A method for rapid non-destructive evaluation of material strength and plasticity based on EBSD data

Abstract

The application relates to the technical field of material performance evaluation, and provides a material strength and plasticity rapid nondestructive evaluation method based on EBSD data, which comprises the following steps: adopting an EBSD technology to characterize a material surface state, obtaining a backscattering diffraction pattern and obtaining original EBSD data and a grain orientation map of the material; based on the reconstructed grain orientation map, microstructure characteristic parameters of each grain in a target region of the sample are extracted respectively; based on the extracted microstructure characteristic parameters, a plasticity sensitivity coefficient of each grain is calculated; based on the slip distribution characteristics of the grains under the plasticity sensitivity coefficient, the target region of the sample is divided into a plasticity deformation dominant area and a strength dominant area, and partition visualization is realized through space mapping and different color filling; and based on the respective microstructure characteristic parameters of the areas, microstructure-mechanical property evaluation models are respectively established, so that the material strength and plasticity are rapidly evaluated.

Description

Technical Field

[0001] This invention relates to the field of material performance evaluation in advanced equipment manufacturing, specifically to a rapid non-destructive evaluation method for material strength and plasticity based on EBSD data, applicable to rapid non-destructive evaluation of the strength and plasticity of polycrystalline metal materials. Background Technology

[0002] With the increasing demands for structural safety and reliability under extreme service conditions in fields such as aerospace, energy equipment, and high-end shipbuilding, the mechanical response of advanced metallic materials under complex conditions such as high strain rates and cyclic loading has become a core factor determining the service life of components. How to achieve rapid and accurate evaluation of material mechanical properties is gradually becoming a key bottleneck restricting structural integrity and life assessment.

[0003] However, traditional mechanical property evaluation methods typically rely on the preparation and testing of standard specimens, which not only suffers from long testing cycles and high costs, but also struggles to meet the demands for efficient material screening and local performance analysis. This is especially true for structures with highly inhomogeneous microstructures, such as welded joints and additively manufactured components, where localized weak areas are often the source of damage and failure. Traditional mechanical testing methods struggle to quantitatively assess the mechanical properties of these areas, posing a significant threat to the service safety of highly reliable components. On the other hand, the macroscopic mechanical behavior of materials is essentially dominated by their internal microstructure characteristics, but current evaluation methods lack effective means to establish a direct correlation between microstructure and macroscopic mechanical properties.

[0004] In recent years, the development of electron backscatter diffraction (EBSD) technology has made it possible to quantitatively characterize the microstructure of materials and qualitatively and statistically analyze mechanical responses such as local dislocation slip, providing an important technical means to reveal the plastic deformation mechanism and microstructure evolution of materials. However, current EBSD data analysis is still mainly based on qualitative description and semi-quantitative interpretation, and there is a lack of effective methods to directly infer the macroscopic mechanical properties of materials based on EBSD characteristic data. In particular, for materials or components with significantly inhomogeneous microstructures, how to effectively transform the microstructure information such as grain size, grain boundary characteristics, and local orientation differences obtained by EBSD into known parameters that can be used for performance prediction, thereby achieving non-destructive prediction of material strength and plasticity without the need for sample preparation and other methods, remains a gap in the industry. Summary of the Invention

[0005] The macroscopic properties of materials are a comprehensive reflection of the coupled effects of various characteristic parameters in their microstructure. Specifically, grain size, grain boundary characteristics, and grain boundary orientation differences jointly influence the plastic deformation mechanism, crack propagation behavior, and strain field distribution characteristics of materials. Because these characteristic parameters are interdependent, a single parameter cannot fully describe the contribution of the microstructure to the macroscopic mechanical properties of materials. Therefore, it is necessary to apply the multi-dimensional microstructure information acquired by EBSD to cross-scale strength and plasticity assessment. Achieving non-destructive, accurate, and rapid evaluation of material strength and plasticity based on initial material data acquired by EBSD will effectively address the urgent needs for performance evaluation and life assessment in the current manufacturing and service of high-end equipment.

[0006] Based on the above, the present invention provides a rapid non-destructive evaluation method for material strength and plasticity based on EBSD data, the evaluation method comprising: S1. The microstructure of the material surface was characterized by EBSD technology. Backscatter diffraction patterns were obtained by scanning the electron beam point by point and the original EBSD data were obtained. The grain orientation map (IPF) of the material was obtained by data screening and grain reconstruction. S2, Based on the reconstructed grain orientation map, extract the microstructural feature parameters of each grain in the target area of ​​the sample; S3, Calculate the plasticity sensitivity coefficient of each grain based on the extracted microstructural characteristic parameters. ; S4, based on the plasticity sensitivity coefficient The slip distribution characteristics of the lower grains divide the target area of ​​the sample into a plastic deformation-dominated area and a strength-dominated area, and the partitioning is visualized by spatial mapping and different color fillings. S5 establishes microstructure-mechanical property evaluation models based on the microstructure characteristic parameters of each region, enabling rapid and non-destructive evaluation of material strength and plasticity.

[0007] Furthermore, the microstructural characteristic parameters in step S2 include: Grain size This represents the grain size of a single grain, in units of 1. ; Average grain size , representing the average value of the equivalent circle diameter of the grains within the target region, in units of ; Number of adjacent grains , indicating the number of grains in contact with the grains; Average number of adjacent grains , which represents the average number of adjacent grains of all grains within the target region.

[0008] Furthermore, in step S3, the plasticity sensitivity coefficient The formula used to characterize the relative sensitivity of grains to plastic deformation under applied load is as follows:

[0009] In the formula, This is the material correction factor.

[0010] Furthermore, the specific evaluation method in step S4 is as follows: The slip or non-slip state of grains is determined by crystallographic characterization. Boundary grains and minimal grains are removed, and the values ​​of slip grains and non-slip grains are statistically analyzed separately. Values, and compare slip grains with unslip grains. The median of the values ​​is denoted as . and To characterize the distribution differences of the two types of grains on plasticity sensitivity parameters; Based on this, using the median and As the grouping boundary, all grains are divided into , and The slip ratio distribution characteristics of grains in the three intervals were statistically analyzed, and slip ratio distribution diagrams were plotted. Through the The grain slip behavior within the interval was further analyzed in detail. The values ​​are incremented in increments of 0.01, and the corresponding slip ratios are calculated to determine the value at which the slip ratio first reaches 40%. The value is defined as the critical value of the plasticity sensitivity coefficient. .

[0011] Based on critical value The region containing the grains is divided as follows: when At this time, the region is defined as the plastic-dominant region, where the grains are located and plastic deformation is dominant; when When this occurs, the region is defined as the strength-dominant region, where no significant plastic deformation occurs and the region is characterized by strength dominance.

[0012] Furthermore, within the intensity-dominant region, when the number of adjacent grains of a grain... Higher than the average number of adjacent grains This indicates that it is strongly constrained by its neighborhood. and The region is considered a potentially vulnerable area.

[0013] Furthermore, the specific steps of step S5 are as follows: Microstructural characteristic parameters of the plastic deformation-dominant and strength-dominant regions are extracted to construct characteristic parameter sets for each region. Based on these characteristic parameter sets, a mapping relationship between regional microstructure and mechanical properties is established, and a microstructure-mechanical property evaluation model is formed accordingly. This model is then used to perform rapid, non-destructive evaluation of material strength and plasticity. This invention has the following beneficial effects: (1) This invention obtains grain orientation maps by collecting raw EBSD data, extracts microstructural feature parameters of each grain based on the reconstructed grain orientation maps, and calculates the plasticity sensitivity coefficient of each grain based on the extracted microstructural feature parameters. Based on plasticity sensitivity coefficient The slip distribution characteristics of the lower grains divide the target area of ​​the sample into a plastic deformation-dominant region and a strength-dominant region. By analyzing the microstructure characteristics and establishing a structure-performance evaluation model, strength and plasticity can be directly evaluated from the microstructure information, thereby achieving non-destructive and rapid material performance evaluation. This significantly improves the efficiency of material research and development, production and quality control, shortens the development cycle, and enables rapid evaluation of material strength and plasticity without mechanical testing, thus possessing truly non-destructive evaluation capabilities.

[0014] (2) The method of the present invention is standardized and simple to operate. It can quickly process EBSD data and output performance prediction results. It is particularly suitable for online rapid screening of material properties and local area performance determination in the process of new material development.

[0015] (3) This invention establishes a complete standardized analysis process to ensure that the mechanical properties of materials prepared under different batches and different process conditions are repeatable and consistent. It can be conveniently promoted and applied in industrial production, quality control and scientific research, and realize high-throughput and high-efficiency rapid screening of material properties or process optimization. Attached Figure Description

[0016] Figure 1 This is a flowchart of the non-destructive evaluation process of the present invention.

[0017] Figure 2 This is the grain orientation pattern obtained in Example 1.

[0018] Figure 3 It is the plasticity sensitivity coefficient of all grains in Example 1. Distribution of calculation results.

[0019] Figure 4 This is a distribution diagram of grain slip probability in each region of Example 1.

[0020] Figure 5 It is based on the grain plasticity sensitivity coefficient in Example 1. A schematic diagram showing the regional distribution of material properties. Detailed Implementation

[0021] The technical solution of the present invention will be further described in detail below with reference to specific embodiments. However, these embodiments are not intended to limit the present invention. Any similar structures and similar variations of the present invention should be included in the protection scope of the present invention. The commas in the present invention all indicate the relationship between and. The English letters in the present invention are case-sensitive.

[0022] like Figure 1 As shown, this invention provides a rapid non-destructive evaluation method for material strength and plasticity based on EBSD data, the evaluation method comprising: S1. The surface state of the material is characterized by EBSD technology. Backscatter diffraction patterns are obtained by scanning the electron beam point by point to obtain the original EBSD data. The grain orientation map (IPF) of the material is obtained by data screening and grain reconstruction. S2, based on the reconstructed grain orientation map, extract the microstructural feature parameters of each grain within the target region of the sample (including at least 100-200 grains); wherein, the microstructural feature parameters include: Grain size This represents the grain size of a single grain, in units of 1. ; Average grain size , representing the average value of the equivalent circle diameter of the grains within the target region, in units of ; Number of adjacent grains , indicating the number of grains in contact with the grains; Average number of adjacent grains , which represents the average number of adjacent grains of all grains within the target region.

[0023] S3, Calculate the plasticity sensitivity coefficient of each grain based on the extracted microstructural characteristic parameters. ; Plasticity sensitivity coefficient The formula used to characterize the relative sensitivity of grains to plastic deformation under applied load is as follows:

[0024] In the formula, η This is a material correction factor. η The stress values ​​were obtained through experimental determination. The steps were as follows: In-situ EBSD tensile tests were conducted on the reference and target materials under the same test conditions. The stress values ​​corresponding to the first appearance of slip traces in the reference and target materials were recorded, and denoted as follows: and The material correction factor is calculated using the following formula:

[0025] S4, based on the plasticity sensitivity coefficient The slip distribution characteristics of the lower grains divide the target region of the sample into a plastic deformation-dominated region and a strength-dominated region. This regional visualization is achieved through spatial mapping and different color fillings. The specific evaluation method is as follows: The slip or non-slip state of grains is determined by crystallographic characterization. Boundary grains and minimal grains are removed, and the values ​​of slip grains and non-slip grains are statistically analyzed separately. Values, and compare slip grains with unslip grains. The median of the values ​​is denoted as . and To characterize the distribution differences of the two types of grains on plasticity sensitivity parameters; Based on this, using the median and As the grouping boundary, all grains are divided into , and The slip ratio distribution characteristics of grains in the three intervals were statistically analyzed, and slip ratio distribution diagrams were plotted. Through the The grain slip behavior within the interval was further analyzed in detail. The values ​​are incremented in increments of 0.01, and the corresponding slip ratios are calculated to determine the value at which the slip ratio first reaches 40%. The value is defined as the critical value of the plasticity sensitivity coefficient. .

[0026] Based on critical value The region containing the grains is divided as follows: when hour, The region is defined as the plastic-dominant region, where the grains are located and plastic deformation is dominant. when hour, The region is defined as the strength-dominant region, where no significant plastic deformation occurs and strength is the dominant factor. Within the strength-dominant region, when the number of adjacent grains of a grain... Higher than the average number of adjacent grains This indicates that it is strongly constrained by its neighborhood. and The region is considered a potentially vulnerable area.

[0027] S5. Based on the microstructure characteristic parameters of each region, establish a microstructure-mechanical property evaluation model to achieve non-destructive evaluation of material strength and plasticity. The specific steps are as follows: Microstructural characteristic parameters of the plastic deformation-dominant and strength-dominant regions are selected to construct characteristic parameter sets for each region; based on the characteristic parameter sets, a mapping relationship between regional microstructure and mechanical properties is established, and a microstructure-mechanical property evaluation model is formed accordingly; the microstructure-mechanical property evaluation model is used to perform non-destructive evaluation of material strength and plasticity.

[0028] Example 1 This embodiment uses 12Cr1MoVR steel as an example to illustrate how the mechanical properties of materials can be quickly evaluated using the method described in this application. The specific steps include: S1. The surface state of the material is characterized by EBSD technology. Backscatter diffraction patterns are obtained by scanning the electron beam point by point to obtain the original EBSD data. The grain orientation map (IPF) of the material is obtained by data screening and grain reconstruction. S2, based on the reconstructed grain orientation map, extracts the microstructural characteristic parameters of each grain within the target region of the sample, such as... Figure 2 As shown, for grain number 1, its grain size is... for Average grain size for Number of adjacent grains for Average number of adjacent grains for ; S3, Define and calculate the plasticity sensitivity coefficient of each grain based on the extracted microstructural feature parameters. ; Plasticity sensitivity coefficient The formula used to characterize the relative sensitivity of grains to plastic deformation under applied load is as follows:

[0029] In this embodiment, 12Cr1MoVR material is used as the target material, and its material correction factor is... η Setting 1 as the baseline state, the characteristic parameters of grain 1 are substituted into formula (1) to obtain the corresponding state of grain 1. value:

[0030] Plasticity sensitivity coefficient of all grains The calculation results are as follows Figure 3 As shown.

[0031] S4, based on the plasticity sensitivity coefficient The slip distribution characteristics of the lower grains divide the target area of ​​the sample into a plastic deformation-dominated area and a strength-dominated area, and the partitioning is visualized by spatial mapping and different color fillings. Crystallographic characterization is used to determine the slip or non-slip state of grains, and the slip or non-slip state of all grains is calculated. Values ​​were calculated by removing boundary grains and extremely small grains (less than 10 pixels in this embodiment), and then statistically analyzing the values ​​of slipped grains and non-slipped grains. Values ​​were calculated, and the medians of the two types of grains were recorded as slip grains. The median of the values ​​is Unslipped grains The median of the values ​​is To characterize the distribution differences of the two types of grains on plasticity sensitivity parameters; Based on this, using the median and As grouping boundaries, all grains are divided into , and The slip ratio distribution characteristics of grains in three intervals were statistically analyzed, and slip ratio distribution diagrams were plotted, as shown below. Figure 4 As shown. In this embodiment, by... Further detailed analysis of grain slip behavior within the interval. The values ​​are incremented in increments of 0.01, and the corresponding slip ratios are calculated to determine the value at which the slip ratio first reaches 40%. The value is 0.59, and it is defined as the critical value of the plasticity sensitivity coefficient. .

[0032] when At this time, the grains are more prone to plastic deformation, The region is considered the dominant area of ​​plastic deformation; when At that time, no significant plastic deformation occurred in the region where the grains were located. The regions are defined as strength-dominant zones. The plastic deformation-dominant zone is filled with green, and the strength-dominant zone is filled with pink, as shown below. Figure 5 As shown.

[0033] S5. Based on the microstructure characteristic parameters of each region, establish a microstructure-mechanical property evaluation model to achieve rapid and non-destructive evaluation of material strength and plasticity. The specific steps are as follows: Microstructural characteristic parameters of the plastic deformation-dominant and strength-dominant regions are extracted to construct characteristic parameter sets for each region. Based on these characteristic parameter sets, a regional microstructure-mechanical property mapping relationship is established, and a microstructure-mechanical property evaluation model is formed accordingly. This model is then used to perform rapid, non-destructive evaluation of the material's strength and plasticity. Figure 5The large proportion of the green area clearly indicates that the material has good overall plasticity.

[0034] This invention, by collecting raw EBSD data, analyzing microstructure characteristics, and establishing a structure-performance evaluation model, can directly evaluate strength and plasticity based on microstructure information, thereby achieving non-destructive and rapid material performance evaluation. This significantly improves the efficiency of material research and development, production, and quality control, shortens the development cycle, and enables rapid evaluation of material strength and plasticity without mechanical testing, possessing truly non-destructive evaluation capabilities.

[0035] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

Claims

1. A rapid non-destructive evaluation method for material strength and plasticity based on EBSD data, characterized in that, The evaluation method includes: S1. The microstructure of the material surface is characterized by EBSD technology. Backscatter diffraction patterns are obtained by scanning the electron beam point by point and the original EBSD data is obtained. The grain orientation map of the material is obtained by data screening and grain reconstruction. S2, Based on the reconstructed grain orientation map, extract the microstructural feature parameters of each grain in the target area of ​​the sample; S3, Calculate the plasticity sensitivity coefficient of each grain based on the extracted microstructural characteristic parameters. ; S4, based on the plasticity sensitivity coefficient The slip distribution characteristics of the lower grains divide the target area of ​​the sample into a plastic deformation-dominated area and a strength-dominated area, and the partitioning is visualized by spatial mapping and different color fillings. S5 establishes microstructure-mechanical property evaluation models based on the microstructure characteristic parameters of each region, enabling rapid and non-destructive evaluation of material strength and plasticity.

2. The rapid non-destructive evaluation method for material strength and plasticity based on EBSD data according to claim 1, characterized in that, The grain microstructure characteristic parameters in step S2 include: Grain size This represents the grain size of a single grain, in units of 1. ; Average grain size , representing the average value of the equivalent circle diameter of the grains within the target region, in units of ; Number of adjacent grains , indicating the number of grains in contact with the grains; Average number of adjacent grains , which represents the average number of adjacent grains of all grains within the target region.

3. The rapid non-destructive evaluation method for material strength and plasticity based on EBSD data according to claim 2, characterized in that, Grain plasticity sensitivity coefficient in step S3 The formula used to characterize the relative sensitivity of grains to plastic deformation under applied load is as follows: In the formula, This is the material correction factor.

4. The rapid non-destructive evaluation method for material strength and plasticity based on EBSD data according to claim 2, characterized in that, The specific evaluation method in step S4 is as follows: The slip or non-slip state of grains is determined by crystallographic characterization. Boundary grains and minimal grains are removed, and the values ​​of slip grains and non-slip grains are statistically analyzed separately. Values, and compare slip grains with unslip grains. The median of the values ​​is denoted as . and To characterize the distribution differences of the two types of grains on plasticity sensitivity parameters; Based on this, using the median and As the grouping boundary, all grains are divided into , and The slip ratio distribution characteristics of grains in the three intervals were statistically analyzed, and slip ratio distribution diagrams were plotted. Through the The grain slip behavior within the interval was further analyzed in detail. The values ​​are incremented in increments of 0.01, and the corresponding slip ratios are calculated to determine the value at which the slip ratio first reaches 40%. The value is defined as the critical value of the plasticity sensitivity coefficient. ; Based on critical value The region containing the grains is divided as follows: when At this time, the region is defined as the plastic-dominant region, where the grains are located and plastic deformation is dominant; when When this occurs, the region is defined as the strength-dominant region, where no significant plastic deformation occurs and the region is characterized by strength dominance.

5. The rapid non-destructive evaluation method for material strength and plasticity based on EBSD data according to claim 4, characterized in that, Within the strength-dominant region, when the number of adjacent grains of a grain... Higher than the average number of adjacent grains This indicates that it is strongly constrained by its neighborhood. and The region is considered a potentially vulnerable area.

6. The rapid non-destructive evaluation method for material strength and plasticity based on EBSD data according to claim 1, characterized in that, The specific steps of step S5 are as follows: Microstructural characteristic parameters of the plastic deformation-dominant and strength-dominant regions are selected to construct characteristic parameter sets for each region. Based on the characteristic parameter sets, a mapping relationship between regional microstructure and mechanical properties is established, and a microstructure-mechanical property evaluation model is formed accordingly. The microstructure-mechanical property evaluation model is used to perform rapid and non-destructive evaluation of material strength and plasticity.

Images