Spark optical emission spectrometry method for distribution of inclusion content on surface of large-sized metal material

Abstract

The application discloses a spark spectrum analysis method for the inclusion content distribution on the surface of large-size metal materials, which continuously excites and scans the surface of the large-size metal materials through spark discharge to obtain the mixed distribution data of the solid solution and inclusions of the inclusion elements on the surface of the large-size metal materials, and further obtains the relative frequency distribution graph of the spectral intensity; the relative frequency distribution graph of the spectral intensity is subjected to normal distribution and Gumbel extreme value distribution peak fitting processing to obtain the Gumbel extreme value distribution data of the spectral intensity of the inclusions; the number and size information of the inclusions of the small sample are acquired to obtain the maximum inclusion size information; the inclusion size information of the small sample and the maximum inclusion size information are associated with the spectral intensity distribution data of the inclusions to determine the corresponding relationship between the size and the spectral intensity of the inclusions, and the content distribution result of the inclusions on the surface of the large-size metal materials is obtained. The application can quickly obtain the accurate distribution information of each element inclusion on the surface of the metal materials.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of surface characterization of metal materials, in particular to a spark spectrum analysis method for inclusion content distribution on the surface of large-size metal materials. BACKGROUND

[0002] The global characterization of inclusions on the surface of large-size metal materials is a difficult and extremely complex technology. Among various means for material inclusion characterization, conventional analysis methods such as metallographic method and scanning electron microscopy method are usually only applicable to 200mm 2 The following test areas cannot directly realize the characterization of inclusions in large-size samples; the metal large sample electrolysis method can analyze inclusions greater than 50um in 100mm size metal samples, the process is complex and time-consuming is greater than 2 weeks, and cannot be used as a conventional and convenient method for characterizing inclusions in large-size samples; the extreme value method as an indirect test method for inclusions in large-size metal material samples can only infer the information of the largest inclusion, and cannot give the inclusion content distribution. In addition, some spectral analysis methods can characterize the inclusions and their distribution information on the surface of metal materials, and the method of separating inclusion element intensity signal by using a rough method greater than the threshold intensity cannot strictly determine the actual relative frequency distribution of the inclusion intensity signal, and the smaller inclusion signal is considered as a solid solution element, and the larger solid solution element intensity is considered as an inclusion signal. SUMMARY

[0003] The purpose of the present application is to provide a spark spectrum analysis method for inclusion content distribution on the surface of large-size metal materials, which correlates the size information under the scanning electron microscope with the inclusion signal data information of the spark spectrum analysis of large-size metal samples, determines the relationship between the inclusion size and the intensity, and thus obtains the content distribution information of the inclusions in the large-size sample, thereby solving the problem of analyzing the inclusion content distribution on the surface of large-size metal materials.

[0004] To achieve the above purpose, the present application provides the following solutions:

[0005] A spark spectrum analysis method for inclusion content distribution on the surface of large-size metal materials, the method comprising the following steps:

[0006] The surface of the large-size metal material is continuously excited and analyzed by spark discharge, and the mixed distribution data of the spectral intensity of the solid solution and inclusions of the inclusion elements on the surface of the large-size metal material are obtained;

[0007] The mixed distribution data of the spectral intensity of the solid solution and inclusions of the inclusion elements are summarized to obtain a spectral intensity relative frequency distribution graph of the solid solution and inclusions of the inclusion elements;

[0008] The spectral intensity relative frequency distribution graph is subjected to peak fitting processing to obtain spectral intensity distribution data of the inclusions.

[0009] taking a sample of a set area on the surface of the large-sized metal material as a small sample, and obtaining the inclusion quantity and size information of the small sample;

[0010] associating the inclusion size information of the small sample with the spectral intensity distribution data of the inclusions, determining the corresponding relationship between the size and the spectral intensity of the inclusions, and obtaining the content distribution result of the inclusions on the surface of the large-sized metal material.

[0011] Further, the continuous spark discharge scanning analysis of the surface of the large-sized metal material obtains the spectral intensity mixed distribution data of the solid solution and inclusions of the inclusion elements on the surface of the large-sized metal material, including:

[0012] First, the scanning probe is placed at the leftmost position on the upper end of the large-sized metal material in the Y direction, and spark discharge scanning is performed along the X direction from left to right. After the first row of scanning is completed, the scanning probe is placed at the leftmost position on the second row of the upper end of the large-sized metal material in the Y direction, and the second row of scanning is completed from left to right. Until all rows of the large-sized metal material are scanned from top to bottom, the spectral intensity mixed distribution data of the solid solution and inclusions of the inclusion elements on the surface of the large-sized metal material is obtained.

[0013] Further, the fitting processing of the spectral intensity relative frequency distribution diagram obtains the spectral intensity distribution data of the inclusions, including:

[0014] The normal distribution and Gumbel extreme value distribution peak fitting processing is performed on the spectral intensity relative frequency distribution diagram to obtain the normal distribution diagram of the left main peak solid solution part and the Gumbel extreme value distribution diagram of the right tail peak inclusions;

[0015] Based on the Gumbel extreme value distribution diagram of the right tail peak inclusions, the spectral intensity distribution data of the inclusions is obtained.

[0016] Further, the taking of the sample of a set area on the surface of the large-sized metal material as a small sample includes:

[0017] The area of the surface of the large-sized metal material is obtained, denoted as S 大 ;

[0018] The set area of the small sample is obtained, denoted as S 小 ;

[0019] The area of the surface of the large-sized metal material and the set area of the small sample satisfy the following relationship:

[0020] T = S 大 / S 小

[0021] Wherein, T is in the range of 100-10000.

[0022] Further, the large size metal material surface is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, including:

[0023] The large size metal material surface is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, including:

[0024] Further, the large size metal material surface is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, including:

[0025] The large size metal material surface is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, including:

[0026] Further, the large size metal material surface is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, including:

[0027] The size information of the inclusions under the scanning electron microscope is classified and counted to obtain the statistical frequency of each group with a group interval of 2um;

[0028] The spectral intensity distribution data of the inclusions are divided into the same groups based on the 2um group interval statistical frequency under the scanning electron microscope to obtain the average size and average intensity under each group;

[0029] According to the average intensity of each group obtained from the group frequency and the relationship between the maximum intensity and the average and maximum size of the inclusions, an intensity size correction curve is drawn;

[0030] According to the intensity size correction curve, the intensity-relative frequency spectrum is converted into the inclusion size-frequency spectrum, multiplied by the total number of inclusion element spectrum intensity, to obtain the inclusion size distribution graph, to set the group interval, to obtain the inclusion content distribution result.

[0031] According to the specific embodiments of the present application, the following technical effects are disclosed: the spark spectrum analysis method for the inclusion content distribution of the surface of the large-size metal material, for the surface of the large-size metal material, the spectral intensity signal data of the inclusion element in the large-size range is obtained through spark spectrum analysis, and the element solid solution intensity signal and the inclusion intensity signal are separated according to the intensity relative frequency distribution graph, to obtain the inclusion intensity distribution graph, so as to realize the separation of the inclusion intensity signal and the element solid solution signal; based on the scanning electron microscope analysis of the small sample in the same large-size metal material, the inclusion size information under the scanning electron microscope and the inclusion intensity distribution of the large-size metal material after spark discharge scanning are associated to determine the corresponding relationship between the inclusion size and the intensity, so as to obtain the size distribution information of the inclusion of the large-size metal sample. The method can effectively overcome the problem that the sample size is large and the inclusion distribution analysis in a large area cannot be directly realized, and can quickly obtain accurate inclusion distribution results of the surface of the large-size metal material. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0033] Figure 1 The flow chart of the spark spectrum analysis method for the inclusion content distribution of the surface of the large-size metal material of the present application;

[0034] Figure 2 The scanning schematic diagram of the spark spectrum analysis;

[0035] Figure 3 The relative frequency distribution schematic diagram of the Al element solid solution and inclusion intensity distribution of the embodiment of the present application.

[0036] Figure 4 The fitting schematic diagram of the Al element intensity frequency distribution of the embodiment of the present application;

[0037] Figure 5 The inclusion content distribution result graph of the Al element of the embodiment of the present application. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0039] For the inclusion content distribution of the surface of a large-size metal material, because the area of a test sample is too large, on the one hand, a conventional test method cannot directly analyze, and on the other hand, an indirect test method (such as an extreme value method) for the large-size inclusion can only infer the content of the largest inclusion, and cannot give the inclusion distribution result. Some spectral analysis methods can characterize the inclusion and its distribution information, but the method cannot obtain the accurate actual distribution of the inclusion by using a rough threshold to distinguish the inclusion signal and obtain the inclusion distribution.

[0040] The purpose of the present application is to provide a spark spectral analysis method for the inclusion content distribution of the surface of a large-size metal material, to correlate the size information under a scanning electron microscope and the inclusion signal data information of the spark spectral analysis of a large-size metal sample, to determine the relationship between the inclusion size and the intensity, and to obtain the content distribution information of the inclusion of the large-size sample, thereby solving the problem of the analysis of the inclusion content distribution of a large-size sample.

[0041] In order to make the above-mentioned purpose, characteristics and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0042] As shown in Figure 1 The spark spectral analysis method for the inclusion content distribution of the surface of a large-size metal material provided by the present application comprises the following steps:

[0043] The surface of the large-size metal material is continuously excited and scanned by spark discharge to obtain the mixed distribution data of the spectral intensity of the solid solution and the inclusion of the inclusion element of the surface of the large-size metal material;

[0044] The mixed distribution data of the spectral intensity of the solid solution and the inclusion of the inclusion element are summarized to obtain a relative frequency distribution graph of the spectral intensity of the solid solution and the inclusion of the inclusion element, and the relative frequency distribution graph of the solid solution and the inclusion intensity of the Al element is shown in Figure 3 As can be seen from the graph, the entire intensity relative frequency distribution is right-skewed, and the reason for the right-skewed is that the aluminum inclusion intensity exceeds the aluminum solid solution intensity;

[0045] The spectral intensity relative frequency distribution graph is fitted to obtain the spectral intensity distribution data of the inclusion, and the fitting graph of the intensity frequency distribution of the Al element is shown inFigure 4 As shown in the figure, the main peak is mainly the relative frequency distribution of solid solution Al intensity, and the right part or the tail part is mainly the relative frequency distribution of inclusion Al intensity;

[0046] Taking a sample of a set area on the surface of the large-size metal material as a small sample, and obtaining the inclusion quantity and size information of the small sample;

[0047] Correlating the inclusion size information of the small sample with the spectral intensity distribution data of the inclusions, determining the corresponding relationship between the size and the spectral intensity of the inclusions, and obtaining the content distribution result of the inclusions on the surface of the large-size metal material. Taking Al element as an example, the Al element inclusion content distribution result is as shown in the figure. Figure 5 As shown in the figure, the Al element inclusion size in the whole large-size sample is concentrated in the range of 0-2um and 2-4um, and the number of Al inclusions greater than 14um is the least.

[0048] The method comprises the following steps:

[0049] As shown in the figure. Figure 2 is a spark spectrum analysis scanning schematic diagram, and the gray part is a continuous scanning trace. The surface of the large-size metal material is continuously scanned and analyzed by the spark spectrum technology. The scanning probe is first placed at the leftmost position of the upper end of the large-size metal material in the Y direction. The spark discharge scanning is performed from left to right along the X direction. After the first row of scanning is completed, the scanning probe is placed at the leftmost position of the second row of the upper end of the large-size metal material in the Y direction. The second row of scanning is completed from left to right. Until all rows of the large-size metal material are scanned from top to bottom, the mixed distribution data of the spectral intensity of the solid solution and the inclusion of the inclusion element on the surface of the large-size metal material is obtained.

[0050] Generally, the scanning analysis method is to use a multi-channel element spark excitation source to excite the sample, and the scanning position is accurately positioned. The corresponding multi-channel element spark emission spectrum intensity I(X, Y) is obtained at each position (X, Y). The measured element spark emission intensity I(X, Y) is arranged from small to large, and 256 intensity signal distribution diagrams are obtained with the corresponding group distance. For the inclusion signal in the element, the spectral intensity signal distribution is a tail distribution on the right side of the normal distribution, that is, the average value is not in the center position of the distribution diagram. The main reason for forming the tail distribution is that the non-solid solution part in the element is in the form of enrichment of the inclusion element in the spectral signal after forming the inclusion, which causes the spectral signal intensity of the inclusion element to be high. The larger the size and area of the inclusion, the higher the enrichment degree of the inclusion element, and the larger the corresponding spectral intensity.

[0051] The present application is directed to the analysis of inclusions on the surface of large-sized metal materials, and adopts a spark spectrum scanning analysis method. First, a spectrum analysis system is configured, and a solid-state pulsed discharge light source is used as an excitation source. An optical system can be a Rowland circle or other optical systems, and a light intensity collection component can be a photomultiplier tube or a CCD detector or a CMOS detector. A precision transmission device in X and Y directions is used. Generally, a scanning analysis method is to use a multi-channel spark excitation source to excite the sample, and the scanning position is accurately positioned. The corresponding spark emission spectrum intensity I(X, Y) is obtained at each position (X, Y), the element spark emission intensity I(X, Y) is counted, and the corresponding group distance is obtained by arranging from small to large to obtain a 256-intensity signal distribution frequency distribution graph. Through mathematical fitting processing on the inclusion element intensity distribution frequency histogram, the relative frequency distribution graph of the inclusion intensity is obtained.

[0052] For example, the fitting processing on the spectrum intensity relative frequency distribution graph to obtain the spectrum intensity distribution data of the inclusions includes:

[0053] The spectrum intensity relative frequency distribution graph is subjected to normal distribution and Gumbel extreme value distribution peak fitting processing to obtain a normal distribution graph of a left main peak solid solution part and a Gumbel extreme value distribution graph of a right tail peak inclusion;

[0054] The left main peak is the intensity distribution of the element solid solution part, which is in a Gaussian function distribution, and the function expression is:

[0055]

[0056] In the formula, μ is the expected value of the average value, and σ is the standard deviation;

[0057] The right tail peak represents the inclusion intensity distribution of the inclusion element, which is in a Gumbel extreme value distribution, and the function expression is:

[0058]

[0059] In the formula, λ is a positioning parameter, and δ is a scale parameter.

[0060] The function distribution expression of the total intensity (including solid solution and inclusions) of the element after fitting is:

[0061]

[0062] Based on the Gumbel extreme value distribution graph of the right tail peak inclusion, the spectrum intensity distribution data of the inclusion is obtained. The tail peak function is the inclusion intensity frequency distribution function, and when the intensity and relative frequency distribution graph starts to have intensity, it is the inclusion intensity threshold, so that the element solid solution intensity-relative frequency distribution and the inclusion intensity-relative frequency distribution are accurately distinguished.

[0063] The present application decomposes the spark intensity distribution into normal distribution and Gumbel extreme value distribution by peak separation mathematical model processing on the relative frequency of inclusion element intensity, but is not limited to peak separation of the relative frequency distribution of inclusion element intensity, and is also not limited to Gumbel extreme value distribution, and can also be applied to other extreme value distributions.

[0064] According to the standard GB / T 40281-2021 "Determination of Non-metallic Inclusion Content in Steel - Extreme Value Analysis Method", a small part of the sample (area S 大 ) of the large-sized metal material (scanning area S 小 ) is taken.

[0065] For example, the sample of the set area on the surface of the large-sized metal material is taken as a small sample, which includes:

[0066] The area of the surface of the large-sized metal material is represented as S 大 , for example, 160000mm 2 ;

[0067] The set area of the small sample is represented as S 小 , for example, 160mm 2 ;

[0068] The area of the surface of the large-sized metal material and the set area of the small sample satisfy the following relationship:

[0069] T=S 大 / S 小

[0070] Wherein, T is in the range of 100-10000. The maximum inclusion probability is 99%-99.99%, and according to the actual scanning area S 大 and the value of T, the value of the small part of the sample S 小 can be determined.

[0071] For example, the sample of the set area on the surface of the large-sized metal material is taken as a small sample, and the number and size information of the inclusions of the small sample are obtained, which includes:

[0072] The sample of the set area on the surface of the large-sized metal material is taken as a small sample, and the number and size information of the inclusions of the small sample are obtained, which includes:

[0073] Further, the sample of the set area on the surface of the large-size metal material is taken as a small sample, and the inclusion quantity and size information of the small sample are obtained, and the method further comprises:

[0074] The sample of the set area on the surface of the large-size metal material is taken again, and a small sample is prepared by re-sampling and grinding and polishing, and then the small sample is placed under the scanning electron microscope again to obtain the maximum inclusion size information, which is recorded as second data; the sampling operation is repeated, and a small sample is prepared by re-sampling and grinding and polishing to obtain the maximum inclusion size information, which is recorded as third data; the sampling operation is repeated until 24 groups of data are recorded; according to the standard GB / T 40281-2021 “Determination of Nonmetallic Inclusion Content in Steel - Extreme Value Analysis Method”, the 24 groups of maximum inclusion size information of the element are collected to calculate the maximum inclusion size of the inclusion element in S 大 The area S corresponding to the maximum inclusion size formed max At this time, the maximum inclusion size of the inclusion element should be A max .

[0075] For example, the inclusion size information of the small sample is associated with the spectral intensity distribution data of the inclusion to determine the corresponding relationship between the size and the spectral intensity of the inclusion, and the content distribution information of the inclusion on the surface of the large-size metal material is obtained, which comprises:

[0076] The size information of the inclusion under the scanning electron microscope is classified and counted in the form of equivalent circles, for example, 0-2um, 2-4um, 4-6um, 6-8um, 8-10um, 10-12um, 12-14um, …, to obtain the statistical frequency of each group with a group interval of 2um;

[0077] The spectral intensity distribution data of the inclusion are divided into the same groups based on the 2um group interval statistical frequency under the scanning electron microscope, to obtain the average size and average intensity under each group, which are recorded as D1, D2, D3, D4, A1, A2, A3, A4, respectively;

[0078] According to the average intensity of each group obtained based on the grouping frequency, and the relationship between the maximum intensity and the average and maximum size of the inclusion, an intensity area correction curve is drawn, specifically, in several literatures on spark spectrum analysis of inclusions, the intensity of the inclusion is positively correlated with the size in a parabolic manner, and the correction curve can be drawn according to the point data (D1, A1), (D2, A2), (D3, A3), (D4, A4), (D max , A max ) and the like, to obtain A=aD 2 +bD+c;

[0079] Then according to the strength and inclusion size correction curve, the strength-relative frequency spectrum diagram is converted into the inclusion size-frequency spectrum diagram, multiplied by the total number of inclusion element spectrum intensity, and the inclusion size distribution diagram is obtained, and the inclusion content distribution result is obtained by setting the group interval.

[0080] In summary, the spark spectrum analysis method for large-size metal material surface inclusion content distribution provided by the present application continuously excites and scans the metal material surface by spark discharge to obtain the solid solution and inclusion spectrum intensity distribution data of the metal material surface. The obtained data is summarized to obtain the mixed relative frequency distribution diagram of the solid solution and inclusion intensity of a certain element. The distribution diagram is fitted and processed to separate the solid solution intensity signal and the inclusion intensity signal of the element, and the inclusion intensity distribution diagram is obtained, so that the separation of the inclusion intensity signal and the solid solution signal is realized. A small part of the large-size metal sample (area S 大 ) is taken as a small sample (area S 小 ), the surface is sampled according to the detection requirement of inclusions, the small sample is placed under the scanning electron microscope, and the inclusion quantity and size information of the small sample are summarized according to the scanning electron microscope analysis. The inclusion size information under the scanning electron microscope and the inclusion intensity distribution of the spark discharge scanning of the large-size metal sample are associated to determine the corresponding relationship between the inclusion size and the intensity, so that the size distribution information of the inclusions of the large-size metal sample is obtained, and the problem of large-size inclusion content distribution analysis is solved.

[0081] The principles and implementation modes of the present application are described in specific examples in this paper, and the above examples are only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A spark spectral analysis method for determining the content distribution of inclusions on the surface of large-sized metallic materials, characterized in that, Includes the following steps: By continuously excitation and scanning analysis of spark discharge on the surface of large-sized metal materials, data on the solid solution of inclusion elements and the mixed distribution of spectral intensity of inclusions on the surface of large-sized metal materials were obtained. The solid solution and spectral intensity mixed distribution data of the inclusion elements are summarized to obtain the relative frequency distribution diagram of the solid solution and spectral intensity of the inclusion elements. The relative frequency distribution of the spectral intensity is fitted to obtain the spectral intensity distribution data of the inclusions, including: The relative frequency distribution of the spectral intensity is subjected to normal distribution and Gumbel extreme value distribution peak fitting processing to obtain the normal distribution of the solid solution part of the main peak on the left and the Gumbel extreme value distribution of the tailing peak inclusion on the right. Based on the Gumbel extreme value distribution diagram of the right-side tailing peak inclusion, the spectral intensity distribution data of the inclusion are obtained; Take a sample of a predetermined area from the surface of a large-sized metal material as a small sample, and obtain the number and size information of inclusions in the small sample; The inclusion size information of the small sample is correlated with the spectral intensity distribution data of the inclusion to determine the correspondence between the size of the inclusion and the spectral intensity, thereby obtaining the content distribution result of inclusions on the surface of large-size metal materials.

2. The spark spectral analysis method for the content distribution of inclusions on the surface of large-size metallic materials according to claim 1, characterized in that, The method of obtaining solid solution and spectral intensity mixing distribution data of inclusion elements on the surface of large-size metal materials by continuous excitation scanning analysis of spark discharge includes: First, place the scanning probe at the leftmost position of the top Y direction of the large-sized metal material, and perform spark discharge scanning from left to right along the X direction. After the first row of scanning is completed, place the scanning probe at the leftmost position of the second row of the top Y direction of the large-sized metal material, and complete the second row of scanning from left to right. Continue until all rows of the large-sized metal material are scanned from top to bottom to obtain solid solution and spectral intensity mixing distribution data of inclusion elements on the surface of the large-sized metal material.

3. The spark spectral analysis method for the content distribution of inclusions on the surface of large-size metallic materials according to claim 1, characterized in that, The step of taking a sample of a predetermined area from the surface of a large-sized metal material as a small sample includes: The area of ​​a large-size metal surface is obtained and denoted as S. 大 ; Obtain the set area of ​​the small sample, denoted as S. 小 ; The surface area of ​​a large-sized metallic material and the designated area of ​​a small sample satisfy the following relationship: T=S 大 / S 小 Where T is in the range of 100-10000.

4. The spark spectral analysis method for the content distribution of inclusions on the surface of large-size metallic materials according to claim 1, characterized in that, The process of taking a sample of a predetermined area from the surface of a large-sized metal material as a small sample and obtaining the quantity and size information of inclusions in the small sample includes: A sample of a predetermined area from the surface of a large-sized metal material is ground and polished to serve as a small sample. The small sample is then placed under a scanning electron microscope (SEM) to identify and quantify inclusions larger than 1 μm on its surface. Simultaneously, aluminum foil is introduced at the edge of the small sample to perform grayscale threshold correction on the SEM image, confirming the brightness threshold for inclusion identification. When the brightness of a particle observed by the SEM is less than the brightness threshold, the particle is identified as an inclusion, and energy dispersive spectroscopy (EDS) analysis is performed. The number and size information of the inclusions are recorded and saved, and the size information of the largest inclusion is recorded as the first data.

5. The spark spectral analysis method for the content distribution of inclusions on the surface of large-size metallic materials according to claim 4, characterized in that, The step of taking a sample of a predetermined area from the surface of a large-sized metal material as a small sample, and obtaining the quantity and size information of inclusions in the small sample, further includes: Take a sample of a predetermined area from the surface of a large-sized metal material, prepare a new sample, grind and polish it to obtain a small sample, and place it under a scanning electron microscope again to obtain the maximum inclusion size information, which is recorded as the second data. Repeat the sampling operation, prepare a new sample, grind and polish it to obtain the maximum inclusion size information, which is recorded as the third data. Continue in this manner, repeating the sampling operation until 24 sets of data are recorded. Based on the extreme value analysis method, calculate the size of the maximum inclusion formed by the inclusion element on the surface of the large-sized metal material, and the maximum intensity signal in the spectral intensity distribution data of the corresponding inclusion.

6. The spark spectral analysis method for the content distribution of inclusions on the surface of large-size metallic materials according to claim 5, characterized in that, The step of correlating the inclusion size information of the small sample with the spectral intensity distribution data of the inclusions to determine the correspondence between the inclusion size and spectral intensity, and obtaining the content distribution results of inclusions on the surface of large-size metal materials, includes: The size information of inclusions under scanning electron microscope was classified and statistically analyzed to obtain the statistical frequency of each group with a group interval of 2 μm. Based on the statistical frequency of 2 μm group interval under scanning electron microscopy, the spectral intensity distribution data of the inclusions were divided into the same groups to obtain the average size and average intensity of each group. Based on the relationship between the average and maximum strength of each group obtained at the grouping frequency and the average and maximum size of the inclusions, a strength-size correction curve is plotted. Based on the intensity-size correction curve, the intensity-relative frequency spectrum is converted into an inclusion size-frequency spectrum. Multiplying this by the total spectral intensity of the inclusion elements yields an inclusion size distribution map. By setting a group interval, the inclusion content distribution results are obtained.

Images