Profile defect detection method, device, electronic equipment and storage medium

Abstract

The present application relates to a profile defect detection method, device, electronic device and storage medium. The profile defect detection method of the present application includes: obtaining a microstructure diagram of a profile with defects; analyzing and obtaining defect detection results based on the microstructure diagram of the profile with defects; determining the order of project detection based on the defect detection results; and performing a defect cause judgment process for the profile based on the order of project detection. Therefore, the present application can improve the profile defect detection method, improve the profile manufacturing process, and thus improve the profile quality.

Description

Technical Field

[0001] The present application relates to the technical field of metal manufacturing, and in particular to a profile defect detection method, device, electronic equipment and storage medium. Background Art

[0002] Extrudate is an object with a certain geometric shape made of iron or steel and materials with certain strength and toughness (such as plastic, aluminum, fiberglass, etc.) through rolling, extrusion, casting and other processes. Among them, the products obtained in each link of the profile manufacturing process, that is, the intermediate product or the final product can be called profile.

[0003] With the development of profile structure, the quality requirements for profiles are getting higher and higher. For example, the requirements for grain refinement and grain homogenization of aluminum alloy profiles are getting higher and higher, so the defect rate requirements for aluminum alloy profiles are also getting higher and higher.

[0004] However, the traditional profile manufacturing method cannot know the cause of the defects after the profile has defects, nor can it improve the profile manufacturing process, thus affecting the improvement of profile quality. Summary of the invention

[0005] The purpose of the present application is to provide a profile defect detection method, device, electronic equipment and storage medium, which can improve the profile defect detection method, improve the profile manufacturing process, and thus improve the profile quality.

[0006] In order to achieve the above objectives,

[0007] In a first aspect, the present invention provides a profile defect detection method, comprising:

[0008] Obtaining microstructure diagram of profiles with defects;

[0009] Analyze and obtain defect detection results according to the microstructure diagram of the profile with defects;

[0010] Determine the order of project inspection according to the defect inspection results;

[0011] According to the detection sequence of the items, the defect cause determination process of the profile is carried out.

[0012] In one embodiment, the defect detection result is obtained by analyzing the microstructure diagram of the profile with defects, including:

[0013] Inputting the microstructure diagram of the profile with defects into a first preset model;

[0014] Using the first preset model, performing image-defect correlation analysis on the microstructure diagram of the profile with defects;

[0015] The defect detection result is obtained according to the correlation analysis result between the image and the defect.

[0016] In one embodiment, the defect detection result includes: grain difference and second phase difference.

[0017] In one embodiment, determining the order of item detection according to the defect detection result includes:

[0018] Inputting the defect detection result into a second preset model;

[0019] Using the second preset model, performing a correlation analysis between the defect and the item to be tested on the defect detection result;

[0020] The order of item detection is determined based on the correlation analysis results between the defects and the items to be detected.

[0021] In one embodiment, according to the item detection sequence, the defect cause determination process of the profile includes:

[0022] Performing initial project testing according to the project testing sequence;

[0023] Determining whether the defect is related to the initial project;

[0024] If the defect is not related to the initial item, the next item to be tested is tested according to the item testing sequence;

[0025] If the defect is related to the initial item, adjusting relevant parameters of the initial item;

[0026] Re-testing the initial project according to the adjusted relevant parameters;

[0027] Determine whether the cause of the defect of the initial project has been eliminated;

[0028] If the cause of the defect of the initial project has not been eliminated, continue to adjust the relevant parameters of the initial project;

[0029] If the defect cause of the initial item is eliminated, then determine whether the defect causes of all items to be tested are completely eliminated;

[0030] If the causes of defects of all items to be tested have not been completely eliminated, the next item to be tested is tested according to the order of item testing;

[0031] If the defect causes of all items to be tested are completely eliminated, the defect cause determination process ends.

[0032] In one embodiment, the item detection sequence includes:

[0033] Conduct project testing of anodizing process;

[0034] Carry out project testing of solution treatment process;

[0035] Carry out project testing of extrusion process;

[0036] Conduct project testing of the original ingot casting process;

[0037] Carry out project testing of aging process.

[0038] In one embodiment, the step of obtaining a microstructure diagram of a profile having defects includes:

[0039] Provide the profile to be tested;

[0040] Testing the profile to be tested;

[0041] Determining whether the profile to be tested has defects;

[0042] If the profile to be tested has defects, a microstructure diagram of the profile with defects is obtained.

[0043] In a second aspect, the present invention provides a profile defect detection device, comprising:

[0044] An acquisition module, used for acquiring a microstructure diagram of a profile with defects;

[0045] An analysis module, used for analyzing and obtaining defect detection results according to the microstructure diagram of the profile with defects;

[0046] A determination module, used to determine the order of project detection according to the defect detection result;

[0047] The detection module is used to perform defect detection on the profile according to the detection sequence of the items.

[0048] In a third aspect, the present invention provides an electronic device, comprising:

[0049] Memory for storing computer programs;

[0050] A processor is used to execute the method as described in any one of the aforementioned embodiments.

[0051] In a fourth aspect, the present invention provides a non-transitory electronic device readable storage medium, comprising: a program, which, when executed by an electronic device, enables the electronic device to execute any of the methods described in the aforementioned embodiments.

[0052] The present application discloses a profile defect detection method, device, electronic device, and storage medium. By analyzing the microstructure diagram of a profile with defects, the defect detection result is obtained, so that the category of the defect can be known; then based on the category of the defect, the defect detection sequence is determined, and the profile defect detection can be performed according to the defect detection sequence, so that the error can be quickly located and eliminated, and the profile manufacturing process can be further improved. Therefore, the present application can improve the profile defect detection method, improve the profile manufacturing process, and thus improve the profile quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A schematic flow chart of a profile defect detection method according to an embodiment of the present application.

[0055] Figure 2 An embodiment of the present application is shown Figure 1 A detailed flowchart of step S110 in the corresponding embodiment.

[0056] Figure 3 An embodiment of the present application is shown Figure 1 A detailed flowchart of step S120 in the corresponding embodiment.

[0057] Figure 4 An embodiment of the present application is shown Figure 1 A detailed flowchart of step S130 in the corresponding embodiment.

[0058] Figure 5 An embodiment of the present application is shown Figure 1 A detailed flowchart of step S140 in the corresponding embodiment.

[0059] Figure 6 This is a schematic diagram of a detection item shown in an embodiment of the present application.

[0060] Figure 7 A schematic diagram of the test process of a profile defect detection method according to an embodiment of the present application.

[0061] Figure 8 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application.

[0062] Fig. 9 This is a schematic structural diagram of a profile defect detection device shown in one embodiment of the present application.

[0063] Icon: 100 - electronic device; 101 - bus; 102 - memory; 103 - processor; 200 - profile defect detection device; 210 - acquisition module; 220 - analysis module; 230 - determination module; 240 - detection module. DETAILED DESCRIPTION

[0064] In the description of the present application, the terms "first", "second", etc. are only used to distinguish the description and do not indicate the order of arrangement, nor can they be understood as indicating or implying relative importance.

[0065] In the description of the present application, the terms "include", "comprising", etc. indicate the existence of the described features, integers, steps, operations, elements and / or components, but do not exclude the existence or addition of one or more other features, steps, operations, elements, components and / or collections thereof.

[0066] In the description of this application, unless otherwise clearly specified and limited, the terms "installed", "set", "provided with", "connected", and "configured to" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection, an indirect connection through an intermediate medium, or an internal connection between two devices, elements, or components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0067] The technical solution of the present application will be described clearly and completely below in conjunction with the accompanying drawings.

[0068] Please refer to Figure 1 , which is a flow chart of a profile defect detection method according to an embodiment of the present application. A profile defect detection method may include the following steps:

[0069] Step S110: obtaining a microstructure diagram of a profile having defects.

[0070] The material of the profile in this step can be metal or non-metal, such as iron, steel, aluminum alloy, plastic or glass fiber, etc. The profile in this step can be the product obtained in each link of the profile manufacturing process, and can be the final product or the intermediate product.

[0071] When the obtained microstructure diagram of the profile with defects belongs to the final product, the profile defect detection method can determine which process link in the entire profile manufacturing process has an error, causing the defect, and correct the process parameters.

[0072] When the obtained microstructure diagram of the defective profile belongs to an intermediate product, the profile defect detection method can determine which process link in the manufacturing process before the intermediate product is wrong, causing the defect, and correct the process parameters.

[0073] In this embodiment, the profile of this step is the final product, and the material of the profile is aluminum alloy.

[0074] Step S120: Analyze and obtain defect detection results based on the microstructure diagram of the profile with defects.

[0075] In order to speed up the detection speed, this step analyzes the microstructure diagram of the profile with defects to obtain the defect detection results, so that the category of the defects can be known, which is convenient for determining the order of project detection in a targeted manner later. The defect detection results in this step include grain differences and second phase differences, and the defect detection results also include the proportion of grain differences and the proportion of second phase differences.

[0076] In one embodiment, the defect detection result of step S120 also includes the properties of the profile of step S110, that is, whether the profile of step S110 is an intermediate product or a final product. When the profile of step S110 is an intermediate product, the defect detection result needs to record the profile manufacturing process link corresponding to the intermediate product.

[0077] Step S130: Determine the order of item detection according to the defect detection result.

[0078] The inspection items in this step are all links of the profile manufacturing process. Since it is necessary to determine which link caused the defect, a reverse method is generally adopted to improve the profile manufacturing process one by one in the form of elimination method to avoid the formation of defects.

[0079] In order to speed up the detection, this step can determine which link is more likely to go wrong based on the characterization results of step S120 and the relationship between the defect and the detection item, so as to adjust the order of each detection item and determine the order of item detection.

[0080] For example, when it is judged that the difference in defective grains of the profile to be tested is relatively serious, the extrusion process can be tested first; when it is judged that the difference in the defective second phase of the profile to be tested is relatively serious, the solution process can be tested first; since the aging process is mainly to eliminate the internal stress of the workpiece and stabilize the structure and size, it has little effect on the generation of profile defects and can be considered to be carried out as the last step.

[0081] When the possibility of error in each link is similar, the order of project testing can be adjusted according to the convenience of testing. For example, the aging process project that requires transmission analysis can be considered as the last step.

[0082] In one embodiment, when the defect detection result of step S120 records that the profile of step S110 is a final product, the items to be tested in the item detection sequence determined in step S130 may include the entire profile manufacturing process.

[0083] In one embodiment, when the defect detection result of step S120 records that the profile of step S110 is an intermediate product, the items to be tested in the item detection sequence determined in step S130 may only include part of the entire profile manufacturing process, excluding the profile manufacturing process after the intermediate product.

[0084] Step S140: According to the order of item detection, the defect cause determination process of the profile is carried out.

[0085] According to the order of item testing, test items one by one.

[0086] Each inspection item can be targeted at two profile samples from the same batch, or two profile samples from the same position of the same profile, and the process treatment corresponding to the inspection item can be carried out under the same conditions to determine whether the products corresponding to the two samples have defects. If defects occur in both, or one has defects and the other does not, it is determined that this process link is related to the cause of the defects. If defects do not occur in both, it is determined that this process link is not related to the cause of the defects and the next inspection item can be carried out.

[0087] According to the test results of each test item, adjust the relevant parameters of the corresponding profile manufacturing process link, and then conduct tests. Based on whether the defects of the product made by the profile manufacturing process parameters adjusted in this link disappear, it can be judged whether the profile manufacturing process parameters have been improved.

[0088] When one of the inspection items is carried out, after testing, if the product made based on the profile manufacturing process parameters adjusted for this item is consistent with or similar to the reference object of this link, it is judged that the cause of the defect in this item has been eliminated.

[0089] Among them, since the defect detection results may include many different differences, there may be multiple corresponding profile manufacturing process links. Therefore, after the defect cause of one inspection item is eliminated, the defect cause of another inspection item needs to be eliminated. Therefore, when the product produced based on the profile manufacturing process parameters adjusted based on multiple links will not produce defects, or the defect rate has been controlled within the expected range, it is judged that the defect causes of all items are completely eliminated.

[0090] During the entire defect cause judgment process, the situation of each step can be recorded in real time. When the entire defect cause judgment process is completed, the corrected profile manufacturing process parameters can be obtained, and it can also be determined which one or several inspection items the defect cause is related to, that is, it can be determined which one or several profile manufacturing process links the defect cause is related to, and the corresponding defect cause analysis report and the corrected profile manufacturing process parameter report can be generated for reference.

[0091] Therefore, this embodiment analyzes the microstructure diagram of the profile with defects to obtain the defect detection result, so that the category of the defect can be known; then based on the category of the defect, the defect detection sequence is determined, and the profile defect detection can be performed according to the defect detection sequence, so that the error can be quickly located and eliminated, and the profile manufacturing process can be further improved. Therefore, this embodiment can improve the profile defect detection method, improve the profile manufacturing process, and thus improve the profile quality.

[0092] Each step in this embodiment may be implemented manually or automatically by a computer according to a preset model, algorithm or program.

[0093] Please refer to Figure 2 , which is shown in an embodiment of the present application Figure 1 The detailed flow chart of step S110 in the corresponding embodiment. Step S110 may include the following steps:

[0094] Step S111: providing a profile to be tested.

[0095] Step S112: testing the profile to be tested.

[0096] Step S113: Determine whether the profile to be tested has defects.

[0097] Step S114: If the profile to be tested has defects, a microstructure diagram of the profile with defects is obtained.

[0098] This embodiment also includes a step of determining whether the profile to be tested has defects. Each step in this embodiment can be implemented manually or automatically by a computer according to a pre-set model, algorithm or program. For example, a microstructure diagram of a normal profile can be stored in the computer in advance, and by comparing the images, it can be determined whether the profile has defects.

[0099] Please refer to the detailed description of step S110 for the profile to be tested in the above steps. It can be the product obtained in each link of the profile manufacturing process, and can be the final product or the intermediate product.

[0100] Please refer to Figure 3 , which is shown in an embodiment of the present application Figure 1The detailed flow chart of step S120 in the corresponding embodiment. Step S120 may include the following steps:

[0101] Step S121: inputting the microstructure diagram of the profile with defects into the first preset model.

[0102] Step S122: using the first preset model, performing correlation analysis between the image and the defects on the microstructure diagram of the profile with defects.

[0103] Step S123: Obtain defect detection results based on the correlation analysis results between the image and the defect.

[0104] The first preset model of this embodiment can be a pre-trained model. A large number of profile microstructure diagrams with defects of different categories can be stored in the computer in advance to train the first preset model. According to the similarity calculation result output by the first preset model, the correlation between the image and the defect is analyzed to obtain the category of the defect, so as to prepare for the next step of determining the order of project detection.

[0105] Please refer to Figure 4 , which is shown in an embodiment of the present application Figure 1 The detailed flow chart of step S130 in the corresponding embodiment. Step S130 may include the following steps:

[0106] Step S131: input the defect detection result into the second preset model.

[0107] Step S132: using the second preset model, performing a correlation analysis between the defect and the item to be tested on the defect detection result.

[0108] Step S133: Determine the order of item detection according to the correlation analysis results between the defects and the items to be detected.

[0109] The second preset model of this embodiment can be a pre-trained model. According to the correlation calculation result output by the second preset model, the correlation between the defect and the item to be tested is analyzed. According to the correlation ranking and the convenience of detection, the order of each detection item is adjusted to determine the order of project detection and prepare for the next step of project detection.

[0110] Please refer to Figure 5 , which is shown in an embodiment of the present application Figure 1 The detailed flow chart of step S140 in the corresponding embodiment. Step S140 may include the following steps:

[0111] Step S141: Perform initial project detection according to the project detection sequence.

[0112] Step S142: Determine whether the defect is related to the initial project.

[0113] In the above steps S141 and S142, each inspection item can be for two profile samples from the same batch, or two profile samples from the same position of the same profile, and the process treatment corresponding to the inspection item can be carried out under the same conditions to determine whether the products corresponding to the two samples have defects, so as to determine whether the defects are related to the initial item. If the defects are not related to the initial item, execute step S143; if the defects are related to the initial item, execute step S144.

[0114] Step S143: Perform the test of the next item to be tested according to the item testing sequence.

[0115] The detection of the next item to be detected in this step is the same as that of step S141 and step S142 except that the detection item is different from the initial item detection in step S141 and step S142.

[0116] Step S144: adjusting the relevant parameters of the initial project.

[0117] Step S145: re-test the initial items according to the adjusted relevant parameters.

[0118] Step S146: Determine whether the defect cause of the initial item has been eliminated.

[0119] In the above-mentioned steps S144, S145 and S146, the relevant parameters of the profile manufacturing process link corresponding to the initial project can be adjusted and then the test can be carried out. If the defects of the product obtained by the test are partially eliminated or completely eliminated and the quality reaches the best, it is judged that the cause of the defect in this link is eliminated and step S147 is executed; otherwise, if the cause of the defect of the initial project is not eliminated, jump to step S144, execute steps S144, S145 and S146 until the cause of the defect of the initial project is eliminated.

[0120] Step S147: Determine whether the causes of defects of all items to be tested are completely eliminated.

[0121] In this step, if the product obtained in step S146 does not have any defects and is highly similar to the microstructure diagram of a normal product, it is determined that the defect causes of all items to be tested are completely eliminated, and the defect cause determination process ends. On the contrary, if the defect causes of all items to be tested are not completely eliminated, step S143 is executed to test the next item to be tested according to the item detection order.

[0122] Each step in step S141-step S147 can record the situation of each step in real time and generate a log. After step S147, a corresponding defect cause analysis report and a corrected profile manufacturing process parameter report can be generated for reference.

[0123] Please refer to Figure 6 , which is a schematic diagram of a detection item shown in an embodiment of the present application. In one embodiment, a detection item may include multiple different detection means, and multiple different detection means may be used successively to improve detection accuracy, or only one of them may be selected to improve detection speed.

[0124] Figure 6 The test items when the profile is aluminum alloy are shown in the figure, and the test items are determined according to the profile manufacturing process. The profile manufacturing process of this embodiment includes: first obtaining an original cast rod, then performing a homogenization process to obtain a homogenized cast rod, then performing an extrusion process to obtain an extruded profile, then performing a solid solution process to obtain a solid solution profile, then performing an aging process to obtain an aged profile, and finally performing an oxidation process to obtain an oxidized profile.

[0125] Among them, when the inspection item is the original cast rod, its inspection means may include: grain (including segregation layer) analysis, composition (radial) segregation analysis, impurity (including oxide scale) analysis and non-equilibrium eutectic phase analysis. When the inspection item is the homogenization process, its inspection means may include: non-equilibrium eutectic phase dissolution analysis, second phase precipitation analysis, grain analysis and overburning structure analysis. When the inspection item is the extrusion process, its inspection means may include: deformation structure analysis, grain recrystallization analysis, grain orientation (texture) analysis and hardness and conductivity analysis. When the inspection item is the solution process, its inspection means may include: second phase dissolution analysis, grain recrystallization analysis, overburning structure analysis and conductivity test. When the inspection item is the aging process, its inspection means may include: nano-precipitation phase analysis, grain and grain boundary analysis and mechanical properties analysis. When the inspection item is the oxidation process, its inspection means may include: oxide film appearance analysis, high-throughput observation of grain differences, second phase analysis and corrosion performance (oxidation) analysis.

[0126] Please refer to Figure 7 , which is a schematic diagram of the test process of a profile defect detection method shown in an embodiment of the present application. Figures 1 to 5 The profile defect detection method shown was tested. The test process includes the following steps:

[0127] Step (1): Conduct the first test of the anodizing process.

[0128] Take the profile to be anodized and perform anodizing treatment to observe whether there are any structural defects on the appearance, so as to determine whether there are any problems with the anodizing process.

[0129] If there are differences in the appearance of structural defects, it is judged that there is a problem with the anodizing process.

[0130] At this time, the parameters of the anodizing process can be improved by adjusting the oxidation electrolyte, current density and / or fixture structure, and can refer to Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0131] Step (2): Conduct the second test of the anodizing process.

[0132] If there is no difference in appearance in step (1), a high-throughput SEM analysis (SEM, High Throughput, high-throughput scanning electron beam microscope) is performed on the oxidized material in the anodizing process to observe whether there is a difference in the structure of the defective area and the normal area, with a focus on the difference in grain size and shape.

[0133] If there is a significant difference in grain size, it is judged that there is a problem with the oxidation material in the anodizing process.

[0134] At this time, the parameters of the anodizing process can be improved by adjusting the extrusion die, extrusion temperature and / or extrusion force, and can refer to Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0135] In one embodiment, the high-throughput SEM scan can perform a regional scan on a location of interest and observe the tissue morphology of the entire region at a color temperature of 2000K-20000K.

[0136] Step (3): Conduct project testing of the solutionizing process.

[0137] If there is no difference in step (2), take the profile after solid solution for SEM analysis to observe whether the second phase in the defect area is different from the second phase in the normal area. Focus on whether the second phase in the defect area is more and coarser than the second phase in the normal area, and pay attention to the composition of the second phase, whether it is SiMg2 or S phase obtained by nitriding and carburizing.

[0138] If the second phase is enriched and coarse in the defect area and the second phase composition is clear, it is judged that there is a problem with the solid solution process.

[0139] At this time, the parameters of the solution process can be improved by adjusting the solution temperature or time, reducing the content of impurity elements and / or increasing the homogenization temperature or time, and can refer to Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0140] Step (4): Conduct project inspection of the extrusion process.

[0141] If there is no difference in step (3), take the extruded profile for EBSD analysis (EBSD, Electron Backscattered Diffraction) to observe the difference in grains between the defective area and the normal area, and analyze whether there are differences in grain orientation and recrystallization.

[0142] If there are obvious differences in the grains, it is judged that there is a problem with the extrusion process.

[0143] At this time, the extrusion process parameters can be improved by adjusting the oil temperature, extrusion pressure, die design and / or adding online cooling facilities, and can refer to Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0144] Step (5): Conduct project inspection of the original ingot casting process.

[0145] If there is no difference in step (4), the original ingot is taken for composition and profile analysis to analyze the radial composition, segregation thickness, profile impurities and radial grain differences of the ingot.

[0146] If there is an obvious thickness of the segregation layer, impurities such as oxide scale are present in the cross section, and there is a large difference between the edge and center grains, it is judged that there is a problem with the original ingot casting process.

[0147] At this time, the parameters of the original ingot casting process can be improved by improving the quality of the ingot car, increasing the casting melt treatment process, adjusting the casting speed and temperature, and / or adjusting the grain refinement, and can refer to Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0148] Step (6): Conduct project testing of the aging process.

[0149] If there is no difference in step (5), take the aged profile for TEM analysis (TEM, Transmission Electron Microscope) to observe the difference in nano-precipitation phases within the grain and at the grain boundary, and pay special attention to whether particles such as ZrAl3 are aggregated.

[0150] If there is aggregation of nano-precipitated phases and the composition of the precipitated phases is consistent with the refiner, it is judged that there is a problem with the aging process.

[0151] At this time, the aging process parameters can be improved by adjusting the amount of casting refiners and micro-alloying elements added, increasing the homogenization temperature or time, and / or adjusting the aging temperature or time. Figure 5 In the illustrated embodiment, it is determined whether to end the test process.

[0152] Please refer to Figure 8, which is a schematic diagram of the structure of an electronic device 100 according to an embodiment of the present application. The electronic device 100 includes: at least one processor 103 and a memory 102, Figure 8 A processor 103 is taken as an example. The processor 103 and the memory 102 are connected via a bus 101. The memory 102 stores instructions that can be executed by the processor 103. The instructions are executed by the processor 103 so that the electronic device 100 can execute all or part of the process of the method in the following embodiment to improve the profile defect detection method and improve the profile manufacturing process.

[0153] In one embodiment, the processor 103 may be a general processor 103, including but not limited to a central processing unit 103 (CPU), a network processor 103 (NP), etc., and may also be a digital signal processor 103 (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general processor 103 may be a microprocessor 103 or the processor 103 may also be any conventional processor 103, etc. The processor 103 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100. The processor 103 may implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application.

[0154] In one embodiment, the memory 102 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to random access memory 102 (Random Access Memory, RAM), read only memory 102 (Read Only Memory, ROM), static random access memory 102 (Static Random Access Memory, SRAM), programmable read-only memory 102 (Programmable Read-Only Memory, PROM), erasable read-only memory 102 (Erasable Programmable Read-Only Memory, EPROM), and electrically erasable read-only memory 102 (Electric Erasable Programmable Read-Only Memory, EEPROM).

[0155] The electronic device 100 may be a mobile phone, a laptop computer, a desktop computer, or a computing system composed of multiple computers. The electronic device 100 may also include Figure 8 More or fewer components as shown, or with Figure 8 For example, the electronic device 100 further includes an input and output device for human-computer interaction.

[0156] Please refer to Fig. 9 , which is a schematic diagram of the structure of a profile defect detection device 200 shown in an embodiment of the present application. The device can be applied to Figure 8 The electronic device 100 shown includes: an acquisition module 210, an analysis module 220, a determination module 230 and a detection module 240. The principle relationship between each module is as follows:

[0157] An acquisition module 210 is used to acquire a microstructure diagram of a profile having defects;

[0158] An analysis module 220 is used to analyze and obtain defect detection results based on the microstructure diagram of the profile with defects;

[0159] A determination module 230 is used to determine the order of project detection according to the defect detection result;

[0160] The detection module 240 is used to perform defect detection of the profile according to the item detection sequence.

[0161] For a detailed description of the above-mentioned profile defect detection device 200, please refer to the description of the relevant method steps in the above-mentioned embodiment.

[0162] The embodiment of the present application also provides a storage medium readable by an electronic device 100, including: a program, when it is run on the electronic device 100, the electronic device 100 can execute all or part of the process of the method in the above embodiment. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory 102 (Flash Memory), a hard disk (Hard Disk Drive, abbreviated: HDD) or a solid-state drive (SSD), etc. The storage medium can also include a combination of the above-mentioned types of memory 102.

[0163] In several embodiments provided in the present application, the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a portion of a code, and a module, a program segment, or a portion of a code includes one or more executable instructions for implementing a specified logical function.

[0164] In some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flow chart, and combinations of blocks in the block diagram and / or flow chart, may be implemented using a dedicated hardware-based system that performs the specified functions or actions, or may be implemented using a combination of dedicated hardware and computer instructions.

[0165] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0166] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. The above are only preferred embodiments of the present application, which are only used to illustrate the technical solution of the present application and are not used to limit the present application. For ordinary technicians in this technical field, any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

[0167] It should be noted that, in the absence of conflict, the features in the embodiments of the present application can be combined with each other. The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A profile defect detection method, characterized in that: include: Obtaining microstructure diagram of profiles with defects; Analyze and obtain defect detection results according to the microstructure diagram of the profile with defects; Determine the order of project inspection according to the defect inspection results; According to the detection order of the items, a defect cause determination process of the profile is carried out; Wherein, determining the order of item detection according to the defect detection result comprises: inputting the defect detection result into a second preset model; using the second preset model to perform a correlation analysis between the defect and the item to be tested on the defect detection result; and determining the order of item detection according to the result of the correlation analysis between the defect and the item to be tested; The process of determining the cause of the defect of the profile according to the order of item detection includes: detecting the initial item according to the order of item detection; determining whether the defect is related to the initial item; if the defect is not related to the initial item, detecting the next item to be detected according to the order of item detection; if the defect is related to the initial item, adjusting the relevant parameters of the initial item; re-detecting the initial item according to the adjusted relevant parameters; determining whether the cause of the defect of the initial item is eliminated; if the cause of the defect of the initial item is not eliminated, continuing to adjust the relevant parameters of the initial item; if the cause of the defect of the initial item is eliminated, determining whether the causes of the defect of all items to be tested are completely eliminated; if the causes of the defects of all items to be tested are not completely eliminated, detecting the next item to be tested according to the order of item detection; if the causes of the defects of all items to be tested are completely eliminated, ending the process of determining the cause of the defect.

2. The profile defect detection method according to claim 1, characterized in that: The defect detection result is obtained by analyzing the microstructure diagram of the defective profile, including: Inputting the microstructure diagram of the profile with defects into a first preset model; Using the first preset model, performing image-defect correlation analysis on the microstructure diagram of the profile with defects; The defect detection result is obtained according to the correlation analysis result between the image and the defect.

3. The profile defect detection method according to claim 2, characterized in that: The defect detection results include: grain difference and second phase difference.

4. The profile defect detection method according to claim 1, characterized in that: The project detection sequence includes: Conduct project testing of anodizing process; Carry out project testing of solution treatment process; Carry out project testing of extrusion process; Conduct project testing of the original ingot casting process; Carry out project testing of aging process.

5. The profile defect detection method according to any one of claims 1 to 4, characterized in that: The step of obtaining a microstructure diagram of a profile having defects comprises: Provide the profile to be tested; Testing the profile to be tested; Determining whether the profile to be tested has defects; If the profile to be tested has defects, a microstructure diagram of the profile with defects is obtained.

6. A profile defect detection device, characterized in that: include: An acquisition module, used for acquiring a microstructure diagram of a profile with defects; An analysis module, used for analyzing and obtaining defect detection results according to the microstructure diagram of the profile with defects; A determination module, used to determine the order of project detection according to the defect detection result; A detection module, used for performing defect detection of the profile according to the detection sequence of the items; Wherein, determining the order of item detection according to the defect detection result comprises: inputting the defect detection result into a second preset model; using the second preset model to perform a correlation analysis between the defect and the item to be tested on the defect detection result; and determining the order of item detection according to the result of the correlation analysis between the defect and the item to be tested; The process of determining the cause of the defect of the profile according to the order of item detection includes: detecting the initial item according to the order of item detection; determining whether the defect is related to the initial item; if the defect is not related to the initial item, detecting the next item to be detected according to the order of item detection; if the defect is related to the initial item, adjusting the relevant parameters of the initial item; re-detecting the initial item according to the adjusted relevant parameters; determining whether the cause of the defect of the initial item is eliminated; if the cause of the defect of the initial item is not eliminated, continuing to adjust the relevant parameters of the initial item; if the cause of the defect of the initial item is eliminated, determining whether the causes of the defect of all items to be tested are completely eliminated; if the causes of the defects of all items to be tested are not completely eliminated, detecting the next item to be tested according to the order of item detection; if the causes of the defects of all items to be tested are completely eliminated, ending the process of determining the cause of the defect.

7. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to execute the method according to any one of claims 1 to 5.

8. A non-transitory electronic device readable storage medium, characterized in that: The invention comprises: a program, which, when executed by an electronic device, causes the electronic device to execute the method according to any one of claims 1 to 5.

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