CN102331391B - Method for measuring and calculating aggregation and coarsening degree of multi-phase grain in refractory steel - Google Patents

Abstract

The invention discloses a method for measuring and calculating aggregation and coarsening degree of a multi-phase grain in refractory steel. The method comprises the following steps of: (1) finishing, polishing and etching an observation surface of a refractory steel sample to be tested; (2) photographing a plurality of pieces of back scattering electronic pictures of precipitated phases in the sample by using an electron probe or a scanning electron microscope; (3) blackening scales of the obtained back scattering electronic pictures so as to obtain pictures containing no scales; (4) counting pixels (N) included by areas (A) of different light and dark regions of one of the pictures containing no scales and scale normal length (L) by using software Image proplus; (5) calculating sizes ofgrain clusters of different precipitated phases by using A, L and N in the step (4); and (6) repeating the steps (4) and (5) to obtain the sizes of the grain clusters of the different precipitated phases in the series of pictures and taking the average value, namely the actual size of the grain clusters of the different precipitated phases. The measurement and calculation result of the invention is excellently matched with related reports, and is easy to operate and time-saving. The method can be used for important fields of design, breakage, failure analysis and the like of refractory steel.

Description

A Method for Measuring and Calculating Coarsening Degree of Multiphase Particles in Heat-resistant Steel

technical field

The invention relates to the determination of the microstructure of heat-resistant steel, in particular to a method for measuring and calculating the degree of aggregation and coarsening of precipitated phase particles in the heat-resistant steel.

Background technique

In order to meet the comprehensive performance requirements of ultra-supercritical thermal power generation units, a new generation of heat-resistant steel (such as P92, Super304h, etc.) has been widely used in high-temperature components of this type of boiler. Studies have shown that the fracture of heat-resistant steel transitions from transgranular fracture to intergranular fracture under high temperature conditions. This phenomenon is microscopically manifested as: because the diffusion is easy to proceed at the grain boundary, the fine and dispersed precipitated phase particles distributed at the grain boundary during the service of the heat-resistant steel will aggregate, coarsen, and form chains, thereby weakening the grain boundary of the material. The strength and toughness of the grain boundary, and eventually lead to the fracture failure of the material; at the same time, the diffusion process makes it easy to form new precipitates at the grain boundaries, and the newly formed precipitates interact with the original precipitates that aggregate, coarsen, and form chains. Thus affecting the strength and toughness of the grain boundary of the material. Therefore, it is very important to correctly and reasonably evaluate the aggregation and coarsening degree of precipitated phase particles in heat-resistant steel for the design, development, production and evaluation of boiler materials for ultra-supercritical thermal power plants. At present, there is no report on the method for measuring the coarsening degree of multiphase particles in heat-resistant steel; only when there is a single precipitated phase in the steel, the traditional metallographic method can analyze the coarsening degree of the phase particles. To use the metallographic method to measure and take a large number of metallographic photos of the sample, and then use relevant software to color the precipitated phase particles in the photos and calculate the size of the colored part in different directions, and then take the average value as the average value of the precipitated phase in the sample size. The problems of using this method are as follows: (1) The magnification of the metallographic microscope is low, and the size of the main precipitated phase in heat-resistant steel is generally between tens to hundreds of nanometers, so in the traditional metallographic microscope It is difficult to clearly observe these smaller phase particles, let alone calculate their size; (2) When there are many kinds of precipitated phase particles in the material, different types of precipitated phases often gather together, and metallographic photographs cannot distinguish them. It is impossible to observe its distribution. Therefore, when there are many kinds of precipitated phase particles in the steel and they are aggregated and coarsened, the traditional metallographic method cannot be used to measure the degree of coarsening of each phase. In order to solve the above problems, this method uses backscattered electron images to distinguish different precipitated phase particles in steel, and characterizes the aggregation and coarsening of multiphase particles in steel according to the size of particle clusters. How to make the quantitative calculation of the size of the multiphase particle clusters in the heat-resistant steel accurate, convenient and time-saving is a key of the present invention.

Contents of the invention

The object of the present invention is to provide a method for measuring and calculating the aggregation and coarsening degree of particles of precipitated phases in heat-resistant steel. The method has accurate calculation results, simple operation and time-saving.

计算钢中不同析出相颗粒簇的当量尺寸L_a1, L_b1…，单位为像素，然后利用公式

换算出析出相颗粒簇的实际尺寸D_a1, D_b1…，其中，k=a ,b…代表试样中不同的析出相；对其他照片重复上述步骤，从而获得系列照片中不同析出相颗粒簇的实际尺寸D_a2, D_b2…，D_a3, D_b3…，下标2、3表示试样所拍摄照片的编号；然后计算D_a1 , D_a2 , D_a3…，D_b1 , D_b2 , D_b3…的平均值，所得结果D_a, D_b…即为该试样a, b…析出相颗粒簇的平均尺寸。 The purpose of the present invention is achieved in this way: firstly, according to the conventional metallographic sample preparation method, the observation surface of the test sample is polished, polished and etched; Electronic imaging mode, take backscattered electron photos of the precipitated phase in the sample at a magnification of 2000~5000 times, and the number of photos taken for each sample is not less than 5; blacken the scale of the obtained backscattered electron photos In order to obtain a photo without a ruler; use the image quantitative software Image pro plus to count the light and dark distribution map of the pixels of one of the above photos (set its number as 1), and divide the map into the matrix area m and the precipitated phase area a, b,.... Among them, the number of peaks R in the light and shade distribution diagram of pixels is the number of precipitated phases, and R is 1, 2, ... R from right to left, a corresponds to the area to the right of peak 1, b corresponds to peak 1, The area between 2..., the last precipitation corresponds to the area between the peak R-1 and the inflection point A on the right side of the peak R; the left side of point A is the matrix area; then calculate the area A _a1 of each precipitated phase area, A _b1 ..., the unit is pixel, where the subscript 1 indicates that the number of the photo taken by the sample is 1; in addition, the number of pixels N included in the photo is determined by the nominal length L of the scale; Areas A _a1 , A _b1... and formulas of phase regions

Calculate the equivalent size L _a1 , L _b1 ... of particle clusters of different precipitated phases in steel, the unit is pixel, and then use the formula

Convert the actual size D _a1 , D _b1 ... of precipitated phase particle clusters, where k=a , b ...represents different precipitated phases in the sample; repeat the above steps for other photos to obtain different precipitated phase particle clusters in a series of photos The actual size D _a2 , D _b2 ... , D _a3 , D _b3 ... , the subscripts 2 and 3 indicate the number of the photos taken by the sample; then calculate D _a1 , D _a2 , D _a3 ... , D _b1 , D _b2 , D The average value of _b3 ..., the obtained results D _a , D _b ... are the average size of the precipitated phase particle clusters of the sample a, b....

The method of the invention has the advantages of accurate measuring and calculating results, simple and convenient operation and time-saving.

Description of drawings

Figure 1 and Figure 2 are the light and shade distribution diagrams of the pixels of the backscattered photos of the P92 steel 625 °C durable sample produced by a certain factory;

Figure 3 is the microstructure diagram of the P92 steel 625°C durable sample produced by the factory;

Figure 4 is a microstructure diagram of a 700°C durable sample of Super304h steel produced by a certain factory;

Fig. 5 is the size diagram of M ₂₃ C ₆ and Laves phase particle clusters in P92 steel 625°C durable sample calculated by this method; Fig. 6 is the change diagram of M ₂₃ C ₆ and Laves phase content in P92 steel 625°C durable sample ;

Figure 7 is the size diagram of M ₂₃ C ₆ phase particle clusters in the Super304h steel 700°C durable sample calculated by this method;

Fig. 8 is a graph showing the change of M ₂₃ C ₆ phase content in the 700°C durable sample of Super304h steel.

Detailed ways

The method of the present invention comprises the following steps:

① Grind, polish and etch the observation surface of the test sample according to the conventional metallographic sample preparation method;

② Select the backscattered electron imaging mode under the electron probe (EPMA) or scanning electron microscope (SEM), and take the backscattered electron photos of the precipitated phase in the sample at a magnification of 2000 to 5000 times. No less than 5 backscattered electron photos (theoretically, the more photos you take, the more accurate the results will be);

③ Blacken the scale of the gained backscattered electron photo to obtain a photo without scale;

④Use the image quantitative software Image pro plus to count the light and shade distribution map of the pixels of one of the photos obtained in step ③ (set its number as 1), and divide the map into matrix region m and precipitated phase regions a, b, ... ; Among them, the number of peaks R in the light and dark distribution diagram of pixels is the number of precipitates, and R is 1, 2, ... R from right to left, a corresponds to the area to the right of peak 1, and b corresponds to peak 1 , 2..., the last precipitation corresponds to the area between the peak R-1 and the inflection point A on the right side of the peak R; the left side of point A is the matrix area; then calculate the area A _a1 of each precipitated phase area, A _b1 ..., the unit is pixel, where the subscript 1 indicates that the number of the photo taken by the sample is 1; in addition, measure the number N of pixels contained in the photo of the nominal length L of the ruler;

计算钢中不同析出相颗粒簇的当量尺寸L_a1, L_b1…，单位为像素，然后利用公式换算出析出相颗粒簇的实际尺寸D_a1, D_b1…，其中，k=a ,b…代表试样中不同的析出相； ⑤According to the area A _a1 , A _b1... and the formula of each precipitated phase region in the backscattered electron photograph obtained in step ④

Calculate the equivalent size L _a1 , L _b1 ... of particle clusters of different precipitated phases in steel, the unit is pixel, and then use the formula Convert the actual size D _a1 , D _b1 ... of the precipitated phase particle clusters, where k=a , b ... represent different precipitated phases in the sample;

⑥Repeat steps ④ and ⑤ to obtain the actual size D _a2 , D _b2 ..., D _a3 , D _b3 ... of different precipitated phase particle clusters in the series of photos; then calculate D _a1 , D _a2 , D _a3 ..., D _b1 , D _b2 , D _b3 ..., the obtained results D _a , D _b ... are the average size of the precipitated phase particle clusters of the sample a, b....

Technical process of the present invention and its characteristics:

①Preparation of samples

In the present invention, the test sample is polished, polished and etched according to the conventional metallographic sample preparation method.

② Microstructure observation and photography

The precipitated phase in the sample was observed and photographed under the backscattered electron imaging mode of the electron probe (EPMA) or scanning electron microscope (SEM). The magnification of the selected photo is 2000~5000, and the number of photos taken for each sample is not less than 5.

③ Photo processing

The scale of the resulting backscattered electron photograph was blackened to obtain a scale-free photograph.

④ Differentiate between different precipitates in the sample

Use the image quantitative software Image pro plus to count the light and shade distribution map of the pixels of one of the photos obtained in step ③ (set its number as 1), and divide the map into matrix region m and precipitated phase regions a, b, ...; Among them, the number of peaks R in the light and shade distribution diagram of pixels is the number of precipitated phases, and R is 1, 2, ... R from right to left, a corresponds to the area to the right of peak 1, b corresponds to peak 1, The area between 2..., the last precipitation corresponds to the area between the peak R-1 and the inflection point A on the right side of the peak R; the left side of point A is the matrix area; then calculate the area A _a1 of each precipitated phase area, A _b1 ..., the unit is pixel, where the subscript 1 indicates that the number of the photo taken by the sample is 1; in addition, measure the number N of pixels contained in the photo of the nominal length L of the ruler. According to the method of the present invention, it is easy to distinguish different types of precipitates in heat-resistant steel and calculate the size of the particle clusters, so as to objectively reflect the authenticity of the aggregation and coarsening degree of the particles of each precipitate in the steel, which is the core of the present invention where.

The invention proposes to use the image quantification software Image pro plus to count the light and shade distribution map of the pixel points of the backscattered electron photo, so as to distinguish different types of precipitated phases in the heat-resistant steel. The specific distinction method is as follows:

Because the elements enriched in different precipitates in steel are different, the lightness and darkness of the particles of each precipitate in the backscattered electron photographs are different: when the relative atomic mass of the elements enriched in the precipitate is large, its The larger the brightness shown in the scattered electron photo; the smaller it is vice versa. In addition, compared with the precipitated phase, the relative proportion of heavy alloy elements contained in the matrix is the lowest, so the brightness is the darkest.

As shown in Figures 1 and 2, in the light and shade distribution diagram of the pixel points in the backscattered photos of the sample, different precipitations correspond to different regions in the diagram, and the boundary point is the inflection point A on the right side of peak 1 in the matrix region and the precipitation phase of crest 2. In addition to the matrix m, there are two precipitated phases, a and b, in the steel. The area of phase a is the part on the right side of phase a precipitation peak 1; the area of phase b is the part between peak 1 and point A; the matrix m is the part to the left of point A. part.

Similarly, when there are more precipitated phases in the steel, the position of each precipitated phase in the light and shade distribution map of the pixel point of the backscattered photo of the sample can be judged according to the peaks of different phases of precipitated phases and the position of point A.

⑤Calculation of particle cluster size of precipitated phase

Through the area A _a1 , A _b1... and the formula of each precipitated phase region in the backscattered electron photograph obtained in step ④

Calculate the equivalent size L _a1 , L _b1 ... of particle clusters of different precipitated phases in steel, the unit is pixel, and then use the formula

The actual sizes D _a1 , D _b1 ... of the precipitated phase particle clusters are converted, where k=a , b ... represent different precipitated phases in the sample.

⑥ Calculation of the average size of precipitated phase particle clusters

Repeat steps ④ and ⑤ to obtain the actual size D _a2 , D _b2 ..., D _a3 , D _b3 ... of different precipitated phase particle clusters in the series of photos; then calculate D _a1 , D _a2 , D _a3 ..., D _b1 , D _b2 respectively , D _b3 ..., the obtained results D _a , D _b ... are the average size of the precipitated phase particle clusters of the sample a, b....

Example:

Example ①: Take the 625°C durable sample of P92 steel for ultra-supercritical boiler as an example.

Figure 3 is a backscattered electron photo of a 625°C durable sample of P92 steel. As shown in the figure, the microstructure of the sample is lath martensite matrix and M ₂₃ C ₆ and Laves phase particles distributed on the prior austenite grain boundary. Among them, the Laves phase is white and bright because it is rich in heavy elements such as W and Mo, and M ₂₃ C ₆ is rich in Cr, which is lighter than W and Mo, so it is gray, and the matrix is the darkest. For this method: first, according to the specific implementation steps ① to ③, a total of 5 backscattered electron photos of the tested sample are obtained, and then according to step ④, use the image quantitative software Image pro plus to count one of the photos obtained in the above steps (assuming that its serial number is 1) The light and dark distribution map of the pixel points and divide the map into three regions of M ₂₃ C ₆ , Laves and matrix m according to the peak position in the distribution map (corresponding to the two precipitated phases of M ₂₃ C ₆ and Laves in the steel and the matrix respectively ), and then calculate the area A _(M23C6)1 , A _(Laves)1 of the M ₂₃ C ₆ and Laves area; at the same time, determine the number of pixels N contained in the photo by the nominal length L of the ruler; then step ④ The area A _(M23C6)1 and A _(Laves)1 of the M ₂₃ C ₆ and Laves regions in the backscattered electron photograph obtained in

Converted to the equivalent size L _(M23C6)1 , L _(Laves)1 (unit is pixel, Pix) of different precipitated phase particle clusters in heat-resistant steel, and then use the formula

( k represents different precipitated phases in steel, in this case k=(M ₂₃ C ₆ ),(Laves) )

Calculate the actual size D _(M23C6)1 , D _(Laves)1 of the precipitated phase particle cluster;

Finally, repeat steps ④ and ⑤ to obtain the actual size D _(M23C6)2 , D _(Laves)2 of different precipitated phase particle clusters in the other 4 photos; D _(M23C6)3 , D _(Laves)3 ; D _(M23C6)4 , D _(Laves)4 ; D _(M23C6)5 , D _(Laves)5 , respectively calculate D _(M23C6)1 , D _(M23C6)2 , D _(M23C6)3 , D _(M23C6)4 , D _(M23C6)5 And the average value of D _(Laves)1 , D _(Laves)2 , D _(Laves)3 , D _(Laves)4 , D _(Laves)5 , the result D _(M23C6) , D _(Laves) is the sample M ₂₃ C ₆ , the particle cluster size of Laves precipitated phase.

The calculation results of this method are shown in Table 1, and the results show that the calculation results of this method (shown in Figure 5) are in good agreement with the change results of the M ₂₃ C ₆ and Laves phase content of the sample (shown in Figure 6).

Table 1 M ₂₃ C ₆ and Laves phase particle cluster size of P92 steel 625°C durable sample measured by the method of the present invention

Loading stress / fracture time (MPa / h) M ₂₃ C ₆ particle cluster size (nm) Laves particle cluster size (nm) 180 / 30 266 - 160 / 170 298 - 160 / 243 334 - 150 / 454 318 262 140 / 2881 331 299 130 / 4018 336 304 120 / 7077 353 351 110 / 10122 371 385

Example ②: Take the 700°C durable sample of Super304H steel for ultra-supercritical boiler as an example.

Figure 4 is a backscattered electron photo of a 700°C durable sample of Super304H steel. As shown in the figure, the microstructure of the sample is mainly austenite matrix and M ₂₃ C ₆ particles distributed on the grain boundaries of prior austenite. Compared with the matrix, M ₂₃ C ₆ is rich in Cr, so it appears off-white in the photo, and the matrix is darker. For this method: first, according to the specific implementation steps ① to ③, a total of 5 backscattered electron photos of the tested sample are obtained, and then according to step ④, use the image quantitative software Image pro plus to count one of the photos obtained in the above steps (assuming that its serial number is 1) According to the light and dark distribution map of the pixel points in the distribution map, the map is divided into two regions of M ₂₃ C ₆ and matrix (Matrix) according to the peak position in the distribution map (corresponding to the M ₂₃ C ₆ precipitated phase and matrix in the steel respectively), and then calculate Go out the area A _(M23C6)1 of M ₂₃ C ₆ regions _; Simultaneously, _measure the nominal length L of ruler and include the number of pixels N in the photo; The area of A _(M23C6)1 is given by the formula:

Converted to the equivalent size L _(M23C6)1 (unit is pixel, Pix) of different precipitated phase particle clusters in heat-resistant steel, and then use the formula

( k represents the different precipitated phases in the steel, in this case k=(M ₂₃ C ₆ ) )

Calculate the actual size D _(M23C6)1 of the precipitated phase particle cluster;

Repeat steps ④ and ⑤ at last to obtain the actual size D _(M23C6) of different precipitated phase particle clusters in other 4 photos; D _{(M23C6) 3} ; D _{(M23C6) 4} ; D _{(M23C6) 5} , then calculate D _{(M23C6 )1} , D _(M23C6)2 , D _(M23C6)3 , D _(M23C6)4 , the average value of D (M23C6 ₎₅ , the obtained result D _(M23C6) is the M ₂₃ C ₆ precipitated phase particle cluster of the sample size.

The calculation results of this method are shown in Table 2, and the results show that the calculation results of this method (shown in Figure 7) are in good agreement with the change results of the M ₂₃ C ₆ phase content of this sample (shown in Figure 8).

Table 2 Size of particle clusters of phase M ₂₃ C ₆ of Super304h 625°C durable sample measured by the method of the present invention

Loading stress / fracture time (MPa / h) M ₂₃ C ₆ particle cluster size (nm) 180 / 523 252 170 / 1080 255 160 / 1588 259 150 / 2024 272 130 / 4109 286 120 / 8688 333

The present invention has the following advantages and positive effects:

① In view of the current situation that there is no method for measuring the coarsening degree of multiphase particle aggregation in heat-resistant steel, it is proposed to use the particle cluster size to characterize the coarsening degree of multiphase particle aggregation;

② When there are only single-phase particles in the steel, compared with conventional metallographic methods, it is possible to measure the size of phase particles and particle clusters that cannot be measured under a metallographic microscope in the range of tens to hundreds of nanometers;

③ The calculation process of this method is simple, fast, and the result is accurate and reliable;

④This method can be used not only for various heat-resistant steels, but also for the size calculation of precipitated phase particles and particle clusters of other steel types and alloys, and has broad application prospects. the

Claims (1)

1. A method for measuring and calculating the coarsening degree of multi-phase particles in heat-resistant steel, is characterized in that, comprises the following steps: 1. according to conventional metallographic sample preparation method, the observation surface of the test sample is polished, polished and etched; 2. Select the backscattered electron imaging mode under the electron probe or scanning electron microscope, and take the backscattered electron photos of the precipitated phase in the sample at a magnification of 2000~5000 times, and the number of photos taken for each sample shall not be less than 5 ; 3. Blacken the scale of the gained backscattered electron photo to obtain a photo without scale; 4. Utilize the image quantification software Image pro plus to count one of the obtained photos in step 3. Set its number as the pixel light and shade distribution map of 1, Divide the graph into matrix region m and precipitated phase regions a, b, ...; among them, the number of peaks R in the light and shade distribution diagram of pixels is the number of precipitated phases, and R is 1, 2 from right to left ,...R, a corresponds to the area to the right of peak 1, b corresponds to the area between peaks 1 and 2..., and the last precipitation corresponds to the area between peak R-1 and the inflection point A on the right side of peak R; The left side of point A is the matrix area; then calculate the area A _a1 , A _b1 ... of each precipitated phase area, the unit is pixel, wherein the subscript 1 indicates that the number of the photo taken by the sample is 1; Weigh the number of pixels N included in the length L in the photo; ⑤ Through the area A _a1 , A _b1... and the formula of each precipitated phase region in the backscattered electron photo obtained in step ④

Calculate the equivalent size L _a1 , L _b1 ... of particle clusters of different precipitated phases in steel, the unit is pixel, and then use the formula

Convert the actual size D _a1 , D _b1 ... of precipitated phase particle clusters, where k=a , b ...represents different precipitated phases in the sample; ⑥Repeat steps ④ and ⑤ for other photos to obtain different precipitated phases in a series of photos The actual size of phase particle clusters D _a2 , D _b2 ... , D _a3 , D _b3 ... , subscripts 2 and 3 indicate the number of photos taken of the sample; then calculate D _a1 , D _a2 , D _a3 ... , D _b1 , D The average value of _b2 , D _b3 ... and the obtained result D _a , D _b ... is the average size of the precipitated phase particle clusters of the sample a, b....

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