtaining the maximum height of the contour of the slip line of the target stamping part after stamping includes: obtaining the maximum height of the contour of the slip line of the target stamping part after stamping through a roughness meter.

[0075] It can be understood that the stamping part slip defect control device 10 based on coating evaluation also includes: a model building unit, which is used to pre-establish a quality prediction model, including the following steps: obtaining multiple groups of samples; inputting the strain of the sample stamping parts of each group of samples in the multiple groups of samples after stamping and the fillet radius of the sample mold into the machine learning model to obtain a second prediction result; determining the loss function of the second prediction result and the actual result; based on the loss function of the second prediction result and the actual result, iteratively optimizing the machine learning model to obtain a quality prediction model.

[0076] It can be understood that the stamping part slip defect control device 10 based on painting evaluation also includes: a sample acquisition unit for pre-acquiring multiple groups of samples, wherein the sample acquisition unit includes: a stamping sub-unit for stamping the sample stamping part through the sample mold of the group of samples, so that the strain of the sample stamping part after stamping reaches the target strain, and the sample stamping part after stamping has a slip line; a spraying sub-unit for performing hanging spraying on the sample stamping part after stamping to obtain the sample stamping part after painting; an analysis sub-unit for performing surface visual analysis on the sample stamping part after painting to obtain an actual result for characterizing the appearance quality of the sample stamping part after painting; an acquisition sub-unit for obtaining data of the group of samples based on the target strain of the sample stamping part after stamping, the fillet radius of the sample mold and the actual result characterizing the appearance quality of the sample stamping part after painting.

[0077] It can be understood that the stamping sub-unit is specifically used to: input the target strain quantity into a preset second corresponding relationship to obtain a target forming height; the second corresponding relationship is the corresponding relationship between the forming height and the strain quantity of the sample stamping part when the sample stamping part is stamped; based on the target forming height, the sample mold is controlled to stamp the sample stamping part so that the strain quantity of the sample stamping part after stamping reaches the target strain quantity.

[0078] It can be understood that the analysis subunit is specifically used to: perform surface visual analysis on the sample stamping part after painting through a visual analysis system to determine whether there are ridges on the surface of the sample stamping part after painting; if there are no ridges on the surface of the sample stamping part after painting, the actual result is judged to be normal; if there are ridges on the surface of the sample stamping part after painting, the actual result is judged to be abnormal.

[0079] It is understandable that the stamping part slip defect control device 10 based on coating evaluation further includes: a marking unit for marking the target stamping part after stamping as an abnormal stamping part if the first prediction result is abnormal.

[0080] It should be understood that more implementation details of the stamping part slip defect control device 10 based on coating evaluation in the embodiment of the present invention can be found in the aforementioned stamping part slip defect control method based on coating evaluation. For the sake of brevity of the specification, they will not be repeated here.

[0081] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device, such as Figure 9As shown, it includes a memory 904, a processor 902 and a computer program stored in the memory 904 and executable on the processor 902. The processor 902 executes the program to implement the steps described in any embodiment of the method for controlling slip defects of stamping parts based on coating evaluation.

[0082] Among them, Figure 9 In the embodiment of the present invention, a bus architecture (represented by bus 900) is shown. Bus 900 may include any number of interconnected buses and bridges, and bus 900 links together various circuits including one or more processors represented by processor 902 and memory represented by memory 904. Bus 900 may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and are therefore not described further herein. Bus interface 905 provides an interface between bus 900 and receiver 901 and transmitter 903. Receiver 901 and transmitter 903 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 902 is responsible for managing bus 900 and general processing, while memory 904 may be used to store data used by processor 902 when performing operations.

[0083] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of the present invention and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or a combination of any of these. Furthermore, each functional unit may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0085] The units described as separate components may or may not be physically separate, and the components of the control device may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0086] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution 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 enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0087] The foregoing description is merely an embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be included within the scope of the claims.

Claims

1. A stamping part slip defect control method based on coating evaluation, characterized in that: include: After the target stamping part is stamped by the target die, if a slip line exists in the target stamping part after the stamping, obtaining the strain of the target stamping part after the stamping; Inputting the strain of the target stamping part after stamping and the fillet radius of the target die into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, each of the multiple groups of samples including the strain of the sample stamping part after stamping, the fillet radius of the sample die, and actual results in history; If the first prediction result is normal, the target stamping part after stamping is painted; the first prediction result being normal indicates that the slip line does not affect the appearance quality of the target stamping part after painting.

2. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 1, characterized in that: The obtaining of the strain of the target stamping part after stamping includes: Obtaining a maximum height of a contour of a slip line of the target stamping part after stamping, wherein the maximum height of the contour of the slip line is a maximum distance between a point on the slip line and a plane on which the slip line is located; The maximum height of the contour of the slip line and the fillet radius of the target mold are input into a preset first corresponding relationship to obtain the strain of the target stamping part after stamping; the first corresponding relationship is the corresponding relationship between the maximum height of the contour of the slip line, the fillet radius of the mold and the strain of the stamping part after stamping.

3. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 2, characterized in that: The obtaining of the maximum height of the slip line profile of the target stamping part after stamping includes: The maximum height of the slip line profile of the target stamping part after stamping is obtained by a roughness meter.

4. The method for controlling slip defects of stamping parts based on coating evaluation according to any one of claims 1 to 3, characterized in that: The quality prediction model is pre-established through the following steps: obtaining the multiple groups of samples; Inputting the strain of the sample stamping parts of each group of samples after stamping and the fillet radius of the sample mold into the machine learning model to obtain a second prediction result; Determining a loss function between the second predicted result and the actual result; Based on the loss function of the second prediction result and the actual result, the machine learning model is iteratively optimized to obtain the quality prediction model.

5. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 4, characterized in that: The data of each group of samples in the plurality of groups of samples are pre-acquired through the following steps: stamping the sample stamping part using the sample die of the group of samples so that the strain of the sample stamping part after stamping reaches the target strain, and a slip line exists on the sample stamping part after stamping; Performing sheet spraying on the stamped sample part to obtain the coated sample stamped part; Performing a surface visual analysis on the painted sample stamping part to obtain actual results for characterizing the appearance quality of the painted sample stamping part; The data of the group of samples are obtained based on the target strain of the sample stamping part after stamping, the fillet radius of the sample mold, and the actual results of characterizing the appearance quality of the sample stamping part after painting.

6. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 5, characterized in that: The step of stamping the sample stamping part by the sample die of the group of samples so that the strain of the sample stamping part reaches the target strain after stamping includes: The target strain amount is input into a preset second corresponding relationship to obtain a target forming height; the second corresponding relationship is a corresponding relationship between the forming height and the strain amount of the sample stamping part when the sample stamping part is stamped; Based on the target forming height, the sample die is controlled to perform stamping on the sample stamping part, so that the strain of the sample stamping part after stamping reaches the target strain.

7. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 5, characterized in that: The surface visual analysis of the painted sample stamping part to obtain actual results for characterizing the appearance quality of the painted sample stamping part includes: Performing a surface visual analysis on the painted sample stamping part by a visual analysis system to determine whether there are ridges on the surface of the painted sample stamping part; If there are no ridges on the surface of the sample stamping part after coating, the actual result is determined to be normal; If there are ridges on the surface of the sample stamped part after painting, the actual result is determined to be abnormal.

8. The method for controlling slip defects of stamping parts based on coating evaluation according to claim 1, characterized in that: Also includes: If the first prediction result is abnormal, the slip line profile height of the target stamping part surface after stamping is marked as abnormal.

9. A stamping part slip defect control device based on coating evaluation, characterized in that: include: a strain amount acquisition unit, configured to acquire the strain amount of the target stamping part after the target stamping part is stamped by the target die, if a slip line exists in the target stamping part after the stamping; a prediction unit, configured to input the strain of the target stamping part after stamping and the fillet radius of the target die into a preset quality prediction model to obtain a first prediction result; the quality prediction model is obtained by training a machine learning model based on multiple groups of samples, each of the multiple groups of samples including the strain of a historical sample stamping part after stamping, the fillet radius of the sample die, and actual results; A painting unit is used to paint the target stamping part after stamping if the first prediction result is normal; the first prediction result being normal indicates that the slip line does not affect the appearance quality of the target stamping part after painting.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 8 when executing the computer program.

Images