Method for determining three-dimensional bulk defects of an alloy

Abstract

The embodiment of the present application provides a kind of alloy three-dimensional defect determination method, the method comprises: establishing body defect quantification model, the body defect quantification model characterizes the mapping relationship between the defect volume fraction of the three-dimensional body defect of the alloy and the sampling thickness of the alloy, wherein the sampling thickness is the etching thickness or un-etching thickness of the alloy;Prepare the test sample of the alloy, and determine the sampling thickness of the test sample;Based on the sampling thickness of the test sample, the corresponding defect volume fraction in the quantification model is determined.The three-dimensional defect determination method in the embodiment of the present application can not only determine the defect volume fraction of the three-dimensional body defect of the alloy at low cost and efficiently, but also be suitable for batch pre-screening.

Description

Technical Field

[0001] This application relates to the field of corrosion detection technology, specifically to a method for determining three-dimensional defects in an alloy. Background Technology

[0002] Magnesium alloys and other alloys are widely used in automotive bodies and aerospace structural components. During the smelting, die casting, and extrusion molding processes, three-dimensional defects such as porosity, shrinkage cavities, micro-porosity, and internal inclusions are easily generated. These defects can disrupt the continuity of the matrix and form preferential corrosion penetration channels, directly affecting the mechanical load-bearing capacity, corrosion resistance life, and service safety of magnesium alloys. The volume fraction, spatial distribution, and size grade of three-dimensional defects are core evaluation indicators for material research and development, production quality control, and incoming inspection.

[0003] Among related technologies, some magnesium alloy defect detection techniques employ industrial CT and ultrasonic scanning equipment. However, industrial CT and ultrasonic scanning are costly and inefficient, only allowing for small-batch sampling inspections, which cannot meet the pre-process batch screening requirements of the entire production line. Other magnesium alloy defect detection technologies utilize metallographic analysis. However, metallographic analysis can only observe surface cross-sectional defects in alloy samples, enabling only qualitative assessment of surface defects and failing to quantitatively evaluate the volume fraction of three-dimensional defects within the material. Summary of the Invention

[0004] In view of this, the embodiments of this application aim to provide a method for determining three-dimensional volume defects of alloys, which can not only determine the defect volume fraction of three-dimensional volume defects of alloys in a low cost and with high efficiency, but is also suitable for batch pre-screening.

[0005] To achieve the above objectives, one embodiment of this application provides a method for determining three-dimensional defects in an alloy, the method comprising: A volume defect quantification model is established, which characterizes the mapping relationship between the defect volume fraction of the three-dimensional volume defects of the alloy and the sampling thickness of the alloy, wherein the sampling thickness is the corrosion thickness or the uncorroded thickness of the alloy. Prepare a test sample of the alloy and determine the sampling thickness of the test sample; Based on the sampling thickness of the test sample, the corresponding defect volume fraction in the quantification model is determined.

[0006] In one embodiment, the step of establishing a volumetric defect quantification model includes: Two control samples of the alloy were prepared, one of which was a control sample without bulk defects, and the other was a control sample with bulk defects having a defined volume fraction of defects. The sampling thickness of the defect-free control sample and the control sample were determined respectively. The volume defect quantification model is established based at least on the sampling thickness of the volume defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness.

[0007] In one embodiment, the step of establishing the volume defect quantification model based at least on the sampling thickness of the defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness includes: The intrinsic correction value is obtained by performing an intrinsic correction on the sampling thickness of the control sample without volume defects based on the sampling thickness of the control sample without volume defects. The volume defect quantification model is established based on the defect volume fraction of the volume defect control sample and the correction value.

[0008] In one embodiment, the step of establishing the volume defect quantification model based on the defect volume fraction of the volume defect control sample and the correction value includes: Linear fitting was performed on the defect volume fraction of the volume defect control sample and the correction value; The mapping relationship of the volume defect quantification model is determined as: Y = k·X + c, where Y represents the defect volume fraction, X represents the correction value, k and c are constants, and k is not equal to 0.

[0009] In one embodiment, the number of volume defect control samples is multiple, and the defect volume fraction of each volume defect control sample is different.

[0010] In one embodiment, before determining the sampling thickness of the control sample without volume defects and the control sample with volume defects, the method further includes: The outer periphery of each of the two control samples is encapsulated, with only one side of each control sample exposed to form a test surface; The same corrosion treatment was applied to both control samples. The sampling thickness of each of the various control samples was measured using the test surface of each control sample as a reference.

[0011] In one embodiment, the step of determining the sampling thickness of each of the various control samples, using the test surface of each control sample as a reference, includes: Using the test surface of the control sample as a reference, the control sample is subjected to multiple grinding and polishing processes. After each grinding and polishing process, the polished surface of the control sample is observed under a microscope to determine whether there are corrosion traces corresponding to the corrosion treatment. If the corrosion marks are present, the next polishing process is performed; if the corrosion marks are not present, the polishing process is stopped. The uncorroded thickness of the control sample is determined based on the polished surface obtained after the final polishing process.

[0012] In one embodiment, the polishing depth of each polishing process does not exceed 50 μm; And / or, the back side of the control sample opposite to the test surface has a first geometric center, and the polished surface obtained after the last grinding and polishing treatment of the control sample has a second geometric center, and the length of the line connecting the first geometric center and the second geometric center is the uncorroded thickness.

[0013] In one embodiment, the step of performing the same corrosion treatment on the two control samples includes: The two control samples were immersed in the same corrosive solution for the same duration.

[0014] In one embodiment, the method further includes: The test sample is subjected to the same corrosion treatment as the control sample, and the sampling thickness of the test sample is determined using the same measurement method as the control sample.

[0015] In one embodiment, the test sample has the same external dimensions as the various control samples.

[0016] In one embodiment, the number of the non-defect control samples is multiple, and the sampling thickness of the non-defect control samples is the average of the sampling thicknesses of the multiple non-defect control samples.

[0017] The method for determining three-dimensional volumetric defects in alloys in this embodiment establishes a volumetric defect quantification model based on the correlation between the defect volume fraction of three-dimensional volumetric defects and the corrosion thickness and uncorroded thickness of the alloy. This model characterizes the mapping relationship between the defect volume fraction of three-dimensional volumetric defects in the alloy and the sampling thickness of the alloy, where the sampling thickness is either the corrosion thickness or the uncorroded thickness of the alloy. When testing the sample, the sampling thickness of the sample is directly converted into the corresponding defect volume fraction through the volumetric defect quantification model, achieving low-cost and efficient determination of the defect volume fraction. Furthermore, the volumetric defect quantification model can be reused after its establishment. In actual testing of the sample, only the sampling thickness needs to be measured, and the corresponding defect volume fraction can be directly obtained by substituting it into the volumetric defect quantification model. The operation is simple and efficient, enabling large-scale testing. Therefore, the three-dimensional volumetric defect determination method in this embodiment can not only determine the defect volume fraction of three-dimensional volumetric defects in alloys at low cost and high efficiency, but is also suitable as a pre-screening method for industrial CT and ultrasonic precision testing. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for determining defects in a three-dimensional body according to an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a control sample according to an embodiment of this application.

[0019] Explanation of reference numerals in the attached figures: 10. Control sample; 10a. Test surface; 10b. Polished surface; 10c. Back side; 10d. First geometric center; 10e. Second geometric center. Detailed Implementation

[0020] This application provides a method for determining three-dimensional defects in an alloy. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: Step S101: Establish a volume defect quantification model. The volume defect quantification model characterizes the mapping relationship between the defect volume fraction of the three-dimensional volume defects of the alloy and the sampling thickness of the alloy, wherein the sampling thickness is the corrosion thickness or uncorroded thickness of the alloy.

[0021] Three-dimensional defects refer to the three-dimensional defects that are easily generated in alloys during their melting, die casting, and extrusion molding processes, such as porosity, shrinkage cavities, micro-porosity, and internal inclusions. These defects disrupt the continuity of the alloy matrix, forming preferential corrosion penetration channels, leading to accelerated corrosion due to the presence of defects within the alloy. The alloy matrix refers to the continuous phase that acts as the framework within the alloy.

[0022] The defect volume fraction of a three-dimensional defect refers to the ratio of the total volume of three-dimensional defects to the effective total volume of the alloy. A larger defect volume fraction results in a faster corrosion penetration rate and a greater penetration depth along the defect channels, leading to different characteristics in the sample thickness. For a given corrosion time, a higher defect volume fraction results in a greater corrosion thickness and a smaller uncorroded thickness. The defect quantification model in this application can characterize the mapping relationship between the defect volume fraction of the three-dimensional defects in the alloy and the sample thickness of the alloy. Therefore, in the defect quantification model, the corresponding defect volume fraction can be determined by determining the sample thickness.

[0023] The software used to build a volume defect quantification model is not limited; for example, a volume defect quantification model can be built in software such as Origin.

[0024] Step S102: Prepare the alloy test sample and determine the sampling thickness of the test sample.

[0025] The test sample refers to an individual alloy in which the volume fraction of three-dimensional volumetric defects needs to be determined. The volume fraction of defects in this individual is unknown before testing.

[0026] Step S103: Based on the sampling thickness of the sample to be tested, determine the corresponding defect volume fraction in the quantization model.

[0027] Determining the corresponding defect volume fraction in the quantification model means that, based on the mapping relationship between the defect volume fraction of the three-dimensional volume defects in the volume defect quantification model and the sampling thickness of the alloy, the sampling thickness of the sample to be tested is input, and the corresponding defect volume fraction of the sample to be tested is calculated.

[0028] The method for determining three-dimensional volumetric defects in alloys in this embodiment establishes a volumetric defect quantification model based on the correlation between the defect volume fraction of three-dimensional volumetric defects and the corrosion thickness and uncorroded thickness of the alloy. This model characterizes the mapping relationship between the defect volume fraction of three-dimensional volumetric defects in the alloy and the sampling thickness of the alloy, where the sampling thickness is either the corrosion thickness or the uncorroded thickness of the alloy. When testing the sample, the sampling thickness of the sample is directly converted into the corresponding defect volume fraction through the volumetric defect quantification model, achieving low-cost and efficient determination of the defect volume fraction. Furthermore, the volumetric defect quantification model can be reused after its establishment. In actual testing of the sample, only the sampling thickness needs to be measured, and the corresponding defect volume fraction can be directly obtained by substituting it into the volumetric defect quantification model. The operation is simple and efficient, enabling large-scale testing. Therefore, the three-dimensional volumetric defect determination method in this embodiment can not only determine the defect volume fraction of three-dimensional volumetric defects in alloys at low cost and high efficiency, but is also suitable as a pre-screening method for industrial CT and ultrasonic precision testing.

[0029] In some embodiments, the steps of establishing a volume defect quantification model include: preparing two control samples of the alloy, one of which is a volume defect-free control sample and the other is a volume defect control sample with a defined defect volume fraction; determining the sampling thickness of the volume defect-free control sample and the control sample, respectively; and establishing a volume defect quantification model based at least on the sampling thickness of the volume defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness.

[0030] The two control samples for preparing the alloy refer to alloy samples that are cut and machined to the specified size and shape according to the test requirements, ensuring that the specifications of each group of samples are consistent, and then the control samples are polished, cleaned and impurities removed.

[0031] A defect-free control sample refers to a sample with a pure matrix free of internal pores, looseness, and inclusions, verified by industrial CT. The defect volume fraction of the defect-free control sample can be approximated as 0. Defect-free control samples are used to calibrate intrinsic corrosion standards. In other words, the sampling thickness of the defect-free control sample originates solely from its inherent properties and can reflect the intrinsic corrosion of the control sample. Intrinsic corrosion refers to a uniform, overall corrosion phenomenon determined by inherent properties under ideal conditions without three-dimensional defects and stress.

[0032] A volumetric defect control specimen refers to an alloy specimen with three-dimensional volumetric defects whose defect volume fraction has been precisely determined by industrial CT. The total corrosion of a volumetric defect control specimen is the result of the coupled superposition of its intrinsic corrosion and defect-accelerated corrosion. In the absence of a volumetric defect control specimen to provide an intrinsic corrosion benchmark, the sample thickness of the volumetric defect control specimen can be compared with the intrinsic corrosion benchmark to strip away the intrinsic corrosion and obtain the defect-accelerated corrosion.

[0033] Therefore, by setting up two types of control samples—a defect-free control sample and a defect-free control sample—and calibrating the intrinsic corrosion benchmark by measuring the sampling thickness of the defect-free control sample, the final established bulk defect quantification model can be freed from the interference of intrinsic corrosion of the alloy, thereby improving the accuracy of the bulk defect quantification model.

[0034] Preferably, the number of control samples without solid defects can be multiple, and the sampling thickness of the control samples without solid defects is the average of the sampling thicknesses of multiple control samples without solid defects. That is, the sampling thickness of each control sample without solid defects is measured separately, and the average of the multiple sampling thicknesses is calculated. The final average value is used as the intrinsic corrosion benchmark. This can effectively suppress the random deviation caused by individual differences and make the intrinsic corrosion benchmark closer to the true intrinsic corrosion properties of the control samples without solid defects.

[0035] Preferably, the number of volume defect control samples can be multiple, and each volume defect control sample has a different defect volume fraction. This allows for the establishment of a precise and continuous mapping relationship between the defect volume fraction and the sampling thickness over a wide range of defect volume fractions, from low to high. This not only verifies the effectiveness and form of the mapping relationship within the overall range, but also significantly improves the measurement accuracy, robustness, and universality of the volume defect quantification model for test samples with different defect volume fractions.

[0036] It should be noted that the grade and molding method of the control sample without volume defects and the control sample with volume defects should be consistent, so as to lock the difference in the thickness of the control sample without volume defects and the control sample with volume defects to the presence and size of the three-dimensional volume defects, thereby minimizing the cross-interference of other factors and ensuring the accuracy and applicability of the volume defect quantification model.

[0037] For example, the step of establishing a volume defect quantification model based at least on the sampling thickness of the volume defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness includes: performing an intrinsic correction on the sampling thickness of the volume defect control sample based on the sampling thickness of the volume defect-free control sample to obtain a correction value; and establishing a volume defect quantification model based on the defect volume fraction of the volume defect control sample and the correction value.

[0038] Intrinsic correction refers to the process of removing the intrinsic corrosion portion of a bulk defect control sample from its sampled thickness using an intrinsic corrosion benchmark established from a non-bulk defect control sample. This process yields the portion of accelerated corrosion caused by defects (i.e., the correction value). In other words, the correction value accurately reflects the corrosion thickness or uncorroded thickness corresponding to accelerated corrosion caused by defects. Therefore, the bulk defect quantification model established based on the defect volume fraction and correction value of the bulk defect control sample eliminates the interference of intrinsic corrosion, ensuring that the defect volume fraction derived from the model is unaffected by intrinsic corrosion, thus significantly improving the accuracy of the bulk defect quantification model.

[0039] For example, the step of establishing a volume defect quantification model based on the defect volume fraction and correction value of the volume defect control sample includes: performing linear fitting on the defect volume fraction and correction value of the volume defect control sample; determining the mapping relationship of the volume defect quantification model: Y=k·X+c, where Y represents the defect volume fraction, X represents the correction value, k and c are constants, and k is not equal to 0.

[0040] Linear fitting is a data fitting method that uses a straight line as the fitting model and solves for the optimal straight line equation based on the least squares principle. This straight line approximates the trend between the defect volume fraction and the correction value. In other words, the mapping relationship Y=k·X+c is a linear function expression, which corresponds to a straight line in a Cartesian coordinate system, where k represents the slope of the line and c represents the ordinate of the line.

[0041] After determining the sampling thickness of the sample to be tested, an intrinsic correction is performed on the sampling thickness to obtain the correction value of the sample. By substituting the correction value of the sample into the mapping relationship Y=k·X+c, the corresponding defect volume fraction can be obtained. According to the mapping relationship, it can be seen that the intrinsically corrected sampling thickness is linearly related to the defect volume fraction. At the same time, the calculation process is simple and fast, and has high accuracy, ensuring the reproducibility of the method and the feasibility of industrial standardization applications.

[0042] In some embodiments, please refer to Figure 2Before determining the sampling thickness of the control sample without volume defects and the control sample with volume defects, the method further includes: encapsulating the outer periphery of the two control samples respectively, with only one side of each control sample exposed to form a test surface; performing the same corrosion treatment on the two control samples; and measuring the sampling thickness of each control sample based on the test surface of each control sample.

[0043] The purpose of encapsulating the outer periphery of the two control samples 10 is to cover the non-test surfaces of the samples with insulating epoxy resin and other materials, leaving only designated areas in contact with the corrosive solution. This precisely controls the corrosion area, avoids unnecessary areas participating in the corrosion reaction, and ensures accurate calculation of the sampling thickness. Since only one side of the two control samples 10 is retained as the test surface 10a, the effective corrosion thickness can be determined intuitively and accurately, avoiding measurement errors in sampling thickness caused by multi-faceted corrosion, and ensuring the authenticity and accuracy of the sampling thickness data.

[0044] The purpose of performing corrosion treatment on the two control samples 10 is to simulate the actual service conditions of the alloy and to determine the corrosion rate of the two control samples 10 under the same corrosion environment and corrosion time. Since the higher the defect volume fraction, the greater the corrosion rate of the alloy, under the premise of a certain corrosion time, the corrosion thickness of the control sample without bulk defects is smaller than that of the control sample with bulk defects (the opposite is true for the uncorroded thickness).

[0045] The method of performing corrosion treatment on the two control samples 10 is not limited. For example, the steps of performing the same corrosion treatment on the two control samples include: immersing the two control samples in the same corrosive solution and maintaining the same immersion time in the corrosive solution.

[0046] This eliminates external interference caused by differences in corrosion treatment, allowing the sampling thickness of the bulk defect control sample to more accurately reflect the intrinsic corrosion of the bulk defect control sample, thus ensuring the accuracy of the bulk defect quantification model.

[0047] It should be noted that the immersion time can be determined based on the preliminary experiment of the control sample without microstructure defects. In other words, the control sample without microstructure defects can undergo a corrosion test in advance to ensure that after immersion, the control sample without microstructure defects only undergoes intrinsic matrix corrosion and no through corrosion penetration, so as to avoid through corrosion penetration of the control sample without microstructure defects due to excessive immersion time in subsequent corrosion treatment.

[0048] For example, please refer to Figure 2The steps of determining the sampling thickness of various control samples by using the test surfaces of various control samples as references include: using the test surfaces of the control samples as references, performing multiple grinding and polishing processes on the control samples, and after each grinding and polishing process, observing the microscopic morphology of the polished surface of the control samples to determine whether there are corrosion traces corresponding to the corrosion treatment; if corrosion traces are present, the next grinding and polishing process is continued; if no corrosion traces are present, the grinding and polishing process is stopped; based on the polished surface obtained after the last grinding and polishing process, the uncorroded thickness of the control samples is determined.

[0049] Corrosion marks refer to the absence of continuous corrosion channels, intergranular penetration marks, and defect-induced corrosion pits. It should be noted that for control specimens with three-dimensional volumetric defects, corrosion marks refer to the corrosion marks formed by the above-mentioned corrosion treatment, rather than the corrosion marks that were present in the specimen itself.

[0050] Polishing refers to directional grinding and radial polishing layer by layer along the normal direction of the test surface 10a. After each layer of grinding is completed, the corrosion morphology on the polished surface 10b is observed using a metallographic microscope. If no corrosion traces are observed on the polished surface 10b after one polishing treatment, the polished surface 10b can be defined as the corrosion penetration termination boundary. Preferably, the grinding depth of each polishing treatment does not exceed 50 μm to avoid the accuracy of the sampling thickness being affected by excessive grinding thickness.

[0051] By following the steps above, the uncorroded thickness X1 of each sample after corrosion treatment can be accurately measured, thereby improving the accuracy of the volume defect quantification model.

[0052] Specifically, please refer to Figure 2 The back surface 10c of the control sample 10 opposite to the test surface 10a has a first geometric center 10d, and the polished surface 10b obtained after the last grinding and polishing treatment of the control sample 10 has a second geometric center 10e. The length of the line connecting the first geometric center 10d and the second geometric center 10e is the uncorroded thickness X1.

[0053] It is understandable that the corrosion state in the central region of the sample is relatively uniform, with almost no accelerated corrosion. The test results can truly reflect the corrosion thickness of the sample. Therefore, by measuring the length of the line connecting the first geometric center 10d and the second geometric center 10e, the interference of edge effects can be eliminated. At the same time, by standardizing the test points of each sample, the corrosion thickness data can be ensured to be accurate and comparable.

[0054] Preferably, the first geometric center 10d and the second geometric center 10e can be marked by laser dot marking, and the first geometric center 10d and the second geometric center 10e can be calibrated by digital micrometer calibration, so as to control the error between the position of the laser dot marking and the actual geometric center to be less than or equal to 0.02mm.

[0055] The above corrosion treatment and uncorroded thickness measurement methods for the test sample are used to establish a volumetric defect quantification model. In the process of determining the sampling thickness of the test sample, the method includes: performing the same corrosion treatment on the test sample as on the control sample, and using the same measurement method as the control sample to measure the sampling thickness of the test sample.

[0056] This ensures that the sampling thickness of the test sample is strictly consistent with the data (sampling thickness of the control sample) on which the volume defect quantification model is based in terms of physical meaning and numerical scale, thereby guaranteeing the accuracy of the measurement results. At the same time, the same corrosion treatment can eliminate external interference introduced by treatment differences, and the fixed measurement method can eliminate systematic bias introduced by different measurement standards, so that the variation of the measured sampling thickness uniquely reflects the defect volume fraction of the test sample, ensuring the reproducibility of the method and the feasibility of industrial standardization applications.

[0057] The following specific embodiment illustrates a method for determining three-dimensional volume defects according to this application. The method includes the following steps: Step S201: Sample grouping preparation and pretreatment.

[0058] The sample consists of two sets of control samples and one set of test samples.

[0059] The two sets of control samples were a defect-free control sample and a defect-free control sample. The defect-free control sample consisted of three alloy samples, which were verified by industrial CT to be free of internal porosity, looseness, and inclusion defects. The defect-free control sample consisted of three alloy samples, and the defect volume fractions were accurately determined by industrial CT to be Y1=0.52%, Y2=1.58%, and Y3=3.31%, respectively. The test samples included two alloy samples with unknown defects.

[0060] Among them, the control samples without volume defects, the control samples with volume defects, and the test samples were all made of die-cast CAMH1 rare earth magnesium alloy, and all samples had uniform external dimensions. For example, each sample was uniformly hexahedral, with external dimensions of 10 mm in length, 10 mm in width, and 10 mm in thickness. All samples were first cleaned of edge machining burrs and surface machining damage using water-resistant metallographic sandpaper with a grit range of 400 to 1500 mesh, progressively grinding the workpiece surface under continuous water cooling and lubrication conditions, from coarse to fine, to gradually remove oxide scale, rust layer, heat-affected layer, and macroscopic scratches, obtaining a smooth, low-damage clean metal surface. Then, all samples were ultrasonically cleaned with anhydrous ethanol for 5 to 10 minutes. After cleaning, the sample surface was purged with high-purity nitrogen at room temperature to thoroughly remove residual ethanol and impurities. Subsequently, they were sealed and stored to eliminate the systematic interference of surface morphology differences between samples on the corrosion treatment results.

[0061] Step S202: Full encapsulation of the sample and calibration of the test surface.

[0062] Each sample was encapsulated with insulating epoxy resin with a temperature resistance of ≥80℃. Specifically, the five outer surfaces of the sample were fully encapsulated, leaving only the 10mm core intact. One side is exposed (10mm) to form the test surface. It should be noted that the area of ​​the test surface, the wetting angle of the corrosive medium, and the liquid phase contact environment of all samples should be consistent to minimize the influence of other variables on the corrosion treatment results. The wetting angle (also called the contact angle θ) refers to the equilibrium angle between the tangent of the liquid-gas interface and the tangent of the solid-liquid interface at the solid-liquid-gas three-phase interface, which is used to quantitatively characterize the wetting and spreading ability of the corrosive medium on the solid surface. The liquid phase contact environment refers to the service environment in which the material surface is in continuous / intermittent contact with the liquid corrosive medium (aqueous solution, acid-base-salt solution, electrolyte, condensate, etc.), as opposed to the gas phase (dry air), alternating wet and dry conditions, or full / partial immersion.

[0063] Subsequently, high-precision fixed-point markings were made by laser dotting at the geometric center of the test surface of each sample. The position of the test surface and the center mark point was calibrated using a digital micrometer, with a position control error ≤0.02mm, eliminating the position offset error during subsequent grinding and measurement.

[0064] Step S203: Constant temperature neutral salt bath immersion corrosion and intrinsic corrosion benchmark calibration of the matrix.

[0065] A corrosion solution was prepared, which was a neutral deionized aqueous solution of 3.5% NaCl by mass. All samples were completely immersed in the corrosion solution for corrosion treatment. Specifically, the temperature of the corrosion solution was maintained at 25±1℃ to ensure that all samples were immersed in a sealed environment at a constant temperature for 48 hours.

[0066] After the corrosion treatment is completed, all samples are taken out and cleaned. Then, they are immersed in a 5wt% chromic acid corrosion inhibitor solution at room temperature to remove surface corrosion products (without corroding the magnesium alloy substrate), and dried with hot air at a constant temperature for later use.

[0067] The uncorroded thickness of three control samples without bulk defects was measured, and the average uncorroded thickness of the three control samples without bulk defects was X0 = 4.32 mm. Therefore, the intrinsic corrosion thickness d = D - X0 = 5.00 - 4.32 = 0.68 mm.

[0068] Step S204: Determine the thickness of the sampled specimen for the defect control and calculate the intrinsic correction.

[0069] All defect-prone control specimens were systematically polished layer by layer. The corrosion termination boundary was located by metallographic microscopy, and the uncorroded thickness was measured. The uncorroded thicknesses of the three defect-prone control specimens were X. 11 =3.86mm, X 12 =2.41mm, X 13 =1.07mm. The intrinsic correction calculation formula X2=X1+d was used to calculate the intrinsic correction value for the three uncorroded thicknesses, yielding the following correction values: X 21 =4.54mm, X 22 =3.09mm, X 23 =1.75mm.

[0070] Step S205: Optimize the model by linear fitting using the least squares method.

[0071] Given data set: X 21 =4.54mm, Y1=0.52%; X 22 =3.09, Y2=1.58%; X 23 =1.75, Y3=3.31%. The mapping relationship of the optimized body defect quantification model is obtained through exact linear regression fitting: Y=-0.7299X+3.8332. Wherein, the model determination coefficient R0 is 1.75, Y1=3.31%. 2 =0.9992 > 0.995, which meets the high-precision modeling index.

[0072] Step S206: Test the sample to be tested, perform quantitative calculations, and calibrate with the true CT value.

[0073] The uncorroded thicknesses of the two test samples with unknown defects are: X 1a =3.25mm, X1b =1.88mm. The intrinsic correction calculation formula X2=X1+d was used to calculate the intrinsic correction value for the two uncorroded thicknesses, yielding the following correction value: X 2a =3.93mm, X 2b =2.56mm. Substituting the two correction values ​​into the mapping relationship Y=-0.7299X+3.8332, the corresponding values ​​are approximately 0.96 and 1.97, which means the corresponding defect volume fractions are 0.96% and 1.97%, respectively.

[0074] Industrial CT verification showed that the actual defect volume fractions were 0.97% and 1.99% respectively, with a relative deviation of ≤2%, and the accuracy met the quality control requirements.

[0075] Step S207: Correction of multi-process iterative model.

[0076] In the above steps, the volume defect quantification model is established based on the die-cast CAMH1 rare earth magnesium alloy. Directly applying the volume defect quantification model to the test sample of extruded CAMH1 magnesium alloy may result in a relative deviation greater than 5%. In this case, a control sample of die-cast CAMH1 rare earth magnesium alloy without volume defects and a control sample with volume defects can be used. The sampling thickness is measured using the same corrosion treatment and the same measurement method as described above, and the relevant data are iteratively fitted and updated to match the k and c parameters corresponding to the extruded CAMH1 magnesium alloy. In a specific embodiment, the relative deviation of the test sample of the extruded CAMH1 magnesium alloy after the update is 2.82%, less than 3%, and the accuracy meets the quality control requirements.

[0077] For rare earth magnesium alloys with grades AZ91D, ZK60, and WE43, it is only necessary to prepare corresponding dual control groups for this grade to calibrate the intrinsic corrosion thickness and iteratively update the corresponding volume defect quantification model.

[0078] Therefore, it can be seen that the method for determining the three-dimensional defects of alloys in the embodiments of this application can be adapted to alloys of different grades and different forming methods.

[0079] In the description of this application, the references to terms such as "in one embodiment," "in some embodiments," "in other embodiments," "in yet another embodiment," or "exemplary," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine the different embodiments or examples described in this application, as well as the features of the different embodiments or examples.

[0080] The above description is merely a preferred embodiment of this application and is not intended to limit the application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A method for determining three-dimensional defects in an alloy, characterized in that, The method includes: A volume defect quantification model is established, which characterizes the mapping relationship between the defect volume fraction of the three-dimensional volume defects of the alloy and the sampling thickness of the alloy, wherein the sampling thickness is the corrosion thickness or the uncorroded thickness of the alloy. Prepare a test sample of the alloy and determine the sampling thickness of the test sample; Based on the sampling thickness of the test sample, the corresponding defect volume fraction in the volume defect quantification model is determined.

2. The method for determining three-dimensional solid defects according to claim 1, characterized in that, The steps for establishing the volumetric defect quantification model include: Two control samples of the alloy were prepared, one of which was a control sample without bulk defects, and the other was a control sample with bulk defects having a defined volume fraction of defects. The sampling thickness of the defect-free control sample and the control sample were determined respectively. The volume defect quantification model is established based at least on the sampling thickness of the volume defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness.

3. The method for determining three-dimensional volume defects according to claim 2, characterized in that, The step of establishing the volume defect quantification model based at least on the sampling thickness of the defect-free control sample, the defect volume fraction of the volume defect control sample, and the sampling thickness includes: The intrinsic correction value is obtained by performing an intrinsic correction on the sampling thickness of the control sample without volume defects based on the sampling thickness of the control sample without volume defects. The volume defect quantification model is established based on the defect volume fraction of the volume defect control sample and the correction value.

4. The method for determining three-dimensional volume defects according to claim 3, characterized in that, The step of establishing the volume defect quantification model based on the defect volume fraction of the volume defect control sample and the correction value includes: Linear fitting was performed on the defect volume fraction of the volume defect control sample and the correction value; The mapping relationship of the volume defect quantification model is determined as: Y = k·X + c, where Y represents the defect volume fraction, X represents the correction value, k and c are constants, and k is not equal to 0.

5. The method for determining three-dimensional volume defects according to any one of claims 2-4, characterized in that, The number of volume defect control samples is multiple, and the defect volume fraction of each volume defect control sample is different.

6. The method for determining three-dimensional volume defects according to any one of claims 2-4, characterized in that, Before determining the sampling thickness of the control specimen without volume defects and the control specimen with volume defects, the method further includes: The outer periphery of each of the two control samples is encapsulated, with only one side of each control sample exposed to form a test surface; The same corrosion treatment was applied to both control samples. The sampling thickness of each of the various control samples was measured using the test surface of each control sample as a reference.

7. The method for determining three-dimensional volume defects according to claim 6, characterized in that, The step of determining the sampling thickness of each of the various control samples, using the test surface of each control sample as a reference, includes: Using the test surface of the control sample as a reference, the control sample is subjected to multiple grinding and polishing processes. After each grinding and polishing process, the polished surface of the control sample is observed under a microscope to determine whether there are corrosion traces corresponding to the corrosion treatment. If the corrosion marks are present, continue with the next polishing process; if the corrosion marks are not present, stop the polishing process. The uncorroded thickness of the control sample is determined based on the polished surface obtained after the final polishing process.

8. The method for determining three-dimensional solid defects according to claim 7, characterized in that, The polishing depth of each polishing process shall not exceed 50 μm; And / or, the back side of the control sample opposite to the test surface has a first geometric center, and the polished surface obtained after the last grinding and polishing treatment of the control sample has a second geometric center, and the length of the line connecting the first geometric center and the second geometric center is the uncorroded thickness.

9. The method for determining three-dimensional solid defects according to claim 6, characterized in that, The step of performing the same corrosion treatment on the two control samples includes: The two control samples were immersed in the same corrosive solution for the same duration.

10. The method for determining three-dimensional volume defects according to claim 6, characterized in that, The method further includes: The test sample is subjected to the same corrosion treatment as the control sample, and the sampling thickness of the test sample is determined using the same measurement method as the control sample.

11. The method for determining three-dimensional volume defects according to any one of claims 2-4, characterized in that, The test sample has the same external dimensions as the various control samples.

12. The method for determining three-dimensional volume defects according to any one of claims 2-4, characterized in that, The number of the volumeless defect control samples is multiple, and the sampling thickness of the volumeless defect control samples is the average of the sampling thicknesses of the multiple volumeless defect control samples.

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